Transcriptional similarity in couples reveals the impact of shared environment and lifestyle on gene regulation through modified cytosines

Gene expression is a complex and quantitative trait that is influenced by both genetic and non-genetic regulators including environmental factors. Evaluating the contribution of environment to gene expression regulation and identifying which genes are more likely to be influenced by environmental factors are important for understanding human complex traits. We hypothesize that by living together as couples, there can be commonly co-regulated genes that may reflect the shared living environment (e.g., diet, indoor air pollutants, behavioral lifestyle). The lymphoblastoid cell lines (LCLs) derived from unrelated couples of African ancestry (YRI, Yoruba people from Ibadan, Nigeria) from the International HapMap Project provided a unique model for us to characterize gene expression pattern in couples by comparing gene expression levels between husbands and wives. Strikingly, 778 genes were found to show much smaller variances in couples than random pairs of individuals at a false discovery rate (FDR) of 5%. Since genetic variation between unrelated family members in a general population is expected to be the same assuming a random-mating society, non-genetic factors (e.g., epigenetic systems) are more likely to be the mediators for the observed transcriptional similarity in couples. We thus evaluated the contribution of modified cytosines to those genes showing transcriptional similarity in couples as well as the relationships these CpG sites with other gene regulatory elements, such as transcription factor binding sites (TFBS). Our findings suggested that transcriptional similarity in couples likely reflected shared common environment partially mediated through cytosine modifications.

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mtDNA eQTLs and the m1A 16S rRNA modification explain mtDNA tissue-specific gene expression pattern in humans

10.1101/495838 ◽

2018 ◽

Author(s):

Tal Cohen ◽

Chen Mordechai ◽

Alal Eran ◽

Dan Mishmar

Keyword(s):

Gene Expression ◽

Mitochondrial Dna ◽

16S Rrna ◽

Gene Expression Pattern ◽

Regulatory Elements ◽

Specific Gene ◽

Dependent Manner ◽

Rna Seq ◽

Genome Wide ◽

The Impact

Expression quantitative trait loci (eQTLs) are instrumental in genome-wide identification of regulatory elements, yet were overlooked in the mitochondrial DNA (mtDNA). By analyzing 5079 RNA-seq samples from 23 tissues we identified association of ancient mtDNA SNPs (haplogroups T2, L2, J2 and V) and recurrent SNPs (mtDNA positions 263, 750, 1438 and 10398) with tissue-dependent mtDNA gene-expression. Since the recurrent SNPs independently occurred in different mtDNA genetic backgrounds, they constitute the best candidates to be causal eQTLs. Secondly, the discovery of mtDNA eQTLs in both coding and non-coding mtDNA regions, propose the identification of novel mtDNA regulatory elements. Third, we identified association between low m1A 947 MT-RNR2 (16S) rRNA modification levels and altered mtDNA gene-expression in twelve tissues. Such association disappeared in skin which was exposed to sun, as compared to sun-unexposed skin from the same individuals, thus supporting the impact of UV on mtDNA gene expression. Taken together, our findings reveal that both mtDNA SNPs and mt-rRNA modification affect mtDNA gene expression in a tissue-dependent manner.

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Tissue-specific sex differences in human gene expression

Human Molecular Genetics ◽

10.1093/hmg/ddz090 ◽

2019 ◽

Vol 28 (17) ◽

pp. 2976-2986 ◽

Cited By ~ 9

Author(s):

Irfahan Kassam ◽

Yang Wu ◽

Jian Yang ◽

Peter M Visscher ◽

Allan F McRae

Keyword(s):

