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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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.
GWAS does not require the identification of the target gene involved in...
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  1. Home
  3. Smarter-database: A Tool To Integrate Snp Array Datasets For Sheep And Goat Breeds.
  1. Home
  3. Smarter-database: A Tool To Integrate Snp Array Datasets For Sheep And Goat Breeds.

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SMARTER-database: a tool to integrate SNP array datasets for sheep and goat breeds.

Paolo Cozzi1, Arianna Manunza1, Johanna Ramirez-Diaz1

  • 1Institute of Agricultural Biology and Biotechnology, National Research Council, Via Alfonso Corti nr. 12, 20133, Milano, Italy.

Gigabyte (Hong Kong, China)
|October 30, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

The SMARTER-database standardizes genomic data for sheep and goats, enabling better genetic diversity analysis. This resource supports research into livestock adaptation and sustainability.

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Area of Science:

  • Animal genetics
  • Genomics
  • Bioinformatics

Background:

  • Underutilized sheep and goat breeds possess unique genetic adaptations to challenging environments.
  • Integrating diverse genomic datasets is crucial for analyzing genetic diversity but is hindered by data inconsistencies.
  • Standardization is needed to harmonize SNP chip array data from global small ruminant populations.

Purpose of the Study:

  • To present the SMARTER-database, a suite of tools and scripts for standardizing genomic data and metadata.
  • To facilitate reproducible genetic diversity analyses in sheep and goats.
  • To support research on livestock adaptation and promote animal genetic resources sustainability.

Main Methods:

  • Developed a collection of tools and scripts to standardize genomic data and metadata.
  • Harmonized genotype data for approximately 12,000 sheep and 6,000 goats to a uniform coding and assembly version.
  • Implemented data access via File Transfer Protocol and a web interface for metadata interaction.

    • Main Results:

    • The SMARTER-database provides standardized genotype data for a large cohort of sheep and goats.
    • Metadata is accessible through a web interface and custom scripts, allowing efficient sample filtering.
    • The database focuses on SNP chip array data from global small ruminant populations.

    Conclusions:

    • The SMARTER-database empowers researchers by providing harmonized genomic data and metadata.
    • Facilitates in-depth analyses of genetic diversity and adaptation in small ruminants.
    • Contributes to the sustainable management of livestock genetic resources.