Abstract: The molecular role of corepressors is poorly understood. Here, we studied the transcriptional function of the corepressor SMRT during terminal adipogenesis. Genome-wide DNA-binding profiling revealed that this corepressor is predominantly located in active chromatin regions and that most distal SMRT binding events are lost after differentiation induction. Promoter-proximal tethering of SMRT in preadipocytes is primarily mediated by KAISO through the conserved TCTCGCGAGA motif. Further characterization revealed that KAISO, similar to SMRT, accelerates the cell cycle and increases fat accumulation upon knockdown, identifying KAISO as an adipogenic repressor that likely modulates the mitotic clonal expansion phase of this process. SMRT-bound promoter-distal sites tend to overlap with C/EBPβ-bound regions, which become occupied by proadipogenic transcription factors after SMRT clearance. This reveals a role for SMRT in masking enhancers from proadipogenic factors in preadipocytes. Finally, we identified SMRT as an adipogenic gatekeeper as it directly fine-tunes transcription of pro- and antiadipogenic genes.
Abstract: Information on nucleotide diversity along completely sequenced human genomes has increased tremendously over the last few years. This makes it possible to reassess the diversity status of distinct receptor proteins in different human individuals. To this end, we focused on the complete inventory of human olfactory receptor coding regions as a model for personal receptor repertoires.
Abstract: Understanding the relationship between genetic and phenotypic variation is one of the great outstanding challenges in biology. To meet this challenge, comprehensive genomic variation maps of human as well as of model organism populations are required. Here, we present a nucleotide resolution catalog of single-nucleotide, multi-nucleotide, and structural variants in 39 Drosophila melanogaster Genetic Reference Panel inbred lines. Using an integrative, local assembly-based approach for variant discovery, we identify more than 3.6 million distinct variants, among which were more than 800,000 unique insertions, deletions (indels), and complex variants (1 to 6,000 bp). While the SNP density is higher near other variants, we find that variants themselves are not mutagenic, nor are regions with high variant density particularly mutation-prone. Rather, our data suggest that the elevated SNP density around variants is mainly due to population-level processes. We also provide insights into the regulatory architecture of gene expression variation in adult flies by mapping cis-expression quantitative trait loci (cis-eQTLs) for more than 2,000 genes. Indels comprise around 10% of all cis-eQTLs and show larger effects than SNP cis-eQTLs. In addition, we identified two-fold more gene associations in males as compared to females and found that most cis-eQTLs are sex-specific, revealing a partial decoupling of the genomic architecture between the sexes as well as the importance of genetic factors in mediating sex-biased gene expression. Finally, we performed RNA-seq-based allelic expression imbalance analyses in the offspring of crosses between sequenced lines, which revealed that the majority of strong cis-eQTLs can be validated in heterozygous individuals.
Abstract: Copy-number variants (CNVs) form an abundant class of genetic variation with a presumed widespread impact on individual traits. While recent advances, such as the population-scale sequencing of human genomes, facilitated the fine-scale mapping of CNVs, the phenotypic impact of most of these CNVs remains unclear. By relating copy-number genotypes to transcriptome sequencing data, we have evaluated the impact of CNVs, mapped at fine scale, on gene expression. Based on data from 129 individuals with ancestry from two populations, we identified CNVs associated with the expression of 110 genes, with 13% of the associations involving complex, multiallelic CNVs. Categorization of CNVs according to variant type, size, and gene overlap enabled us to examine the impact of different CNV classes on expression variation. While many small (<4 kb) CNVs were associated with expression variation, overall we observed an enrichment of large duplications and deletions, including large intergenic CNVs, relative to the entire set of expression-associated CNVs. Furthermore, the copy number of genes intersecting with CNVs typically correlated positively with the genes' expression, and also was more strongly correlated with expression than nearby single nucleotide polymorphisms, suggesting a frequent causal role of CNVs in expression quantitative trait loci (eQTLs). We also elucidated unexpected cases of negative correlations between copy number and expression by assessing the CNVs' effects on the structure and regulation of genes. Finally, we examined dosage compensation of transcript levels. Our results suggest that association studies can gain in resolution and power by including fine-scale CNV information, such as those obtained from population-scale sequencing.
Abstract: Copy-number variations (CNVs) are widespread in the human genome, but comprehensive assignments of integer locus copy-numbers (i.e., copy-number genotypes) that, for example, enable discrimination of homozygous from heterozygous CNVs, have remained challenging. Here we present CopySeq, a novel computational approach with an underlying statistical framework that analyzes the depth-of-coverage of high-throughput DNA sequencing reads, and can incorporate paired-end and breakpoint junction analysis based CNV-analysis approaches, to infer locus copy-number genotypes. We benchmarked CopySeq by genotyping 500 chromosome 1 CNV regions in 150 personal genomes sequenced at low-coverage. The assessed copy-number genotypes were highly concordant with our performed qPCR experiments (Pearson correlation coefficient 0.94), and with the published results of two microarray platforms (95-99% concordance). We further demonstrated the utility of CopySeq for analyzing gene regions enriched for segmental duplications by comprehensively inferring copy-number genotypes in the CNV-enriched >800 olfactory receptor (OR) human gene and pseudogene loci. CopySeq revealed that OR loci display an extensive range of locus copy-numbers across individuals, with zero to two copies in some OR loci, and two to nine copies in others. Among genetic variants affecting OR loci we identified deleterious variants including CNVs and SNPs affecting ~15% and ~20% of the human OR gene repertoire, respectively, implying that genetic variants with a possible impact on smell perception are widespread. Finally, we found that for several OR loci the reference genome appears to represent a minor-frequency variant, implying a necessary revision of the OR repertoire for future functional studies. CopySeq can ascertain genomic structural variation in specific gene families as well as at a genome-wide scale, where it may enable the quantitative evaluation of CNVs in genome-wide association studies involving high-throughput sequencing.
Abstract: Differences in gene expression may play a major role in speciation and phenotypic diversity. We examined genome-wide differences in transcription factor (TF) binding in several humans and a single chimpanzee by using chromatin immunoprecipitation followed by sequencing. The binding sites of RNA polymerase II (PolII) and a key regulator of immune responses, nuclear factor kappaB (p65), were mapped in 10 lymphoblastoid cell lines, and 25 and 7.5% of the respective binding regions were found to differ between individuals. Binding differences were frequently associated with single-nucleotide polymorphisms and genomic structural variants, and these differences were often correlated with differences in gene expression, suggesting functional consequences of binding variation. Furthermore, comparing PolII binding between humans and chimpanzee suggests extensive divergence in TF binding. Our results indicate that many differences in individuals and species occur at the level of TF binding, and they provide insight into the genetic events responsible for these differences.
