Abstract:
:Whole-organism metabolic rate co-varies allometrically with body mass, and is also affected by temperature through different biochemical mechanisms. Here we implement a computational platform to map specific quantitative trait loci (QTLs) that govern the dependence of metabolic rate on size and temperature. The model was formulated within settings of genetic mapping or genome-wide association studies through a mapping population genotyped by a set of molecular markers throughout the genome and phenotyped for metabolic parameters over a range of temperature. The model, estimated by a maximum-likelihood approach, allows a genome-wide search for the underlying metabolic QTLs and the estimation of genotype-specific parameters that specify the metabolism of an organism. Our model provides a tool to detect pleiotropy and epistasis that cause the size- and temperature-dependent change of metabolic rate.
journal_name
Brief Bioinformjournal_title
Briefings in bioinformaticsauthors
Yan Q,Zhu X,Jiang L,Ye M,Sun L,Terblanche JS,Wu Rdoi
10.1093/bib/bbv116subject
Has Abstractpub_date
2017-01-01 00:00:00pages
137-144issue
1eissn
1467-5463issn
1477-4054pii
bbv116journal_volume
18pub_type
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