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Understaning mechanisms underlying human gene expression variation with RNA sequencing

ABSTRACT: Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals. RNA-Seq in 69 lymphoblastoid cell lines from multiple Yoruban HapMap individuals in at least two replicate lanes per individual

OTHER RELATED OMICS DATASETS IN: PRJNA122271

ORGANISM(S): Homo sapiens

SUBMITTER: Yoav Gilad Joseph Pickrell Jonathan Pritchard

PROVIDER: E-GEOD-19480 | ArrayExpress | 2010-02-28

SECONDARY ACCESSION(S): SRP001540GSE19480PRJNA122271

REPOSITORIES: GEO, ArrayExpress, ENA

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	E-GEOD-19480.idf.txt	Idf
	E-GEOD-19480.processed.1.zip	Processed
	E-GEOD-19480.processed.10.zip	Processed
	E-GEOD-19480.processed.100.zip	Processed
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Understanding mechanisms underlying human gene expression variation with RNA sequencing.

Pickrell Joseph K JK Marioni John C JC Pai Athma A AA Degner Jacob F JF Engelhardt Barbara E BE Nkadori Everlyne E Veyrieras Jean-Baptiste JB Stephens Matthew M Gilad Yoav Y Pritchard Jonathan K JK

Nature 20100310 7289

Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. Although all eQTL studies so far have assayed messenger RNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblasto ...[more]

PMID: 20220758

Similar Datasets

Project description:BACKGROUND: While the possible sources underlying the so-called 'missing heritability' evident in current genome-wide association studies (GWAS) of complex traits have been actively pursued in recent years, resolving this mystery remains a challenging task. Studying heritability of genome-wide gene expression traits can shed light on the goal of understanding the relationship between phenotype and genotype. Here we used microarray gene expression measurements of lymphoblastoid cell lines and genome-wide SNP genotype data from 210 HapMap individuals to examine the heritability of gene expression traits. RESULTS: Heritability levels for expression of 10,720 genes were estimated by applying variance component model analyses and 1,043 expression quantitative loci (eQTLs) were detected. Our results indicate that gene expression traits display a bimodal distribution of heritability, one peak close to 0% and the other summit approaching 100%. Such a pattern of the within-population variability of gene expression heritability is common among different HapMap populations of unrelated individuals but different from that obtained in the CEU and YRI trio samples. Higher heritability levels are shown by housekeeping genes and genes associated with cis eQTLs. Both cis and trans eQTLs make comparable cumulative contributions to the heritability. Finally, we modelled gene-gene interactions (epistasis) for genes with multiple eQTLs and revealed that epistasis was not prevailing in all genes but made a substantial contribution in explaining total heritability for some genes analysed. CONCLUSIONS: We utilised a mixed effect model analysis for estimating genetic components from population based samples. On basis of analyses of genome-wide gene expression from four HapMap populations, we demonstrated detailed exploitation of the distribution of genetic heritabilities for expression traits from different populations, and highlighted the importance of studying interaction at the gene expression level as an important source of variation underlying missing heritability.

Project description:Genetic variants that impact gene regulation are important contributors to human phenotypic variation. For this reason, considerable efforts have been made to identify genetic associations with differences in mRNA levels of nearby genes, namely, cis expression quantitative trait loci (eQTLs). The phenotypic consequences of eQTLs are presumably due, in most cases, to their ultimate effects on protein expression levels. Yet, only few studies have quantified the impact of genetic variation on proteins levels directly. It remains unclear how faithfully eQTLs are reflected at the protein level, and whether there is a significant layer of cis regulatory variation acting primarily on translation or steady state protein levels. To address these questions, we measured ribosome occupancy by high-throughput sequencing, and relative protein levels by high-resolution quantitative mass spectrometry, in a panel of lymphoblastoid cell lines (LCLs) in which we had previously measured transcript expression using RNA sequencing. We then mapped genetic variants that are associated with changes in transcript expression (eQTLs), ribosome occupancy (rQTLs), or protein abundance (pQTLs). Most of the QTLs we detected are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, we found that eQTLs tend to have significantly reduced effect sizes on protein levels, suggesting that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we confirmed the presence of a class of cis QTLs that specifically affect protein abundance with little or no effect on mRNA levels; most of these QTLs have little effect on ribosome occupancy, and hence may arise from differences in post-translational regulation. We measured level of translation transcriptome-wide in lymphoblastoid cell lines derived from 72 HapMap Yoruba individuals using ribosome profiling assay, for which we have transcript level, protein level (62 out of 72) and genotype information collected.

Project description:To determine whether cellular apoptosis is a suitable phenotypic trait for pharmacogenomics studies by evaluating caspase 3/7-mediated activity in lymphoblastoid cell lines after treatment with six chemotherapeutic agents: 5'-deoxyfluorouridine, pemetrexed, cytarabine, paclitaxel, carboplatin, and cisplatin.Using monozygotic twin pair and sibling pair lymphoblastoid cell lines, we identified conditions for measurement of caspase 3/7 activity in lymphoblastoid cell lines. Genome-wide association studies were performed with over 2 million single nucleotide polymorphisms (SNPs) and cisplatin-induced apoptosis in HapMap CEU cell lines (n=77).Although treatment with 5'-deoxyfluorouridine and pemetrexed for up to 24 h resulted in low levels of apoptosis or interindividual variation in caspase-dependent cell death; paclitaxel, cisplatin, carboplatin, and cytarabine treatment for 24 h resulted in 9.4-fold, 9.1-fold, 7.0-fold, and 6.0-fold increases in apoptosis relative to control, respectively. There was a weak correlation between caspase activity and cytotoxicity (r(2)=0.03-0.29) demonstrating that cytotoxicity and apoptosis are two distinct phenotypes that may produce independent genetic associations. Estimated heritability (h(2)) for apoptosis was 0.57 and 0.29 for cytarabine (5 and 40 ?mol/l, respectively), 0.22 for paclitaxel (12.5 nmol/l), and 0.34 for cisplatin (5 ?mol/l). In the genome-wide association study using the HapMap CEU panel, we identified a significant enrichment of cisplatin-induced cytotoxicity SNPs within the significant cisplatin-induced apoptosis SNPs and an enrichment of expression quantitative trait loci (eQTL). Among these eQTLs, we identified several eQTLs with known function related to apoptosis and/or cytotoxicity.Our study identifies apoptosis as a phenotype for pharmacogenomic studies in lymphoblastoid cell lines after treatment with paclitaxel, cisplatin, carboplatin, and cytarabine that may have utility for discovering biomarkers to predict response to certain chemotherapeutics.