Genes

12 pages, 1407 KiB

Open AccessArticle

Serendipitous In Situ Conservation of Faba Bean Landraces in Tunisia: A Case Study

by Elyes Babay, Khalil Khamassi, Wilma Sabetta, Monica Marilena Miazzi, Cinzia Montemurro, Domenico Pignone, Donatella Danzi, Mariella Matilde Finetti-Sialer and Giacomo Mangini

Genes 2020, 11(2), 236; https://doi.org/10.3390/genes11020236 - 24 Feb 2020

Cited by 8 | Viewed by 4017

Abstract

Cultivation of faba bean (Vicia faba L.) in Tunisia is largely based on improved varieties of the crop. However, a few farmers continue to produce local cultivars or landraces. The National Gene Bank of Tunisia (NGBT) recently launched a collection project for [...] Read more.

Cultivation of faba bean (Vicia faba L.) in Tunisia is largely based on improved varieties of the crop. However, a few farmers continue to produce local cultivars or landraces. The National Gene Bank of Tunisia (NGBT) recently launched a collection project for faba bean landraces, with special focus on the regions of the North West, traditionally devoted to cultivating grain legumes, and where around 80% of the total national faba bean cultivation area is located. The seed phenotypic features of the collected samples were studied, and the genetic diversity and population structure analyzed using simple sequence repeat markers. The genetic constitution of the present samples was compared to that of faba bean samples collected by teams of the International Center for Agricultural Research in the Dry Areas (ICARDA) in the 1970s in the same region, and stored at the ICARDA gene bank. The results of the diversity analysis demonstrate that the recently collected samples and those stored at ICARDA largely overlap, thus demonstrating that over the past 50 years, little genetic change has occurred to the local faba bean populations examined. These findings suggest that farmers serendipitously applied international best practices for in situ conservation of agricultural crops. Full article

(This article belongs to the Special Issue Genetic Diversity Assessment and Marker-Assisted Selection in Crops)

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13 pages, 4581 KiB

Open AccessArticle

Comprehensive Sequence Analysis of IQD Gene Family and their Expression Profiling in Grapevine (Vitis vinifera)

by Zhongjie Liu, Muhammad Salman Haider, Nadeem Khan and Jinggui Fang

Genes 2020, 11(2), 235; https://doi.org/10.3390/genes11020235 - 24 Feb 2020

Cited by 13 | Viewed by 3566

Abstract

The plant-specific IQ67-domain (IQD) protein family members are downstream targets of calcium sensors, known to regulate plant growth and lateral organ polarity, and basal defense response against environmental cues. No systematic study of IQD gene family has been performed on grapevine. The public [...] Read more.

The plant-specific IQ67-domain (IQD) protein family members are downstream targets of calcium sensors, known to regulate plant growth and lateral organ polarity, and basal defense response against environmental cues. No systematic study of IQD gene family has been performed on grapevine. The public availability of grapevine genome enables us to perform identification, phylogeny, chromosomal orientation, and gene structure analysis of the IQD genes in grapevine. We identified 49 VvIQD genes (VvIQD1–VvIQD49) and further classified them into eight subgroups based on phylogenetic relationships. The 49 VvIQD genes were assigned to 19 different chromosomal positions. The collinear relationship between grapevine and Arabidopsis IQDs (VvIQD and AtIQD), and within grapevine VvIQDs, was highly conserved. In addition, most of duplicated gene pairs showed Ka/Ks ratio less than 1.00, indicating purifying selection within these gene pairs, implying functional discrepancy after duplication. Transcription profiling of VvIQD genes shed light on their specific role in grapevine tissue and organ development. The qRT-PCR validation of the 49 VvIQD genes in grape berry tissue from cultivars with distinct berry shape during developmental phases suggested candidate genes involved in the shape of grape berries. The subcellular prediction of VvIQD22, VvIQD23, VvIQD38, and VvIQD49 genes validated their localization in the nucleus and plasma membrane. The VvIQD49 protein interaction with VvCaM2 was also verified by bimolecular fluorescence complementation (BiFC) analysis in the plasma membrane. Our findings will be valuable for the functional genomic studies for desirable shape development of grape berries. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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Motif structure of VvIQDs and gene structure analysis of IQD members in grapevine (A) and (B). The coding sequences (CDS), untranslated regions (UTR). Full article ">Figure 2
The collinear correlation of VvIQDs between grapevines and Arabidopsis (indicated with red colored lines) and within grapevine (indicated with yellow colored lines). The two random genes in grapevine genes are also given at the bottom. Full article ">Figure 3
Phylogenetic relationships of V. vinifera VvIQD genes with A. thalinana, P. patens, O. sativa, S. lycopersicum, and B. distachyon. The phylogenetic tree was drawn by using the maximum likelihood (ML) method with 1000 bootstrap replicates in MEGA (Version 7.0). Full article ">Figure 4
Expression profiles of the VvIQDs genes in different grapevine cultivars with distinct shape at different developmental stages. Where OC shows oblate circle; NR, nearly round; R, round; O, oval; and LO, long oval. The numbering (1–4) of each shape indicates V. vinifera different developmental stages (i.e., 20daf, 50daf, 80daf, and 110daf). Full article ">Figure 5
Subcellular localization of VvIQD22 (A), VvIQD23 (B), VvIQD38 (C), and VvIQD49 (D) in nucleus and membrane, using the N. benthamiana epidermal cells. Full article ">Figure 6
BiFC interaction analysis indicating VvIQD49 interaction with VvCaM2 by using the N. benthamiana epidermal cells. Full article ">

15 pages, 1269 KiB

Open AccessArticle

The Genetic Basis of Natural Variation in Drosophila melanogaster Immune Defense against Enterococcus faecalis

by Joanne R Chapman, Maureen A Dowell, Rosanna Chan and Robert L Unckless

Genes 2020, 11(2), 234; https://doi.org/10.3390/genes11020234 - 22 Feb 2020

Cited by 13 | Viewed by 4647

Abstract

Dissecting the genetic basis of natural variation in disease response in hosts provides insights into the coevolutionary dynamics of host-pathogen interactions. Here, a genome-wide association study of Drosophila melanogaster survival after infection with the Gram-positive entomopathogenic bacterium Enterococcus faecalis is reported. There was [...] Read more.

Dissecting the genetic basis of natural variation in disease response in hosts provides insights into the coevolutionary dynamics of host-pathogen interactions. Here, a genome-wide association study of Drosophila melanogaster survival after infection with the Gram-positive entomopathogenic bacterium Enterococcus faecalis is reported. There was considerable variation in defense against E. faecalis infection among inbred lines of the Drosophila Genetics Reference Panel. We identified single nucleotide polymorphisms associated with six genes with a significant (p < 10⁻⁰⁸, corresponding to a false discovery rate of 2.4%) association with survival, none of which were canonical immune genes. To validate the role of these genes in immune defense, their expression was knocked-down using RNAi and survival of infected hosts was followed, which confirmed a role for the genes krishah and S6k in immune defense. We further identified a putative role for the Bomanin gene BomBc1 (also known as IM23), in E. faecalis infection response. This study adds to the growing set of association studies for infection in Drosophila melanogaster and suggests that the genetic causes of variation in immune defense differ for different pathogens. Full article

(This article belongs to the Special Issue Genetic Basis of Phenotypic Variation in Drosophila and Other Insects)

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Genome-wide association study (GWAS) analysis using fitted data. (A) Distribution of survival rates amongst DGRP lines infected with E. faecalis after fitting a model to control for the effects of Date, Infector and Wolbachia status. Black line represents fitted average for a model of survival taking into account the fixed effects of infector and date of infection. The plot is sorted by increasing survival, and blue bars indicate standard error of the mean, per line. (B) Manhattan plot of genetic variants across the D. melanogaster genome and their association with E. faecalis survival. p-value is plotted as −log10 p-value. Solid red line indicates p-value cut-off of 10−7 (which equates to a −log10 p-value of 6). Points above this line were used for generating list of variants putatively associated with survival after infection (see <a href="#app1-genes-11-00234" class="html-app">Table S1</a>). Dashed red line indicates p-value cut-off of 10−8 (which equates to a −log10 p-value of 7). Most variants above this line were selected for candidate gene analysis; variants associated with genes are labelled with gene name. Black and grey shading delineates chromosomes. Full article ">Figure 2
Survival of GOI lines versus empty cassette controls (attP40 control line 36304). (A) krishah (kri, Line 62238) infected with E. faecalis at a dose of OD = 1.5; (B) S6 kinase (S6k, Line 42572) infected with E. faecalis at a dose of OD = 1.5; (C) S6 kinase (S6k, Line 42572) infected with E. faecalis at a dose of OD = 2.4. In all cases, infections were conducted across multiple days. As such, the y axis is the residuals from a model controlling for Date effects. Full article ">Figure 3
Relationship between Bomanin genes and E. faecalis survival. (A) Manhattan plot of genetic variants within the Bomanin cluster on chromosome 2R of the D. melanogaster genome and their association with E. faecalis survival. p-value is plotted as −log10 p-value. Light grey polygons denote the limits of genes, and the dark grey polygons indicate coding sequences within genes. Color of points denotes location of variant with respect to the closest gene, as per legend. (B) Expression of the perfectly linked SNPs 2R_14270226 and 2R_14270228 in uninfected DGRP individuals plotted against survival of the same lines after infection with E. faecalis. Red dots denote the six lines homozygous for the minor allele. In general, these lines display lowered survival after E. faecalis infection (lower left quadrant). Dashed lines indicate means for survival (horizontal line) and uninfected expression (vertical line). (C) Survival of Bom-lines versus empty cassette controls after five days of infection with E. faecalis at a dose of OD = 1.5. From left to right, BomBc1, BomS1, BomT1, BomS4. Full article ">

18 pages, 1209 KiB

Open AccessReview

Hearing Impairment Overview in Africa: the Case of Cameroon

by Edmond Wonkam Tingang, Jean Jacques Noubiap, Jean Valentin F. Fokouo, Oluwafemi Gabriel Oluwole, Séraphin Nguefack, Emile R. Chimusa and Ambroise Wonkam

Genes 2020, 11(2), 233; https://doi.org/10.3390/genes11020233 - 22 Feb 2020

Cited by 18 | Viewed by 4960

Abstract

The incidence of hearing impairment (HI) is higher in low- and middle-income countries when compared to high-income countries. There is therefore a necessity to estimate the burden of this condition in developing world. The aim of our study was to use a systematic [...] Read more.

The incidence of hearing impairment (HI) is higher in low- and middle-income countries when compared to high-income countries. There is therefore a necessity to estimate the burden of this condition in developing world. The aim of our study was to use a systematic approach to provide summarized data on the prevalence, etiologies, clinical patterns and genetics of HI in Cameroon. We searched PubMed, Scopus, African Journals Online, AFROLIB and African Index Medicus to identify relevant studies on HI in Cameroon, published from inception to 31 October, 2019, with no language restrictions. Reference lists of included studies were also scrutinized, and data were summarized narratively. This study is registered with PROSPERO, number CRD42019142788. We screened 333 records, of which 17 studies were finally included in the review. The prevalence of HI in Cameroon ranges from 0.9% to 3.6% in population-based studies and increases with age. Environmental factors contribute to 52.6% to 62.2% of HI cases, with meningitis, impacted wax and age-related disorder being the most common ones. Hereditary HI comprises 0.8% to 14.8% of all cases. In 32.6% to 37% of HI cases, the origin remains unknown. Non-syndromic hearing impairment (NSHI) is the most frequent clinical entity and accounts for 86.1% to 92.5% of cases of HI of genetic origin. Waardenburg and Usher syndromes account for 50% to 57.14% and 8.9% to 42.9% of genetic syndromic cases, respectively. No pathogenic mutation was described in GJB6 gene, and the prevalence of pathogenic mutations in GJB2 gene ranged from 0% to 0.5%. The prevalence of pathogenic mutations in other known NSHI genes was <10% in Cameroonian probands. Environmental factors are the leading etiology of HI in Cameroon, and mutations in most important HI genes are infrequent in Cameroon. Whole genome sequencing therefore appears as the most effective way to identify variants associated with HI in Cameroon and sub-Saharan Africa in general. Full article

(This article belongs to the Special Issue Genetic Epidemiology of Deafness)

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12 pages, 2376 KiB

Open AccessReview

RECQ5: A Mysterious Helicase at the Interface of DNA Replication and Transcription

by Martin Andrs, Zdenka Hasanova, Anna Oravetzova, Jana Dobrovolna and Pavel Janscak

Genes 2020, 11(2), 232; https://doi.org/10.3390/genes11020232 - 21 Feb 2020

Cited by 16 | Viewed by 5562

Abstract

RECQ5 belongs to the RecQ family of DNA helicases. It is conserved from Drosophila to humans and its deficiency results in genomic instability and cancer susceptibility in mice. Human RECQ5 is known for its ability to regulate homologous recombination by disrupting RAD51 nucleoprotein [...] Read more.

RECQ5 belongs to the RecQ family of DNA helicases. It is conserved from Drosophila to humans and its deficiency results in genomic instability and cancer susceptibility in mice. Human RECQ5 is known for its ability to regulate homologous recombination by disrupting RAD51 nucleoprotein filaments. It also binds to RNA polymerase II (RNAPII) and negatively regulates transcript elongation by RNAPII. Here, we summarize recent studies implicating RECQ5 in the prevention and resolution of transcription-replication conflicts, a major intrinsic source of genomic instability during cancer development. Full article

(This article belongs to the Special Issue DNA Helicases: Mechanisms, Biological Pathways, and Disease Relevance)

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Figure 1
Domain organization of human RECQ5 helicase. For description of the individual domains see the main text. The positions of amino acids at domain boundaries are indicated. Full article ">Figure 2
Proposed model for the role of RECQ5 in the suppression of crossovers during homologous recombination repair. RECQ5 promotes the SDSA sub-pathway of HR by disrupting RAD51 filaments formed on ssDNA after RTEL1-mediated unwinding of the extended D-loop. This prevents D-loop reassembly and its conversion to double-Holliday junction, which can be resolved to crossover (CO) or non-crossover (NCO) products. Full article ">Figure 3
Proposed roles for RECQ5 in resolution of transcription-replication conflicts. (A) Role of RECQ5 in resolution of R-loop-mediated TRCs. Head-on TRCs can promote R-loop formation followed by the build-up of positively-supercoiled (+SC) domains between converging transcription- and replication machineries, which will cause replication fork stalling. Stalled replication forks are protected by the RAD51 filament, which can promote fork reversal by DNA translocase ZRANB3. Fork reversal is counteracted by RECQ1 helicase. RECQ5 helicase disrupts the RAD51 filament to prevent fork reversal and to facilitate fork cleavage by MUS81 endonuclease, which releases the topological barrier in the DNA template and triggers reactivation of transcription by ELL. After fork religation by RAD52 and LIG4/XRCC4, the reactivated transcription complex can bypass the replication-stalling site and continue RNA synthesis on the lagging arm of the fork. This is followed by replisome reloading and restart of DNA synthesis. It is assumed that after fork stalling, the replicative helicase CMG traverses the fork junction onto dsDNA via its ssDNA gate [<a href="#B59-genes-11-00232" class="html-bibr">59</a>]. After fork religation, CMG translocates back onto ssDNA to allow the passage of the transcription complex and to nucleate a functional replisome. (B) TRC resolution mediated by RECQ5-dependent PCNA SUMOylation. Interaction of RNAPIIo-bound RECQ5 with PCNA triggers the PCNA SUMO2 conjugation. SUMO2-PCNA enriches histone chaperones CAF1 and FACT at replication forks to deposit repressive histones, causing RNAPII dissociation. Full article ">

23 pages, 7207 KiB

Open AccessArticle

Comparative Genomics and Evolutionary Analysis of RNA-Binding Proteins of Burkholderia cenocepacia J2315 and Other Members of the B. cepacia Complex

by Joana R. Feliciano, António M. M. Seixas, Tiago Pita and Jorge H. Leitão

Genes 2020, 11(2), 231; https://doi.org/10.3390/genes11020231 - 21 Feb 2020

Cited by 7 | Viewed by 4062

Abstract

RNA-binding proteins (RBPs) are important regulators of cellular functions, playing critical roles on the survival of bacteria and in the case of pathogens, on their interaction with the host. RBPs are involved in transcriptional, post-transcriptional, and translational processes. However, except for model organisms [...] Read more.

