Summary Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of mRNA and miRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project – the first uniformly processed RNA-seq data from multiple human populations with high-quality genome sequences. We discovered extremely widespread genetic variation affecting regulation of the majority of genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on cellular mechanisms of regulatory and loss-of-function variation, and allowed us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.
RNA sequencing is an increasingly popular technology for genome-wide analysis of transcript sequence and abundance. However, understanding of the sources of technical and interlaboratory variation is still limited. To address this, the GEUVADIS consortium sequenced mRNAs and small RNAs of lymphoblastoid cell lines of 465 individuals in seven sequencing centers, with a large number of replicates. The variation between laboratories appeared to be considerably smaller than the already limited biological variation. Laboratory effects were mainly seen in differences in insert size and GC content and could be adequately corrected for. In small-RNA sequencing, the microRNA (miRNA) content differed widely between samples owing to competitive sequencing of rRNA fragments. This did not affect relative quantification of miRNAs. We conclude that distributing RNA sequencing among different laboratories is feasible, given proper standardization and randomization procedures. We provide a set of quality measures and guidelines for assessing technical biases in RNA-seq data.
The availability of complete genome sequence data from both bacteria and eukaryotes provides information about the contribution of bacterial genes to the origin and evolution of mitochondria. Phylogenetic analyses based on genes located in the mitochondrial genome indicate that these genes originated from within the a-proteobacteria. A number of ancestral bacterial genes have also been transferred from the mitochondrial to the nuclear genome, as evidenced by the presence of orthologous genes in the mitochondrial genome in some species and in the nuclear genome of other species. However, a multitude of mitochondrial proteins encoded in the nucleus display no homology to bacterial proteins, indicating that these originated within the eukaryotic cell subsequent to the acquisition of the endosymbiont. An analysis of the expression patterns of yeast nuclear genes coding for mitochondrial proteins has shown that genes predicted to be of eukaryotic origin are mainly translated on polysomes that are free in the cytosol whereas those of putative bacterial origin are translated on polysomes attached to the mitochondrion. The strong relationship with a-proteobacterial genes observed for some mitochondrial genes, combined with the lack of such a relationship for others, indicates that the modern mitochondrial proteome is the product of both reductive and expansive processes.
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