scholarly journals Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids

2020 ◽  
Author(s):  
Guanjing Hu ◽  
Corrinne E Grover ◽  
Mark A Arick ◽  
Meiling Liu ◽  
Daniel G Peterson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Duplicate Gene ◽  
Network Analyses ◽  
Construction Methods ◽  
Gene Copies ◽  
Evolutionary Inference ◽  
Expression Evolution ◽  
Widespread Phenomenon ◽  
Downstream Analysis ◽  
Binary Networks

Abstract Polyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, EAGLE-RC and GSNAP-PolyCat outperform other quantification pipelines tested, and their derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an overestimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.

scholarly journals Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids

2019 ◽  
Author(s):  
Guanjing Hu ◽  
Corrinne E. Grover ◽  
Mark A. Arick ◽  
Meiling Liu ◽  
Daniel G. Peterson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Duplicate Gene ◽  
Network Analyses ◽  
Construction Methods ◽  
Gene Copies ◽  
Evolutionary Inference ◽  
Expression Evolution ◽  
Widespread Phenomenon ◽  
Downstream Analysis ◽  
Binary Networks

ABSTRACTPolyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, GSNAP-PolyCat outperforms other quantification pipelines tested, and its derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an over-estimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.

scholarly journals Learning retention mechanisms and evolutionary parameters of duplicate genes from their expression data

2020 ◽  
Author(s):  
Michael DeGiorgio ◽  
Raquel Assis
Keyword(s):  
Gene Expression ◽  
Gene Duplication ◽  
Statistical Learning ◽  
Gene Evolution ◽  
Functional Divergence ◽  
Duplicate Gene ◽  
Duplicate Genes ◽  
Evolutionary Mechanisms ◽  
Retention Mechanisms ◽  
Gene Copies

AbstractLearning about the roles that duplicate genes play in the origins of novel phenotypes requires an understanding of how their functions evolve. To date, only one method—CDROM—has been developed with this goal in mind. In particular, CDROM employs gene expression distances as proxies for functional divergence, and then classifies the evolutionary mechanisms retaining duplicate genes from comparisons of these distances in a decision tree framework. However, CDROM does not account for stochastic shifts in gene expression or leverage advances in contemporary statistical learning for performing classification, nor is it capable of predicting the underlying parameters of duplicate gene evolution. Thus, here we develop CLOUD, a multi-layer neural network built upon a model of gene expression evolution that can both classify duplicate gene retention mechanisms and predict their underlying evolutionary parameters. We show that not only is the CLOUD classifier substantially more powerful and accurate than CDROM, but that it also yields accurate parameter predictions, enabling a better understanding of the specific forces driving the evolution and long-term retention of duplicate genes. Further, application of the CLOUD classifier and predictor to empirical data from Drosophila recapitulates many previous findings about gene duplication in this lineage, showing that new functions often emerge rapidly and asymmetrically in younger duplicate gene copies, and that functional divergence is driven by strong natural selection. Hence, CLOUD represents the best available method for classifying retention mechanisms and predicting evolutionary parameters of duplicate genes, thereby also highlighting the utility of incorporating sophisticated statistical learning techniques to address long-standing questions about evolution after gene duplication.

scholarly journals Gene expression shapes the patterns of parallel evolution of herbicide resistance in the agricultural weedMonochoria vaginalis

2021 ◽  
Author(s):  
Shinji Tanigaki ◽  
Akira Uchino ◽  
Shigenori Okawa ◽  
Chikako Miura ◽  
Kenshiro Hamamura ◽  
...  
Keyword(s):  
Gene Expression ◽  
Herbicide Resistance ◽  
Parallel Evolution ◽  
Acetolactate Synthase ◽  
Duplicate Gene ◽  
Target Site ◽  
Loss Of Function ◽  
Functional Characterisation ◽  
Gene Copies ◽  
Key Factor

AbstractThe evolution of herbicide resistance in weeds is an example of parallel evolution, through which genes encoding herbicide target proteins are repeatedly represented as evolutionary loci. The number of herbicide target-site genes differs among species, and little is known regarding the effects of duplicate gene copies on the evolution of herbicide resistance. We investigated the evolution of herbicide resistance inMonochoria vaginalis, which carries five copies of sulfonylurea target-site acetolactate synthase (ALS) genes. Suspected resistant populations collected across Japan were investigated for herbicide sensitivity andALSgene sequences, followed by functional characterisation andALSgene expression analysis. We identified over 60 resistant populations, all of which carried resistance-conferring amino acid substitutions exclusively inMvALS1orMvALS3. AllMvALS4alleles carried a loss-of-function mutation. Although the enzymatic properties of ALS encoded by these genes were not markedly different, the expression ofMvALS1andMvALS3was prominently higher among allALSgenes. The higher expression ofMvALS1andMvALS3is the driving force of the biased representation of genes during the evolution of herbicide resistance inM. vaginalis. Our findings highlight that gene expression is a key factor in creating evolutionary hotspots.

scholarly journals Integrative genomics reveals paths to sex dimorphism in Salix purpurea L

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Brennan Hyden ◽  
Craig H. Carlson ◽  
Fred E. Gouker ◽  
Jeremy Schmutz ◽  
Kerrie Barry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sex Determination ◽  
Bisulfite Sequencing ◽  
Epigenetic Modification ◽  
Small Rna Sequencing ◽  
Regulation Of Transcription ◽  
Eqtl Analysis ◽  
Sex Dimorphism ◽  
Network Analyses ◽  
Salix Purpurea

