Genomic basis for RNA alterations in cancer.

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data.

MOTIVATION: Genome Architecture Mapping (GAM) was recently introduced as a digestion- and ligation-free method to detect chromatin conformation. Orthogonal to existing approaches based on chromatin conformation capture (3C), GAM's ability to capture both inter- and intra-chromosomal contacts from low amounts of input data makes it particularly well suited for allele-specific analyses in a clinical setting. Allele-specific analyses are powerful tools to investigate the effects of genetic variants on many cellular phenotypes including chromatin conformation, but require the haplotypes of the individuals under study to be known a priori. So far, however, no algorithm exists for haplotype reconstruction and phasing of genetic variants from GAM data, hindering the allele-specific analysis of chromatin contact points in non-model organisms or individuals with unknown haplotypes. RESULTS: We present GAMIBHEAR, a tool for accurate haplotype reconstruction from GAM data. GAMIBHEAR aggregates allelic co-observation frequencies from GAM data and employs a GAM-specific probabilistic model of haplotype capture to optimize phasing accuracy. Using a hybrid mouse embryonic stem cell line with known haplotype structure as a benchmark dataset, we assess correctness and completeness of the reconstructed haplotypes, and demonstrate the power of GAMIBHEAR to infer accurate genome-wide haplotypes from GAM data. AVAILABILITY AND IMPLEMENTATION: GAMIBHEAR is available as an R package under the open-source GPL-2 license at https://bitbucket.org/schwarzlab/gamibhear. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Extensive folding variability between homologous chromosomes in mammalian cells.

Genetic variation and 3D chromatin structure have major roles in gene regulation. Due to challenges in mapping chromatin conformation with haplotype-specific resolution, the effects of genetic sequence variation on 3D genome structure and gene expression imbalance remain understudied. Here, we applied Genome Architecture Mapping (GAM) to a hybrid mouse embryonic stem cell (mESC) line with high density of single nucleotide polymorphisms (SNPs). GAM resolved haplotype-specific 3D genome structures with high sensitivity, revealing extensive allelic differences in chromatin compartments, topologically associating domains (TADs), long-range enhancer-promoter contacts, and CTCF loops. Architectural differences often coincide with allele-specific differences in gene expression, mediated by Polycomb repression. We show that histone genes are expressed with allelic imbalance in mESCs, are involved in haplotype-specific chromatin contact marked by H3K27me3, and are targets of Polycomb repression through conditional knockouts of Ezh2 or Ring1b. Our work reveals highly distinct 3D folding structures between homologous chromosomes, and highlights their intricate connections with allelic gene expression.

Serial genomic inversions induce tissue-specific architectural stripes, gene misexpression and congenital malformations.

Balanced chromosomal rearrangements such as inversions and translocations can cause congenital disease or cancer by inappropriately rewiring promoter-enhancer contacts1,2. To study the potentially pathogenic consequences of balanced chromosomal rearrangements, we generated a series of genomic inversions by placing an active limb enhancer cluster from the Epha4 regulatory domain at different positions within a neighbouring gene-dense region and investigated their effects on gene regulation in vivo in mice. Expression studies and high-throughput chromosome conformation capture from embryonic limb buds showed that the enhancer cluster activated several genes downstream that are located within asymmetric regions of contact, the so-called architectural stripes3. The ectopic activation of genes led to a limb phenotype that could be rescued by deleting the CCCTC-binding factor (CTCF) anchor of the stripe. Architectural stripes appear to be driven by enhancer activity, because they do not form in mouse embryonic stem cells. Furthermore, we show that architectural stripes are a frequent feature of developmental three-dimensional genome architecture often associated with active enhancers. Therefore, balanced chromosomal rearrangements can induce ectopic gene expression and the formation of asymmetric chromatin contact patterns that are dependent on CTCF anchors and enhancer activity.