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相关概念视频

Light Acquisition02:16

Light Acquisition

9.4K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Trihybrid Crosses02:27

Trihybrid Crosses

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Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
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Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

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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.
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Test Cross01:39

Test Cross

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Alleles are different forms of the same gene. Humans and other diploid organisms inherit two alleles of every gene, one from each parent.
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Monohybrid Crosses01:20

Monohybrid Crosses

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Overview
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Dihybrid Crosses01:18

Dihybrid Crosses

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Overview
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相关实验视频

Updated: Jan 13, 2026

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
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互惠BLUP:一种可预测性引导的多态学框架,用于植物表型预测.

Hayato Yoshioka1, Gota Morota1, Hiroyoshi Iwata1

  • 1Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo 113-8657, Japan.

Plants (Basel, Switzerland)
|January 10, 2026
PubMed
概括

一个新的互惠BLUP框架整合了基因组,代谢组和微生物组数据来预测作物表现. 这种多组学方法通过识别关键分子参与者并提高特征预测精度来增强植物育种,特别是在环境压力下.

科学领域:

  • 植物基因组学和育种
  • 多omics数据集成多omics数据集成
  • 系统生物学在农业中的应用

背景情况:

  • 提高作物性能需要通过分子途径将遗传变异与可观察的特征联系起来.
  • 当前的方法往往难以整合多样化的OMIC数据来进行全面的表型预测.
  • 了解基因型-环境-微生物群相互作用对于可持续农业至关重要.

研究的目的:

  • 引入互惠最佳线性无偏预测 (互惠BLUP),这是一个多主题集成的框架.
  • 量化基因组,代谢组和微生物组之间的跨层关系,以提高表型预测.
  • 评估可预测性引导特征选择在植物育种应用中的有用性.

主要方法:

  • 开发并应用了互惠BLUP框架,用于大豆在不同的水条件下加入.
  • 评估了四种特定方向的预测模型,以评估跨omics特征的可预测性.
  • 使用可预测性选择特征与随机选择和全功能模型相比,比较表型预测准确度.

主要成果:

  • 确定了一个不对称的关系,即代谢组可以从微生物组中预测,但不能反过来.
  • 与随机选择相比,以可预测性为指导的特征选择显著提高了表型预测的准确性.
  • 代谢和微生物模型 (MetBLUP,MicroBLUP) 在干旱下的生物质特征方面表现优于基因组预测 (GBLUP).
关键词:
基因组 基因组是基因组的组成部分.线性混合模型线性混合模型代谢组代谢组的代谢微生物组是一个微生物组.

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结论:

  • 代谢组作为关键的调解者,将植物的基因型,环境和微生物组合联系起来.
  • 互惠BLUP提供了一种生物学上可解释的方法,用于整合植物育种中的多omics数据.
  • 该框架增强了表型预测,并指导了作物改进的基于奥米克的特征选择.