scholarly journals Genetic regulation of transcriptional variation in natural Arabidopsis thaliana accessions

2016 ◽  
Author(s):  
Yanjun Zan ◽  
Xia Shen ◽  
Simon K. G. Forsberg ◽  
Örjan Carlborg
Keyword(s):  
Arabidopsis Thaliana ◽  
Genetic Regulation ◽  
Global Gene Expression ◽  
Structural Variations ◽  
Regulation Of Expression ◽  
Cis Acting ◽  
Rna Transcripts ◽  
Genome Wide ◽  
Transcriptional Variation ◽  
Genome Wide Data

AbstractAn increased knowledge of the genetic regulation of expression in Arabidopsis thaliana is likely to provide important insights about the basis of the plant’s extensive phenotypic variation. Here, we reanalysed two publicly available datasets with genome-wide data on genetic and transcript variation in large collections of natural A. thaliana accessions. Transcripts from more than half of all genes were detected in the leaf of all accessions, and from nearly all annotated genes in at least one accession. Thousands of genes had high transcript levels in some accessions but no transcripts at all in others and this pattern was correlated with the genome-wide genotype. In total, 2,669 eQTL were mapped in the largest population, and 717 of them were replicated in the other population. 646 cis-eQTLs regulated genes that lacked detectable transcripts in some accessions, and for 159 of these we identified one, or several, common structural variants in the populations that were shown to be likely contributors to the lack of detectable RNA-transcripts for these genes. This study thus provides new insights on the overall genetic regulation of global gene-expression diversity in the leaf of natural A. thaliana accessions. Further, it also shows that strong cis-acting polymorphisms, many of which are likely to be structural variations, make important contributions to the transcriptional variation in the worldwide A. thaliana population.

scholarly journals Genome-wide transcriptomic analysis reveals correlation between higher WRKY61 expression and reduced symptom severity in Turnip crinkle virus infected Arabidopsis thaliana

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ruimin Gao ◽  
Peng Liu ◽  
Yuhan Yong ◽  
Sek-Man Wong
Keyword(s):  
Arabidopsis Thaliana ◽  
Transcriptome Analysis ◽  
Plant Immunity ◽  
Plant Defence ◽  
Enrichment Analysis ◽  
Global Gene Expression ◽  
Chemical Stimulus ◽  
Turnip Crinkle Virus ◽  
Rna Seq ◽  
Genome Wide

Abstract Turnip crinkle virus (TCV) is a carmovirus that infects many Arabidopsis ecotypes. Most studies mainly focused on discovery of resistance genes against TCV infection and there is no Next Generation Sequencing based comparative genome wide transcriptome analysis reported. In this study, RNA-seq based transcriptome analysis revealed that 238 (155 up-regulated and 83 down-regulated) significant differentially expressed genes with at least 15-fold change were determined. Fifteen genes (including upregulated, unchanged and downregulated) were selected for RNA-seq data validation using quantitative real-time PCR, which showed consistencies between these two sets of data. GO enrichment analysis showed that numerous terms such as stress, immunity, defence and chemical stimulus were affected in TCV-infected plants. One putative plant defence related gene named WRKY61 was selected for further investigation. It showed that WRKY61 overexpression plants displayed reduced symptoms and less virus accumulation, as compared to wild type (WT) and WRKY61 deficient lines, suggesting that higher WRKY61 expression level reduced TCV viral accumulation. In conclusion, our transcriptome analysis showed that global gene expression was detected in TCV-infected Arabidopsis thaliana. WRKY61 gene was shown to be negatively correlated with TCV infection and viral symptoms, which may be connected to plant immunity pathways.

scholarly journals Machine learning approaches to identify sleep genes

2021 ◽  
Author(s):  
Yin Yeng Lee ◽  
Mehari Endale ◽  
Gang Wu ◽  
Marc D Ruben ◽  
Lauren J Francey ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prior Knowledge ◽  
Molecular Mechanisms ◽  
Genetic Regulation ◽  
Learning Approaches ◽  
Sleep Regulation ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Key Genes

