结合 GS 辅助 GWAS 和转录组分析挖掘毛白杨氮利用效率的候选基因。

Combining GS-assisted GWAS and transcriptome analysis to mine candidate genes for nitrogen utilization efficiency in Populus cathayana.

机构信息

State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China.

Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, Jiangsu, China.

出版信息

BMC Plant Biol. 2023 Apr 5;23(1):182. doi: 10.1186/s12870-023-04202-1.

DOI:10.1186/s12870-023-04202-1

PMID:37020197

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10074878/

Abstract

BACKGROUND

Forest trees such as poplar, shrub willow, et al. are essential natural resources for sustainable and renewable energy production, and their wood can reduce dependence on fossil fuels and reduce environmental pollution. However, the productivity of forest trees is often limited by the availability of nitrogen (N), improving nitrogen use efficiency (NUE) is an important way to address it. Currently, NUE genetic resources are scarce in forest tree research, and more genetic resources are urgently needed.

RESULTS

Here, we performed genome-wide association studies (GWAS) using the mixed linear model (MLM) to identify genetic loci regulating growth traits in Populus cathayana at two N levels, and attempted to enhance the signal strength of single nucleotide polymorphism (SNP) detection by performing genome selection (GS) assistance GWAS. The results of the two GWAS analyses identified 55 and 40 SNPs that were respectively associated with plant height (PH) and ground diameter (GD), and 92 and 69 candidate genes, including 30 overlapping genes. The prediction accuracy of the GS model (rrBLUP) for phenotype exceeds 0.9. Transcriptome analysis of 13 genotypes under two N levels showed that genes related to carbon and N metabolism, amino acid metabolism, energy metabolism, and signal transduction were differentially expressed in the xylem of P. cathayana under N treatment. Furthermore, we observed strong regional patterns in gene expression levels of P. cathayana, with significant differences between different regions. Among them, P. cathayana in Longquan region exhibited the highest response to N. Finally, through weighted gene co-expression network analysis (WGCNA), we identified a module closely related to the N metabolic process and eight hub genes.

CONCLUSIONS

Integrating the GWAS, RNA-seq and WGCNA data, we ultimately identified four key regulatory genes (PtrNAC123, PtrNAC025, Potri.002G233100, and Potri.006G236200) involved in the wood formation process, and they may affect P. cathayana growth and wood formation by regulating nitrogen metabolism. This study will provide strong evidence for N regulation mechanisms, and reliable genetic resources for growth and NUE genetic improvement in poplar.

摘要

背景

杨树、柳树等森林树木是可持续和可再生能源生产的重要自然资源，其木材可以减少对化石燃料的依赖，减少环境污染。然而，森林树木的生产力通常受到氮（N）供应的限制，提高氮利用效率（NUE）是解决这一问题的重要途径。目前，森林树木研究中 NUE 遗传资源稀缺，急需更多的遗传资源。

结果

本研究采用混合线性模型（MLM）进行全基因组关联研究（GWAS），鉴定了两种氮水平下影响毛白杨生长性状的遗传位点，并尝试通过基因组选择（GS）辅助 GWAS 来增强单核苷酸多态性（SNP）检测信号强度。两种 GWAS 分析的结果分别鉴定出 55 个和 40 个与株高（PH）和地径（GD）相关的 SNP，以及 92 个和 69 个候选基因，其中 30 个基因重叠。GS 模型（rrBLUP）对表型的预测准确性超过 0.9。两种氮水平下 13 个基因型的转录组分析表明，在 N 处理下，毛白杨木质部中与碳和 N 代谢、氨基酸代谢、能量代谢和信号转导相关的基因差异表达。此外，我们观察到毛白杨基因表达水平存在强烈的区域模式，不同区域之间存在显著差异。其中，龙泉地区的毛白杨对 N 的反应最高。最后，通过加权基因共表达网络分析（WGCNA），我们鉴定了一个与 N 代谢过程密切相关的模块和 8 个枢纽基因。

结论

整合 GWAS、RNA-seq 和 WGCNA 数据，最终鉴定出 4 个参与木材形成过程的关键调控基因（PtrNAC123、PtrNAC025、Potri.002G233100 和 Potri.006G236200），它们可能通过调节氮代谢影响毛白杨的生长和木材形成。本研究为 N 调控机制提供了有力证据，为杨树生长和 NUE 遗传改良提供了可靠的遗传资源。