1722-P: Colocalization of TOPMed Whole Genome Sequencing Analysis and Tissue-Specific eQTL Signals Detects Target Genes for Type 2 Diabetes Risk

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1722-P
Author(s):  
MINDY D. SZETO ◽  
HEATHER M. HIGHLAND ◽  
ALISA MANNING ◽  
Keyword(s):  
Type 2 Diabetes ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Target Genes ◽  
Diabetes Risk ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Tissue Specific

scholarly journals Rare Non-coding Variation Identified by Large Scale Whole Genome Sequencing Reveals Unexplained Heritability of Type 2 Diabetes

2020 ◽  
Author(s):  
Jennifer Wessel ◽  
Timothy D Majarian ◽  
Heather M Highland ◽  
Sridharan Raghavan ◽  
Mindy D Szeto ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Regulatory Elements ◽  
Whole Genome Sequence ◽  
European Ancestry ◽  
Substantial Contribution ◽  
Whole Genome

Type 2 diabetes is increasing in all ancestry groups1. Part of its genetic basis may reside among the rare (minor allele frequency <0.1%) variants that make up the vast majority of human genetic variation2. We analyzed high-coverage (mean depth 38.2x) whole genome sequencing from 9,639 individuals with T2D and 34,994 controls in the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program2 to show that rare, non-coding variants that are poorly captured by genotyping arrays or imputation panels contribute h2=53% (P=4.2×10−5) to the genetic component of risk in the largest (European) ancestry subset. We coupled sequence variation with islet epigenomic signatures3 to annotate and group rare variants with respect to gene expression4, chromatin state5 and three-dimensional chromatin architecture6, and show that pancreatic islet regulatory elements contribute to T2D genetic risk (h2=8%, P=2.4×10−3). We used islet annotation to create a non-coding framework for rare variant aggregation testing. This approach identified five loci containing rare alleles in islet regulatory elements that suggest novel biological mechanisms readily linked to hypotheses about variant-to-function. Large scale whole genome sequence analysis reveals the substantial contribution of rare, non-coding variation to the genetic architecture of T2D and highlights the value of tissue-specific regulatory annotation for variant-to-function discovery.

30-OR: Whole Genome Sequence Analysis of Type 2 Diabetes Risk in 44,713 Humans of Diverse Ancestry in the TOPMed Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 30-OR
Author(s):  
HEATHER M. HIGHLAND ◽  
JENNIFER WESSEL ◽  
ALISA MANNING ◽  
Keyword(s):  
Type 2 Diabetes ◽  
Sequence Analysis ◽  
Genome Sequence ◽  
Diabetes Risk ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequence Analysis

scholarly journals Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

2018 ◽  
Author(s):  
Maxime Garcia ◽  
Szilveszter Juhos ◽  
Malin Larsson ◽  
Pall I. Olason ◽  
Marcel Martin ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Open Source ◽  
Genome Sequencing ◽  
Development Project ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Insertion And Deletion ◽  
Sample Heterogeneity

AbstractSummaryWhole-genome sequencing (WGS) is a cornerstone of precision medicine, but portable and reproducible open-source workflows for WGS analyses of germline and somatic variants are lacking. We present Sarek, a modular, comprehensive, and easy-to-install workflow, combining a range of software for the identification and annotation of single-nucleotide variants (SNVs), insertion and deletion variants (indels), structural variants, tumor sample heterogeneity, and karyotyping from germline or paired tumor/normal samples. Sarek is implemented in a bioinformatics workflow language (Nextflow) with Docker and Singularity compatible containers, ensuring easy deployment and full reproducibility at any Linux based compute cluster or cloud computing environment. Sarek supports the human reference genomes GRCh37 and GRCh38, and can readily be used both as a core production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups.AvailabilitySource code and instructions for local installation are available at GitHub (https://github.com/SciLifeLab/Sarek) under the MIT open-source license, and we invite the research community to contribute additional functionality as a collaborative open-source development project.

scholarly journals Whole-genome sequencing analysis of Y chromosome microdeletion: a case report

2020 ◽  
Vol 48 (12) ◽  
pp. 030006052097649
Author(s):  
Zhixiang Gao ◽  
Feng Yuan ◽  
Qiaoqiao Li ◽  
Renlan Xia ◽  
Kai Fu ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Y Chromosome ◽  
Genome Sequencing ◽  
Sperm Quality ◽  
Sperm Count ◽  
Therapeutic Targets ◽  
Camp Signaling ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Y Chromosome Microdeletion

The mechanisms by which Y chromosome microdeletions cause infertility have been well described; however, the therapeutic targets remain a challenge. Here, we used whole-genome sequencing to explore the mechanism of Y chromosome deletion and potential therapeutic targets in a patient with infertility. There were no abnormalities in the patient’s medical history. Routine semen analysis showed immotile sperm and only two motile spermatozoa were occasionally see after centrifugation, indicating that the direct cause of infertility was an abnormal sperm count and motility. A Y chromosome microdeletion test revealed partial deletion of the AZFc region, including AZFc1, AZFc2, AZFc3, and AZFc4. Whole-genome sequencing showed that the patient had seven harmful mutations, with only one significant epigenetic mutation, SH3KBP1. Gene Ontology analysis of these meaningful mutations indicated involvement of cAMP signaling pathways. The patient’s wife became pregnant following in vitro fertilization, and no significant abnormalities were found during prenatal examination. This case suggests that Y chromosome microdeletion and gene mutation may affect the cAMP signaling pathway, leading to reduced sperm quality and male infertility.

484 Whole Genome Sequencing Analysis of Gastroparesis

2019 ◽  
Vol 114 (1) ◽  
pp. S280-S281
Author(s):  
Sandra P. Smieszek ◽  
Jesse L. Carlin ◽  
Gunther Birznieks ◽  
Mihael H. Polymeropoulos
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Sequencing Analysis
Sign in / Sign up

Export Citation Format

Share Document