Genomic features that predict allelic imbalance in humans suggest patterns of constraint on gene expression variation

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

Assessing Loss of Regulatory Divergence, Genome-Transcriptome Incongruence, and Preferential Expression Switching in Abaca × Banana Backcrosses

The Musa textilis var. Abuab has high fiber quality (FQ) but is susceptible to abaca bunchy top virus (AbBTV); the Musa balbisiana var. Pacol has low FQ but is resistant against AbBTV. Their backcrosses (BC2 and BC3) possess both desirable traits. Analysis using RNA-seq showed that the regulatory divergence of Abuab and Pacol is largely explained by cis differences with 27.4% and 22.3% if we are to assess it using BC2 and BC3, respectively. Cis differences between the two genotypes are significantly reduced from BC2 to BC3 due to changes in genomic constitution. Trans, on the other hand, is robust to changes in allelic composition. All these are attributed to the loss of heterozygosity in BC3 relative to BC2. Further analysis showed that both backcrosses exhibited genome-wide preferential expression of Pacol- over Abuab-specific alleles, despite the wider genetic presence of the latter in the hybrids. The ratio of the two genotype-specific expressed transcripts and the ratio of their corresponding genetic make-up are significantly disproportionate, a phenomenon that we refer to here as "genome-transcriptome incongruence". We also observed preferential expression switching in which several genes prefer the Abuab- (or Pacol-) specific allele in BC2 but switched to the Pacol- (or Abuab-) specific allele in the BC3 genome.

Expression quantitative trait locus mapping across water availability environments reveals contrasting associations with genomic features in Arabidopsis

The regulation of gene expression is crucial for an organism's development and response to stress, and an understanding of the evolution of gene expression is of fundamental importance to basic and applied biology. To improve this understanding, we conducted expression quantitative trait locus (eQTL) mapping in the Tsu-1 (Tsushima, Japan) × Kas-1 (Kashmir, India) recombinant inbred line population of Arabidopsis thaliana across soil drying treatments. We then used genome resequencing data to evaluate whether genomic features (promoter polymorphism, recombination rate, gene length, and gene density) are associated with genes responding to the environment (E) or with genes with genetic variation (G) in gene expression in the form of eQTLs. We identified thousands of genes that responded to soil drying and hundreds of main-effect eQTLs. However, we identified very few statistically significant eQTLs that interacted with the soil drying treatment (GxE eQTL). Analysis of genome resequencing data revealed associations of several genomic features with G and E genes. In general, E genes had lower promoter diversity and local recombination rates. By contrast, genes with eQTLs (G) had significantly greater promoter diversity and were located in genomic regions with higher recombination. These results suggest that genomic architecture may play an important a role in the evolution of gene expression.

Social environment influences the relationship between genotype and gene expression in wild baboons

Variation in the social environment can have profound effects on survival and reproduction in wild social mammals. However, we know little about the degree to which these effects are influenced by genetic differences among individuals, and conversely, the degree to which social environmental variation mediates genetic reaction norms. To better understand these relationships, we investigated the potential for dominance rank, social connectedness and group size to modify the effects of genetic variation on gene expression in the wild baboons of the Amboseli basin. We found evidence for a number of gene-environment interactions (GEIs) associated with variation in the social environment, encompassing social environments experienced in adulthood as well as persistent effects of early life social environment. Social connectedness, maternal dominance rank and group size all interacted with genotype to influence gene expression in at least one sex, and either in early life or in adulthood. These results suggest that social and behavioural variation, akin to other factors such as age and sex, can impact the genotype-phenotype relationship. We conclude that GEIs mediated by the social environment are important in the evolution and maintenance of individual differences in wild social mammals, including individual differences in responses to social stressors.

Genetic architecture of regulatory variation in Arabidopsis thaliana

Studying the genetic regulation of expression variation is a key method to dissect complex phenotypic traits. To examine the genetic architecture of regulatory variation in Arabidopsis thaliana, we performed genome-wide association (GWA) mapping of gene expression in an F(1) hybrid diversity panel. At a genome-wide false discovery rate (FDR) of 0.2, an associated single nucleotide polymorphism (SNP) explains >38% of trait variation. In comparison with SNPs that are distant from the genes to which they were associated, locally associated SNPs are preferentially found in regions with extended linkage disequilibrium (LD) and have distinct population frequencies of the derived alleles (where Arabidopsis lyrata has the ancestral allele), suggesting that different selective forces are acting. Locally associated SNPs tend to have additive inheritance, whereas distantly associated SNPs are primarily dominant. In contrast to results from mapping of expression quantitative trait loci (eQTL) in linkage studies, we observe extensive allelic heterogeneity for local regulatory loci in our diversity panel. By association mapping of allele-specific expression (ASE), we detect a significant enrichment for cis-acting variation in local regulatory variation. In addition to gene expression variation, association mapping of splicing variation reveals both local and distant genetic regulation for intron and exon level traits. Finally, we identify candidate genes for 59 diverse phenotypic traits that were mapped to eQTL.

Selection at linked sites shapes heritable phenotypic variation in C. elegans

Mutation generates the heritable variation that genetic drift and natural selection shape. In classical quantitative genetic models, drift is a function of the effective population size and acts uniformly across traits, whereas mutation and selection act trait-specifically. We identified thousands of quantitative trait loci (QTLs) influencing transcript abundance traits in a cross of two Caenorhabditis elegans strains; although trait-specific mutation and selection explained some of the observed pattern of QTL distribution, the pattern was better explained by trait-independent variation in the intensity of selection on linked sites. Our results suggest that traits in C. elegans exhibit different levels of variation less because of their own attributes than because of differences in the effective population sizes of the genomic regions harboring their underlying loci.