Biology subjects

Sims, D.

Publications and source records attributed to Sims, D..

4 recordsLinked to original sources

bioRxiv2018

The genetic architecture of hair colour in the UK population

We have extensively mapped the genes responsible for hair colour in the UK population. MC1R mutations are well established as the principal genetic cause of red hair colour, but with variable penetrance. We find variation at genes encoding its agonist (POMC), inverse agonist (ASIP) and other loci contribute to red hair and demonstrate epistasis between MC1R and some of these loci. Blonde hair is associated with over 200 loci, and we find a genetic continuum from black through dark and light brown to blonde. Many of the associated genes are involved in hair growth or texture, emphasising the cellular connections between keratinocytes and melanocytes in the determination of hair colour.

genetics↗

bioRxiv2018

Co-transcriptional loading of RNA export factors shapes the human transcriptome.

During gene expression, RNA export factors are mainly known for driving nucleocytoplasmic transport. Whilst early studies suggested that the Exon Junction Complex provides a binding platform for them, subsequent work proposed that they are only recruited by the Cap-Binding Complex to the 5 end of RNAs, as part of TREX. Using iCLIP, we show that the export receptor Nxf1 and two TREX subunits, Alyref and Chtop, are actually recruited to the whole mRNA co-transcriptionally via splicing but before 3-end processing. Consequently, Alyref alters splicing decisions and Chtop regulates alternative polyadenylation. Alyref is recruited to the 5-end of RNAs by CBC and our data reveal subsequent binding to RNAs near EJCs. We demonstrate eIF4A3 stimulates Alyref deposition not only on spliced RNAs close to EJC sites, but also single exon transcripts. Our study reveals mechanistic insights into the co-transcriptional recruitment of mRNA export factors and how this shapes the human transcriptome.

molecular biology↗

bioRxiv2017

Effect of vitamin D supplementation on biomarkers of inflammation and immune function: functional genomics analysis of the BEST-D trial

Vitamin D deficiency has been associated with multiple diseases, but the causal relevance and underlying processes are not fully understood. Elucidating the mechanisms of action of drug treatments in humans is challenging, but application of functional genomic approaches in randomised trials may afford an opportunity to systematically assess molecular responses to treatments. In the Biochemical Efficacy and Safety Trial of Vitamin D (BEST-D), 305 community-dwelling individuals aged over 65 years were randomly allocated to treatment with vitamin D34000 IU, 2000 IU or placebo daily for 12 months. Genome-wide genotypes at baseline, and transcriptome and plasma levels of cytokines (IFN-{gamma}, IL-10, IL-8, IL-6 and TNF-) at baseline and after 12 months, were measured. The trial had >90% power to detect a 2-fold change in gene expression. Allocation to vitamin D for 12-months was associated with 2-fold higher plasma levels of 25-hydroxy-vitamin D (25[OH]D), but had no significant effect on whole-blood gene expression (FDR <5%) or on plasma levels of cytokines compared with placebo. In pre-specified analysis, rs7041 (intron variant, GC) had a significant effect on circulating levels of 25(OH)D in the low dose but not on the placebo or high dose vitamin D regimen. A gene expression quantitative trait locus analysis (eQTL) demonstrated evidence of 31,568 cis-eQTLs (unique SNP-probe pairs) among individuals at baseline and 34,254 after supplementation for 12 months (any dose), but had no significant effect on cis-eQTLs specific to vitamin D supplementation. The trial demonstrates the feasibility of application of functional genomics approaches in randomised trials to assess the effects of vitamin D on immune function.\n\nOne sentence summarySupplementation with high-dose vitamin D in older people for 12 months in a randomised, placebo-controlled trial had no significant effect on gene expression or on plasma concentrations of cytokines.\n\nTrial registrationSRCTN registry (Number 07034656) and the European Clinical Trials Database (EudraCT Number 2011-005763-24).\n\nFundingMedical Research Council, British Heart Foundation, Wellcome Trust, European Research Council and Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom\n\nCopyrightOpen access article under the terms of CC BY.

clinical trials↗

bioRxiv2017

The Sorghum bicolor reference genome: improved assembly and annotations, a transcriptome atlas, and signatures of genome organization

2Sorghum bicolor is a drought tolerant C4 grass used for production of grain, forage, sugar, and lignocellulosic biomass and a genetic model for C4 grasses due to its relatively small genome (~800 Mbp), diploid genetics, diverse germplasm, and colinearity with other C4 grass genomes. In this study, deep sequencing, genetic linkage analysis, and transcriptome data were used to produce and annotate a high quality reference genome sequence. Reference genome sequence order was improved, 29.6 Mbp of additional sequence was incorporated, the number of genes annotated increased 24% to 34,211, average gene length and N50 increased, and error frequency was reduced 10-fold to 1 per 100 kbp. Sub-telomeric repeats with characteristics of Tandem Repeats In Miniature (TRIM) elements were identified at the termini of most chromosomes. Nucleosome occupancy predictions identified nucleosomes positioned immediately downstream of transcription start sites and at different densities across chromosomes. Alignment of the reference genome sequence to 56 resequenced genomes from diverse sorghum genotypes identified ~7.4M SNPs and 1.8M indels. Large scale variant features in euchromatin were identified with periodicities of ~25 kbp. An RNA transcriptome atlas of gene expression was constructed from 47 samples derived from growing and developed tissues of the major plant organs (roots, leaves, stems, panicles, seed) collected during the juvenile, vegetative and reproductive phases. Analysis of the transcriptome data indicated that tissue type and protein kinase expression had large influences on transcriptional profile clustering. The updated assembly, annotation, and transcriptome data represent a resource for C4 grass research and crop improvement.

plant biology↗