Exploring the genetic basis of gene transcript abundance and metabolite level in loblolly pine (Pinus taeda L.) using association mapping and network construction
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https://bmcgenet.biomedcentral.com/articles/10.1186/s12863-018-0687-7https://elib.sfu-kras.ru/handle/2311/129608
Автор:
Mengmeng, Lu
Candace M. Seeve
Konstantin V. Krutovsky
Carol A. Loopstra
Коллективный автор:
Институт фундаментальной биологии и биотехнологии
Базовая кафедра защиты и современных технологии мониторинга лесов
Дата:
2018-11Журнал:
BMC GeneticsКвартиль журнала в Scopus:
Q2Квартиль журнала в Web of Science:
Q3Библиографическое описание:
Mengmeng, Lu. Exploring the genetic basis of gene transcript abundance and metabolite level in loblolly pine (Pinus taeda L.) using association mapping and network construction [Текст] / Lu Mengmeng, Candace M. Seeve, Konstantin V. Krutovsky, Carol A. Loopstra // BMC Genetics. — 2018. — Т. 19 (№ 100).Аннотация:
Gene transcripts and metabolites are important regulatory checkpoints between genetic variation and complex biological processes such as wood development and drought response in conifers. Loblolly pine (Pinus taeda L.) is one of the most commonly planted forest tree species in the southern U.S. In this study, we tested for associations between 2.8 million exome-derived SNPs and the transcript abundance of 110 wood development genes, 88 disease or drought related genes as well as levels of 82 known metabolites. We identified 1841 SNPs associated with 191 gene expression phenotypes and 524 SNPs associated with 53 metabolite level phenotypes. The identified SNPs reside in genes with a wide variety of functions. We further integrated the identified SNPs and their associated expressed genes and metabolites into networks. We described the SNP-SNP interactions that significantly impacted the gene transcript abundance and metabolite level in the networks. The key loci and genes in the wood development and drought response networks were identified and analyzed. This work provides candidate genes for research on the genetic basis of gene expression and metabolism linked to wood development and drought response in loblolly pine, and highlights the efficiency of using association-mapping-based networks to discover candidate genes with important roles in complex biological processes.