RNA-binding proteins (RBPs) are important regulators of cellular functions, playing critical roles on the survival of bacteria and in the case of pathogens, on their interaction with the host. RBPs are involved in transcriptional, post-transcriptional, and translational processes. However, except for model organisms like Escherichia coli, there is little information about the identification or characterization of RBPs in other bacteria, namely in members of the Burkholderia cepacia complex (Bcc). Bcc is a group of bacterial species associated with a poor clinical prognosis in cystic fibrosis patients. These species have some of the largest bacterial genomes, and except for the presence of two-distinct Hfq-like proteins, their RBP repertoire has not been analyzed so far. Using in silico approaches, we identified 186 conventional putative RBPs in Burkholderia cenocepacia J2315, an epidemic and multidrug resistant pathogen of cystic fibrosis patients. Here we describe the comparative genomics and phylogenetic analysis of RBPs present in multiple copies and predicted to play a role in transcription, protein synthesis, and RNA decay in Bcc bacteria. In addition to the two different Hfq chaperones, five cold shock proteins phylogenetically close to E. coli CspD protein and three distinct RhlE-like helicases could be found in the B. cenocepacia J2315 genome. No RhlB, SrmB, or DeaD helicases could be found in the genomes of these bacteria. These results, together with the multiple copies of other proteins generally involved in RNA degradation, suggest the existence, in B. cenocepacia and in other Bcc bacteria, of some extra and unexplored functions for the mentioned RBPs, as well as of alternative mechanisms involved in RNA regulation and metabolism in these bacteria. Full article

(This article belongs to the Section Microbial Genetics and Genomics)

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Burkholderia cenocepacia J2315 ribosomal proteins that compose the 30S (A) and the 50S (B) subunits of the bacterial ribosome described for Escherichia coli. Panels A and B, left part: schematic representation of the ribosomal RNA (light brown lines) and the r-proteins colored in light blue (one copy gene) or dark blue (at least two paralogs genes in E. coli or B. cenocepacia J2315). Right part: loci tags of each B. cenocepacia J2315 ortholog are mentioned. Rectangles colored in blue represent r-proteins only encoded in bacterial genomes, and grey rectangles represent universal r-proteins that can be found in all domains of life. (C) Alignment of the amino acid sequences of the small subunit protein S21 (RpsU)-like proteins from B. cenocepacia J2315 (BCAL0115, BCAM0915, and BCAS0245) and E. coli (b3065). Asterisks (*) indicate identical amino acid residues, one (.) or two dots (:) indicate semi-conserved or conserved substitutions, respectively. The predicted secondary structure of E. coli RpsU protein is shown above the alignment segment, where cylinders represent α-helices. Alignments and secondary structure predictions were performed with MUSCLE [<a href="#B41-genes-11-00231" class="html-bibr">41</a>] and PSIPRED [<a href="#B43-genes-11-00231" class="html-bibr">43</a>] software, respectively. Full article ">Figure 2
Evolutionary analysis of hfq and hfq2 genes from 24 and 2 species of the genera Burkholderia and Paraburkholderia, respectively. (A) Phylogenetic tree constructed based on the alignment, performed by MUSCLE, of the 52 hfq nucleotide sequences listed in <a href="#app1-genes-11-00231" class="html-app">Table S2</a>. The evolutionary relatedness was inferred by using the Maximum Likelihood method and the Tamura–Nei model and conducted in MEGAX software [<a href="#B44-genes-11-00231" class="html-bibr">44</a>]. The tree with the highest log likelihood (−5911.51) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained by applying the neighbor-joining method to a matrix of pairwise distances estimated using the maximum composite likelihood (MCL) approach. The tree is drawn to scale, with branch lengths measured as the number of substitutions per site. (A1) Representation of the consensus sequence, determined by the alignment of Burkholderia hfq or (A2) hfq2 genes, as a sequence logo in which the size of each nucleotide and the black histogram corresponds to its degree of conservation. (B) Mean Ka/Ks values calculated among the hfq and hfq2 orthologs from the different Bcc or Burkholderia bacteria, or among the hfq and hfq2 paralogs from the 26 species selected. (C) Mean Ka/Ks values of two distinct regions of the orthologs hfq2 genes (white for 5′ region and grey for 3′ region). Error bars indicate standard deviation. The p-value was determined with the two-tailed Mann–Whitney test and represented by **** when p < 0.0001. Full article ">Figure 3
Distribution of Hfq proteins among bacteria and archaea. The phylogenetic tree was inferred by analysis of 798 Hfq protein sequences from 765 distinct species as described in <a href="#sec2-genes-11-00231" class="html-sec">Section 2</a>. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Seven distinct groups were formed and highlighted: α-Proteobacteria (blue), β-Proteobacteria (orange), γ-Proteobacteria (grey), Acidobacteria (olive green), δ-Proteobacteria (dark purple), Firmicutes (dark green), and Archaea (light purple). E. coli Hfq is colored red and Pseudomonas aeruginosa Hfq is green. When present, copies of Hfq-like proteins (Hfq or Hfq2) from γ-Proteobacteria are highlighted with (a), while for Deferribacteriaceae these proteins are highlighted with (*). Full article ">Figure 4
Phylogenetic tree for cold shock proteins of all domains of life. The phylogenetic tree was inferred for the alignment of 4636 non-redundant cold shock protein sequences (annotated with the reference COG1278) from 1436 species. The tree was drawn to scale using the iTol v5 software [<a href="#B45-genes-11-00231" class="html-bibr">45</a>], with branch lengths measured in number of substitutions per site. The groups containing cold shock proteins from γ or β-proteobacteria are colored, respectively, in grey or orange. Cold shock proteins (Csps) from E. coli are highlighted in brown and from P. aeruginosa in green. The five main clades recently defined by Yu and co-authors are highlighted [<a href="#B64-genes-11-00231" class="html-bibr">64</a>]. Full article ">Figure 5
The cold shock-like proteins encoding genes from bacteria of the Burkholderia genus. (A) Phylogenetic tree constructed based on the analysis of 135 nucleotide sequences listed in <a href="#app1-genes-11-00231" class="html-app">Table S3</a>. The evolutionary relatedness was inferred using the Maximum Likelihood method and Tamura–Nei model and conducted on MEGA X. The tree with the highest log likelihood (−6068.10) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained by applying the neighbor-joining method to a matrix of pairwise distances estimated using the maximum composite likelihood (MCL) approach. The tree is drawn to scale, with branch length units as the number of base substitutions per site. Upper panels: representation of the consensus sequences, determined by the alignment of the Burkholderia Csps genes clustered in Cluster BCAM1619 (orange), BCAM1810 (blue), BCAL0368 (yellow), BCAL3006 (brown), or BCAL2732 (green), as a sequence logo in which the size of each nucleotide with the black background corresponds to its degree of conservation. (B) Alignment of the amino acid sequences of the cold shock-like proteins from B. cenocepacia J2315 and the E. coli CspD (b0880). Asterisks (*) indicate identical amino acid residues, one (.) or two dots (:) indicate semi-conserved or conserved substitutions, respectively. The predicted secondary structure of E. coli CspD protein is shown above the alignment segment, where cylinders represent α-helices and arrows represent β-sheets. Alignments and secondary structure predictions were performed with MUSCLE and PSIPRED software, respectively. RBM: RNA binding motif. (C) Mean Ka/Ks values of the different Bcc (colored bars without pattern) or Burkholderia species (bars with pattern), calculated using orthologs csps genes. Error bars indicate the standard deviation. The p-values were determined with the two-tailed Mann–Whitney test and represented by * when p < 0.05, ** when p < 0.01, **** when p < 0.0001, or ns—nonsignificant. Full article ">Figure 6
Phylogenetic tree of DEAD-box RNA helicases. The phylogenetic tree was inferred for the analysis of 9254 sequences of proteins annotated with the reference COG0513 from 1815 species. The tree was drawn to scale using the iTol v5 software [<a href="#B45-genes-11-00231" class="html-bibr">45</a>], with branch lengths measured in number of substitutions per site. Clusters containing proteins from bacteria of the proteobacteria class were colored: α-Proteobacteria (blue), β-Proteobacteria (orange), γ-Proteobacteria (grey), δ-Proteobacteria (olive green). Clusters of orthologs genes from DEAD, DbpA, RhlE, RlhB, or SrmB proteins are highlighted. RNA helicases from E. coli are colored in brown and from P. aeruginosa in green. Full article ">Figure 7
RhlE-like helicases encoded in genomes of Burkholderia species. (A) Phylogenetic tree constructed based on the alignment of 72 amino acid sequences from 24 species of Burkholderia genus and two Paraburkholderia species (<a href="#app1-genes-11-00231" class="html-app">Table S4</a>). Sequences of E. coli and P. aeruginosa RhlE-like proteins were also included. The evolutionary relatedness was inferred using the maximum likelihood method and the Jones-Taylor-Thornton matrix-based model. The tree with the highest log likelihood (−16941.58) is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained by applying the neighbor-joining method to a matrix of pairwise distances estimated using a JTT model. The tree is drawn to scale, with branch length measured as the number of substitutions per site. Evolutionary analyses were conducted in MEGA X. (B) Alignment of the amino acid sequences of the RhlE-like helicases from B. cenocepacia J2315 and the E. coli RhlE. The Q motif is higlighted in grey. Asterisks (*) indicate identical amino acid residues, one (.) or two (:) dots indicate semi-conserved or conserved substitutions, respectively. (C) Mean Ka/Ks values of the different Bcc (colored bars) and Burkholderia bacteria (colored pattern bars), calculated using orthologs of rhlE1, rhlE2 or rhlE3 genes and using paralogs rhlE genes from 11 Burkholderia species (grey bars). Error bars indicate standard deviation. The p-value was determined with the two-tailed Mann–Whitney test and represented by *** when p < 0.001, **** when p < 0.0001 or ns—nonsignificant. Full article ">Figure 8
Schematic representation of the membrane-associated RNA degradosome. The main degradosome components were identified and the locus tag of each ortholog gene encoded in B. cenocepacia J2315, E. coli strain K-12 MG1655, and P. aeruginosa PAO1 genomes is mentioned. Full article ">

19 pages, 3904 KiB

Open AccessArticle

Anti-Aging Effects of Leontopodium alpinum (Edelweiss) Callus Culture Extract through Transcriptome Profiling

by Won Kyong Cho, Hye-In Kim, Soo-Yun Kim, Hyo Hyun Seo, Jihyeok Song, Jiyeon Kim, Dong Sun Shin, Yeonhwa Jo, Hoseong Choi, Jeong Hun Lee and Sang Hyun Moh

Genes 2020, 11(2), 230; https://doi.org/10.3390/genes11020230 - 21 Feb 2020

Cited by 27 | Viewed by 10022

Abstract

Edelweiss (Leontopodium Alpinum) in the family Asteraceae is a wildflower that grows in rocky limestone places. Here, we investigated the efficacy of edelweiss callus culture extract (Leontopodium Alpinum callus culture extract; LACCE) using multiple assays from in vitro to in [...] Read more.

Edelweiss (Leontopodium Alpinum) in the family Asteraceae is a wildflower that grows in rocky limestone places. Here, we investigated the efficacy of edelweiss callus culture extract (Leontopodium Alpinum callus culture extract; LACCE) using multiple assays from in vitro to in vivo as well as transcriptome profiling. Several in vitro assay results showed the strong antioxidant activity of LACCE in response to UVB treatment. Moreover, LACCE suppressed inflammation and wrinkling; however, moisturizing activity was increased by LACCE. The clinical test in vivo demonstrated that constant application of LACCE on the face and skin tissues improved anti-periorbital wrinkles, skin elasticity, dermal density, and skin thickness compared with the placebo. The RNA-Sequencing results showed at least 16.56% of human genes were expressed in keratinocyte cells. LACCE up-regulated genes encoding several KRT proteins; DDIT4, BNIP3, and IGFBP3 were involved in the positive regulation of the developmental process, programmed cell death, keratinization, and cornification forming skin barriers, which provide many advantages in the human skin. By contrast, down-regulated genes were stress-responsive genes, including metal, oxidation, wounding, hypoxia, and virus infection, suggesting LACCE did not cause any harmful stress on the skin. Our comprehensive study demonstrated LACCE is a promising agent for anti-aging cosmetics. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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Figure 1
Experimental procedure to obtain Leontopodium Alpinum callus culture extract (LACCE) from edelweiss callus using a bioreactor. (A) Edelweiss seeds were sterilized and germinated. (B) Callus was induced from edelweiss leaf tissue. (C) Induced callus was suspension cultured. (D) Obtained cells were cultured in a bioreactor. (E) Callus cells were harvested and lyophilized in a large quantity. Full article ">Figure 2
In vitro assessment of LACCE as an anti-aging agent, including cytotoxicity and anti-oxidant activity. Cell viability for three different concentrations (0.1%, 0.5%, and 1%) of LACCE in HaCaT cells (A) and Detroit551 cells (B) by MTT assay. Gray bar indicates cells treated with distilled water. (C) HaCaT cells were treated with hydrogen peroxide. Cell viability for three different LACCE concentrations was measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. N-acetyl cysteine (NAC) was used as a positive control. (D) Antioxidant activity of different LACCE concentrations was measured by DPPH assay. Vitamin C (Vit. C) was used as a positive control. * and ** indicate statistical significance with p-values of less than 0.05 and 0.01, respectively. (E) Cell morphology in each sample treated with hydrogen peroxide was visualized with methylene blue staining. Full article ">Figure 3
In vitro assessment of LACCE as anti-inflammatory, moisturizing, and anti-wrinkle agents by real-time RT-PCR. Relative expression of COX2 (A) and iNOS (B), two inflammatory marker genes, in different LACCE concentrations in response to UVB-treated samples was measured by real-time RT-PCR. Dexamethasone (Dex) was used as a positive control. Gray and blue bars indicate HaCaT cells without and with UVB treatment, respectively. (C) Relative expression of AQP3, a positive marker for moisturizing effect, in different LACCE concentrations. (D) Relative expression of MMP-2, a cell growth marker, in different LACCE concentrations in response to UVB. Expression of individual gene was normalized to GAPDH gene expression. * and ** indicate statistical significance with p-values of less than 0.05 and 0.01, respectively. Full article ">Figure 4
In vivo clinical tests of LACCE for facial lifting and improving periorbital wrinkles, skin elasticity, dermal density, and skin thickness. Ra (A) and Rq (B) values were measured by the PRIMOS high-resolution system at three different time points to observe periorbital wrinkle effect of LACCE (1%). Gross elasticity (R2) (C), net elasticity (R5) (D), and biological elasticity (R7) (E) values were measured to observe skin elasticity with LACCE. Measurement of dermal density (F) and skin thickness (G). R measurement at corner of mouth (H). Before/after: probability p (repeated measures ANOVA, significant: * p < 0.05, ** p < 0.01, *** p < 0.001). LACCE/Placebo B: probability p (repeated measures ANOVA, significant: † p < 0.05). Full article ">Figure 5
Mapping results, distribution of fragments per kilobase of transcript per million (FPKM) values, and visualization of differentially-expressed genes. (A) Portion of mapped (orange) and unmapped (gray) reads on human reference transcriptome. (B) Boxplot showing distribution of FPKM values in each library. (C) Volcano plot displaying distribution of log10 (padj) and log2 (FC) for all expressed genes. Padj and FC indicate adjusted p-value and fold change, respectively. Ten identified DEGs are indicated with blue (down-regulated genes, Down), red (up-regulated genes, Up), and gray (not significantly expressed genes, NS) dots. Full article ">Figure 6
Hierarchical structure of identified enriched GO terms for up-regulated human genes in response to LACCE. Directed acyclic graphs (DAGs) visualize hierarchical structure of identified enriched GO terms for up-regulated genes upon LACCE treatment according to biological process (A) and cellular component (B). Each GO term is indicated by different box color based on p-value. Detailed information for identified GO terms can be found in <a href="#app1-genes-11-00230" class="html-app">Table S2</a>. Full article ">

