Low density marker-based effectiveness and efficiency of early-generation genomic selection relative to phenotype-based selection in dolichos bean (Lablab purpureus L. Sweet).
Mugali Pundalik Kalpana, Sampangi Ramesh, Chindi Basavaraj Siddu, Gonal Basanagouda, K Madhusudan, Hosakoti Sathish, Dinesh Sindhu, Munegowda Kemparaju, C Anilkumar
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引用次数: 0
Abstract
Genomic prediction has been demonstrated to be an efficient approach for the selection of candidates based on marker information in many crops. However, efforts to understand the efficiency of genomic selection over phenotype-based selection in understudied crops such as dolichos bean (Lablab purpureus L. Sweet) are limited. Our objectives were to (i) explore the effective marker density for achieving high prediction accuracy and (ii) assess the effectiveness and efficiency of genomic selection over phenotype-based selection on seed yield at early segregating generations in dolichos bean. In this study, the training population, which consisted of F5:6 recombinant inbreds, had a shared common parent with the breeding population, which consisted of F2 generation breeding population. The populations were genotyped with newly synthesized genomic simple sequence repeat-based markers. The effective marker density for genomic prediction was assessed by using a varying number of markers in predictions using 11 different models. Furthermore, the effectiveness of genomic selection was assessed by comparing the genetic gains in progenies between genotypes selected based on predicted seed yield and phenotypically selected genotypes. Our results indicate that low-density markers that are evenly distributed throughout the genome are sufficient for the integration of genomic selection in dolichos breeding programs. The genomic selection was proved to be two times more effective than phenotypic selection in early-generation selection in dolichos beans. The results have a significant impact on adopting genomic selection in regular breeding programs of Dolichos beans at a low cost.
在许多作物中,基因组预测已被证明是一种基于标记信息的候选作物选择的有效方法。然而,在未充分研究的作物中,如豆(Lablab purpureus L. Sweet),了解基因组选择比基于表型选择的效率的努力是有限的。我们的目标是:(i)探索实现高预测精度的有效标记密度;(ii)评估基因组选择在豆早期分离代种子产量方面的有效性和效率,而不是基于表型的选择。在本研究中,由F5:6重组自交系组成的训练群体与由F2代繁殖群体组成的繁殖群体具有共同的亲本。用新合成的基因组简单序列重复标记对群体进行基因分型。通过使用11种不同模型的不同数量的预测标记来评估基因组预测的有效标记密度。此外,通过比较基于预测种子产量选择的基因型和表型选择的基因型在后代中的遗传增益,评估了基因组选择的有效性。我们的研究结果表明,在整个基因组中均匀分布的低密度标记足以在多穗草育种计划中整合基因组选择。基因组选择比表型选择的早代选择效率高2倍。研究结果对在常规低成本育种中采用基因组选择具有重要意义。
期刊介绍:
The Plant Genome publishes original research investigating all aspects of plant genomics. Technical breakthroughs reporting improvements in the efficiency and speed of acquiring and interpreting plant genomics data are welcome. The editorial board gives preference to novel reports that use innovative genomic applications that advance our understanding of plant biology that may have applications to crop improvement. The journal also publishes invited review articles and perspectives that offer insight and commentary on recent advances in genomics and their potential for agronomic improvement.