scholarly journals Environmental perturbations lead to extensive directional shifts in RNA processing

2017 ◽  
Author(s):  
A. L. Richards ◽  
D. Watza ◽  
A. Findley ◽  
A. Alazizi ◽  
X. Wen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Rna Processing ◽  
Complex Traits ◽  
Intron Retention ◽  
Vast Number ◽  
Factor Binding ◽  
Environmental Perturbations ◽  
Exon Usage ◽  
The Impact

AbstractEnvironmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in AFE usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.Author SummaryChanges in a cell’s environment and genetic variation have been shown to impact gene expression. Here, we demonstrate that environmental perturbations also lead to extensive changes in alternative RNA processing across a large number of cellular environments that we investigated. These changes often occur in a non-random manner. For example, many treatments lead to increased intron retention and usage of the downstream first exon. We also show that the changes to first exon usage are likely dependent on changes in transcription factor binding. We provide support for this hypothesis by considering how first exon usage is affected by disruption of binding due to treatment with selenium. We further validate the role of a specific factor by considering the effect of genetic variation in its binding sites on first exon usage. These results help to shed light on the vast number of changes that occur in response to environmental stimuli and will likely aid in understanding the impact of compounds to which we are daily exposed.

scholarly journals Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits

2018 ◽  
Author(s):  
Eilis Hannon ◽  
Tyler J Gorrie-Stone ◽  
Melissa C Smart ◽  
Joe Burrage ◽  
Amanda Hughes ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Genetic Variation ◽  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Common Genetic Variation ◽  
Online Data ◽  
The Relationship ◽  
Methylation Quantitative Trait Loci

ABSTRACTCharacterizing the complex relationship between genetic, epigenetic and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. In this study, we describe the most comprehensive analysis of common genetic variation on DNA methylation (DNAm) to date, using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (P < 6.52x10-14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified using previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits, using Summary data–based Mendelian Randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression, identifying 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database (http://www.epigenomicslab.com/online-data-resources/) as a resource to the research community.

scholarly journals Imputed gene associations identify replicable trans-acting genes enriched in transcription pathways and complex traits

2018 ◽  
Author(s):  
Heather E. Wheeler ◽  
Sally Ploch ◽  
Alvaro N. Barbeira ◽  
Rodrigo Bonazzola ◽  
Angela Andaleon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Complex Traits ◽  
Target Gene ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nucleic Acid Binding ◽  
Expression Of Genes ◽  
Gene Associations ◽  
Made In

AbstractRegulation of gene expression is an important mechanism through which genetic variation can affect complex traits. A substantial portion of gene expression variation can be explained by both local (cis) and distal (trans) genetic variation. Much progress has been made in uncovering cis-acting expression quantitative trait loci (cis-eQTL), but trans-eQTL have been more difficult to identify and replicate. Here we take advantage of our ability to predict the cis component of gene expression coupled with gene mapping methods such as PrediXcan to identify high confidence candidate trans-acting genes and their targets. That is, we correlate the cis component of gene expression with observed expression of genes in different chromosomes. Leveraging the shared cis-acting regulation across tissues, we combine the evidence of association across all available GTEx tissues and find 2356 trans-acting/target gene pairs with high mappability scores. Reassuringly, trans-acting genes are enriched in transcription and nucleic acid binding pathways and target genes are enriched in known transcription factor binding sites. Interestingly, trans-acting genes are more significantly associated with selected complex traits and diseases than target or background genes, consistent with percolating trans effects. Our scripts and summary statistics are publicly available for future studies of trans-acting gene regulation.

scholarly journals Splicing Control in Normal and Aberrant Erythropoiesis

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. SCI-47-SCI-47
Author(s):  
Esther Obeng
Keyword(s):  
Gene Expression ◽  
Rna Processing ◽  
Iron Transport ◽  
Rna Binding ◽  
Intron Retention ◽  
Point Mutations ◽  
Cytoskeletal Proteins ◽  
Mrna Splicing ◽  
Splice Sites ◽  
Erythroid Maturation

