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Integrating a genome-wide association study with a large-scale transcriptome analysis to predict genetic regions influencing the glycemic index and texture in rice

ABSTRACT: Reliably generating rice varieties with low glycemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome-wide association study (GWAS) with a transcriptome-wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re-sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate-to-high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate-to-high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis-acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa) explained the intermediate-to-high GI variation. A SNP (C>T) at exon-10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non‑starch polysaccharide pathway in lowering GI.

ORGANISM(S): Oryza sativa Indica Group

PROVIDER: GSE123616 | GEO | 2019/02/01

REPOSITORIES: GEO

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Project description:A major goal of genetics research is to elucidate mechanisms explaining how genetic variation contributes to phenotypic variation. The genetic variants identified in genome-wide association studies (GWASs) generally explain only a small proportion of heritability of phenotypic traits, the so-called missing heritability problem. Recent evidence suggests that additional common variants beyond lead GWAS variants contribute to phenotypic variation; however, their mechanistic underpinnings generally remain unexplored. Herein, we undertake a study of haplotype-specific mechanisms of gene regulation at 8p23.1 in the human genome, a region associated with a number of complex diseases. The FAM167A-BLK locus in this region has been consistently found in the genome-wide association studies (GWASs) of systemic lupus erythematosus (SLE) in all major ancestries. Our haplotype-specific chromatin interaction (Hi-C) experiments, allele-specific enhancer activity measurements, genetic analyses, and epigenome editing experiments revealed that: (1) haplotype-specific long-range chromatin interactions are prevalent in 8p23.1; (2) BLK promoter and cis-regulatory elements cooperatively interact with haplotype-specificity; (3) genetic variants at distal regulatory elements are allele-specific modifiers of the promoter variants at FAM167A-BLK; (4) the BLK promoter interacts with and, as an enhancer-like promoter, regulates FAM167A expression and (5) local allele-specific enhancer activities are influenced by global haplotype structure due to chromatin looping. Although SLE causal variants at the FAM167A-BLK locus are thought to reside in the BLK promoter region, our results reveal that genetic variants at distal regulatory elements modulate promoter activity, changing BLK and FAM167A gene expression and disease risk. Our results suggest that global haplotype-specific 3-dimensional chromatin looping architecture has a strong influence on local allelic BLK and FAM167A gene expression, providing mechanistic details for how regional variants controlling the BLK promoter may influence disease risk.

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Integrating a genome-wide association study with a large-scale transcriptome analysis to predict genetic regions influencing the glycemic index and texture in rice

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