Graphtyper enables population-scale genotyping using pangenome graphs.

To access publisher's full text version of this article click on the hyperlink belowA fundamental requirement for genetic studies is an accurate determination of sequence variation. While human genome sequence diversity is increasingly well characterized, there is a need for efficient ways to use this knowledge in sequence analysis. Here we present Graphtyper, a publicly available novel algorithm and software for discovering and genotyping sequence variants. Graphtyper realigns short-read sequence data to a pangenome, a variation-aware graph structure that encodes sequence variation within a population by representing possible haplotypes as graph paths. Our results show that Graphtyper is fast, highly scalable, and provides sensitive and accurate genotype calls. Graphtyper genotyped 89.4 million sequence variants in the whole genomes of 28,075 Icelanders using less than 100,000 CPU days, including detailed genotyping of six human leukocyte antigen (HLA) genes. We show that Graphtyper is a valuable tool in characterizing sequence variation in both small and population-scale sequencing studies

Ice on banks of Snowy River, Snowy Mountains, New South Wales, 1935, [3] [transparency]/

Title devised by cataloguer from list.; "Ice on banks of Snowy R. 10."--In ink on slide label.; Condition: Fair.; Part of: Collection of glass lantern slides of the Snowy Mountains, 1935.; Also available in an electronic version via the Internet at: http://nla.gov.au/nla.pic-vn4236846

Variants with large effects on blood lipids and the role of cholesterol and triglycerides in coronary disease

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked Files. This article is open access.Sequence variants affecting blood lipids and coronary artery disease (CAD) may enhance understanding of the atherogenicity of lipid fractions. Using a large resource of whole-genome sequence data, we examined rare and low-frequency variants for association with non-HDL cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides in up to 119,146 Icelanders. We discovered 13 variants with large effects (within ANGPTL3, APOB, ABCA1, NR1H3, APOA1, LIPC, CETP, LDLR, and APOC1) and replicated 14 variants. Five variants within PCSK9, APOA1, ANGPTL4, and LDLR associate with CAD (33,090 cases and 236,254 controls). We used genetic risk scores for the lipid fractions to examine their causal relationship with CAD. The non-HDL cholesterol genetic risk score associates most strongly with CAD (P = 2.7 x 10(-28)), and no other genetic risk score associates with CAD after accounting for non-HDL cholesterol. The genetic risk score for non-HDL cholesterol confers CAD risk beyond that of LDL cholesterol (P = 5.5 x 10(-8)), suggesting that targeting atherogenic remnant cholesterol may reduce cardiovascular risk.Emory Neuroscience NINDS Core Facilities grant P30NS055077 deCODE Genetics/Amgen Emory by NIH grants from the Clinical and Translational Science Award program / UL1RR025008 R01HL089650-0

Large-scale whole-genome sequencing of the Icelandic population.

To access publisher's full text version of this article click on the hyperlink at the bottom of the pageHere we describe the insights gained from sequencing the whole genomes of 2,636 Icelanders to a median depth of 20×. We found 20 million SNPs and 1.5 million insertions-deletions (indels). We describe the density and frequency spectra of sequence variants in relation to their functional annotation, gene position, pathway and conservation score. We demonstrate an excess of homozygosity and rare protein-coding variants in Iceland. We imputed these variants into 104,220 individuals down to a minor allele frequency of 0.1% and found a recessive frameshift mutation in MYL4 that causes early-onset atrial fibrillation, several mutations in ABCB4 that increase risk of liver diseases and an intronic variant in GNAS associating with increased thyroid-stimulating hormone levels when maternally inherited. These data provide a study design that can be used to determine how variation in the sequence of the human genome gives rise to human diversity