Genetics impacts sleep, yet, the molecular mechanisms underlying sleep regulation remain elusive. We built machine learning (ML) models to predict genes based on their similarity to known sleep genes. Our predictions fit with prior knowledge of sleep regulation and also identify several key genes/pathways to pursue in follow-up studies. We tested one of our findings, the NF-κB pathway, and showed that its genetic alteration affects sleep duration in mice. Our study highlights the power of ML to integrate prior knowledge and genome-wide data to study genetic regulation of sleep and other complex behaviors.

scholarly journals Network Analysis Prioritizes DEWAX and ICE1 as the Candidate Genes for Major eQTL Hotspots in Seed Germination of Arabidopsis thaliana

2020 ◽  
Vol 10 (11) ◽  
pp. 4215-4226
Author(s):  
Margi Hartanto ◽  
Ronny V. L. Joosen ◽  
Basten L. Snoek ◽  
Leo A. J. Willems ◽  
Mark G. Sterken ◽  
...  
Keyword(s):  
Gene Expression ◽  
Arabidopsis Thaliana ◽  
Network Analysis ◽  
Seed Germination ◽  
Recombinant Inbred Lines ◽  
Genetic Regulation ◽  
Regulation Of Gene Expression ◽  
Regulatory Genes ◽  
Regulation Of Expression ◽  
Trait Locus

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTL in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination.

scholarly journals Genome-wide profiling of stored mRNA in Arabidopsis thaliana seed germination: epigenetic and genetic regulation of transcription in seed

2005 ◽  
Vol 41 (5) ◽  
pp. 697-709 ◽  
Author(s):  
Kazumi Nakabayashi ◽  
Masanori Okamoto ◽  
Tomokazu Koshiba ◽  
Yuji Kamiya ◽  
Eiji Nambara
Keyword(s):  
Arabidopsis Thaliana ◽  
Seed Germination ◽  
Genetic Regulation ◽  
Regulation Of Transcription ◽  
Genome Wide ◽  
Stored Mrna

scholarly journals Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

2021 ◽  
Vol 7 (3) ◽  
pp. eabd9036
Author(s):  
Sara Saez-Atienzar ◽  
Sara Bandres-Ciga ◽  
Rebekah G. Langston ◽  
Jonggeol J. Kim ◽  
Shing Wan Choi ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Membrane Trafficking ◽  
Molecular Mechanisms ◽  
Cell Types ◽  
Polygenic Risk Score ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Data Driven Approach ◽  
Single Nucleus ◽  
Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

scholarly journals Ancient genomic time transect from the Central Asian Steppe unravels the history of the Scythians

2021 ◽  
Vol 7 (13) ◽  
pp. eabe4414
Author(s):  
Guido Alberto Gnecchi-Ruscone ◽  
Elmira Khussainova ◽  
Nurzhibek Kahbatkyzy ◽  
Lyazzat Musralina ◽  
Maria A. Spyrou ◽  
...  
Keyword(s):  
Bronze Age ◽  
Iron Age ◽  
Gene Pools ◽  
Social Rules ◽  
Eurasian Steppe ◽  
Central Asian ◽  
Genome Wide ◽  
Genome Wide Data ◽  
History Of ◽  
First Millennium

The Scythians were a multitude of horse-warrior nomad cultures dwelling in the Eurasian steppe during the first millennium BCE. Because of the lack of first-hand written records, little is known about the origins and relations among the different cultures. To address these questions, we produced genome-wide data for 111 ancient individuals retrieved from 39 archaeological sites from the first millennia BCE and CE across the Central Asian Steppe. We uncovered major admixture events in the Late Bronze Age forming the genetic substratum for two main Iron Age gene-pools emerging around the Altai and the Urals respectively. Their demise was mirrored by new genetic turnovers, linked to the spread of the eastern nomad empires in the first centuries CE. Compared to the high genetic heterogeneity of the past, the homogenization of the present-day Kazakhs gene pool is notable, likely a result of 400 years of strict exogamous social rules.

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