Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics

Abstract

Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations (“ultrasensitive”) and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, “motif-breakers”). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

A comprehensive multicenter comparison of whole genome sequencing pipelines using a uniform tumor-normal sample pair

“…Discrepancies outside of the coding regions were more substantial, which may be of significance as the role of the non--coding genome to human disease becomes clearer 15,16 . Library preparation methods clearly had a significant impact on downstream data output, even when using one standardized variant calling pipeline.…”

Functional annotation of noncoding variants and prioritization of cancer-associated lncRNAs in lung cancer

“…Evolutionarily conserved structures were RNA secondary structures predicted using comparative structure prediction algorithms based on multiple genomes (42). Promoters, defined as regions 2.5 kb from transcription start sites (TSS), were generated from the Gerstein lab (http://funseq.gersteinlab.org/data) (13). RNA-seq data in bam format, transcription factor binding sites (TFBS), DNase I hypersensitive sites and histone modification data (H3K4me1, H3K9ac and others) of the A549 cell line were acquired from ENCODE (8).…”

“…In particular, the ENCODE project has provided researchers with a genome-wide map of histone modification, DNase I hypersensitive sites, formaldehyde-assisted isolation of regulatory elements, transcription factor binding sites, RNA-seq and replication timing data across a number of cell lines (8). An increasing number of studies have taken advantage of these annotations of human functional elements to investigate non-coding disease-implicated variants or drivers in cancer, including RegulomeDB (11), HaploReg (12) and Funseq (13); the scoring systems that these approaches rely on are primarily empirical scoring algorithms, which are not scientifically rigorous and stringent (14).…”

Cis-regulatory Elements and Human Evolution

“…They found that putative regulatory sequences showed almost no evidence of constraint in hominids, 38 but were significantly constrained in mouse and rat. Finding no signs of positive selection, they argued that 39 regulatory sequences in hominids had experienced "widespread degradation" due to their reduced effective 40 population sizes (see also [1,15,16] that mutations that decrease the matching score of a motif were enriched for rare alleles compared to ones 83 that did not [31]. However, Khurana and colleagues found evidence of contributions from positive selection 84 as well as negative selection in several types of regulatory elements, including DNase-I hypersensitive sites 85 (DHSs) and sequence-specific TFBSs.…”

“…This principle is based on the expectation that mutations will occur at 30 approximately equal rates in both functional and nonfunctional sites, but natural selection will alter the rates 31 at which derived alleles reach fixation in functional sites ( Figure 1). This idea has been applied for decades 32 to protein-coding sequences, where amino acid altering (nonsynonymous) and non-altering (synonymous) 33 substitutions provide convenenient classes to contrast [11][12][13].…”