15 pages, 3608 KiB

Open AccessArticle

Ubiquitin E3 Ligase AaBre1 Responsible for H2B Monoubiquitination Is Involved in Hyphal Growth, Conidiation and Pathogenicity in Alternaria alternata

by Ye Liu, Jingjing Xin, Lina Liu, Aiping Song, Yuan Liao, Zhiyong Guan, Weimin Fang and Fadi Chen

Genes 2020, 11(2), 229; https://doi.org/10.3390/genes11020229 - 21 Feb 2020

Cited by 6 | Viewed by 2893

Abstract

Ubiquitination is one of several post-transcriptional modifications of histone 2B (H2B) which affect the chromatin structure and, hence, influence gene transcription. This study focuses on Alternaria alternata, a fungal pathogen responsible for leaf spot in many plant species. The experiments show that the [...] Read more.

Ubiquitination is one of several post-transcriptional modifications of histone 2B (H2B) which affect the chromatin structure and, hence, influence gene transcription. This study focuses on Alternaria alternata, a fungal pathogen responsible for leaf spot in many plant species. The experiments show that the product of AaBRE1, a gene which encodes H2B monoubiquitination E3 ligase, regulates hyphal growth, conidial formation and pathogenicity. Knockout of AaBRE1 by the homologous recombination strategy leads to the loss of H2B monoubiquitination (H2Bub1), as well as a remarkable decrease in the enrichment of trimethylated lysine 4 on histone 3 (H3K4me3). RNA sequencing assays elucidated that the transcription of genes encoding certain C2H2 zinc-finger family transcription factors, cell wall-degrading enzymes and chitin-binding proteins was suppressed in the AaBRE1 knockout cells. GO enrichment analysis showed that these proteins encoded by the set of genes differentially transcribed between the deletion mutant and wild type were enriched in the functional categories “macramolecular complex”, “cellular metabolic process”, etc. A major conclusion was that the AaBRE1 product, through its effect on histone 2B monoubiquitination and histone 3 lysine 4 trimethylation, makes an important contribution to the fungus’s hyphal growth, conidial formation and pathogenicity. Full article

(This article belongs to the Section Microbial Genetics and Genomics)

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18 pages, 4892 KiB

Open AccessArticle

Comparative Transcriptome Analysis Reveals Stem Secondary Growth of Grafted Rosa rugosa ‘Rosea’ Scion and R. multiflora ‘Innermis’ Rootstock

by Jing-shuang Sun, Rui-yang Hu, Fu-ling Lv, Yan-fang Yang, Zhi-min Tang, Guang-shun Zheng, Jian-bo Li, Hua Tian, Yan Xu and Shao-feng Li

Genes 2020, 11(2), 228; https://doi.org/10.3390/genes11020228 - 21 Feb 2020

Cited by 7 | Viewed by 3043

Abstract

Grafted plant is a chimeric organism formed by the connection of scion and rootstock through stems, so stem growth and development become one of the important factors to affect grafted plant state. However, information regarding the molecular responses of stems secondary growth after [...] Read more.

Grafted plant is a chimeric organism formed by the connection of scion and rootstock through stems, so stem growth and development become one of the important factors to affect grafted plant state. However, information regarding the molecular responses of stems secondary growth after grafting is limited. A grafted Rosa plant, with R. rugosa ‘Rosea’ as the scion (Rr_scion) grafted onto R. multiflora ‘Innermis’ as the stock (Rm_stock), has been shown to significantly improve stem thickness. To elucidate the molecular mechanisms of stem secondary growth in grafted plant, a genome-wide transcription analysis was performed using an RNA sequence (RNA-seq) method between the scion and rootstock. Comparing ungrafted R. rugosa ‘Rosea’ (Rr) and R. multiflora ‘Innermis’ (Rm) plants, there were much more differentially expressed genes (DEGs) identified in Rr_scion (6887) than Rm_stock (229). Functional annotations revealed that DEGs in Rr_scion are involved in two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways: the phenylpropanoid biosynthesis metabolism and plant hormone signal transduction, whereas DEGs in Rm_stock were associated with starch and sucrose metabolism pathway. Moreover, different kinds of signal transduction-related DEGs, e.g., receptor-like serine/threonine protein kinases (RLKs), transcription factor (TF), and transporters, were identified and could affect the stem secondary growth of both the scion and rootstock. This work provided new information regarding the underlying molecular mechanism between scion and rootstock after grafting. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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15 pages, 6186 KiB

Open AccessArticle

Alternative Splicing Events as Indicators for the Prognosis of Uveal Melanoma

by Qi Wan, Xuan Sang, Lin Jin and Zhichong Wang

Genes 2020, 11(2), 227; https://doi.org/10.3390/genes11020227 - 21 Feb 2020

Cited by 17 | Viewed by 3405

Abstract

Growing evidence has revealed that abnormal alternative splicing (AS) events are closely related to carcinogenic processes. However, the comprehensive study on the prognostic value of splicing events involved in uveal melanoma (UM) is still lacking. Therefore, splicing data of 80 UM patients were [...] Read more.

Growing evidence has revealed that abnormal alternative splicing (AS) events are closely related to carcinogenic processes. However, the comprehensive study on the prognostic value of splicing events involved in uveal melanoma (UM) is still lacking. Therefore, splicing data of 80 UM patients were obtained from the Cancer Genome Atlas (TCGA) SpliceSeq and RNA sequence data of UM and patient clinical features were downloaded from the Cancer Genome Atlas (TCGA) database to identify survival related splicing events in UM. As a result, a total of 37996 AS events of 17911 genes in UM were detected, among which 5299 AS events of 3529 genes were significantly associated with UM patients’ survival. Functional enrichment analysis revealed that this survival related splicing genes are corelated with mRNA catabolic process and ribosome pathway. Based on survival related splicing events, seven types of prognostic markers and the final overall prognostic signature could independently predict the overall survival of UM patients. Finally, an 11 spliced gene was identified in the final signature. On the basis of these 11 genes, we constructed a Support Vector Machine (SVM) classifier and evaluated it with leave-one-out cross-validation. The results showed that the 11 genes could determine short- and long-term survival with a predicted accuracy of 97.5%. Besides, the splicing factors and alternative splicing events correlation network was constructed to serve as therapeutic targets for UM treatment. Thus, our study depicts a comprehensive landscape of alternative splicing events in the prognosis of UM. The correlation network and associated pathways would provide additional potential targets for therapy and prognosis. Full article

(This article belongs to the Special Issue Melanoma Genetics)

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19 pages, 3485 KiB

Open AccessArticle

Integrative Analysis Identifies Candidate Tumor Microenvironment and Intracellular Signaling Pathways that Define Tumor Heterogeneity in NF1

by Jineta Banerjee, Robert J Allaway, Jaclyn N Taroni, Aaron Baker, Xiaochun Zhang, Chang In Moon, Christine A Pratilas, Jaishri O Blakeley, Justin Guinney, Angela Hirbe, Casey S Greene and Sara JC Gosline

Genes 2020, 11(2), 226; https://doi.org/10.3390/genes11020226 - 21 Feb 2020

Cited by 12 | Viewed by 5966

Abstract

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40–60% of [...] Read more.

Neurofibromatosis type 1 (NF1) is a monogenic syndrome that gives rise to numerous symptoms including cognitive impairment, skeletal abnormalities, and growth of benign nerve sheath tumors. Nearly all NF1 patients develop cutaneous neurofibromas (cNFs), which occur on the skin surface, whereas 40–60% of patients develop plexiform neurofibromas (pNFs), which are deeply embedded in the peripheral nerves. Patients with pNFs have a ~10% lifetime chance of these tumors becoming malignant peripheral nerve sheath tumors (MPNSTs). These tumors have a severe prognosis and few treatment options other than surgery. Given the lack of therapeutic options available to patients with these tumors, identification of druggable pathways or other key molecular features could aid ongoing therapeutic discovery studies. In this work, we used statistical and machine learning methods to analyze 77 NF1 tumors with genomic data to characterize key signaling pathways that distinguish these tumors and identify candidates for drug development. We identified subsets of latent gene expression variables that may be important in the identification and etiology of cNFs, pNFs, other neurofibromas, and MPNSTs. Furthermore, we characterized the association between these latent variables and genetic variants, immune deconvolution predictions, and protein activity predictions. Full article

(This article belongs to the Special Issue Genomics and Models of Nerve Sheath Tumors)

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Transfer learning reduced dimensionality and added additional context to gene expression datasets. (A) Principal components analysis (PCA) of gene expression data indicated that counts-level data may have been batch confounded. (B) The relative distributions of latent variable expression across the four tumor types using a density plot indicated that the majority of latent variables (LVs) had an expression value near 0 and that the four tumor types had similar latent variable expression distributions. (C) PCA of LVs indicated that batch effects, although reduced, may still have existed in the LV data (D) A look at the 5% most variable LVs across the cohort of gene expression data indicated that the latent variables represented a wide swath of biological processes, as well as some LVs that had no clear association to a defined biological pathway. Full article ">Figure 2
An ensemble of random forests selected the most important latent variables for classifying different tumor types in NF1. (A) Density plot showing the distribution of F1 scores of 500 iterations of independent random forest models using all latent variables. (B) Density plot showing the distribution of F1 scores of 500 iterations of independent random forest models trained using only the top 40 features with high importance scores for each class obtained from models included in (A). (C) Ridgeplots of top 20 latent variables selected by the random forest for each tumor type and their importance scores for each class that were selected for later analyses. Full article ">Figure 3
Selected latent variables (LVs) represented gene combinations unique to each tumor type. (A) Venn diagram showing the distribution of the top 40 LVs from each tumor type. (B,C) Total values of the LVs as measured by multiPLIER across samples are represented in the dot-plots, where color of the dots represents the tumor type (“Class” label colors described in the lower left). Loading values for the top 10 genes for each LV are represented in bar-plots below. The higher the loading, the greater impact that the gene expression had on the total multiPLIER value. (B,i–iii) Genes constituting the latent variables associated with known cell signaling pathways. (C,i–iii) Genes constituting the uncharacterized latent variables. Full article ">Figure 4
Some genes significantly distinguished expression of latent variables. (A) Latent variables (y-axis) whose values are significantly altered by mutations in specific genes. (B) MultiPLIER value of LV 851 across tumor samples. (C) MultiPLIER value of LV 851 across all samples. (D) Loading values of the top 20 genes that comprise LV 851. Full article ">Figure 5
Various immune cell signatures correlated to specific LVs that differentiate tumor types in NF1. (A) CIBERSORT deconvolution of bulk nerve sheath tumor expression data predicted the presence of activated mast cells and M2 macrophages and resting CD4+ memory T cells in all of the tested tumor types. (B) MCP-counter based deconvolution of bulk nerve sheath tumor expression data predicted the presence of cancer-associated fibroblasts across all tumor types, and diversity in T cell population across tumor types. (C) Correlation of CIBERSORT immune score (x-axis) with expression of latent variable 546 highlighted the increased presence of activated mast cells and resting dendritic cells in cNFs (circles). (D) Top 20 gene loadings of LV 546. (E) Correlation of MCP-counter score of Tell infiltration (x-axis) with LV 540. (F) Top 20 gene loadings of LV 540. Full article ">Figure 6
Integration of protein activity information with LVs can identify candidate drug targets for different NF1 tumor types. (A) A heatmap of correlation scores of known proteins with regulatory networks (or regulons) that are represented in the characterized and uncharacterized LVs selected above. The green bar across the top depicts how many protein activity scores had a Spearman correlation greater than 0.65. (B) Clustering of the LV-correlated VIPER proteins highlighted five clusters of latent variables with similar VIPER protein predictions, suggesting that these five clusters may have functional overlap. (C) Mean LV expression within the clusters highlighted differential expression within the clusters across tumor types. Tumor type is indicated by colors on the right. (D) Drug set enrichment analysis of the average VIPER protein correlation of cluster 2 identified some drugs and preclinical molecules that are enriched with targets in this cluster. Full article ">

28 pages, 868 KiB

Open AccessReview

Working on Genomic Stability: From the S-Phase to Mitosis

by Sara Ovejero, Avelino Bueno and María P. Sacristán

Genes 2020, 11(2), 225; https://doi.org/10.3390/genes11020225 - 20 Feb 2020

Cited by 35 | Viewed by 8346

Abstract

Fidelity in chromosome duplication and segregation is indispensable for maintaining genomic stability and the perpetuation of life. Challenges to genome integrity jeopardize cell survival and are at the root of different types of pathologies, such as cancer. The following three main sources of [...] Read more.

