COPY NUMBER VARIATION IN METABOLIC SYNDROME

2008 ◽  
Vol 31 (4) ◽  
pp. 15
Author(s):  
M Lanktree ◽  
R A Hegele

Metabolic syndrome (MetS) is defined by the presence of abdominal obesity, hypertension, dysglycemia, and dyslipidemia. Many mutations have been discovered that cause rare monogenic components of metabolic syndrome, and association studies have linked common variants with increased risk of MetS and its components. Despite successes in identifying genetic contributors to metabolic syndrome, unexplained heritability exists and copy number variation (CNV) could be responsible for a portion of this variation. As observed with single nucleotide changes, it is likely that both rare and common CNVs will contribute to MetS disease susceptibility. Recent efforts to map CNVs in control populations have given insight into their size, frequency and distribution. However, despite being observed in controls, the reported CNVs could still modulate susceptibility for late-onset complex traitsor produce subtle metabolic phenotypes. Here we examine the overlap between CNVs found in control datasets and genes with functional hypotheses or evidence of previous association to MetS. Secondly, we present the results and methodology of a search for a rare CNV in a high-penetrance Mendelian disorder, namely familial partial lipodystrophy. As methods to identify CNVs increase in precision and accuracy, the prospect of identifying their role in both rare Mendelian and common complex diseases is exciting.

2012 ◽  
Vol 36 (3) ◽  
pp. 253-262 ◽  
Author(s):  
Xiaojing Zheng ◽  
John R. Shaffer ◽  
Caitlin P. McHugh ◽  
Cathy C. Laurie ◽  
Bjarke Feenstra ◽  
...  

PLoS ONE ◽  
2012 ◽  
Vol 7 (4) ◽  
pp. e34262 ◽  
Author(s):  
Patrick Breheny ◽  
Prabhakar Chalise ◽  
Anthony Batzler ◽  
Liewei Wang ◽  
Brooke L. Fridley

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yibin Qiu ◽  
Rongrong Ding ◽  
Zhanwei Zhuang ◽  
Jie Wu ◽  
Ming Yang ◽  
...  

Abstract Background In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. Copy number variation (CNV), an important source of genetic diversity, can affect a variety of complex traits and diseases and has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs using SNP genotyping data from 6627 animals. We also performed a copy number variation region (CNVR)-based genome-wide association studies (GWAS) for growth and fatness traits in two Duroc populations. Results Our study identified 953 nonredundant CNVRs in U.S. and Canadian Duroc pigs, covering 246.89 Mb (~ 10.90%) of the pig autosomal genome. Of these, 802 CNVRs were in U.S. Duroc pigs with 499 CNVRs were in Canadian Duroc pigs, indicating 348 CNVRs were shared by the two populations. Experimentally, 77.8% of nine randomly selected CNVRs were validated through quantitative PCR (qPCR). We also identified 35 CNVRs with significant association with growth and fatness traits using CNVR-based GWAS. Ten of these CNVRs were associated with both ADG and AGE traits in U.S. Duroc pigs. Notably, four CNVRs showed significant associations with ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. In Canadian Duroc pigs, nine CNVRs were significantly associated with both ADG and AGE traits. Further bioinformatic analysis identified a subset of potential candidate genes, including PDGFA, GPER1, PNPLA2 and BSCL2. Conclusions The present study provides a necessary supplement to the CNV map of the Duroc genome through large-scale population genotyping. In addition, the CNVR-based GWAS results provide a meaningful way to elucidate the genetic mechanisms underlying complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in the molecular-guided breeding of modern commercial pigs.


2013 ◽  
Vol 45 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Wenli Li ◽  
Michael Olivier

Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a small number of characterized genomic regions. However, the pervasiveness and full impact of such variation remains unclear. Suitable analytic methods are needed to thoroughly mine human genomes for genomic structural variation, and to explore the interplay between observed CNV and disease phenotypes, but many medical researchers are unfamiliar with the features and nuances of recently developed technologies for detecting CNV. In this article, we evaluate a suite of commonly used and recently developed approaches to uncovering genome-wide CNVs and discuss the relative merits of each.


2010 ◽  
Vol 19 (1) ◽  
pp. 69-77 ◽  
Author(s):  
Erin L. Heinzen ◽  
Anna C. Need ◽  
Kathleen M. Hayden ◽  
Ornit Chiba-Falek ◽  
Allen D. Roses ◽  
...  

2016 ◽  
Author(s):  
Shishi Luo ◽  
Jane A Yu ◽  
Yun S. Song

The study of genomic regions that contain gene copies and structural variation is a major challenge in modern genomics. Unlike variation involving single nucleotide changes, data on the variation of copy number is difficult to collect and few tools exist for analyzing the variation between individuals. The immunoglobulin heavy variable (IGHV) locus, which plays an integral role in the adaptive immune response, is an example of a genomic region that is known to vary in gene copy number. Lack of standard methods to genotype this region prevents it from being included in association studies and is holding back the growing field of antibody repertoire analysis. Here, we establish a convention of representing the locus in terms of a reference panel of operationally distinguishable segments defined by hierarchical clustering. Using this reference set, we develop a pipeline that identifies copy number and allelic variation in the IGHV locus from whole-genome sequencing reads. Tests on simulated reads demonstrate that our approach is feasible and accurate for detecting the presence and absence of gene segments using reads as short as 70 bp. With reads 100 bp and longer, coverage depth can also be used to determine copy number. When applied to a family of European ancestry, our method finds new copy number variants and confirms existing variants. This study paves the way for analyzing population-level patterns of variation in the IGHV locus in larger diverse datasets and for quantitatively handling regions of copy number variation in other structurally varying and complex loci.


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