101.6K液相GWAS探针的研制及马尾松抗枯萎病育种基因组选择

IF 3.9 2区 生物学 Q1 GENETICS & HEREDITY
Plant Genome Pub Date : 2025-03-01 DOI:10.1002/tpg2.70005
Jingyi Zhu, Qinghua Liu, Shu Diao, Zhichun Zhou, Yangdong Wang, Xianyin Ding, Mingyue Cao, Dinghui Luo
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引用次数: 0

摘要

马尾松(Pinus massoniana Lamb.)是中国南方的一种本土植物,面临着松树枯萎病(PWD)的严重威胁。几种天然基因型在PWD暴发中幸存下来。利用这些抗性基因型进行遗传育种有望增强马尾松对PWD的抗性。为了推进马尾松抗病育种,对来自72个同父异母家族的1013株马尾松幼苗进行了全基因组关联研究(GWAS)和基因组选择(GS)。建立了一套高效的101.6K液相探针,通过靶测序进行单核苷酸多态性(snp)基因分型。然后进行PWD接种实验以获得这些群体的表型数据。我们的分析表明,目标测序数据成功地将实验种群划分为与来源一致的三个亚种群,验证了液相探针的可靠性。使用四种GWAS算法,共有548个snp与抗病性状显著相关。其中283份定位于或连锁于169个基因,包括NBS-LRR和AP2/ERF等常见植物抗病相关蛋白家族。DNNGP(基于深度神经网络的基因组预测方法)模型在GS中表现出优异的性能,达到了0.71的最大预测精度。在按抗性基因组估计育种值排序的前20%的测试群体中,疾病抗性预测的准确性达到90%。本研究为马尾松抗病基因的深入研究奠定了基础框架,并为利用GS技术早期鉴定马尾松抗病个体的可行性提供了初步证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of a 101.6K liquid-phased probe for GWAS and genomic selection in pine wilt disease-resistance breeding in Masson pine.

Masson pine (Pinus massoniana Lamb.), indigenous to southern China, faces serious threats from pine wilt disease (PWD). Several natural genotypes have survived PWD outbreaks. Conducting genetic breeding with these resistant genotypes holds promise for enhancing resistance to PWD in Masson pine at its source. We conducted a genome-wide association study (GWAS) and genomic selection (GS) on 1013 Masson pine seedlings from 72 half-sib families to advance disease-resistance breeding. A set of efficient 101.6K liquid-phased probes was developed for single-nucleotide polymorphisms (SNPs) genotyping through target sequencing. PWD inoculation experiments were then performed to obtain phenotypic data for these populations. Our analysis reveals that the targeted sequencing data successfully divided the experimental population into three subpopulations consistent with the provenance, verifying the reliability of the liquid-phased probe. A total of 548 SNPs were considerably associated with disease-resistance traits using four GWAS algorithms. Among them, 283 were located on or linked to 169 genes, including common plant disease resistance-related protein families such as NBS-LRR and AP2/ERF. The DNNGP (deep neural network-based method for genomic prediction) model demonstrated superior performance in GS, achieving a maximum predictive accuracy of 0.71. The accuracy of disease resistance predictions reached 90% for the top 20% of the testing population ordered by resistance genomic estimated breeding value. This study establishes a foundational framework for advancing research on disease-resistant genes in P. massoniana and offers preliminary evidence supporting the feasibility of utilizing GS for the early identification of disease-resistant individuals.

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来源期刊
Plant Genome
Plant Genome PLANT SCIENCES-GENETICS & HEREDITY
CiteScore
6.00
自引率
4.80%
发文量
93
审稿时长
>12 weeks
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.
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