Fidelity in chromosome duplication and segregation is indispensable for maintaining genomic stability and the perpetuation of life. Challenges to genome integrity jeopardize cell survival and are at the root of different types of pathologies, such as cancer. The following three main sources of genomic instability exist: DNA damage, replicative stress, and chromosome segregation defects. In response to these challenges, eukaryotic cells have evolved control mechanisms, also known as checkpoint systems, which sense under-replicated or damaged DNA and activate specialized DNA repair machineries. Cells make use of these checkpoints throughout interphase to shield genome integrity before mitosis. Later on, when the cells enter into mitosis, the spindle assembly checkpoint (SAC) is activated and remains active until the chromosomes are properly attached to the spindle apparatus to ensure an equal segregation among daughter cells. All of these processes are tightly interconnected and under strict regulation in the context of the cell division cycle. The chromosomal instability underlying cancer pathogenesis has recently emerged as a major source for understanding the mitotic processes that helps to safeguard genome integrity. Here, we review the special interconnection between the S-phase and mitosis in the presence of under-replicated DNA regions. Furthermore, we discuss what is known about the DNA damage response activated in mitosis that preserves chromosomal integrity. Full article

(This article belongs to the Special Issue Chromosome Segregation Defects in the Origin of Genomic Instability)

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Cell cycle events and checkpoints controlling chromosome stability. Factors promoting cell cycle progression are shown in green, whereas those involved in cell cycle arrest are shown in red and downstream factors of the DDR pathways are shown in pink. The main cell cycle events are represented in the upper part. Origin licensing takes place during G1, and replication initiation is the triggering event of the S-phase. During the S-phase, the kinase Wee1 controls fork speed and maintains the activity of the nuclease complex SLX-MUS (SLX1-SLX4-MUS81-EME1) in a reduced state. CFSs replication initiation starts by the mid-S-phase; this late replication initiation increases the risk of entering into mitosis with under-replicated DNA at these particular loci. At the G2/M transition, the activation of the Cdk1/cyclinB1 complexes is governed by a feedback loop, in which the cyclin-dependent kinase (CDK) complexes inhibit the Wee1 kinase and activate the Cdc25s phosphatases by direct phosphorylation to promote their own activation. The kinase Plk1 contributes to this process by also inhibiting Wee1 and activating Cdc25s. Once in mitosis, the correct attachment to the spindle and alignment of the chromosomes at the metaphase plate satisfies the SAC and allows the activation of the anaphase promoting complex/cyclosome (APC/C). This, in turn, drives the exit from mitosis and guarantees proper chromosome segregation. Checkpoints activated throughout the cell cycle in response to DNA damage or replication problems are depicted in the lower part of the figure. DNA damage in interphase, replication stress, and under-replicated DNA at CFSs activate the ataxia-telangiectasia and Rad3-related and ataxia-telangiectasia mutated (ATR/ATM) pathways and their downstream effectors Chk1/Chk2 in order to arrest cell cycle progression by the inhibition of the CDK complexes and triggering repair mechanisms or programmed cell death, if the damage cannot be repaired. The persistence of incomplete replicated DNA in mitosis activates a DDR, which shares some common effectors with the interphasic mechanisms (ATM, ATR, FANCD2, MUS81-EME1, and TopBP1), in order to induce repair in mitosis or protection of the damaged DNA until the next cell cycle starts and it can be properly repaired. Interactions between DDR and SAC components indicate that the ATM/ATR and SAC checkpoint pathways crosstalk to restrain mitotic progression in the presence of unresolved DNA damage. Moreover, ATM and ATR kinase are involved in SAC regulation in both cells exposed to DNA damage and normal cycling cells. Mitotic DNA synthesis (MiDAS) is the most recently identified mechanism to complete replication at CFSs and telomeres before the end of cell division. MiDAS also plays an unexpected role in the maintenance of chromosome stability. FA, Fanconi anemia; ssDNA, single strand DNA; DSBs, double strand breaks; CFSs, common fragile sites; DDR, DNA damage response; SAC, spindle assembly checkpoint; HR, homologous recombination; NHEJ, non-homologous end joining; UFBs, ultrafine bridges; P, prophase; PM, prometaphase; M, metaphase; A, anaphase; T, telophase. Full article ">

22 pages, 2352 KiB

Open AccessReview

Yeast Genome Maintenance by the Multifunctional PIF1 DNA Helicase Family

by Julius Muellner and Kristina H. Schmidt

Genes 2020, 11(2), 224; https://doi.org/10.3390/genes11020224 - 20 Feb 2020

Cited by 34 | Viewed by 6039

Abstract

The two PIF1 family helicases in Saccharomyces cerevisiae, Rrm3, and ScPif1, associate with thousands of sites throughout the genome where they perform overlapping and distinct roles in telomere length maintenance, replication through non-histone proteins and G4 structures, lagging strand replication, replication fork convergence, [...] Read more.

The two PIF1 family helicases in Saccharomyces cerevisiae, Rrm3, and ScPif1, associate with thousands of sites throughout the genome where they perform overlapping and distinct roles in telomere length maintenance, replication through non-histone proteins and G4 structures, lagging strand replication, replication fork convergence, the repair of DNA double-strand break ends, and transposable element mobility. ScPif1 and its fission yeast homolog Pfh1 also localize to mitochondria where they protect mitochondrial genome integrity. In addition to yeast serving as a model system for the rapid functional evaluation of human Pif1 variants, yeast cells lacking Rrm3 have proven useful for elucidating the cellular response to replication fork pausing at endogenous sites. Here, we review the increasingly important cellular functions of the yeast PIF1 helicases in maintaining genome integrity, and highlight recent advances in our understanding of their roles in facilitating fork progression through replisome barriers, their functional interactions with DNA repair, and replication stress response pathways. Full article

(This article belongs to the Special Issue DNA Helicases: Mechanisms, Biological Pathways, and Disease Relevance)

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19 pages, 1752 KiB

Open AccessArticle

Genes ScBx1 and ScIgl—Competitors or Cooperators?

by Anna Wlazło, Magdalena Święcicka, Marek D. Koter, Tomasz Krępski, Leszek Bolibok, Anna Stochmal, Mariusz Kowalczyk and Monika Rakoczy-Trojanowska

Genes 2020, 11(2), 223; https://doi.org/10.3390/genes11020223 - 20 Feb 2020

Cited by 6 | Viewed by 2783

Abstract

Two genes, Bx1 and Igl, both encoding indole-3-glycerol phosphate lyase (IGL), are believed to control the conversion of indole-3-glycerol phosphate (IGP) to indole. The first of these has generally been supposed to be regulated developmentally, being expressed at early stages of plant [...] Read more.

Two genes, Bx1 and Igl, both encoding indole-3-glycerol phosphate lyase (IGL), are believed to control the conversion of indole-3-glycerol phosphate (IGP) to indole. The first of these has generally been supposed to be regulated developmentally, being expressed at early stages of plant development with the indole being used in the benzoxazinoid (BX) biosynthesis pathway. In contrast, it has been proposed that the second one is regulated by stresses and that the associated free indole is secreted as a volatile. However, our previous results contradicted this. In the present study, we show that the ScIgl gene takes over the role of ScBx1 at later developmental stages, between the 42nd and 70th days after germination. In the majority of plants with silenced ScBx1 expression, ScIgl was either expressed at a significantly higher level than ScBx1 or it was the only gene with detectable expression. Therefore, we postulate that the synthesis of indole used in BX biosynthesis in rye is controlled by both ScBx1 and ScIgl, which are both regulated developmentally and by stresses. In silico and in vivo analyses of the promoter sequences further confirmed our hypothesis that the roles and modes of regulation of the ScBx1 and ScIgl genes are similar. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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Figure 1
Biosynthesis pathway of benzoxazinoids in maize (Zea mays) (modified scheme according to Niculaes et al. [<a href="#B15-genes-11-00223" class="html-bibr">15</a>]). Rye orthologs of Bx genes isolated and sequenced are marked in bold, 1 KF636825–KF636828 and KF620524, 2 MN120476, 3 HG380520, 4 MG519859, 5 AB548283.1, 6 AY586531.2. Full article ">Figure 2
Expression patterns of the ScBx1 gene of three rye inbred lines, L318, D33, and D39 at six time points, 14, 21, 28, 42, 70, and 77 dag. The data represent mean value with standard deviation. There is no statistically significant difference between the expression level of the ScBx1 gene at subsequent time points within each of the three tested lines. Full article ">Figure 3
Expression patterns of the ScIgl gene of three rye inbred lines, L318, D33, and D39 at six time points, 14, 21, 28, 42, 70, and 77 dag. The data represent mean value with standard deviation. The letters a, b, c, and d denote statistically significant (p ≤ 0.05) differences in relative expression level between subsequent time points in a given line. Full article ">Figure 4
Comparison of the expression patterns of the ScBx1 and ScIgl genes of three rye inbred lines, L318, D33, and D39 at six time points, 14, 21, 28, 42, 70, and 77 dag. The data represent mean value with standard deviation. The letters a, b, c, and d denote statistically significant (p ≤ 0.05) differences in relative expression of the studied genes between successive time points within one line. Full article ">Figure 5
Benzoxazinoid (BX) content in aboveground parts of rye lines, (A) L318, (B) D33, (C) D39 at six time points, 14, 21, 28, 42, 70, and 77 dag. The data represent mean value with standard deviation. The letters a, b, c, d and e denote statistically significant (p ≤ 0.05) differences between subsequent time points in a given BX. Full article ">Figure 6
Patterns of normalized (in respect to the empty BSMV:PDS vector) expression of ScIgl and ScBx1 genes in leaves of rye cv. Stach F1 inoculated with BSMV:ScBx1 on the 14th dpi, for methodological details related to silencing procedure see Groszyk et al. [<a href="#B14-genes-11-00223" class="html-bibr">14</a>]. The results represent mean value and standard deviations of three technical replicates. Full article ">Figure 7
Patterns of normalized (in respect to the empty BSMV:PDS vector) expression of ScIgl and ScBx1 genes in leaves of rye cv. Stach F1 inoculated with BSMV:ScBx1 on the 21st dpi; for methodological details related to silencing procedure see Groszyk et al. [<a href="#B14-genes-11-00223" class="html-bibr">14</a>]. The results represent mean value and standard deviations of three technical replicates. Full article ">

14 pages, 5447 KiB

Open AccessCase Report

Two Novel FAM20C Variants in a Family with Raine Syndrome

by Araceli Hernández-Zavala, Fernando Cortés-Camacho, Icela Palma-Lara, Ricardo Godínez-Aguilar, Ana María Espinosa, Javier Pérez-Durán, Patricia Villanueva-Ocampo, Carlos Ugarte-Briones, Carlos Alberto Serrano-Bello, Paula Jesús Sánchez-Santiago, José Bonilla-Delgado, Marco Antonio Yáñez-López, Georgina Victoria-Acosta, Adolfo López-Ornelas, Patricia García Alonso-Themann, José Moreno and Carmen Palacios-Reyes

Genes 2020, 11(2), 222; https://doi.org/10.3390/genes11020222 - 20 Feb 2020

Cited by 10 | Viewed by 6868

Abstract

Two siblings from a Mexican family who carried lethal Raine syndrome are presented. A newborn term male (case 1) and his 21 gestational week brother (case 2), with a similar osteosclerotic pattern: generalized osteosclerosis, which is more evident in facial bones and cranial [...] Read more.

Two siblings from a Mexican family who carried lethal Raine syndrome are presented. A newborn term male (case 1) and his 21 gestational week brother (case 2), with a similar osteosclerotic pattern: generalized osteosclerosis, which is more evident in facial bones and cranial base. Prenatal findings at 21 weeks and histopathological features for case 2 are described. A novel combination of biallelic FAM20C pathogenic variants were detected, a maternal cytosine duplication at position 456 and a paternal deletion of a cytosine in position 474 in exon 1, which change the reading frame with a premature termination at codon 207 and 185 respectively. These changes are in concordance with a negative detection of the protein in liver and kidney as shown in case 2. Necropsy showed absence of pancreatic Langerhans Islets, which are reported here for the first time. Corpus callosum absence is added to the few reported cases of brain defects in Raine syndrome. This report shows two new FAM20C variants not described previously, and negative protein detection in the liver and the kidney. We highlight that lethal Raine syndrome is well defined as early as 21 weeks, including mineralization defects and craniofacial features. Pancreas and brain defects found here in FAM20C deficiency extend the functional spectrum of this protein to previously unknown organs. Full article

(This article belongs to the Special Issue Molecular Genetics of Facial Traits and Malformations)

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Family pedigree and phenotype of affected siblings (case 1 and 2). (A) Pedigree of the family showing reported cases (case 1 corresponds to individual II.2 and case 2 corresponds to individual II.3). (B) Clinical picture of the first proband (case 1). (C) Clinical pictures of the second patient (case 2). Full article ">Figure 2
Image findings of cases 1 and 2. (A) X-ray of cranium, hands, and feet and babygram of the case 1, showing generalized osteosclerosis, more prominent in cranium base and facial bones, with hypomineralization of the other skull areas; periostic reaction in humerus, distal phalangeal hypoplasia of hands, carpal ossification defects (delayed bone age), and generalized osteosclerosis. (B) Transfontanellar ultrasound of case 1, showing brain calcifications, mostly periventricular. (C) Babygram of case 2, showing cranium with osteosclerosis, also more prominent in skull base and facial bones, cranial vault hypomineralization, and increased density of all the bones. (D) Obstetric structural USG at 21GW of case 2, showing exophthalmos and oral anomalies. Full article ">Figure 3
Anatomopathological findings of case 2. (A) Brain section showing corpus callosum agenesia. (B) Histological analysis of brain sections revealed brain parenchyma with disorganized cortex layers, and zones with laminated microcalcifications (arrows). (C) Neuropile with concentric calcospherites. (D) Pancreas with absence of Langerhans’ islets. (H&E stain). Full article ">Figure 4
FAM20C gene sequence analysis from Family. (A) Electropherogram showing wild-type FAM20C sequence and localization sites of maternal and paternal variants. (B) Electropherogram showing identified maternal variant sequence c.456dup corresponding to p.Gly153Argfs*56 and effect on size protein. (C) Electropherogram showing paternal variant sequence c.474delC corresponding to p.Ser159Profs*28 and size protein effect. Full article ">Figure 5
Representative images of FAM20C detection by immunohistochemistry (40×) in kidney and liver of patient with lethal Raine Syndrome (RS) (case 2) and necropsy tissue from a newborn without RS (gestational age 31 weeks). (A) Kidney from case 2, (a) negative control. (B) Kidney from newborn without RS (31GW), (b) negative control. (C) Liver from case 2, (c) negative control. (D) Liver from newborn without RS (31GW), (d) negative control. Full article ">

16 pages, 4813 KiB

Open AccessArticle

AaCOI1, Encoding a CORONATINE INSENSITIVE 1-Like Protein of Artemisia annua L., Is Involved in Development, Defense, and Anthocyanin Synthesis

by Rong Liu, Jinbiao Wang, Mu Xiao, Xiewang Gao, Jin Chen and Yanjiao Dai

Genes 2020, 11(2), 221; https://doi.org/10.3390/genes11020221 - 19 Feb 2020

Cited by 4 | Viewed by 3065

Abstract

Artemisia annua is an important medicinal plant producing the majority of the antimalarial compound artemisinin. Jasmonates are potent inducers of artemisinin accumulation in Artemisisa annua plants. As the receptor of jasmonates, the F-box protein COI1 is critical to the JA signaling required for [...] Read more.