Gene Expression ◽

Sex Differences ◽

Complex Traits ◽

Tissue Expression ◽

Regulatory Elements ◽

Tissue Specific ◽

Significance Threshold ◽

Expression Of Genes ◽

Causal Variants ◽

Similar Distance

Abstract Despite extensive sex differences in human complex traits and disease, the male and female genomes differ only in the sex chromosomes. This implies that most sex-differentiated traits are the result of differences in the expression of genes that are common to both sexes. While sex differences in gene expression have been observed in a range of different tissues, the biological mechanisms for tissue-specific sex differences (TSSDs) in gene expression are not well understood. A total of 30 640 autosomal and 1021 X-linked transcripts were tested for heterogeneity in sex difference effect sizes in n = 617 individuals across 40 tissue types in Genotype–Tissue Expression (GTEx). This identified 65 autosomal and 66 X-linked TSSD transcripts (corresponding to unique genes) at a stringent significance threshold. Results for X-linked TSSD transcripts showed mainly concordant direction of sex differences across tissues and replicate previous findings. Autosomal TSSD transcripts had mainly discordant direction of sex differences across tissues. The top cis-expression quantitative trait loci (eQTLs) across tissues for autosomal TSSD transcripts are located a similar distance away from the nearest androgen and estrogen binding motifs and the nearest enhancer, as compared to cis-eQTLs for transcripts with stable sex differences in gene expression across tissue types. Enhancer regions that overlap top cis-eQTLs for TSSD transcripts, however, were found to be more dispersed across tissues. These observations suggest that androgen and estrogen regulatory elements in a cis region may play a common role in sex differences in gene expression, but TSSD in gene expression may additionally be due to causal variants located in tissue-specific enhancer regions.

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Environmental perturbations lead to extensive directional shifts in RNA processing

10.1101/119974 ◽

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.

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Mutational Signatures as Sensors of Environmental Exposures: Role of Smoking in COVID-19 Vulnerabilities

10.1101/2021.09.27.461855 ◽

2021 ◽

Author(s):

Yoo-Ah Kim ◽

Ermin Hodzic ◽

Ariella Saslafsky ◽

Damian Wojtowicz ◽

Bayarbaatar Amgalan ◽

...

Keyword(s):

Gene Expression ◽

Environmental Factors ◽

Disease Progression ◽

Environmental Exposures ◽

Biological Processes ◽

Mutational Signatures ◽

Mutational Signature ◽

The Impact ◽

Pathway Level

Background: Environmental exposures such as smoking are widely recognized risk factors in the emergence of lung diseases such as lung cancer and acute respiratory distress syndrome (ARDS). However, the strength of environmental exposures is difficult to measure, making it challenging to understand their impacts. On the other hand, some COVID-19 patients develop ARDS in an unfavorable disease progression and smoking has been suggested as a potential risk factor among others. Yet initial studies on COVID-19 cases reported contradictory results on the effects of smoking on the disease. Some suggest that smoking might have a protective effect against it while other studies report an increased risk. A better understanding of how the exposure to smoking and other environmental factors affect biological processes relevant to SARS-CoV-2 infection and unfavorable disease progression is needed. Approach: In this study, we utilize mutational signatures associated with environmental factors as sensors of their exposure level. Many environmental factors including smoking are mutagenic and leave characteristic patterns of mutations, called mutational signatures, in affected genomes. We postulated that analyzing mutational signatures, combined with gene expression, can shed light on the impact of the mutagenic environmental factors to the biological processes. In particular, we utilized mutational signatures from lung adenocarcinoma (LUAD) data set collected in TCGA to investigate the role of environmental factors in COVID-19 vulnerabilities. Integrating mutational signatures with gene expression in normal tissues and using a pathway level analysis, we examined how the exposure to smoking and other mutagenic environmental factors affects the infectivity of the virus and disease progression. Results: By delineating changes associated with smoking in pathway-level gene expression and cell type proportions, our study demonstrates that mutational signatures can be utilized to study the impact of exogenous mutagenic factors on them. Consistent with previous findings, our analysis showed that smoking mutational signature (SBS4) is associated with activation of cytokines mediated singling pathways, leading to inflammatory responses. Smoking related changes in cell composition were also observed, including the correlation of SBS4 with the expansion of goblet cells. On the other hand, increased basal cells and decreased ciliated cells in proportion were associated with the strength of a different mutational signature (SBS5), which is present abundantly but not exclusively in smokers. In addition, we found that smoking increases the expression levels of genes that are upregulated in severe COVID-19 cases. Jointly, these results suggest an unfavorable impact of smoking on the disease progression and also provide novel findings on how smoking impacts biological processes in lung.

