Project description:Promoter-proximal pausing and divergent transcription at promoters and enhancers, which are prominent features in animals, have been reported to be absent in plants based on a study of Arabidopsis thaliana. Here, our PRO-Seq analysis in cassava (Manihot esculenta) identified peaks of transcriptionally-engaged RNA polymerase II (Pol2) at both 5’ and 3’ ends of genes, consistent with paused or slowly-moving Pol2, and divergent transcription at potential intragenic enhancers. A full genome search for bi-directional transcription using an algorithm for enhancer detection developed in mammals (dREG) identified many enhancer candidates. These sites show distinct patterns of methylation and nucleotide variation based on genomic evolutionary rate profiling characteristic of active enhancers. Maize GRO-Seq data showed RNA polymerase occupancy at promoters and enhancers consistent with cassava but not Arabidopsis. Furthermore, putative enhancers in maize identified by dREG significantly overlapped with sites previously identified on the basis of open chromatin, histone marks, and methylation. As evidence of the functional relevance of these sites in cassava, we show that SNPs in them predict significantly more variation in fitness and root composition than SNPs in chromosomal segments randomly ascertained from the same intergenic distribution. The findings shed new light on plant transcription regulation and its impact on development and plasticity.
Project description:Fulfilling the promise of human genetics in elucidating disease requires identifying causal variants and genes underlying genetic association signals. Molecular quantitative trait locus (molQTL) analyses, e.g. expression QTL (eQTL) and splicing QTL (sQTL), link genetic variants to intermediate molecular phenotypes, but pinpointing causal variants and their regulatory effects remains challenging. Here, we integrate sQTL analysis with deep-learning-based splicing effect annotation to identify causal genetic variants and elucidate their functional mechanisms affecting human phenotypes. Using a single-cell GWAS method (scHi-HOST) on 96 lymphoblastoid cell lines (LCLs) with and without influenza A virus (IAV) infection, we discovered ~43,000 sQTL-SNP-junction pairs associated with 217 genes during IAV infection. Integrating sQTLs with AI splice prediction and statistical fine-mapping, we uncovered 57 likely causal variants that affect cis-acting molecular splicing components (5’ donor, 3’ acceptor). Among these, we experimentally validated a causal sQTL signal affecting poly (ADP-ribose) polymerase 2 (PARP2). The causal variant, rs2297616, alters the 5’ splice donor site in the second intron of PARP2, resulting in two protein isoforms differing by 13 amino acids. The derived A allele was associated with the longer protein isoform and increased IAV levels in LCLs. CRISPR editing validated the causal effect of this variant on both protein length and IAV infection. Lastly, these 57 putative causal sQTLs were further linked to over a hundred GWAS traits, including many variants associated with autoimmune diseases. Our work provides a catalog of causal sQTL with direct splicing impacts, providing causal mechanistic insights from genotype to disease susceptibility.
Project description:We investigated whether variants fine-mapped for Rheumatoid Arthritis (RA) and Type 1 Diabetes overlap with open chromatin regions specifically after stimulation. We show that rs117701653, a potentially causal variant for RA near CD28, overlaps open chromatin regions only after stimulation. We futhermore observe a small increase in enhancer activity for this variant under stimulatory conditions using a luciferase assay. Reads were anonimized prior to upload.
Project description:Although GWASs have identified thousands of variants associated with human complex traits, most of which reside in the non-coding regions, especially enhancers, and biological mechanisms remain unclear. To created enhancer-gene maps to determine causal variant of CRC risk, we performed multi-omics analyses of ATAC-seq, H3K27ac ChIP-seq and RNA-seq with high quality from our 10 CRC tissues. By computationally integrating these multi-omics data, we identified 34,130 enhancer-gene connections involving 15,121 unique enhancers and 12,351 expressed genes. We demonstrated an ABC regulatory variant rs4810856 that is significantly associated with an increased CRC risk with large-scale population study and biological experiments. Our study provides regulation maps linking enhancers to genes, providing new insights into colorectal cancer etiology.
Project description:Although GWASs have identified thousands of variants associated with human complex traits, most of which reside in the non-coding regions, especially enhancers, and biological mechanisms remain unclear. To created enhancer-gene maps to determine causal variant of CRC risk, we performed multi-omics analyses of ATAC-seq, H3K27ac ChIP-seq and RNA-seq with high quality from our 10 CRC tissues. By computationally integrating these multi-omics data, we identified 34,130 enhancer-gene connections involving 15,121 unique enhancers and 12,351 expressed genes. We demonstrated an ABC regulatory variant rs4810856 that is significantly associated with an increased CRC risk with large-scale population study and biological experiments. Our study provides regulation maps linking enhancers to genes, providing new insights into colorectal cancer etiology.
Project description:Although GWASs have identified thousands of variants associated with human complex traits, most of which reside in the non-coding regions, especially enhancers, and biological mechanisms remain unclear. To created enhancer-gene maps to determine causal variant of CRC risk, we performed multi-omics analyses of ATAC-seq, H3K27ac ChIP-seq and RNA-seq with high quality from our 10 CRC tissues.