Artemisia annua is an important medicinal plant producing the majority of the antimalarial compound artemisinin. Jasmonates are potent inducers of artemisinin accumulation in Artemisisa annua plants. As the receptor of jasmonates, the F-box protein COI1 is critical to the JA signaling required for plant development, defense, and metabolic homeostasis. AaCOI1 from Artemisia annua, homologous to Arabidopsis AtCOI1, encodes a F-box protein located in the nuclei. Expressional profiles of the AaCOI1 in the root, stem, leaves, and inflorescence was investigated. The mRNA abundance of AaCOI1 was the highest in inflorescence, followed by in the leaves. Upon mechanical wounding or MeJA treatment, expression of AaCOI1 was upregulated after 6 h. When ectopically expressed, driven by the native promoter from Arabidopsis thaliana, AaCOI1 could partially complement the JA sensitivity and defense responses, but fully complemented the fertility, and the JA-induced anthocyanin accumulation in a coi1-16 loss-of-function mutant. Our study identifies the paralog of AtCOI1 in Artemisia annua, and revealed its implications in development, hormone signaling, defense, and metabolism. The results provide insight into JA perception in Artemisia annua, and pave the way for novel molecular breeding strategies in the canonical herbs to manipulate the anabolism of pharmaceutic compounds on the phytohormonal level. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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Figure 1
Phylogenetic tree COI1 paralogs (A) in Artemisia annua, Helianthus annuus, Oryza sativa, Zea mays and Arabidopsis thaliana, and their sequences (B). The relationships were analyzed for deduced full-length amino acid sequences using MEGA7 by using the Maximum Likelihood (ML) method with Partial deletion and Poisson model, and a Bootstrap test of 1000 replicates for internal branch reliability. Bootstrap values were shown near the nodes. Abbreviations: Artemisia annua (Aa), Helianthus annuus (Ha), Oryza sativa (Os), Zea mays (Zm), and Arabidopsis thaliana (At). Full article ">Figure 2
The predicted AaCOI1 3D mode (A) and the contribution of amino acid residues to the structure (B). The LRRs and F-box are indicated in the figure. The LRRs are marked by red lines, while the F-box is marked by a yellow line (B). Full article ">Figure 3
Transcription analysis of AaCOI in different tissues (A) and in response to wounding and MeJA treatment (B). The error bar represents the mean (±standard error) of three independent biological replicates. Columns marked with different letters (a–c) are significantly different from the others (ANOVA followed by Tukey’s multiple comparison test (p < 0.05)); any points of the line chart marked with an asterisk are significantly different (Student’s t-test; ** p < 0.01). Error bars indicate SD. Full article ">Figure 4
Subcellular localization of AaCOI1. GFP, GFP fluorescence; Bright, bright-field image; Merge, merged GFP and bright-field image. The scale bar represents 10 μm. Full article ">Figure 5
Phenotypes of Col-0, complemented lines #1 and #2, and coi1-16 mutant. Overall appearance of Arabidopsis thaliana plants of different backgrounds (A); close-up of fully developed siliques about 10 days after pollination (B); the fertility was determined by counting the seeds number per silique (C) (N > 10). The error bar represents the mean (±standard error) of 10 independent biological replicates. Columns marked with different letters (a–b) are significantly different from the others (ANOVA followed by Tukey’s multiple comparison test (p < 0.05)). Full article ">Figure 6
Sensitivity to MeJA of Col-0, complemented lines #1 and #2, and coi1-16 mutant. Growth of Arabidopsis thaliana seedlings on MS supplemented with 50 μM MeJA (A); primary root length (N > 10) of seedlings after growing on MS supplemented with 50 μM MeJA for 10 days (B); the expression of COI1-dependent and JA-responsive genes in Arabidopsis seedlings of different backgrounds ((C), PDF1.2; (D), VSP1; (E), VSP2). The error bar represents the mean (±standard error) of at least three biological replicates. Columns marked with different letters (a–c) are significantly different from the others (ANOVA followed by Tukey’s multiple comparison test (p < 0.05)). Full article ">Figure 7
The defense response to herbivory in Col-0, #1, #2, and coi1-16 mutant. The overall appearance of Arabidopsis plants after 10 days of feeding by larvae (A); the overall appearance of larvae after feeding on Arabidopsis for 10 days (B); the fresh weight per larva after 10 days of feeding on Arabidopsis plants were measured (C). The error bar represents the mean (±standard error) of at least 20 biological replicates. Columns marked with different letters (a–c) are significantly different from the others (ANOVA followed by Tukey’s multiple comparison test (p < 0.05)). Full article ">Figure 8
The anthocyanin accumulation in Col-0, #1, #2, and coi1-16 mutant. The overall appearance of Arabidopsis plants after treatment of 50 μM MeJA for 48 h (A); the accumulation content measured from 1 g leaf tissue from MeJA-treated Col-0, #1, #2, coi1-16 (B). The error bar represents the mean (±standard error) of at least three biological replicates. Columns marked with different letters (a,b) are significantly different from the others (ANOVA followed by Tukey’s multiple comparison test (p < 0.05)). Full article ">

18 pages, 3213 KiB

Open AccessArticle

Development of Molecular Marker Linked with Bacterial Fruit Blotch Resistance in Melon (Cucumis melo L.)

by Md. Rafiqul Islam, Mohammad Rashed Hossain, Denison Michael Immanuel Jesse, Hee-Jeong Jung, Hoy-Taek Kim, Jong-In Park and Ill-Sup Nou

Genes 2020, 11(2), 220; https://doi.org/10.3390/genes11020220 - 19 Feb 2020

Cited by 13 | Viewed by 4438

Abstract

Bacterial fruit blotch (BFB) causes losses in melon marketable yield. However, until now, there has been no information about the genetic loci responsible for resistance to the disease or their pattern of inheritance. We determined the inheritance pattern of BFB resistance from a [...] Read more.

Bacterial fruit blotch (BFB) causes losses in melon marketable yield. However, until now, there has been no information about the genetic loci responsible for resistance to the disease or their pattern of inheritance. We determined the inheritance pattern of BFB resistance from a segregating population of 491 F₂ individuals raised by crossing BFB-resistant (PI 353814) and susceptible (PI 614596) parental accessions. All F₁ plants were resistant to Acidovorax citrulli strain KACC18782, and F₂ plants segregated with a 3:1 ratio for resistant and susceptible phenotypes, respectively, in a seedling bioassay experiment, indicating that BFB resistance is controlled by a monogenic dominant gene. In an investigation of 57 putative disease-resistance related genes across the melon genome, only the MELO3C022157 gene (encoding TIR-NBS-LRR domain), showing polymorphism between resistant and susceptible parents, revealed as a good candidate for further investigation. Cloning, sequencing and quantitative RT-PCR expression of the polymorphic gene MELO3C022157 located on chromosome 9 revealed multiple insertion/deletions (InDels) and single nucleotide polymorphisms (SNPs), of which the SNP A²⁰³⁵T in the second exon of the gene caused loss of the LRR domain and truncated protein in the susceptible accession. The InDel marker MB157-2, based on the large (504 bp) insertion in the first intron of the susceptible accession, was able to distinguish resistant and susceptible accessions among 491 F₂ and 22 landraces/inbred accessions with 98.17% and 100% detection accuracy, respectively. This novel PCR-based, co-dominant InDel marker represents a practical tool for marker-assisted breeding aimed at developing BFB-resistant melon accessions. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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Figure 1
Bacterial fruit blotch phenotypes on leaves of the two parental melon accessions, PI 353814 (resistant) and PI 614596 (susceptible), and their F1 hybrid (resistant) 12 days after inoculation with A. citrulli strain KACC18782, as compared to uninoculated controls. All leaves were detached just before the photographs were taken. Full article ">Figure 2
Microsynteny analysis of melon R-genes compared with watermelon and cucumber. Brown orange, blue and green indicate melon, watermelon and cucumber chromosomes, respectively. Red marking indicates genes showing polymorphism between the resistant (PI 353814) and susceptible (PI 614596) parents of the melon. Microsynteny analysis of genes on the melon chromosomes were drawn using the web-based tool Circos (<a href="http://circos.ca/software/download/" target="_blank">http://circos.ca/software/download/</a>) circos-0.69-9.tgz. Full article ">Figure 3
Banding patterns of six pairs of primers designed against the gene MELO3C022157. Polymorphic primer MB157-2 is marked with red underline. R—resistant parent PI 353814, S—susceptible parent PI 614596 and F1—their F1 hybrid. Primer details are given in <a href="#genes-11-00220-t003" class="html-table">Table 3</a>. Full article ">Figure 4
Polymorphism in the TIR-NBS-LRR gene MELO3022157 linked with bacterial fruit blotch (BFB) resistance in melon. (a) Idiogram of gene MELO3022157 showing the positions of the six sets of primers used (<a href="#genes-11-00220-t003" class="html-table">Table 3</a>) and of insertion/deletion (InDel) and SNP polymorphisms between the resistant (PI 353814) and susceptible (PI 614596) parental accessions. (b) Polymorphic PCR amplicons generated by the MB157-2 primer pair in resistant and susceptible parents and their F1 progeny. (c) Sequence alignment showing a long insertion (green highlighted region) in the susceptible parent. Grey shaded regions indicate exons and yellow highlighted segments indicate MB157-2-F and MB157-2-R primer sequences with primer names marked by blue highlights. (d) SNP at the 2035th bp causing a frameshift mutation marker is indicated in red (<a href="#app1-genes-11-00220" class="html-app">Supplementary Figure S6b</a>). (e) Loss of LRR domain in the susceptible accession. The complete alignment is shown in <a href="#app1-genes-11-00220" class="html-app">Supplementary Figure S6b</a>. Full article ">Figure 5
Relative expression levels of putative candidate R-gene (MELO3022157) in A. citrulli-resistant and susceptible melon accession. Error bars represent (± SE) of three individual observations. Different letters above the bars indicate significant differences. Ct—control, h—hour and d—day. Full article ">Figure 6
Validation of the InDel marker MB175-2 in 491 plants of an F2 population raised from resistant and susceptible parental accessions PI 353814 and PI 614596, respectively. Red numbers indicate accessions with a mismatch between phenotypic and genotypic results. Full article ">

11 pages, 2124 KiB

Open AccessArticle

Clinical Ketosis-Associated Alteration of Gene Expression in Holstein Cows

by Zhou-Lin Wu, Shi-Yi Chen, Chao Qin, Xianbo Jia, Feilong Deng, Jie Wang and Song-Jia Lai

Genes 2020, 11(2), 219; https://doi.org/10.3390/genes11020219 - 19 Feb 2020

Cited by 14 | Viewed by 4541

Abstract

Ketosis is one of the most prevalent transition metabolic disorders in dairy cows, and has been intrinsically influenced by both genetic and nutritional factors. However, altered gene expression with respective to dairy cow ketosis has not been addressed yet, especially at the genome-wide [...] Read more.

Ketosis is one of the most prevalent transition metabolic disorders in dairy cows, and has been intrinsically influenced by both genetic and nutritional factors. However, altered gene expression with respective to dairy cow ketosis has not been addressed yet, especially at the genome-wide level. In this study, we recruited nine Holsteins diagnosed with clinical ketosis and ten healthy controls, for which whole blood samples were collected at both prepartum and postpartum. Four groups of blood samples were defined: from cows with ketosis at prepartum (PCK, N = 9) and postpartum (CK, N = 9), respectively, and controls at prepartum (PHC, N = 10) and postpartum (HC, N = 10). RNA-Seq approach was used for investigating gene expression, by which a total of 27,233 genes were quantified with four billion high-quality reads. Subsequently, we revealed 75 and four differentially expressed genes (DEGs) between sick and control cows at postpartum and prepartum, respectively, which indicated that sick and control cows had similar gene expression patterns at prepartum. Meanwhile, there were 95 DEGs between postpartum and prepartum for sick cows, which showed depressed changes of gene expression during this transition period in comparison with healthy cows (428 DEGs). Functional analyses revealed the associated DEGs with ketosis were mainly involved in biological stress response, ion homeostasis, AA metabolism, energy signaling, and disease related pathways. Finally, we proposed that the expression level of STX1A would be potentially used as a new biomarker because it was the only gene that was highly expressed in sick cows at both prepartum and postpartum. These results could significantly help us to understand the underlying molecular mechanisms for incidence and progression of ketosis in dairy cows. Full article

(This article belongs to the Section Animal Genetics and Genomics)

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14 pages, 1449 KiB

Open AccessArticle

Effect of Phenotype Selection on Genome Size Variation in Two Species of Diptera

by Carl E. Hjelmen, Jonathan J. Parrott, Satyam P. Srivastav, Alexander S. McGuane, Lisa L. Ellis, Andrew D. Stewart, J. Spencer Johnston and Aaron M. Tarone

Genes 2020, 11(2), 218; https://doi.org/10.3390/genes11020218 - 19 Feb 2020

Cited by 8 | Viewed by 3830

Abstract

Genome size varies widely across organisms yet has not been found to be related to organismal complexity in eukaryotes. While there is no evidence for a relationship with complexity, there is evidence to suggest that other phenotypic characteristics, such as nucleus size and [...] Read more.

Genome size varies widely across organisms yet has not been found to be related to organismal complexity in eukaryotes. While there is no evidence for a relationship with complexity, there is evidence to suggest that other phenotypic characteristics, such as nucleus size and cell-cycle time, are associated with genome size, body size, and development rate. However, what is unknown is how the selection for divergent phenotypic traits may indirectly affect genome size. Drosophila melanogaster were selected for small and large body size for up to 220 generations, while Cochliomyia macellaria were selected for 32 generations for fast and slow development. Size in D. melanogaster significantly changed in terms of both cell-count and genome size in isolines, but only the cell-count changed in lines which were maintained at larger effective population sizes. Larger genome sizes only occurred in a subset of D. melanogaster isolines originated from flies selected for their large body size. Selection for development time did not change average genome size yet decreased the within-population variation in genome size with increasing generations of selection. This decrease in variation and convergence on a similar mean genome size was not in correspondence with phenotypic variation and suggests stabilizing selection on genome size in laboratory conditions. Full article

(This article belongs to the Special Issue Genetic Basis of Phenotypic Variation in Drosophila and Other Insects)

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Figure 1
Range of development time and genome size for generations 1, 10, and 32 for different populations of the blow fly Cochliomyia macellaria. Hours of development time are plotted on the X-axis and genome size (Mbp) is plotted on the Y-axis. Points represent mean of the phenotype and lines represent the range of each trait. Colors represent development and shapes represent origin city. No change in development time by generation was seen in control lines, increases in development time was seen in slow selected lines, and decrease in development time was seen in fast selected lines. Variation in genome size reduced with generation and converged on a mean size of approximately 530 Mbp. Variation in development time increased from generation one and was maintained. Full article ">Figure 2
Pupal cases for D. melanogaster selected for large and small body size. All strains from this picture were maintained together, fed from the same batch of medium and the vials established for this image were started on the same day. Full article ">Figure 3
Boxplot comparisons of genome size and cell-counts between D. melanogaster differentially selected for body size. Genome size and cell-counts plotted by strain for outbred strains and isolines. Different letters above each box represent values significantly different according to Tukey HSD at the p < 0.05 level. (A) Genome size variation for outbred populations in control lines (C1, C2), large selected lines (L1, L2), and small selected lines (S1, S2). (B) Variation in cell-count ratio for outbred populations in control lines (C1, C2), large selected lines (L1, L2), and small selected lines (S1, S2). (C) Genome size variation for isolines developed from outbred populations for large-body size selected lines (L1, L2) and small-body size selected lines (S1, S2). (D) Variation in cell-count ratio for isolines developed from outbred populations for large-body size selected lines (L1, L2) and small-body size selected lines (S1, S2). Full article ">Figure 4
Distribution of genome sizes and relative cell-count ratio for large and small body size selected lines of D. melanogaster. Relative cell-count ratio (X-axis) plotted against genome size in Mbp (Y-axis) for large and small body size selected isolines. Large body size selected lines are represented in red circles (L1) and green triangles (L2), small body size lines represented in blue squares (S1) and purple diamonds (S2). Ellipses represent 95% confidence ellipses determined using the stat_ellipse() function in the ggplot2 package of R. Only a subset of large body size selected D. melanogaster isolines showed an increase in genome size. A two-dimensional Kolmogorov-Smirnov test using the function peacock2() in the package ‘Peacock.test’ found the distributions of large and small body size flies to be significantly different (p < 0.001) [<a href="#B41-genes-11-00218" class="html-bibr">41</a>]. Full article ">

14 pages, 3253 KiB

Open AccessArticle

BTG4 is A Novel p53 Target Gene That Inhibits Cell Growth and Induces Apoptosis

by Na Zhang, Tinghui Jiang, Yitao Wang, Lanyue Hu and Youquan Bu

Genes 2020, 11(2), 217; https://doi.org/10.3390/genes11020217 - 19 Feb 2020

Cited by 9 | Viewed by 3274

Abstract

BTG4 is the last cloned and poorly studied member of BTG/Tob family. Studies have suggested that BTG4 is critical for the degradation of maternal mRNAs in mice during the process of maternal-to-zygotic transition, and downregulated in cancers, such as gastric cancer. However, the [...] Read more.

