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相关概念视频

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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Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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,...
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Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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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%...
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相关实验视频

Updated: Jan 11, 2026

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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使用GWAS预选变体和固定效果SNP增加了果的基因组预测能力.

Norman Munyengwa1, Melanie J Wilkinson1,2,3,4, Daniel Ortiz-Barrientos2,3

  • 1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, QLD, Australia.

Frontiers in plant science
|November 14, 2025
PubMed
概括
此摘要是机器生成的。

果的基因组选择通过结合从全基因组关联研究 (GWAS) 和固定效应标记物中预先选择的变异来提高准确性. 这一策略增强了对关键水果特征的预测能力,提高了育种效率.

关键词:
由GWAS预选的变种.全基因组关联研究研究.基因组预测 基因组预测子子子子子子人口结构 人口结构.预测的准确性 预测的准确性进行全基因组测序.

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科学领域:

  • 植物育种 植物育种
  • 基因组学就是基因组学.
  • 量化遗传学 量化遗传学

背景情况:

  • 使用全基因组测序 (WGS) 数据的基因组选择 (GS) 提供了提高果树育种价值准确性的潜力.
  • 之前的研究表明,与高密度标记集相比,WGS数据的收益有限,因此需要制定提高预测能力的策略.
  • 从全基因组关联研究 (GWAS) 中纳入预选变体是一个有前途的方法来改进GS模型.

研究的目的:

  • 研究将GWAS预选变体和固定效应标记物纳入基因组最佳线性无偏预测 (GBLUP) 模型的影响.
  • 评估果 (Mangifera indica L.) 果实红色 (FBC),平均果实重量 (AFW),果实坚硬度 (FF) 和树干周长 (TC) 的预测能力的改善.

主要方法:

  • 利用了来自225个果加入的WGS数据与跨越1999-2024年的表型数据.
  • 使用GBLUP模型评估预测能力,比较通过固定主要组件忽略或考虑人口结构的方法.
  • 评估了包括GWAS预选变体和固定效应单核酸多态 (SNP) 在预测能力上的影响.

主要成果:

  • 考虑到人口结构显著降低了预测能力,这表明子群体影响了初步估计.
  • 与使用所有WGS数据相比,GWAS预选的变体提高了预测能力,特别是当考虑人口结构时.
  • 固定效应的SNP显著提高了FBC的预测能力,GWAS预选变体和固定效应标记物的组合为FBC和TC带来了最高的改善.

结论:

  • 利用GWAS预选变体和固效SNP有效地提高了果基因组选择的预测能力.
  • 这种精细的方法有可能通过提高准确性来显著提高果树的育种效率.
  • GWAS确定了FBC,AFW和TC的特定特征相关SNP,为标记器辅助选择提供了有价值的标.