AbstractSex dimorphism and gene expression were studied in developing catkins in 159 F2 individuals from the bioenergy crop Salix purpurea, and potential mechanisms and pathways for regulating sex development were explored. Differential expression, eQTL, bisulfite sequencing, and network analysis were used to characterize sex dimorphism, detect candidate master regulator genes, and identify pathways through which the sex determination region (SDR) may mediate sex dimorphism. Eleven genes are presented as candidates for master regulators of sex, supported by gene expression and network analyses. These include genes putatively involved in hormone signaling, epigenetic modification, and regulation of transcription. eQTL analysis revealed a suite of transcription factors and genes involved in secondary metabolism and floral development that were predicted to be under direct control of the sex determination region. Furthermore, data from bisulfite sequencing and small RNA sequencing revealed strong differences in expression between males and females that would implicate both of these processes in sex dimorphism pathways. These data indicate that the mechanism of sex determination in Salix purpurea is likely different from that observed in the related genus Populus. This further demonstrates the dynamic nature of SDRs in plants, which involves a multitude of mechanisms of sex determination and a high rate of turnover.

scholarly journals Molecular pathology associated with altered synaptic transcriptome in the dorsolateral prefrontal cortex of depressed subjects

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuta Yoshino ◽  
Bhaskar Roy ◽  
Nilesh Kumar ◽  
M. Shahid Mukhtar ◽  
Yogesh Dwivedi
Keyword(s):  
Gene Expression ◽  
Cell Death ◽  
Prefrontal Cortex ◽  
Dorsolateral Prefrontal Cortex ◽  
Gene Network ◽  
Nervous System Development ◽  
Network Analyses ◽  
Dorsolateral Prefrontal ◽  
Total Fraction ◽  
Transcriptomic Changes

AbstractDisrupted synaptic plasticity is the hallmark of major depressive disorder (MDD), with accompanying changes at the molecular and cellular levels. Often, the maladaptive molecular changes at the synapse are the result of global transcriptional reprogramming dictated by activity-dependent synaptic modulation. Thus far, no study has directly studied the transcriptome-wide expression changes locally at the synapse in MDD brain. Here, we have examined altered synaptic transcriptomics and their functional relevance in MDD with a focus on the dorsolateral prefrontal cortex (dlPFC). RNA was isolated from total fraction and purified synaptosomes of dlPFC from well-matched 15 non-psychiatric controls and 15 MDD subjects. Transcriptomic changes in synaptic and total fractions were detected by next-generation RNA-sequencing (NGS) and analyzed independently. The ratio of synaptic/total fraction was estimated to evaluate a shift in gene expression ratio in MDD subjects. Bioinformatics and network analyses were used to determine the biological relevance of transcriptomic changes in both total and synaptic fractions based on gene–gene network, gene ontology (GO), and pathway prediction algorithms. A total of 14,005 genes were detected in total fraction. A total of 104 genes were differentially regulated (73 upregulated and 31 downregulated) in MDD group based on 1.3-fold change threshold and p < 0.05 criteria. In synaptosomes, out of 13,236 detectable genes, 234 were upregulated and 60 were downregulated (>1.3-fold, p < 0.05). Several of these altered genes were validated independently by a quantitative polymerase chain reaction (qPCR). GO revealed an association with immune system processes and cell death. Moreover, a cluster of genes belonged to the nervous system development, and psychological disorders were discovered using gene–gene network analysis. The ratio of synaptic/total fraction showed a shift in expression of 119 genes in MDD subjects, which were primarily associated with neuroinflammation, interleukin signaling, and cell death. Our results suggest not only large-scale gene expression changes in synaptosomes, but also a shift in the expression of genes from total to synaptic fractions of dlPFC of MDD subjects with their potential role in immunomodulation and cell death. Our findings provide new insights into the understanding of transcriptomic regulation at the synapse and their possible role in MDD pathogenesis.

scholarly journals Microtubule Dynamics Plays a Vital Role in Plant Adaptation and Tolerance to Salt Stress

2021 ◽  
Vol 22 (11) ◽  
pp. 5957
Author(s):  
Hyun Jin Chun ◽  
Dongwon Baek ◽  
Byung Jun Jin ◽  
Hyun Min Cho ◽  
Mi Suk Park ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Wall ◽  
Salt Stress ◽  
Differentially Expressed ◽  
Differentially Expressed Proteins ◽  
Related Gene ◽  
Plant Adaptation ◽  
Salt Stress Response ◽  
Network Analyses ◽  
Cell Wall Biogenesis

Although recent studies suggest that the plant cytoskeleton is associated with plant stress responses, such as salt, cold, and drought, the molecular mechanism underlying microtubule function in plant salt stress response remains unclear. We performed a comparative proteomic analysis between control suspension-cultured cells (A0) and salt-adapted cells (A120) established from Arabidopsis root callus to investigate plant adaptation mechanisms to long-term salt stress. We identified 50 differentially expressed proteins (45 up- and 5 down-regulated proteins) in A120 cells compared with A0 cells. Gene ontology enrichment and protein network analyses indicated that differentially expressed proteins in A120 cells were strongly associated with cell structure-associated clusters, including cytoskeleton and cell wall biogenesis. Gene expression analysis revealed that expressions of cytoskeleton-related genes, such as FBA8, TUB3, TUB4, TUB7, TUB9, and ACT7, and a cell wall biogenesis-related gene, CCoAOMT1, were induced in salt-adapted A120 cells. Moreover, the loss-of-function mutant of Arabidopsis TUB9 gene, tub9, showed a hypersensitive phenotype to salt stress. Consistent overexpression of Arabidopsis TUB9 gene in rice transgenic plants enhanced tolerance to salt stress. Our results suggest that microtubules play crucial roles in plant adaptation and tolerance to salt stress. The modulation of microtubule-related gene expression can be an effective strategy for developing salt-tolerant crops.

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