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Analysis of copy number variations in the sheep genome using 50K SNP BeadChip array
Jiasen Liu1, Li Zhang, Lingyang Xu
1National Center for Molecular Genetics and Breeding of Animal, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, People's Republic of China.
BMC Genomics
|April 10, 2013
Summary
This study constructed the first sheep copy number variation (CNV) map using SNP data. It identified 238 CNV regions, highlighting their role in environmental response and providing a foundation for future sheep trait association studies.
Area of Science:
- Genomics
- Animal Genetics
- Bioinformatics
Background:
- Genome-wide association studies (GWAS) identify single-nucleotide polymorphisms (SNPs) for complex traits, but explain limited heritability.
- High-throughput techniques reveal abundant submicroscopic structural variations, primarily copy number variations (CNVs).
- CNVs are increasingly recognized as a significant source of genetic variation and phenotypic diversity in organisms.
Purpose of the Study:
- To construct the first comprehensive sheep copy number variation (CNV) map.
- To analyze CNVs across three sheep breeds using high-density SNP data.
- To investigate the potential functional roles and genomic distribution of identified CNVs.
Main Methods:
- Analysis of CNVs in three sheep breeds utilizing the Ovine SNP50 BeadChip array.
- Identification and characterization of 238 copy number variation regions (CNVRs) across the sheep autosomal genome.
- Validation of selected CNVRs using quantitative polymerase chain reaction (qPCR) and comparison with existing ruminant CNV data.
Main Results:
- A total of 238 CNVRs were identified, covering 60.35 Mb (2.27%) of the sheep autosomal genome.
- CNVRs ranged from 13.66 kb to 1.30 Mb, with 75 events exceeding 3% frequency.
- Functional enrichment analysis revealed significant involvement of genes within CNVRs in environmental response; 6 CNVRs were validated by qPCR.
Conclusions:
- This study presents the first sheep CNV map constructed from Ovine SNP50 array data.
- Integration of multiple detection algorithms enhances the identification of sheep genomic structural variations.
- The findings provide a foundational resource for understanding sheep genome variation and future CNV association studies with economically important traits.
Related Concept Videos
02:26Comparing Copy Number Variations and SNPs
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
01:05Single Nucleotide Polymorphisms-SNPs
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
01:11Genome-wide Association Studies-GWAS
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
02:34DNA Microarrays
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...