Abstract Alternative splicing is employed by all eukaryotic cells to increase proteome diversity and to regulate gene expression. RNA sequencing analysis of purified populations of erythroblasts at different stages of maturation has led to the identification of a dynamic alternative splicing program that directly modulates the protein isoform expression of cytoskeletal proteins and genes involved in RNA processing, heme biosynthesis, and iron transport. Regulated interactions of multiple RNA-binding proteins and cis-regulatory sequences located within exons or their flanking introns promote or inhibit functional spliceosome assembly at splice junctions, leading to altered exon inclusion or intron retention. Exon skipping regulates tissue and stage specific isoform expression of red cell membrane cytoskeletal proteins including EPB41, ankyrin, and band 3. Intron retention can lead to a frame shift during translation and introduction of a premature termination codon (PTC), that marks the transcript for degradation via the nonsense mediated decay pathway (NMD) upon export from the nucleus into the cytoplasm. Intron retention leading to posttranscriptional regulation of gene expression during terminal erythroid maturation has been identified in genes involved in RNA processing and iron transport including SF3B1, SNRNP70, SLC25A37 and SLC25A28. Mutations that alter mRNA splice sites or introduce PTCs lead to a variety of congenital anemias including beta thalassemia, hereditary pyropoikilocytosis, hereditary elliptocytosis, and hereditary spherocytosis. Aberrant mRNA splicing has subsequently been shown to lead to acquired anemias in subsets of patients with myelodysplastic syndromes (MDS). Somatic missense mutations in components of the spliceosome are the most common category of mutations in MDS. These point mutations lead to changes in the RNA binding specificity of the involved proteins and aberrant splicing of a subset of transcripts. Mutant SF3B1, the most commonly mutated splicing factor in MDS, has been shown to cause aberrant pre-mRNA splicing and an increase in transcripts predicted to undergo NMD due to use of upstream, cryptic 3' splice sites. Our group and others evaluating the strong genotype-phenotype association between SF3B1 point mutations and subtypes of MDS with ring sideroblasts have shown that the expression of the mitochondrial iron transporter, ABCB7, is decreased in samples from SF3B1-mutant MDS patients due to cryptic 3' splice site selection and introduction of a PTC between exons 8 and 9. The identification and functional validation of additional aberrantly spliced mutant-SF3B1 target genes is ongoing, with the goal of understanding how point mutations in a core component of the mRNA splicing machinery can lead to such specific effects on erythroid maturation. Disclosures No relevant conflicts of interest to declare.

scholarly journals Crossing design shapes patterns of genetic variation in synthetic recombinant populations of Saccharomyces cerevisiae

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mark A. Phillips ◽  
Ian C. Kutch ◽  
Kaitlin M. McHugh ◽  
Savannah K. Taggard ◽  
Molly K. Burke
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Genetic Variation ◽  
Experimental Evolution ◽  
Complex Traits ◽  
Inbred Lines ◽  
Equal Proportion ◽  
Adaptive Potential ◽  
Synthetic Populations ◽  
The Impact ◽  
Isogenic Strains

Abstract“Synthetic recombinant” populations have emerged as a useful tool for dissecting the genetics of complex traits. They can be used to derive inbred lines for fine QTL mapping, or the populations themselves can be sampled for experimental evolution. In the latter application, investigators generally value maximizing genetic variation in constructed populations. This is because in evolution experiments initiated from such populations, adaptation is primarily fueled by standing genetic variation. Despite this reality, little has been done to systematically evaluate how different methods of constructing synthetic populations shape initial patterns of variation. Here we seek to address this issue by comparing outcomes in synthetic recombinant Saccharomyces cerevisiae populations created using one of two strategies: pairwise crossing of isogenic strains or simple mixing of strains in equal proportion. We also explore the impact of the varying the number of parental strains. We find that more genetic variation is initially present and maintained when population construction includes a round of pairwise crossing. As perhaps expected, we also observe that increasing the number of parental strains typically increases genetic diversity. In summary, we suggest that when constructing populations for use in evolution experiments, simply mixing founder strains in equal proportion may limit the adaptive potential.

