利用 BLUPIS 早期选择大豆谷物产量的策略。

IF 4.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Andreia Schuster, Felipe Lopes da Silva, João Amaro Ferreira Vieira Netto, Emanuel Ferrari do Nascimento, Paulo Eduardo Teodoro, Leonardo Lopes Bhering
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引用次数: 0

摘要

在大豆育种计划中,大量时间都用于使用在最初几代对单株进行选择的方法。我们的假设是,在大豆育种计划的初始阶段应用 BLUPIS(模拟个体 BLUP)可以提高效率。本研究旨在探索 BLUPIS 在大豆育种计划早期几代中的潜力,并评估划分实验田有用面积的策略在估计基因型效应和植株选择方面的可行性。实验涉及 F2 和 F3 代的 84 个分离群体和 15 个大豆亲本。产量数据收集自 2019/2020 年和 2020/2021 年种植季节。在 F2 代中,采用了不同的数据探索方法来确定 F3 代中最适合的适应性。使用来自不同重复的信息和/或与 BLUPI 所用信息相同的信息,将单个 BLUP(BLUPI)与 BLUPIS 进行比较。BLUPIS 和 BLUPI 的选育结果表明,所选植株的一致性很高。在 F3 代中,根据正基因型效应选择分离群体,并根据 BLUPIS 确定的植株数量进一步选择这些群体中的单株。在 F3 代中,划分小区是选择分离群体和优势群体中单株的有效策略,每株可获得约 1.56 克的遗传增益。BLUPIS 方法与在淡季推进世代的策略相结合,缩短了实现高同质性所需的时间。因此,BLUPIS 被证明是基于大豆谷物产量进行早期选育的强大统计工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Strategy for early selection for grain yield in soybean using BLUPIS.

In soybean breeding programs, a great deal of time is devoted to the use of methods that perform selection of individual plants during the initial generations. Our hypothesis is that BLUPIS (simulated individual BLUP) can be efficient when applied in the initial stages of soybean breeding programs. This study aimed to explore the potential of BLUPIS in the early generations of a soybean breeding program, as well as to assess the viability of the strategy of dividing the useful area of experimental plots for estimating genotypic effects and plant selection. The experiment involved 84 segregating populations and 15 soybean parents in the F2 and F3 generations. Yield data was collected from the 2019/2020 and 2020/2021 cropping seasons. In the F2 generation, different data exploration methods were applied to determine the most suitable adaptation to be used in the F3 generation. The individual BLUP (BLUPI) was compared with BLUPIS using information from different replications and/or equal to the information used in BLUPI. The selection conducted by BLUPIS and BLUPI showed high concordance regarding the selected plants. In the F3 generation, segregating populations were selected based on positive genotypic effects, and individual plants within these populations were further selected according to the number of plants determined by BLUPIS. The division of the plot area was an efficient strategy for selecting segregating populations and individual plants within superior populations in the F3 generation, resulting in genetic gains of approximately 1.56 g per plant. When combined with the strategy of advancing generations in the off-season, the BLUPIS approach reduces the time required to achieve a high level of homozygosity. Therefore, BLUPIS proved to be a powerful statistical tool for early selection based on grain yield in soybeans.

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来源期刊
Plant Methods
Plant Methods 生物-植物科学
CiteScore
9.20
自引率
3.90%
发文量
121
审稿时长
2 months
期刊介绍: Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences. There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics. Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.
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