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Impact and evolutionary determinants of Neanderthal introgression on transcriptional and post-transcriptional regulation

10.1101/532366 ◽

2019 ◽

Author(s):

Martin Silvert ◽

Lluis Quintana-Murci ◽

Maxime Rotival

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Transcriptional Regulation ◽

Regulatory Elements ◽

Strong Impact ◽

Modern Humans ◽

Archaic Admixture ◽

Archaic Introgression ◽

Post Transcriptional Regulation ◽

The Impact

AbstractArchaic admixture is increasingly recognized as an important source of diversity in modern humans, with Neanderthal haplotypes covering 1-3% of the genome of present-day Eurasians. Recent work has shown that archaic introgression has contributed to human phenotypic diversity, mostly through the regulation of gene expression. Yet, the mechanisms through which archaic variants alter gene expression, and the forces driving the introgression landscape at regulatory regions remain elusive. Here, we explored the impact of archaic introgression on transcriptional and post-transcriptional regulation, focusing on promoters and enhancers across 127 different tissues as well as microRNA-mediated regulation. Although miRNAs themselves harbor few archaic variants, we found that some of these variants may have a strong impact on miRNA-mediated gene regulation. Enhancers were by far the regulatory elements most affected by archaic introgression, with one third of the tissues tested presenting significant enrichments. Specifically, we found strong enrichments of archaic variants in adipose-related tissues and primary T cells, even after accounting for various genomic and evolutionary confounders such as recombination rate and background selection. Interestingly, we identified signatures of adaptive introgression at enhancers of some key regulators of adipogenesis, raising the interesting hypothesis of a possible adaptation of early Eurasians to colder climates. Collectively, this study sheds new light onto the mechanisms through which archaic admixture have impacted gene regulation in Eurasians and, more generally, increases our understanding of the contribution of Neanderthals to the regulation of acquired immunity and adipose homeostasis in modern humans.

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Comparative chromatin accessibility upon BDNF-induced neuronal activity delineates neuronal regulatory elements

10.1101/2021.05.28.446128 ◽

2021 ◽

Author(s):

Ignacio L. Ibarra ◽

Vikram S. Ratnu ◽

Lucia Gordillo ◽

In-Young Hwang ◽

Luca Mariani ◽

...

Keyword(s):

Gene Expression ◽

Synaptic Plasticity ◽

Neuronal Activity ◽

Cortical Neurons ◽

Complex Traits ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Regulatory Control ◽

Comparative Genomic ◽

Regulatory Sequences

Neuronal activity induced by brain-derived neurotrophic factor (BDNF) triggers gene expression, which is crucial for neuronal survival, differentiation, synaptic plasticity, memory formation, and neurocognitive health. However, its role in chromatin regulation is unclear. Here, using temporal profiling of chromatin accessibility and transcription in mouse primary cortical neurons upon either BDNF stimulation or depolarization (KCl), we identify features that define BDNF-specific chromatin-to-gene expression programs. Enhancer activation is an early event in the regulatory control of BDNF-treated neurons, where the bZIP motif-binding Fos protein pioneered chromatin opening and cooperated with co-regulatory transcription factors (Homeobox, EGRs, and CTCF) to induce transcription. Deleting cis-regulatory sequences decreased BDNF-mediated Arc expression, a regulator of synaptic plasticity. BDNF-induced accessible regions are linked to preferential exon usage by neurodevelopmental disorder-related genes and heritability of neuronal complex traits, which were validated in human iPSC-derived neurons. Thus, we provide a comprehensive view of BDNF-mediated genome regulatory features using comparative genomic approaches to dissect mammalian neuronal activity.