scholarly journals Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: evidence for “polygenic epistasis”

2019 ◽  
Author(s):  
Christoph D. Rau ◽  
Natalia M. Gonzales ◽  
Joshua S. Bloom ◽  
Danny Park ◽  
Julien Ayroles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Statistical Tests ◽  
Inbred Mice ◽  
Statistical Test ◽  
Genetic Ancestry ◽  
Human Populations ◽  
Epistatic Interactions ◽  
Variable Effect ◽  
The Impact

AbstractBackgroundThe majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors.ResultsWe applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection.ConclusionsUnlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.Author SummaryMany statistical tests which link genetic markers in the genome to differences in traits rely on the assumption that the same polymorphism will have identical effects in different individuals. However, there is substantial evidence indicating that this is not the case. Epistasis is the phenomenon in which multiple polymorphisms interact with one another to amplify or negate each other’s effects on a trait. We hypothesized that individual SNP effects could be changed in a polygenic manner, such that the proportion of as genetic ancestry, rather than specific markers, might be used to capture epistatic interactions. Motivated by this possibility, we develop a new statistical test that allowed us to examine the genome to identify polymorphisms which have different effects depending on the ancestral makeup of each individual. We use our test in two different populations of inbred mice and a yeast panel and demonstrate that these sorts of variable effect polymorphisms exist in 14 different physical traits in mice and 38 phenotypes in yeast as well as in murine gene expression. We use the term “polygenic epistasis” to distinguish these interactions from the more conventional two- or multi-locus interactions.

scholarly journals FUS ALS-causative mutations impair FUS autoregulation and splicing factor networks through intron retention

2020 ◽  
Vol 48 (12) ◽  
pp. 6889-6905 ◽  
Author(s):  
Jack Humphrey ◽  
Nicol Birsa ◽  
Carmelo Milioto ◽  
Martha McLaughlin ◽  
Agnieszka M Ule ◽  
...  
Keyword(s):  
Rna Processing ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Intron Retention ◽  
Mrna Splicing ◽  
Loss Of Function ◽  
Induced Changes ◽  
The Impact ◽  
High Depth ◽  
Lateral Sclerosis

Abstract Mutations in the RNA-binding protein FUS cause amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease. FUS plays a role in numerous aspects of RNA metabolism, including mRNA splicing. However, the impact of ALS-causative mutations on splicing has not been fully characterized, as most disease models have been based on overexpressing mutant FUS, which will alter RNA processing due to FUS autoregulation. We and others have recently created knockin models that overcome the overexpression problem, and have generated high depth RNA-sequencing on FUS mutants in parallel to FUS knockout, allowing us to compare mutation-induced changes to genuine loss of function. We find that FUS-ALS mutations induce a widespread loss of function on expression and splicing. Specifically, we find that mutant FUS directly alters intron retention levels in RNA-binding proteins. Moreover, we identify an intron retention event in FUS itself that is associated with its autoregulation. Altered FUS levels have been linked to disease, and we show here that this novel autoregulation mechanism is altered by FUS mutations. Crucially, we also observe this phenomenon in other genetic forms of ALS, including those caused by TDP-43, VCP and SOD1 mutations, supporting the concept that multiple ALS genes interact in a regulatory network.

scholarly journals Cis acting variation is common, can propagates across multiple regulatory layers, but is often buffered in developmental programs

2020 ◽  
Author(s):  
Swann Floc’hlay ◽  
Emily Wong ◽  
Bingqing Zhao ◽  
Rebecca R. Viales ◽  
Morgane Thomas-Chollier ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Transcription Factors ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cis Acting ◽  
Dna Mutations ◽  
Allele Specific ◽  
Regulatory Dna ◽  
The Impact

