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.

Authors

Institutions

Publication Details

Journal
The Plant Genome
Published
2025-03-01
DOI
https://doi.org/10.1002/tpg2.70005
Citations
3
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
5.45
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a 101.6K liquid‐phased probe for GWAS and genomic selection in pine wilt disease‐resistance breeding in Masson pine

Zhichun Zhou, Shu Diao, Xianyin Ding, Qinghua Liu et al.
3 citations
The Plant Genome
Genetic and phenotypic traits in livestock
5.45
article

Development of a 101.6K liquid‐phased probe for GWAS and genomic selection in pine wilt disease‐resistance breeding in Masson pine

Zhichun Zhou, Shu Diao, Xianyin Ding, Qinghua Liu, Jing-qiu Zhu, Yangdong Wang, Dong Luo, Mingyue Cao
article en
3 citations

Abstract

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.

The Plant GenomeVol. 18(1)
Nanjing Forestry University (CN), Chinese Academy of Forestry (CN), Research Institute of Forestry (CN), Qinghai Meteorological Bureau (CN)
Life in Land
Openalex Percentile: Top 5%
Genetic and phenotypic traits in livestock
5.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.