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代谢预测能否替代大麦中的基因组预测?

Can metabolic prediction be an alternative to genomic prediction in barley?

机构信息

Institute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany.

Institute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany.

出版信息

PLoS One. 2020 Jun 5;15(6):e0234052. doi: 10.1371/journal.pone.0234052. eCollection 2020.

DOI:10.1371/journal.pone.0234052
PMID:32502173
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7274421/
Abstract

Like other crop species, barley, the fourth most important crop worldwide, suffers from the genetic bottleneck effect, where further improvements in performance through classical breeding methods become difficult. Therefore, indirect selection methods are of great interest. Here, genomic prediction (GP) based on 33,005 SNP markers and, alternatively, metabolic prediction (MP) based on 128 metabolites with sampling at two different time points in one year, were applied to predict multi-year agronomic traits in the nested association mapping (NAM) population HEB-25. We found prediction abilities of up to 0.93 for plant height with SNP markers and of up to 0.61 for flowering time with metabolites. Interestingly, prediction abilities in GP increased after reducing the number of incorporated SNP markers. The estimated effects of GP and MP were highly concordant, indicating MP as an interesting alternative to GP, being able to reflect a stable genotype-specific metabolite profile. In MP, sampling at an early developmental stage outperformed sampling at a later stage. The results confirm the value of GP for future breeding. With MP, an interesting alternative was also applied successfully. However, based on our results, usage of MP alone cannot be recommended in barley. Nevertheless, MP can assist in unravelling physiological pathways for the expression of agronomically important traits.

摘要

与其他作物一样,大麦作为全球第四大重要作物,也受到遗传瓶颈效应的影响,通过传统的育种方法进一步提高其性能变得困难。因此,间接选择方法具有很大的吸引力。在这里,基于 33005 个 SNP 标记的基因组预测(GP)和基于 128 种代谢物的代谢预测(MP),在一年中的两个不同时间点进行采样,应用于嵌套关联作图(NAM)群体 HEB-25 中预测多年农业性状。我们发现 SNP 标记的植物高度预测能力高达 0.93,代谢物的开花时间预测能力高达 0.61。有趣的是,在减少纳入 SNP 标记的数量后,GP 的预测能力增加。GP 和 MP 的估计效应高度一致,表明 MP 是 GP 的一个有趣的替代方法,能够反映稳定的基因型特异性代谢物特征。在 MP 中,早期发育阶段的采样优于后期的采样。结果证实了 GP 在未来育种中的价值。通过 MP,也成功地应用了一种有趣的替代方法。然而,根据我们的结果,不能单独推荐 MP 在大麦中的应用。然而,MP 可以帮助揭示对农业重要性状表达的生理途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/03f51ca92329/pone.0234052.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/825bad991a28/pone.0234052.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/e46e941fa817/pone.0234052.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/03f51ca92329/pone.0234052.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/825bad991a28/pone.0234052.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/e46e941fa817/pone.0234052.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f052/7274421/03f51ca92329/pone.0234052.g003.jpg

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