BTG4 is the last cloned and poorly studied member of BTG/Tob family. Studies have suggested that BTG4 is critical for the degradation of maternal mRNAs in mice during the process of maternal-to-zygotic transition, and downregulated in cancers, such as gastric cancer. However, the regulatory mechanism of BTG4 and its function in cancers remain elusive. In this study, we have for the first time identified the promoter region of the human BTG4 gene. Serial luciferase reporter assay demonstrated that the core promoter of BTG4 is mainly located within the 388 bp region near its transcription initiation site. Transcription factor binding site analysis revealed that the BTG4 promoter contains binding sites for canonical transcription factors, such as Sp1, whereas its first intron contains two overlapped consensus p53 binding sites. However, overexpression of Sp1 has negligible effects on BTG4 promoter activity, and site-directed mutagenesis assay further suggested that Sp1 is not a critical transcription factor for the transcriptional regulation of BTG4. Of note, luciferase assay revealed that one of the intronic p53 binding sites is highly responsive to p53. Both exogenous p53 overexpression and adriamycin-mediated endogenous p53 activation result in the transcriptional upregulation of BTG4. In addition, BTG4 is downregulated in lung and colorectal cancers, and overexpression of BTG4 inhibits cell growth and induces apoptosis in cancer cells. Taken together, our results strongly suggest that BTG4 is a novel p53-regulated gene and probably functions as a tumor suppressor in lung and colorectal cancers. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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Figure 1
BTG4 gene structure and chromosomal state. The human genomic region harboring the BTG4 gene (chr11:111,3327,050-111,394,285 67,236 bp, human species genomic assembly version, GRCh37/hg19) is schematically represented with the indicated tracks (<a href="http//genome.ucsc.edu/" target="_blank">http//genome.ucsc.edu/</a>). As for the chromatin state segmentation, the active promoter is shown in bright red, inactivated/poised promoter in purple, strong enhancer in orange, insulator in blue, transcriptional elongation in deep green, and weakly transcribed region in light green. Full article ">Figure 2
Identification of the BTG4 promoter region. (a) Schematic diagram of the BTG4 gene promoter reporter constructs. The positions relative to the major BTG4 transcription start site (+1) are indicated. The first and second exons of BTG4 are displayed by two open boxes. The two overlapped p3 binding sites (p53BS1/2) are shown by gray boxes. MiR34b and miR34c are transcribed in the opposite orientation from BTG4. The CpG island is indicated by thick black lines. (b) Luciferase assay. HCT116 and H1299 cells were transiently co-transfected with the indicated luciferase reporter constructs together with pRL-TK. Forty-eight hours later, luciferase activities were determined by the Dual Luciferase Assay System (Promega). Data are shown as the fold induction compared to that of the empty pGL3-basic vector. The results are presented as the mean and standard deviation (S.D.) of triplicates from a representative experiment. Full article ">Figure 3
Nucleotide sequences of the human BTG4 gene promoter. (a) The putative transcription factor binding sites in the promoter region of the BTG4 gene were predicted and underlined. Nucleotides are numbered based on the major transcription start site of BTG4 (+1). (b) Conservative analysis of the BTG4 promoter sequence. Sequence alignment of the nucleotide sequences of partial BTG4 gene promoters from the indicated species was conducted by the online software Clustal Omega. The putative Sp1-binding sites are boxed. Identical bases among different species are marked with stars (*). Full article ">Figure 4
Functional analysis of Sp1 binding sites in the BTG4 promoter. (a) Schematic diagram of site-directed mutagenesis of Sp1 binding sites in the BTG4-P412 luciferase reporter harboring the BTG4 promoter. The four potential Sp1 binding sites are indicated as open boxes (Sp1BS1, Sp1BS2, Sp1BS3, and Sp1BS4). The indicated point mutations are denoted by a cross at the potential Sp1 binding sites. (b) Luciferase reporter assays. The indicated luciferase reporter constructs were transfected into HCT116 and H1299 cells together with empty vector or with Sp1 expression plasmid. Forty-eight hours later, their luciferase activities were determined, as in <a href="#genes-11-00217-f003" class="html-fig">Figure 3</a>d. Full article ">Figure 5
BTG4 gene contains a p53 response element and is induced by p53. (a) Partial sequences of the first intron of the BTG4 gene were aligned across the human, mouse, and rat by online software Clustal Omega. The position is relative to the transcription start site of BTG4. The two overlapped p53 binding sites are indicated as p53BS1 and p53BS2. (b) The two overlapped p53 binding sites were cloned into the wildtype reporter BTG4-P388, respectively. The indicated reporters were cotransfected into H1299 cells with empty or Flag-p53 expression plasmids and pRL-TK. The luciferase activities were determined as described in <a href="#genes-11-00217-f002" class="html-fig">Figure 2</a>. The two potential p53 binding sites of p53BS1 and p53BS2 compared to the consensus p53 binding site (p53 CBS). R, purine; Y, pyrimidine; W, adenine or thymine. (c) H1299 cells were transiently transfected with empty vector (pcDNA3.0-Flag) or pcDNA3.0-Flag-p53 expression plasmid. Forty-eight hours later, cells were collected and subjected to RT-PCR analysis. A549 and HCT116 cells were treated with adriamycin at the final concentration of 1μM. Cells were then collected and subjected to RT-PCR analysis at the indicated time points. Full article ">Figure 6
BTG4 inhibits cell proliferation and migration, and induces apoptosis. (a) HCT116 cells were transiently transfected with empty vector (pcDNA3.0-Flag) or pcDNA3.0-Flag-BTG4 expression plasmid, and then subjected to cell proliferation assay. (b) HCT116 cells were transfected as in (a). Forty-eight hours later, cells were harvested and subjected to apoptosis assay. The lower-left quadrant represents viable cells (FITC−/PI−); lower right represents early apoptotic cells (FITC+/PI−); upper right represents late apoptotic and secondary necrotic cells (FITC+/PI+). (c) H1299 cells were transiently transfected with empty vector (pcDNA3.0-Flag) or pcDNA3.0-Flag-BTG4 expression plasmid, and then subjected to the wound healing assay. Cell migration status was monitored under a microscope at the indicated time points, and subsequently quantified. Full article ">Figure 7
The expression of BTG4 mRNA in lung and colon cancers. BTG4 expression levels in normal and cancerous tissues were analyzed with quantitative RT-PCR using OriGene TissueScan cancer panels (CSRT101). 0 denotes normal lung or colorectal tissues. I, II, III, IV represent different clinical stages of lung and colorectal cancers. Full article ">

10 pages, 1993 KiB

Open AccessFeature PaperArticle

Repetitive DNA Restructuring Across Multiple Nicotiana Allopolyploidisation Events Shows a Lack of Strong Cytoplasmic Bias in Influencing Repeat Turnover

by Steven Dodsworth, Maïté S. Guignard, Oscar A. Pérez-Escobar, Monika Struebig, Mark W. Chase and Andrew R. Leitch

Genes 2020, 11(2), 216; https://doi.org/10.3390/genes11020216 - 19 Feb 2020

Cited by 5 | Viewed by 3113

Abstract

Allopolyploidy is acknowledged as an important force in plant evolution. Frequent allopolyploidy in Nicotiana across different timescales permits the evaluation of genome restructuring and repeat dynamics through time. Here we use a clustering approach on high-throughput sequence reads to identify the main classes [...] Read more.

Allopolyploidy is acknowledged as an important force in plant evolution. Frequent allopolyploidy in Nicotiana across different timescales permits the evaluation of genome restructuring and repeat dynamics through time. Here we use a clustering approach on high-throughput sequence reads to identify the main classes of repetitive elements following three allotetraploid events, and how these are inherited from the closest extant relatives of the maternal and paternal subgenome donors. In all three cases, there was a lack of clear maternal, cytoplasmic bias in repeat evolution, i.e., lack of a predicted bias towards maternal subgenome-derived repeats, with roughly equal contributions from both parental subgenomes. Different overall repeat dynamics were found across timescales of <0.5 (N. rustica L.), 4 (N. repanda Willd.) and 6 (N. benthamiana Domin) Ma, with nearly additive, genome upsizing, and genome downsizing, respectively. Lower copy repeats were inherited in similar abundance to the parental subgenomes, whereas higher copy repeats contributed the most to genome size change in N. repanda and N. benthamiana. Genome downsizing post-polyploidisation may be a general long-term trend across angiosperms, but at more recent timescales there is species-specific variance as found in Nicotiana. Full article

(This article belongs to the Special Issue Cytonuclear Interactions in Polyploid Species)

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Figure 1
The evolutionary history of the three allotetraploid sections studied here (Rusticae, Repandae and Suaveolentes) including chromosome numbers, genome sizes and direction of hybridisation. Figure adapted from [<a href="#B19-genes-11-00216" class="html-bibr">19</a>,<a href="#B21-genes-11-00216" class="html-bibr">21</a>,<a href="#B22-genes-11-00216" class="html-bibr">22</a>]. Full article ">Figure 2
Repeat dynamics for N. rustica (section Rusticae), N. repanda (section Repandae) and N. benthamiana (section Suaveolentes). Curves for each accession represent the absolute cumulative deviation from expectation (sum of parental values). Clusters are ranked from smallest (left) to largest (right), plotted on a natural log scale. Full article ">Figure 3
Regression analyses of cluster size (read number) in the parental subgenomes versus the tetraploid genome, natural log-transformed. (A) N. rustica against N. paniculata (maternal; blue) and N. undulata (paternal; red). (B) N. repanda against N. obtusifolia (paternal; blue) and N. sylvestris (maternal; red). (C) N. benthamiana against N. noctiflora (maternal; blue) and N. sylvestris (paternal; red). Full article ">Figure 4
Results of 3D regression analyses. Cluster size is coloured from blue (low) to red (high). (A) N. rustica against N. paniculata (maternal) and N. undulata (paternal). (B) N. repanda against N. obtusifolia (paternal) and N. sylvestris (maternal). (C) N. benthamiana against N. noctiflora (maternal) and N. sylvestris (paternal). Full article ">

15 pages, 2628 KiB

Open AccessArticle

Drosophila Interspecific Hybridization Causes a Deregulation of the piRNA Pathway Genes

by Víctor Gámez-Visairas, Valèria Romero-Soriano, Joan Martí-Carreras, Eila Segarra-Carrillo and Maria Pilar García Guerreiro

Genes 2020, 11(2), 215; https://doi.org/10.3390/genes11020215 - 19 Feb 2020

Cited by 5 | Viewed by 3429

Abstract

Almost all eukaryotes have transposable elements (TEs) against which they have developed defense mechanisms. In the Drosophila germline, the main transposable element (TE) regulation pathway is mediated by specific Piwi-interacting small RNAs (piRNAs). Nonetheless, for unknown reasons, TEs sometimes escape cellular control during [...] Read more.

Almost all eukaryotes have transposable elements (TEs) against which they have developed defense mechanisms. In the Drosophila germline, the main transposable element (TE) regulation pathway is mediated by specific Piwi-interacting small RNAs (piRNAs). Nonetheless, for unknown reasons, TEs sometimes escape cellular control during interspecific hybridization processes. Because the piRNA pathway genes are involved in piRNA biogenesis and TE control, we sequenced and characterized nine key genes from this pathway in Drosophila buzzatii and Drosophila koepferae species and studied their expression pattern in ovaries of both species and their F1 hybrids. We found that gene structure is, in general, maintained between both species and that two genes—armitage and aubergine—are under positive selection. Three genes—krimper, methyltransferase 2, and zucchini—displayed higher expression values in hybrids than both parental species, while others had RNA levels similar to the parental species with the highest expression. This suggests that the overexpression of some piRNA pathway genes can be a primary response to hybrid stress. Therefore, these results reinforce the hypothesis that TE deregulation may be due to the protein incompatibility caused by the rapid evolution of these genes, leading to a TE silencing failure, rather than to an underexpression of piRNA pathway genes. Full article

(This article belongs to the Section Population and Evolutionary Genetics and Genomics)

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Figure 1
Expression rates in the parental species D. koepferae and D. buzzatii. Note that D. buzzatii females are not involved in the cross. For D. koepferae samples the mean between two families involved in the crosses is shown. Error bars represent standard deviation. Full article ">Figure 2
Expression rates relative to rp49 housekeeping gene in parental species (Dko and Dbu) and hybrids. Boxes are determined by the first and third quartile values, with an intermediate deep line corresponding to the median value. Circles correspond to outliers (above or below 1.5-fold the interquartile range) and asterisks correspond to atypical values. Every group is shown in the same order in every plot: Dbu parental species, hybrids groups A and B and Dko maternal species groups A and B. Graphics from (A) to (I) refer to each studied gene. Full article ">Figure 3
Fluorescent in situ hybridization (FISH) of ago3 RNA expression in ovaries. Red staining are ago3 transcripts, blue staining is DAPI (cells nuclei). Arrows mark the presence of ago3 transcripts. (A) positive control using Osvaldo retrotransposon probe, (B) negative control, (C) D. buzzatii, (D) D. koepferae, (E) hybrid. Full article ">

13 pages, 2201 KiB

Open AccessArticle

Characteristics of Microsatellites Mined from Transcriptome Data and the Development of Novel Markers in Paeonia lactiflora

by Yingling Wan, Min Zhang, Aiying Hong, Yixuan Zhang and Yan Liu

Genes 2020, 11(2), 214; https://doi.org/10.3390/genes11020214 - 19 Feb 2020

Cited by 9 | Viewed by 2956

Abstract

The insufficient number of available simple sequence repeats (SSRs) inhibits genetic research on and molecular breeding of Paeonia lactiflora, a flowering crop with great economic value. The objective of this study was to develop SSRs for P. lactiflora with Illumina RNA sequencing [...] Read more.