AbstractPrecise patterns of gene expression are driven by interactions between transcription factors, regulatory DNA sequence, and chromatin. How DNA mutations affecting any one of these regulatory ‘layers’ is buffered or propagated to gene expression remains unclear. To address this, we quantified allele-specific changes in chromatin accessibility, histone modifications, and gene expression in F1 embryos generated from eight Drosophila crosses, at three embryonic stages, yielding a comprehensive dataset of 240 samples spanning multiple regulatory layers. Genetic variation in cis-regulatory elements is common, highly heritable, and surprisingly consistent in its effects across embryonic stages. Much of this variation does not propagate to gene expression. When it does, it acts through H3K4me3 or alternatively through chromatin accessibility and H3K27ac. The magnitude and evolutionary impact of mutations is influenced by a genes’ regulatory complexity (i.e. enhancer number), with transcription factors being most robust to cis-acting, and most influenced by trans-acting, variation. Overall, the impact of genetic variation on regulatory phenotypes appears context-dependent even within the constraints of embryogenesis.

scholarly journals Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver

2018 ◽  
Author(s):  
Minal Çalışkan ◽  
Elisabetta Manduchi ◽  
H. Shanker Rao ◽  
Julian A Segert ◽  
Marcia Holsbach Beltrame ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Histone Modification ◽  
Human Liver ◽  
Complex Disease ◽  
Regulation Of Gene Expression ◽  
Regulatory Elements ◽  
Chromatin Interaction ◽  
Genome Wide ◽  
The Impact

ABSTRACTDeciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory regions of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the impacts of genetic variation that direct histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 77 GWAS loci that have been associated with at least one complex phenotype. Our results contribute to the repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.

scholarly journals Impact of Genetic Variation in Gene Regulatory Sequences: A Population Genomics Perspective

2021 ◽  
Vol 12 ◽  
Author(s):  
Manas Joshi ◽  
Adamandia Kapopoulou ◽  
Stefan Laurent
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Population Genomics ◽  
Natural Populations ◽  
Regulatory Elements ◽  
Regulatory Sequences ◽  
Coding Sequences ◽  
The Impact

The unprecedented rise of high-throughput sequencing and assay technologies has provided a detailed insight into the non-coding sequences and their potential role as gene expression regulators. These regulatory non-coding sequences are also referred to as cis-regulatory elements (CREs). Genetic variants occurring within CREs have been shown to be associated with altered gene expression and phenotypic changes. Such variants are known to occur spontaneously and ultimately get fixed, due to selection and genetic drift, in natural populations and, in some cases, pave the way for speciation. Hence, the study of genetic variation at CREs has improved our overall understanding of the processes of local adaptation and evolution. Recent advances in high-throughput sequencing and better annotations of CREs have enabled the evaluation of the impact of such variation on gene expression, phenotypic alteration and fitness. Here, we review recent research on the evolution of CREs and concentrate on studies that have investigated genetic variation occurring in these regulatory sequences within the context of population genetics.

scholarly journals Core gene identification using gene expression

2020 ◽  
Author(s):  
◽  
Annique Claringbould
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Genetic Code ◽  
Genetic Variants ◽  
Complex Traits ◽  
Drug Targets ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Altered Level ◽  
Common Genetic Variants

While humans share most of their genetic code with one another, small differences in the DNA can have an impact on an individual’s risk of disease. Common genetic variants exert individually small effects on the development of a disease, but their combined impact is substantial. Although recent research has identified thousands of variants that are associated to complex traits, our understanding of the molecular mechanisms that eventually lead to disease is limited. One way to dive into the molecular changes that result from genetic variation, is to look at changes in gene activity (‘gene expression’). Each cell contains the same genetic code, but genes are only expressed when and where they are required. Research has shown that many disease-associated genetic variants also affect gene expression. Such a change in the expression of a gene can lead to an altered level of the protein it encodes, which in turn can be the start of a dysregulation in the system that can eventually develop into a disease. This thesis describes how gene expression patterns can be used to prioritise and describe the function of trait-relevant genes. The first chapters evaluate methodological considerations for doing gene expression research. Another study covers the systematic linking of genetic variation to gene expression in blood and the last research chapter describes a method for gene prioritisation that leverages the idea that multiple genetic variants converge onto disease-causing genes. These insights can be used to better understand disease and to identify potential drug targets.

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