Transcriptome genetics using second generation sequencing in a Caucasian population

By Stephen B. Montgomery, M. Sammeth, M. Gutiérrez-Arcelus, R. Lach, Catherine E. Ingle, J. Nisbett, Roderic Guigó, Emmanouil T. Dermitzakis. Nature, 2010

871 citations recorded by the source corpus.

Gene expression is an important phenotype that informs about genetic and environmental effects on cellular state. Many studies have previously identified genetic variants for gene expression phenotypes using custom and commercially available microarrays. Second generation sequencing technologies are now providing unprecedented access to the fine structure of the transcriptome. We have sequenced the mRNA fraction of the transcriptome in 60 extended HapMap individuals of European descent and have combined these data with genetic variants from the HapMap3 project. We have quantified exon abundance based on read depth and have also developed methods to quantify whole transcript abundance. We have found that approximately 10 million reads of sequencing can provide access to the same dynamic range as arrays with better quantification of alternative and highly abundant transcripts. Correlation with SNPs (small nucleotide polymorphisms) leads to a larger discovery of eQTLs (expression quantitative trait loci) than with arrays. We also detect a substantial number of variants that influence the structure of mature transcripts indicating variants responsible for alternative splicing. Finally, measures of allele-specific expression allowed the identification of rare eQTLs and allelic differences in transcript structure. This analysis shows that high throughput sequencing technologies reveal new properties of genetic effects on the transcriptome and allow the exploration of genetic effects in cellular processes.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1cb944f8732e34a3719348d0a9eacceb195a5303

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Citations in the corpus

Intron-centric estimation of alternative splicing from RNA-seq data (2012, methodology): “It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists.”
Fast and efficient QTL mapper for thousands of molecular phenotypes (2015, methodology): “…eQTL has been used so far in multiple large scale studies (Lappalainen et al., 2013; GTEx Consortium., 2015), it still suffers from a main drawback which makes its practical application relatively laborious and time consuming: there is no efficient built-in permutation scheme forcing users to…”
Fast Computation and Applications of Genome Mappability (2012, background): “In fact, deconvolving the originating alternative transcripts of RNASeq reads is one of the most important challenges that need to be overcome to produce accurate quantifications at the alternative transcript level, and a number of methods are being explored towards that end [20,21].”
Differential analysis of gene regulation at transcript resolution with RNA-seq (2012, neutral): “7–10).”
Tools and best practices for data processing in allelic expression analysis (2015, methodology): “Using this ratio as a null in statistical tests instead of 0.5 [5, 6] can improve results (Figure S6b – e in Additional file 6).”
A quantitative atlas of polyadenylation in five mammals (2012, methodology): “…al. 2009; Levin et al. 2010) and have been used to discover and monitor alternative splicing (Sultan et al. 2008; Wang et al. 2008; Wilhelm et al. 2008), as well as gene expression (Marioni et al. 2008) and its underlying regulatory genetic variation (Montgomery et al. 2010; Pickrell et al. 2010).”
svaseq: removing batch effects and other unwanted noise from sequencing data (2014, methodology): “in two separate Hapmap populations [23, 24].”