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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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Multiple Allele Traits01:49

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The Concept of Multiple Allelism
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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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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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Frequency-dependent Selection01:21

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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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非線形ゲノム選択指数は,多特性の作物改良を加速する.

J Jesús Cerón-Rojas1, Osval A Montesinos-López2, Abelardo Montesinos-López3

  • 1Colegio de Postgraduados, Montecillos, Edo. de México, México.

Nature communications
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まとめ

Quadratic Genomic Selection Index (QGSI) は,作物の改良を迅速にするために,非線形的な関係を把握しています. このゲノム学的アプローチは,選択反応と多特性の育種プログラムにおける予測の精度を向上させます.

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科学分野:

  • 植物育種 植物育種
  • 定量遺伝学 定量遺伝学とは
  • ゲノミクスゲノミクスとは

背景:

  • 線形選択指標は,複雑な非線形特性の関係を利用することを制限する.
  • ゲノム選択は繁殖を進めてきましたが,しばしば添加モデルに依存しています.

研究 の 目的:

  • 非線形ゲノム情報を統合するために,二次ゲノム選択指数 (QGSI) を導入する.
  • ゲノム推定繁殖値 (GEBVs) を使用して,フェノタイプフリー,急速サイクル,マルチ特性の選択を可能にします.

主な方法:

  • ゲノムフレームワークに二次的な現象型選択指数 (QPSI) を拡張することによって,QGSIを開発しました.
  • GEBVsの統合添加物,二乗,およびクロス製品用語.
  • 最大確率添加および非線形ガウス核ゲノム予測モデルを使用してQGSIを評価した.

主要な成果:

  • QGSIは,シミュレートされたデータセットと実際のデータセット (トウモロコシと小麦) の間で優れたパフォーマンスを示しました.
  • 線形指数と二次指数と比較して,より高い選択応答と低い予測誤差差を達成しました.
  • ゲノム全体の非線形関係とエピスタティック信号を効果的に捕捉した.

結論:

  • 非線形ゲノム予測と二次選択指標の組み合わせにより,多特性の作物の改善が加速されます.
  • QGSIは,複雑な遺伝子構造を利用して,繁殖効率を高めるための一般的な戦略を提供します.