Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

18.7K
Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
18.7K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.7K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.3K
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...
12.3K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Statistics and data science unlock the predictive power of quantitative genetics.

Frontiers in plant science·2026
Same author

Genomics for next-generation wheat breeding.

The plant genome·2026
Same author

Multimodal genomic prediction is not a buzzword: why modern plant breeding must integrate genomics, enviromics, and phenomics.

G3 (Bethesda, Md.)·2026
Same author

Computational Predictions and Evolutionary Analysis of <i>LrK10</i> Kinase-Related Putative <i>PSTOL1</i> Gene Homeologs in Wheat and Orthologs of Its Wild Relatives.

International journal of molecular sciences·2026
Same author

Large scale wheat data integration improves genomic prediction accuracy with the potential to facilitate international breeding collaborations.

Communications biology·2026
Same author

Correction: Multi-trait and multi-environment genomic prediction enhances yield components improvement in durum wheat.

Frontiers in plant science·2026

相关实验视频

Updated: May 23, 2025

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

9.6K

提高小麦谷物产量基因组预测准确性使用历史数据.

Paolo Vitale1, Osval Montesinos-López2, Guillermo Gerard1

  • 1International Maize and Wheat Improvement Center (CIMMYT), Km 45 Carretera México-Veracruz, El Batan, Edo. de México 5623, Mexico.

G3 (Bethesda, Md.)
|March 8, 2025
PubMed
概括

在小麦育种中,基因组选择随着更多的历史数据而得到改善,但平衡遗传多样性是准确预测的关键. 使用扩展数据集可以增强遗传收益,并支持高产品种的发展.

关键词:
基因组预测 基因组预测历史数据 历史数据植物育种 植物育种预测的准确性 预测的准确性小麦品种小麦品种小麦

更多相关视频

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
08:36

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis

Published on: July 16, 2019

11.5K
Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

7.4K

相关实验视频

Last Updated: May 23, 2025

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

9.6K
Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
08:36

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis

Published on: July 16, 2019

11.5K
Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

7.4K

科学领域:

  • 农业科学 农业科学
  • 植物育种 植物育种
  • 遗传学 遗传学 是一个

背景情况:

  • 基因组选择对于加速小麦育种中的遗传收益至关重要.
  • 提高预测准确度对于开发优质小麦品种至关重要.
  • CIMMYT的历史数据集为基因组选择研究提供了宝贵的资源.

研究的目的:

  • 为了提高在各种环境中提高小麦谷物产量的预测准确性.
  • 评估历史数据深度对基因组预测的影响.
  • 评估遗传多样性在基因组选择准确性中的作用.

主要方法:

  • 来自六个选择环境的十年小麦谷物产量数据的分析.
  • 利用前几年的培训人群和最近几年的验证人群.
  • 调查预测准确性,训练数据持续时间和遗传多样性之间的相关性.

主要成果:

  • 预测准确性通常会随着培训年数的增加而改善或稳定.
  • 特定环境对延长训练数据的反应各不相同,有些早期停滞.
  • 观察到预测准确度和遗传距离之间的负相关性,突出显示了遗传多样性的重要性.

结论:

  • 扩展的历史数据集显著有利于小麦育种中的基因组选择.
  • 在培训和验证人群中平衡遗传多样性对于最大限度地提高预测准确性至关重要.
  • 这些发现支持为高产小麦品种开发更有效的基因组选择策略.