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Related Concept Videos

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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.
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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Related Experiment Video

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Infinium Assay for Large-scale SNP Genotyping Applications
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PHARP: a pig haplotype reference panel for genotype imputation.

Zhen Wang1, Zhenyang Zhang1, Zitao Chen1

  • 1College of Animal Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.

Scientific Reports
|July 25, 2022
PubMed
Summary

Researchers developed the pig Haplotype Reference Panel (PHARP), a comprehensive resource for pig genetic imputation. This panel enhances genome-wide association studies (GWAS) and other analyses by providing high-quality, diverse pig haplotype data.

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Area of Science:

  • Genomics and Bioinformatics
  • Animal Genetics
  • Agricultural Science

Background:

  • Pigs are crucial as a global meat source and as animal models for human complex traits.
  • Genotype imputation using haplotype reference panels is vital for downstream genomic analyses like GWAS and genomic prediction (GS).
  • A significant limitation in pig genetics research is the scarcity of large, diverse, and publicly accessible high-quality haplotype reference panels.

Purpose of the Study:

  • To construct a comprehensive and publicly available pig haplotype reference panel (PHARP) to address the existing data gap.
  • To provide web-based tools for efficient and consistent phasing and imputation of pig genomic data.
  • To demonstrate the utility of PHARP in improving the accuracy and scope of pig genetic studies.

Main Methods:

  • Assembled a reference panel of 2012 pig haplotypes across 34 million single nucleotide polymorphisms (SNPs).
  • Utilized whole-genome sequence data from over 49 studies encompassing 71 diverse pig breeds.
  • Developed web-based analytical tools for consistent and efficient phasing and imputation.

Main Results:

  • The PHARP database offers a high-quality reference panel for pig genetic imputation.
  • Demonstrated accurate imputation of 2.6 billion genotypes from commercial 50K SNP arrays with a concordance rate of 0.971.
  • Successfully applied the reference panel to impute low-density SNP chip data for three GWAS, identifying novel significantly associated SNPs.

Conclusions:

  • PHARP significantly enhances the capabilities for genotype imputation in pigs, overcoming previous limitations.
  • The availability of PHARP and its associated tools will accelerate discoveries in pig genetics, including complex trait research and breeding.
  • Imputation using PHARP facilitates the identification of potential causal variants in GWAS, advancing our understanding of pig genomics.