Project description:Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation in gut microbial metagenome and host genome but they could not adequately represent the protein-level variants. Single amino-acid polymorphisms (SAP) derived from non-synonymous SNPs can cause functional changes of proteins and are important forces of adaption. However, SAP remain quite unexplored for human gut microbiome. Here, we present a comprehensive large-scale analysis of SAP in the gut ecosystem, introducing a rigorous computational pipeline for detecting such protein variation from 992 published human metaproteomes.
Project description:Body weight (BW) is a critical economic trait for meat production in sheep. The current study aimed to perform a genome-wide association study (GWAS) to detect significant single-nucleotide polymorphisms (SNPs) that are associated with BW in Hu sheep.
Project description:Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift (EMSA) and luciferase reporter assays. To identify binding of transcription factors and/or other nuclear proteins in an allele-determined manner, we employed pulldown using nuclear extract from Daudi cells and silver staining in SNPs that had exhibited allele-specific differential binding by EMSA. Each pulldown product for each allele of the five high-probability SNPs (rs2297550 C/G, rs13213604 C/G, rs276461 T/C, rs9907955 C/T, rs7302634 T/C) was evaluated by mass spectrometry (MS) to identify binding nuclear proteins, yielding a set of candidate proteins for each.
Project description:Tacrolimus (TAC) is an immunosuppressant widely used in kidney transplantation. TAC displays considerable inter-individual variability in pharmacokinetics (PK). Genetic and clinical factors play important roles in TAC PK. To define genetic factors associated with tacrolimus blood trough concentration, we performed a genome-wide association study of renal transplant samples from 251 Chinese renal transplant recipients. We identified 23 single nucleotide polymorphisms (SNPs) related to TAC PK variability. All 23 genome-wide significant SNPs (p<5E-8) were located on chromosome 7, including rs776746. These findings suggest that these SNPs may be associated with the unexlained TAC PK variability in renal transplant recipients and require further investigation.
Project description:The majority of single nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to systematically detect regulatory activity of 5,987 noncoding GWASs SNPs in three IR-relevant cell lines. We identified 876 SNPs with biased allelic enhancer activity across 133 loci, and further uncovered the genetic regulatory mechanisms underlying functional SNPs through integrating multi-omics analyses.
Project description:Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with diseases of the colon including inflammatory bowel diseases (IBD) and colorectal cancer (CRC). However, the functional role of many of these SNPs is largely unknown and tissue-specific resources are lacking. Expression quantitative trait loci (eQTL) mapping identifies target genes of disease-associated SNPs. Here, we comprehensively map eQTLs in the human colon, assess their relevance for GWAS of colonic diseases and provide functional characterization.
Project description:Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) associated with human traits and diseases. But because the vast majority of these SNPs are located in the noncoding regions of the genome their risk promoting mechanisms are elusive. Employing a new methodology combining cistromics, epigenomics and genotype imputation we annotate the noncoding regions of the genome in breast cancer cells and systematically identify the functional nature of SNPs associated with breast cancer risk. Our results demonstrate that breast cancer risk-associated SNPs are enriched in the cistromes of FOXA1 and ESR1 and the epigenome of H3K4me1 in a cancer and cell-type-specific manner. Furthermore, the majority of these risk-associated SNPs modulate the affinity of chromatin for FOXA1 at distal regulatory elements, which results in allele-specific gene expression, exemplified by the effect of the rs4784227 SNP on the TOX3 gene found within the 16q12.1 risk locus. Examination of histone modification H3K4me2 in untreated and E2 treated cells
Project description:We analysed the impact of single nucleotide polymorphisms (SNPs) in drug transporter genes on the molecular response to imatinib, using 857 SNPs covering 94 drug transporter genes on 355 chronic phase chronic myeloid leukemia (CP-CML) patients.
Project description:Most of the millions of single-nucleotide polymorphisms (SNPs) in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on enhancer and promoter activity. Here, we have leveraged the throughput of the SuRE reporter technology to survey a total of 5.9 million SNPs, including 57% of the known common SNPs world-wide. We identified more than 30 thousand SNPs that alter the activity of putative regulatory elements, often in a cell-type specific manner. These data indicate that a large proportion of human non-coding SNPs may affect gene regulation. Integration of these SuRE data with genome-wide association studies may help to identify causal SNPs.