The insufficient number of available simple sequence repeats (SSRs) inhibits genetic research on and molecular breeding of Paeonia lactiflora, a flowering crop with great economic value. The objective of this study was to develop SSRs for P. lactiflora with Illumina RNA sequencing and assess the role of SSRs in gene regulation. The results showed that dinucleotides with AG/CT repeats were the most abundant type of repeat motif in P. lactiflora and were preferentially distributed in untranslated regions. Significant differences in SSR size were observed among motif types and locations. A large number of unigenes containing SSRs participated in catalytic activity, metabolic processes and cellular processes, and 28.16% of all transcription factors and 21.74% of hub genes for inflorescence stem straightness were found to contain SSRs. Successful amplification was achieved with 89.05% of 960 pairs of SSR primers, 55.83% of which were polymorphic, and most of the 46 tested primers had a high level of transferability to the genus Paeonia. Principal component and cluster dendrogram analyses produced results consistent with known genealogical relationships. This study provides a set of SSRs with abundant information for future accession identification, marker-trait association and molecular assisted breeding in P. lactiflora. Full article

(This article belongs to the Special Issue Genetic Diversity Assessment and Marker-Assisted Selection in Crops)

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Figure 1
Distribution of different repeat motifs and positions of simple sequence repeats (SSRs) in unigenes. (A) Proportion and distribution of each type of motif in dinucleotide (Di-), trinucleotide (Tri-), tetranucleotide (Tetra-) and other (i.e., Penta-, Hexa- and compound) repeats. In the legend, ‘other Tri-’ consists of ACG/CGT (0.26%), ACT/AGT (0.26%) and CCG/CGG (0.42%), and ‘Other Tetra-’ consists of 26 types of Tetra- repeats, the most abundant of which are AATC/ATTG (0.22%) and AGGG/CCCT (0.22%). (B) Abundances of six motifs in different unigene positions. Two types of SSRs were located in multiple regions. One of these SSRs was located across two 5′ UTRs, a coding sequences (CDS) and a 3′ UTR; another was located in multiple CDSs in one unigene. The SSR locations differed from each other. Unknown refers to the SSRs without matching locations. Full article ">Figure 2
Gene Ontology (GO) analysis of unigenes containing SSRs. The lighter color of each bar represents the number of unigenes without matching coding sequences. Full article ">Figure 3
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation of unigenes with embedded SSRs. The numbers outside the circle represent the cumulative number of unigenes beginning at zero and moving in a clockwise manner. Full article ">Figure 4
Principal coordinates analysis (PCoA) of amplified loci (A) and dendrogram generated by Bruvo’s distances (B) of 31 accessions, including seven species and 24 cultivars of Paeonia lactiflora. The cultivar names are abbreviated with capitalized letters in (A), and their full names are shown in (B). The UPGMA tree was produced with 1000 bootstrap replicates, and the node values greater than 50 are shown in the tree. Full article ">

24 pages, 8889 KiB

Open AccessArticle

Evolutionary Dynamics of the POTE Gene Family in Human and Nonhuman Primates

by Flavia Angela Maria Maggiolini, Ludovica Mercuri, Francesca Antonacci, Fabio Anaclerio, Francesco Maria Calabrese, Nicola Lorusso, Alberto L’Abbate, Melanie Sorensen, Giuliana Giannuzzi, Evan E. Eichler, Claudia Rita Catacchio and Mario Ventura

Genes 2020, 11(2), 213; https://doi.org/10.3390/genes11020213 - 18 Feb 2020

Cited by 7 | Viewed by 4801

Abstract

POTE (prostate, ovary, testis, and placenta expressed) genes belong to a primate-specific gene family expressed in prostate, ovary, and testis as well as in several cancers including breast, prostate, and lung cancers. Due to their tumor-specific expression, POTEs are potential oncogenes, therapeutic targets, [...] Read more.

POTE (prostate, ovary, testis, and placenta expressed) genes belong to a primate-specific gene family expressed in prostate, ovary, and testis as well as in several cancers including breast, prostate, and lung cancers. Due to their tumor-specific expression, POTEs are potential oncogenes, therapeutic targets, and biomarkers for these malignancies. This gene family maps within human and primate segmental duplications with a copy number ranging from two to 14 in different species. Due to the high sequence identity among the gene copies, specific efforts are needed to assemble these loci in order to correctly define the organization and evolution of the gene family. Using single-molecule, real-time (SMRT) sequencing, in silico analyses, and molecular cytogenetics, we characterized the structure, copy number, and chromosomal distribution of the POTE genes, as well as their expression in normal and disease tissues, and provided a comparative analysis of the POTE organization and gene structure in primate genomes. We were able, for the first time, to de novo sequence and assemble a POTE tandem duplication in marmoset that is misassembled and collapsed in the reference genome, thus revealing the presence of a second POTE copy. Taken together, our findings provide comprehensive insights into the evolutionary dynamics of the primate-specific POTE gene family, involving gene duplications, deletions, and long interspersed nuclear element (LINE) transpositions to explain the actual repertoire of these genes in human and primate genomes. Full article

(This article belongs to the Special Issue A Tale of Genes and Genomes)

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Figure 1
(A) Chromosome ideograms showing the localization of POTE (prostate, ovary, testis, and placenta expressed) genes in human. The colored bars indicate the four different POTE groups described later on in the results: red for group I, blue for group II, yellow for group III, and green for group IV. POTEKP mapping is indicated by the gray arrowhead. (B) Domain structure of the 14 canonical transcripts of human POTE genes. Coding (colored vertical bars) and noncoding (shorter and gray vertical bars) exons are shown and numbered on each transcript and are based on the Ensembl gene sequences. Half-sized LIR is indicated by a single light blue circle. Dark gray blocks flanking the transcripts indicate UTRs. Orange framed rectangles indicate actin-coding sequences outside of the CDS. Full article ">Figure 2
Phylogenetic tree built using the Ensembl genomic sequence of the 14 human POTE genes from exons 1 to 3. For each paralog, the Ensembl ID is indicated together with the approved symbol. Colored circles indicate the four different groups: red for group I, blue for group II, yellow for group III, and green for group IV. The estimated log likelihood value of the topology shown is −19,591.8948. The tree is drawn to scale, with branch lengths measured in the relative number of substitutions per site. Full article ">Figure 3
(A) FISH validation of the fosmid clone ABC12-49207800H13 (in red) in human, chimpanzee, gorilla, and orangutan. (B) Parasight view of the CJA BAC CH259-195P19. Red lines show internal duplications. The gray bar indicates the POTE gene content, with coding (colored) and noncoding (dark gray) exons shown as vertical bars. Yellow and purple blocks show the most continuous portion (96 kb) of the marmoset reference genome where the BAC maps. The human POTE RefSeq mapping is shown in blue. (C) FISH results of the clone CH259-195P19 (in red) in marmoset. Full article ">Figure 4
LINE contents of the 14 human POTE genes are displayed under each gene representation. The LINEs annotated as black blocks represent less frequent elements, thus not explained in the color legend at the bottom of the figure. Full article ">Figure 5
Phylogenetic tree built using the Ensembl genomic sequence from exons 1 to 3 of the collected human and nonhuman primate POTE genes. CH259-195P19_g1 and CH259-195P19_g2 sequences are based on the Augustus prediction; all the others have been retrieved from the Ensembl browser. For each paralog, the Ensembl ID is indicated together with the approved symbol. Colored circles indicate the four different groups: red for group I, blue for group II, yellow for group III, and green for group IV. The estimated log likelihood value of the topology shown is −74,555.8895. The tree is drawn to scale, with branch lengths measured as the relative number of substitutions per site. Full article ">Figure 6
Evolutionary model of the POTE gene family. The emergence of each POTE copy, the actin module fusion, the full-sized LIR, and the group III intraduplication are described. Colored circles indicate the four different groups: red for group I, blue for group II, yellow for group III, and green for group IV. Purple circles represent POTE paralogs that have not been assigned to specific groups due to the lack of sequence data. Full article ">

11 pages, 1815 KiB G Mutation—A Post-Mortem Genotype–Phenotype Analysis" data-journal="genes">

Open AccessArticle

Heteroplasmy and Copy Number in the Common m.3243A>G Mutation—A Post-Mortem Genotype–Phenotype Analysis

by Leila Motlagh Scholle, Stephan Zierz, Christian Mawrin, Claudia Wickenhauser and Diana Lehmann Urban

Genes 2020, 11(2), 212; https://doi.org/10.3390/genes11020212 - 18 Feb 2020

Cited by 30 | Viewed by 3980

Abstract

Different mitochondrial DNA (mtDNA) mutations have been identified to cause mitochondrial encephalopathy, lactate acidosis and stroke-like episodes (MELAS). The underlying genetic cause leading to an enormous clinical heterogeneity associated with m.3243A>G-related mitochondrial diseases is still poorly understood. Genotype–phenotype correlation (heteroplasmy levels and clinical [...] Read more.

Different mitochondrial DNA (mtDNA) mutations have been identified to cause mitochondrial encephalopathy, lactate acidosis and stroke-like episodes (MELAS). The underlying genetic cause leading to an enormous clinical heterogeneity associated with m.3243A>G-related mitochondrial diseases is still poorly understood. Genotype–phenotype correlation (heteroplasmy levels and clinical symptoms) was analysed in 16 patients (15 literature cases and one unreported case) harbouring the m.3243A>G mutation. mtDNA copy numbers were correlated to heteroplasmy levels in 30 different post-mortem tissue samples, including 14 brain samples of a 46-year-old female. In the central nervous system, higher levels of heteroplasmy correlated significantly with lower mtDNA copy numbers. Skeletal muscle levels of heteroplasmy correlated significantly with kidney and liver. There was no significant difference of heteroplasmy levels between clinically affected and unaffected patients. In the patient presented, we found >75% heteroplasmy levels in all central nervous system samples, without harbouring a MELAS phenotype. This underlines previous suggestions, that really high levels in tissues do not automatically lead to a specific phenotype. Missing significant differences of heteroplasmy levels between clinically affected and unaffected patients underline recent suggestions that there are additional factors such as mtDNA copy number and nuclear factors that may also influence disease severity. Full article

(This article belongs to the Special Issue Forensic Mitochondrial Genomics)

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Figure 1
Correlation of heteroplasmy levels (%) and mtDNA copy number (MT-ND1/18S5) in the central nervous system tissue (black circles) and in the peripheral tissues (red circles) from the case report patient. In both the central nervous system samples and the peripheral tissues, higher levels of heteroplasmy correlated with lower mtDNA copy number, however only significantly in the central nervous system samples (p < 0.05). Full article ">Figure 2
m.3243A>G heteroplasmy levels across literature cases with regard to tissues and clinical phenotype MELAS (mitochondrial encephalopathy, lactate acidosis and stroke-like episodes) versus non-MELAS. Full article ">Figure 3
Correlation of heteroplasmy levels (%) in skeletal muscle to levels in cardiac (p = n.s.), liver (p = 0.0156), kidney (p = 0.0100) and brain (p = n.s.), plotted on the left y-axis. Correlation of heteroplasmy levels (%) in muscle to deceased age (p = n.s.) is plotted on the right y-axis. n.s.: no significant. Full article ">Figure 4
(A) Heteroplasmy levels (%) of skeletal, cardiac and brain between MELAS and non-MELAS phenotype patients. Liver and kidney heteroplasmy levels were significantly different in MELAS (closed circles) and non-MELAS (open circles) phenotype patients. Liver (p < 0.05) and kidney (p < 0.05) heteroplasmy levels were significantly higher in the MELAS patients. (B) Heteroplasmy levels (%) of cardiac, brain and skeletal in clinically affected (closed circles) and unaffected patients (open circles), showing no significant difference between affected and unaffected patients. Full article ">

18 pages, 6036 KiB

Open AccessArticle

Inhibition of Angiotensin-Converting Enzyme Ameliorates Renal Fibrosis by Mitigating DPP-4 Level and Restoring Antifibrotic MicroRNAs

by Swayam Prakash Srivastava, Julie E. Goodwin, Keizo Kanasaki and Daisuke Koya

Genes 2020, 11(2), 211; https://doi.org/10.3390/genes11020211 - 18 Feb 2020

Cited by 63 | Viewed by 5378

Abstract

Two class of drugs 1) angiotensin-converting enzyme inhibitors (ACEis) and 2) angiotensin II receptor blockers (ARBs) are well-known conventional drugs that can retard the progression of chronic nephropathies to end-stage renal disease. However, there is a lack of comparative studies on the effects [...] Read more.

Two class of drugs 1) angiotensin-converting enzyme inhibitors (ACEis) and 2) angiotensin II receptor blockers (ARBs) are well-known conventional drugs that can retard the progression of chronic nephropathies to end-stage renal disease. However, there is a lack of comparative studies on the effects of ACEi versus ARB on renal fibrosis. Here, we observed that ACEi ameliorated renal fibrosis by mitigating DPP-4 and TGFβ signaling, whereas, ARB did not show. Moreover, the combination of N-acetyl-seryl-aspartyl-lysyl-proline (AcSDKP), one of the substrates of ACE, with ACEi slightly enhanced the inhibitory effects of ACEi on DPP-4 and associated-TGFβ signaling. Further, the comprehensive miRome analysis in kidneys of ACEi+AcSDKP (combination) treatment revealed the emergence of miR-29s and miR-let-7s as key antifibrotic players. Treatment of cultured cells with ACEi alone or in combination with AcSDKP prevented the downregulated expression of miR-29s and miR-let-7s induced by TGFβ stimulation. Interestingly, ACEi also restored miR-29 and miR-let-7 family cross-talk in endothelial cells, an effect that is shared by AcSDKP suggesting that AcSDKP may be partially involved in the anti-mesenchymal action of ACEi. The results of the present study promise to advance our understanding of how ACEi regulates antifibrotic microRNAs crosstalk and DPP-4 associated-fibrogenic processes which is a critical event in the development of diabetic kidney disease. Full article

(This article belongs to the Collection microRNA Omnibus)

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3 pages, 177 KiB

Open AccessEditorial

Form from Function, Order from Chaos in Male Germline Chromatin

by Peter J. I. Ellis and Darren K. Griffin

Genes 2020, 11(2), 210; https://doi.org/10.3390/genes11020210 - 18 Feb 2020

Cited by 1 | Viewed by 2223

Abstract

Spermatogenesis requires radical restructuring of germline chromatin at multiple stages, involving co-ordinated waves of DNA methylation and demethylation, histone modification, replacement and removal occurring before, during and after meiosis. This Special Issue has drawn together papers addressing many aspects of chromatin organization and [...] Read more.

Spermatogenesis requires radical restructuring of germline chromatin at multiple stages, involving co-ordinated waves of DNA methylation and demethylation, histone modification, replacement and removal occurring before, during and after meiosis. This Special Issue has drawn together papers addressing many aspects of chromatin organization and dynamics in the male germ line, in humans and in model organisms. Two major themes emerge from these studies: the first is the functional significance of nuclear organisation in the developing germline; the second is the interplay between sperm chromatin structure and susceptibility to DNA damage and mutation. The consequences of these aspects for fertility, both in humans and other animals, is a major health and social welfare issue and this is reflected in these nine exciting manuscripts. Full article

(This article belongs to the Special Issue Male Germline Chromatin)

21 pages, 2692 KiB

Open AccessReview

Transforming Ocean Conservation: Applying the Genetic Rescue Toolkit

by Ben J. Novak, Devaughn Fraser and Thomas H. Maloney

Genes 2020, 11(2), 209; https://doi.org/10.3390/genes11020209 - 18 Feb 2020

Cited by 11 | Viewed by 8244

Abstract

Although oceans provide critical ecosystem services and support the most abundant populations on earth, the extent of damage impacting oceans and the diversity of strategies to protect them is disconcertingly, and disproportionately, understudied. While conventional modes of conservation have made strides in mitigating [...] Read more.