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Single-cell RNA sequencing of a European and an African lymphoblastoid cell line

10.1101/548115 ◽

2019 ◽

Cited By ~ 1

Author(s):

Daniel Osorio ◽

Xue Yu ◽

Peng Yu ◽

Erchin Serpedin ◽

James J. Cai

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

African Ancestry ◽

Peripheral Blood Lymphocytes ◽

Barr Virus ◽

Single Cell Rna Sequencing ◽

Suitable Reference ◽

The Impact

AbstractIn biomedical research, lymphoblastoid cell lines (LCLs), often established byin vitroinfection of resting B cells with Epstein Barr Virus, are commonly used as surrogates for peripheral blood lymphocytes. Genomic and transcriptomic information on LCLs has been used to study the impact of genetic variation on gene expression in humans. Here we present single-cell RNA sequencing (scRNA-seq) data on GM12878 and GM18502—two LCLs derived from the blood of female donors of European and African ancestry, respectively. Cells from three samples (the two LCLs and a 1:1 mixture of the two) were prepared separately using a 10X Genomics Chromium Controller and deeply sequenced. The final dataset contained 7,045 cells from GM12878, 5,189 from GM18502, and 5,820 from the mixture, offering valuable information on single-cell gene expression in highly homogenous cell populations. This dataset is a suitable reference of population differentiation in gene expression at the single-cell level. Data from the mixture provides additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction.

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

10.1101/555383 ◽

2019 ◽

Cited By ~ 1

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.

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Maternal Overnutrition Programs Central Inflammation and Addiction-Like Behavior in Offspring

BioMed Research International ◽

10.1155/2018/8061389 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 13

Author(s):

Larisa Montalvo-Martínez ◽

Roger Maldonado-Ruiz ◽

Marcela Cárdenas-Tueme ◽

Diana Reséndez-Pérez ◽

Alberto Camacho

Keyword(s):

Gene Expression ◽

Fetal Programming ◽

Gene Expression Pattern ◽

Cell Types ◽

Addictive Behavior ◽

Adaptive Responses ◽

Inflammatory Phenotype ◽

Pregnancy And Lactation ◽

Maternal Overnutrition ◽

The Impact

Obesity or maternal overnutrition during pregnancy and lactation might have long-term consequences in offspring health. Fetal programming is characterized by adaptive responses to specific environmental conditions during early life stages. Programming alters gene expression through epigenetic modifications leading to a transgenerational effect of behavioral phenotypes in the offspring. Maternal intake of hypercaloric diets during fetal development programs aberrant behaviors resembling addiction in offspring. Programming by hypercaloric surplus sets a gene expression pattern modulating axonal pruning, synaptic signaling, and synaptic plasticity in selective regions of the reward system. Likewise, fetal programming can promote an inflammatory phenotype in peripheral and central sites through different cell types such as microglia and T and B cells, which contribute to disrupted energy sensing and behavioral pathways. The molecular mechanism that regulates the central and peripheral immune cross-talk during fetal programming and its relevance on offspring’s addictive behavior susceptibility is still unclear. Here, we review the most relevant scientific reports about the impact of hypercaloric nutritional fetal programming on central and peripheral inflammation and its effects on addictive behavior of the offspring.

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The HapMap Resource is Providing New Insights into Ourselves and its Application to Pharmacogenomics

Bioinformatics and Biology Insights ◽

10.4137/bbi.s455 ◽

2008 ◽

Vol 2 ◽

pp. BBI.S455 ◽

Cited By ~ 30

Author(s):

Wei Zhang ◽

Mark J. Ratain ◽

M. Eileen Dolan

Keyword(s):

Gene Expression ◽

Complex Traits ◽

Drug Response ◽

Human Populations ◽

International Hapmap Project ◽

Hapmap Project ◽

Phenotypic Data ◽

Human Lymphoblastoid Cell ◽

Human Lymphoblastoid Cell Lines ◽

Japanese Ancestry

The exploration of quantitative variation in complex traits such as gene expression and drug response in human populations has become one of the major priorities for medical genetics. The International HapMap Project provides a key resource of genotypic data on human lymphoblastoid cell lines derived from four major world populations of European, African, Chinese and Japanese ancestry for researchers to associate with various phenotypic data to find genes affecting health, disease and response to drugs. Recent progress in dissecting genetic contribution to natural variation in gene expression within and among human populations and variation in drug response are two examples in which researchers have utilized the HapMap resource. The HapMap Project provides new insights into the human genome and has applicability to pharmacogenomics studies leading to personalized medicine.

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