Andreia Schuster, Felipe Lopes da Silva, João Amaro Ferreira Vieira Netto, Emanuel Ferrari do Nascimento, Paulo Eduardo Teodoro, Leonardo Lopes Bhering
{"title":"利用 BLUPIS 早期选择大豆谷物产量的策略。","authors":"Andreia Schuster, Felipe Lopes da Silva, João Amaro Ferreira Vieira Netto, Emanuel Ferrari do Nascimento, Paulo Eduardo Teodoro, Leonardo Lopes Bhering","doi":"10.1186/s13007-024-01298-w","DOIUrl":null,"url":null,"abstract":"<p><p>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 F<sub>2</sub> and F<sub>3</sub> generations. Yield data was collected from the 2019/2020 and 2020/2021 cropping seasons. In the F<sub>2</sub> generation, different data exploration methods were applied to determine the most suitable adaptation to be used in the F<sub>3</sub> 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 F<sub>3</sub> 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 F<sub>3</sub> 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.</p>","PeriodicalId":20100,"journal":{"name":"Plant Methods","volume":"20 1","pages":"176"},"PeriodicalIF":4.7000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11580668/pdf/","citationCount":"0","resultStr":"{\"title\":\"Strategy for early selection for grain yield in soybean using BLUPIS.\",\"authors\":\"Andreia Schuster, Felipe Lopes da Silva, João Amaro Ferreira Vieira Netto, Emanuel Ferrari do Nascimento, Paulo Eduardo Teodoro, Leonardo Lopes Bhering\",\"doi\":\"10.1186/s13007-024-01298-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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 F<sub>2</sub> and F<sub>3</sub> generations. Yield data was collected from the 2019/2020 and 2020/2021 cropping seasons. In the F<sub>2</sub> generation, different data exploration methods were applied to determine the most suitable adaptation to be used in the F<sub>3</sub> 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 F<sub>3</sub> 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 F<sub>3</sub> 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. 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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.
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.