Although oceans provide critical ecosystem services and support the most abundant populations on earth, the extent of damage impacting oceans and the diversity of strategies to protect them is disconcertingly, and disproportionately, understudied. While conventional modes of conservation have made strides in mitigating impacts of human activities on ocean ecosystems, those strategies alone cannot completely stem the tide of mounting threats. Biotechnology and genomic research should be harnessed and developed within conservation frameworks to foster the persistence of viable ocean ecosystems. This document distills the results of a targeted survey, the Ocean Genomics Horizon Scan, which assessed opportunities to bring novel genetic rescue tools to marine conservation. From this Horizon Scan, we have identified how novel approaches from synthetic biology and genomics can alleviate major marine threats. While ethical frameworks for biotechnological interventions are necessary for effective and responsible practice, here we primarily assessed technological and social factors directly affecting technical development and deployment of biotechnology interventions for marine conservation. Genetic insight can greatly enhance established conservation methods, but the severity of many threats may demand genomic intervention. While intervention is controversial, for many marine areas the cost of inaction is too high to allow controversy to be a barrier to conserving viable ecosystems. Here, we offer a set of recommendations for engagement and program development to deploy genetic rescue safely and responsibly. Full article

(This article belongs to the Section Technologies and Resources for Genetics)

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Figure 1
The Genetic Rescue Toolkit Continuum of “Readiness”. A qualitative framework for assessing the technological and sociopolitical/economic factors influencing the readiness and deployment of applications within the Genetic Rescue Toolkit. Triangles denote genetic insight applications and diamonds indicate genomic intervention applications. The sociopolitical/economic axis encompasses consideration of regulations, public perception, cultural influence, and economic factors on the gradient of resistance to use these applications, the left-hand side being acceptable tools and the right-hand being applications met with higher levels of concern. With particular technological developments all these tools can be refined to deployable states, but while social and ethical engagement will improve many tools to acceptable consensus, some tools will face persistent resistance from certain stakeholders for reasons other than safety or efficacy (e.g., ideologies opposing human intervention in nature). Full article ">Figure 2
Comparing actual marine animal biodiversity to sequenced marine animal genomes. (A) Presents the proportionate taxonomic biodiversity of all accepted marine species [<a href="#B89-genes-11-00209" class="html-bibr">89</a>]. (B) Presents the breakdown of marine animal genome assemblies deposited to the National Center for Biotechnology Information as of September 2019. Eleven of the phyla in (A) (including one major and ten minor) have yet had a single genome sequenced and assembled. These include Bryozoa, Sipuncula, Nematomorpha, Gnathostomulida, Gastrotricha, Entoprocta, Dicyemida, Cycliophora, Chaetognatha, Aschelminthes. Several of these missing phyla are entirely marine, meaning they are wholly unrepresented in genomics. Outer circles of (A,B) delineate nonchordate invertebrates (dark gray) from the phyla chordata (light gray), which has been further subdivided, revealing a gross over-representation of sequenced genomes for vertebrate classes compared to entire invertebrate phyla. Full article ">Figure 3
Global Distributions of Coral Reefs and Kelp Forests. (A) Presents northern California kelp forest loss from 2008 to 2016. (B) Presents the first consecutive severe bleaching event in Great Barrier Reef Survey history from 2016 and 2017. Sources of maps and graphs: [<a href="#B104-genes-11-00209" class="html-bibr">104</a>,<a href="#B105-genes-11-00209" class="html-bibr">105</a>], California Department of Fish and Wildlife Marine Management Team Aerial Surveys, and Australian Institute of Marine Science (AIMS). Full article ">

14 pages, 2496 KiB

Open AccessReview

Cas3 Protein—A Review of a Multi-Tasking Machine

by Liu He, Michael St. John James, Marin Radovcic, Ivana Ivancic-Bace and Edward L. Bolt

Genes 2020, 11(2), 208; https://doi.org/10.3390/genes11020208 - 18 Feb 2020

Cited by 20 | Viewed by 7300

Abstract

Cas3 has essential functions in CRISPR immunity but its other activities and roles, in vitro and in cells, are less widely known. We offer a concise review of the latest understanding and questions arising from studies of Cas3 mechanism during CRISPR immunity, and [...] Read more.

Cas3 has essential functions in CRISPR immunity but its other activities and roles, in vitro and in cells, are less widely known. We offer a concise review of the latest understanding and questions arising from studies of Cas3 mechanism during CRISPR immunity, and highlight recent attempts at using Cas3 for genetic editing. We then spotlight involvement of Cas3 in other aspects of cell biology, for which understanding is lacking—these focus on CRISPR systems as regulators of cellular processes in addition to defense against mobile genetic elements. Full article

(This article belongs to the Special Issue CRISPR-Cas: Interactions with Genome and Physiological Maintenance)

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Figure 1

Figure 1
A summary of Cas3 as covered in this review. A. The main events in CRISPR-Cas systems that use Cas3. DNA from a mobile genetic element (bacteriophage shown here) is captured and integrated into a CRISPR locus by “Adaptation”, catalyzed by Cas1-Cas2 proteins helped by various non-Cas host proteins. Transcription of CRISPR generates RNA that after further processing is called CRISPR RNA (crRNA) that is loaded into a multi-protein effector complex, forming “Cascade”, which targets crRNA to the invader DNA. Cascade recruits Cas3 to targeted DNA forming the “Interference” complex that degrades DNA and in so doing can provide DNA for capture by Cas1-Cas2. We highlight Cas3 within the interference complex, leading into part B., illustrating that studies of Cas3 enzymology in vitro have detailed Cas3 mechanism when associated with Cascade and in isolation. Genetic analyses of the cas3 gene and its regulation in bacteria (e.g., by HtpG and H-NS) provoke ideas for additional roles of Cas3 in natural cellular physiology and in biotechnology. In the figure we highlight experimental observations that indicate potential roles for Cas3 in RNA processing and biofilm formation, and usefulness in genetic editing reactions. Full article ">Figure 2
Cas3 structure-function. A. PHYRE2-predicted Escherichia coli Cas3 structure, modeled from Cas3 structures solved from Thermobaculum terrenum (PDB 4Q2C) and Thermobifida fusca (PDB 4QQW, 4QQX and 4QQY), represented in two orientations and with a corresponding cartoon of primary sequence presented below. We highlight the HD domain (purple), two RecA-like domains (green and orange) and the accessory C-terminal domain (CTD, pale blue). Active sites comprising the Asp-His HD domain and the amino acid DEVH motif of one RecA-like domain for ATP-hydrolysis are highlighted in red spheres within the structures, and marked on the cartoon primary structure. Also marked are the prominent solvent-exposed alpha helix (ACH) and an arginine rich channel (ARC) described in the main text. B. Panels should be followed from top left, clockwise. The location of Cas3 (using same domain colors as used in part A) bound to Cascade subunit protein Cse1 (grey), presented from the T. fusca Cascade-Cas3 structure (PDB: 6C66). DNA parts of the R-loop are colored orange—in CRISPR interference this DNA is nicked by the Cas3 HD domain, and then assimilated into the translocase/helicase active sites, possibly via interaction between DNA and the arginine residues of the ‘ARC’, highlighted as blue spheres. Captured single-strand DNA (ssDNA) is then translocated through the Cas3 protein by a reeling mechanism, which is associated with nuclease activity that generates DNA fragments. Full article ">Figure 3
Temperature-dependent Cas3/CRISPR functions in E. coli and the E. coli Δhns strain. A. Cas3 stimulates uncontrolled ColE1 plasmid replication in a temperature-dependent manner. ColE1 plasmid yield was stimulated by Cas3 in cells at 37 °C but not at 30 °C. This requires a functional helicase domain. We speculate that this phenomenon may indicate a possible change in Cas3 conformational ‘state’, illustrated by coloring Cas3 in blue ‘demotivated’ or red ‘motivated’. At 37 °C, ‘motivated’ Cas3 may interact with R-loop formation in ori by dissociating RNA II from the complementary strand, and lead to increased plasmid replication in vitro. B. Temperature impacts CRISPR function in E. coli cells lacking H-NS. This Δhns strain at 30 °C can defend against invader DNA during phage infection, even though Cas3 is in ‘unmotivated’ state. However, Δhns strain cannot survive under infection pressure at 37 °C. Full article ">Figure 3 Cont.
Temperature-dependent Cas3/CRISPR functions in E. coli and the E. coli Δhns strain. A. Cas3 stimulates uncontrolled ColE1 plasmid replication in a temperature-dependent manner. ColE1 plasmid yield was stimulated by Cas3 in cells at 37 °C but not at 30 °C. This requires a functional helicase domain. We speculate that this phenomenon may indicate a possible change in Cas3 conformational ‘state’, illustrated by coloring Cas3 in blue ‘demotivated’ or red ‘motivated’. At 37 °C, ‘motivated’ Cas3 may interact with R-loop formation in ori by dissociating RNA II from the complementary strand, and lead to increased plasmid replication in vitro. B. Temperature impacts CRISPR function in E. coli cells lacking H-NS. This Δhns strain at 30 °C can defend against invader DNA during phage infection, even though Cas3 is in ‘unmotivated’ state. However, Δhns strain cannot survive under infection pressure at 37 °C. Full article ">

13 pages, 2314 KiB

Open AccessArticle

Evolution of the Small Family of Alternative Splicing Modulators Nuclear Speckle RNA-Binding Proteins in Plants

by Leandro Lucero, Jeremie Bazin, Johan Rodriguez Melo, Fernando Ibañez, Martín D. Crespi and Federico Ariel

Genes 2020, 11(2), 207; https://doi.org/10.3390/genes11020207 - 18 Feb 2020

Cited by 11 | Viewed by 3453

Abstract

RNA-Binding Protein 1 (RBP1) was first identified as a protein partner of the long noncoding RNA (lncRNA) ENOD40 in Medicago truncatula, involved in symbiotic nodule development. RBP1 is localized in nuclear speckles and can be relocalized to the cytoplasm by the interaction [...] Read more.

RNA-Binding Protein 1 (RBP1) was first identified as a protein partner of the long noncoding RNA (lncRNA) ENOD40 in Medicago truncatula, involved in symbiotic nodule development. RBP1 is localized in nuclear speckles and can be relocalized to the cytoplasm by the interaction with ENOD40. The two closest homologs to RBP1 in Arabidopsis thaliana were called Nuclear Speckle RNA-binding proteins (NSRs) and characterized as alternative splicing modulators of specific mRNAs. They can recognize in vivo the lncRNA ALTERNATIVE SPLICING COMPETITOR (ASCO) among other lncRNAs, regulating lateral root formation. Here, we performed a phylogenetic analysis of NSR/RBP proteins tracking the roots of the family to the Embryophytes. Strikingly, eudicots faced a reductive trend of NSR/RBP proteins in comparison with other groups of flowering plants. In Medicago truncatula and Lotus japonicus, their expression profile during nodulation and in specific regions of the symbiotic nodule was compared to that of the lncRNA ENOD40, as well as to changes in alternative splicing. This hinted at distinct and specific roles of each member during nodulation, likely modulating the population of alternatively spliced transcripts. Our results establish the basis to guide future exploration of NSR/RBP function in alternative splicing regulation in different developmental contexts along the plant lineage. Full article

(This article belongs to the Special Issue Genetic Evolution of Root Nodule Symbioses)

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Figure 1
Nuclear Speckle RNA-binding proteins NSR phylogeny of selected eudicot families and motif analysis of NSR proteins in vascular plants. (A) Maximum likelihood tree of NSR proteins in Fabaceae; M. truncatula sequences are bolded. Bootstrap values are indicated above branches. (B) Protein motifs’ occurrence in land plants. The 21 conserved motifs identified with MEME are detailed in <a href="#app1-genes-11-00207" class="html-app">Supplementary Figure S3</a>. (C) Comparison of motifs 1 and 9 depicting conserved amino acid residues shared between both motifs (see the text for more explanation). (D) Weblogo of motifs 3 and 6 exclusive to flowering plants. The Nuclear Localization Signaling (NLS) can be visualized in position four to seven of motif 6. Full article ">Figure 2
Gene structure and alternatively spliced variants of NSR genes and their expression profile, together with the lncRNAs ENOD40 of Medicago truncatula and Lotus japonicus during nodulation. (A) Exon-intron structure of NSRs genes in both species. The alternative splicing variant LjNSR2.2 includes part of exon 4 and exons 5 and 6, which coded for motif 1 (blue box) and motif 2 (orange box). (B) Heat map of NSRs and ENOD40 expression in inoculated roots of M. truncatula [<a href="#B17-genes-11-00207" class="html-bibr">17</a>]. (C) Heat map of L. japonicus NSR1.1, NSR1.2, NSR2, ENOD40-1, and ENOD40-2 expression in root hairs post inoculation with rhizobia, (D) in a time course of nodule formation (7 dpi = nodule primordia, 24 dpi = fixing nodule), and (E) in response to exogenous treatment with Nod factors [<a href="#B18-genes-11-00207" class="html-bibr">18</a>]. For C to E, the Heatmap shows the mean of normalized expression (Transcript Per Million reads (TPM)) for all replicates for each time point. dpi stands for days post inoculation. hpi stands for hours post inoculation. Full article ">Figure 3
Expression pattern of NSR genes and the lncRNA ENOD40 in each zone of the Medicago truncatula mature nodule, based on [<a href="#B16-genes-11-00207" class="html-bibr">16</a>]. (A) Schematic representation of a transversal cut of a M. truncatula root and mature nodule, indicating the zones isolated by laser micro-dissection. Fraction I (FI) corresponds to the nodule meristematic zone; the zones below FI correspond to samples collected as a distal and a proximal Fraction (FIId and FIIp, respectively) and corresponding to cells undergoing differentiation or infection; the Interzone (IZ) separates the fractions above from the nitrogen-fixation zone ZIII. (B) Relative transcript levels of NSR1, NSR2, and ENOD40 in each zone of the mature nodule. (C) Absolute levels of the same genes shown in B. Full article ">Figure 4
Alternatively processed mRNAs profile during nodule development in M. truncatula and L. japonicus. Alternative isoforms between samples were identified using SUPPA. The number of genes or events (indistinguishable from what gene) suffering Differential Alternative Splicing (DAS) were scored in (A) M. truncatula and (B) L. japonicus. A3 and A5 stand for Alternative processing of the 5′ and 3′ ends, respectively; IR stands for Intron Retention; MX stands for Mutually exclusive Exons, and ES stands for Exon Skipping. The identity of the DAS genes was compared between samples showing little overlapping in (C) M. truncatula and (D) L. japonicus. Full article ">

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Genes, Volume 11, Issue 2 (February 2020) – 121 articles

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