利用 REML/BLUP 对木薯采后生理退化耐受性和根系性状的遗传参数和基因型值进行预测

IF 2.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochemical Genetics Pub Date : 2024-11-18 DOI:10.1007/s10528-024-10972-6
Visalakshi Chandra, M N Sheela, V Ravi, Bishal Gurung, Senthil Alias Sankar, J Sreekumar
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引用次数: 0

摘要

该研究旨在利用限制性最大似然法(REML)和最佳线性无偏预测法(BLUP)估计木薯(Manihot esculentaCrantz)收获后生理退化和根系特征的遗传参数并预测其基因型值。在两个生长季节中,共对 76 个木薯品种进行了评估。评估的性状包括收获后生理退化反应(PPD)、根长(RL)、根径(RD)、根重(RW)、干物质含量(DMC)、总淀粉含量(TS)和总糖含量(TSU)。所有性状的表型变异成分均高于遗传或环境变异,基因型变异在表型总变异中所占比例较大。遗传力估计值从低到高不等,其中干物质含量、PPD 和根直径的遗传力值较高。研究发现 PPD、根重和直径的基因型变异系数(CVg)很高,这表明基因型变异性很强,有利于选择。由于遗传效应大于非遗传效应会导致选择收益增加,因此干物质含量和 PPD 的 CVr 值最高,表明选择收益的可能性最大。收获后生理退化(PPD)的遗传进展最大,表明下一代的收益显著。根据 BLUP 指数,有 38 个基因型被选为最有前途的基因型,促进了多个性状的改良和遗传增益。所选基因型可纳入木薯育种计划,以提高木薯对 PPD 的耐受性和其他块茎性状。
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Genetic Parameters and Prediction of Genotypic Values for Postharvest Physiological Deterioration Tolerance and Root Traits in Cassava using REML/BLUP.

The study aimed to estimate the genetic parameters and predict the genotypic values of postharvest physiological deterioration and root characteristics in cassava (Manihot esculentaCrantz) using restricted maximum likelihood (REML) and the best linear unbiased prediction (BLUP). A total of 76 cassava accessions were evaluated over two growing seasons. The evaluated traits included postharvest physiological deterioration response (PPD), root length (RL), root diameter (RD), root weight (RW), dry matter content (DMC), total starch content (TS) and total sugar content (TSU). All the traits had a higher phenotypic variance component than genetic or environmental variance, with genotypic variance making up a larger portion of the total phenotypic variance. Heritability estimates ranged from low to high, with high heritability values being recorded for dry matter content, PPD, and root diameter. The study discovered high genotypic coefficients of variation (CVg) for PPD, root weight and diameter, indicating strong genotypic variability beneficial for selection. As larger genetic effects than non-genetic effects lead to increased selection gains, the highest CVr values for dry matter content and PPD suggest the biggest probability of selection gain. Postharvest Physiological deterioration (PPD) had the highest genetic advance, indicating significant gain in the following generation. Thirty eight genotypes were selected as the most promising based on BLUP index, promoting improvement and genetic gain in several traits. The genotypes selected can be included in cassava breeding programs for PPD tolerance and other tuber traits.

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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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