TY - CHAP
T1 - QTL Mapping of Molecular Traits for Studies of Human Complex Diseases
AU - Liu, Chunyu
N1 - Publisher Copyright: © Springer Science+Business Media Dordrecht 2012.
PY - 2012
Y1 - 2012
N2 - Genetic mapping of quantitative trait loci (QTL) offers a powerful and efficient approach to discover putative regulatory regions of traits and to define novel functional implications of genetic variants. Here we reviewed recent progress on QTL mapping of molecular traits, including gene expression, DNA methylation, as well as protein expression, metabolites. QTL mapping of molecular traits has better chance to succeed in relatively small sample size study as fewer nongenetic factors or gene-gene interactions may involve. Knowledge derived from QTL mapping will help us to uncover understanding of biology in complex traits and diseases and enhance power of genetic association study. In the context of study of complex diseases, we focused on expression QTL and methylation QTL, presenting major findings and technique considerations, including experimental platform, sample quality, size, and heterogeneity, as well as analytical procedure and significance criteria. Lastly, we discussed the current and future use of QTL data in study of complex diseases.
AB - Genetic mapping of quantitative trait loci (QTL) offers a powerful and efficient approach to discover putative regulatory regions of traits and to define novel functional implications of genetic variants. Here we reviewed recent progress on QTL mapping of molecular traits, including gene expression, DNA methylation, as well as protein expression, metabolites. QTL mapping of molecular traits has better chance to succeed in relatively small sample size study as fewer nongenetic factors or gene-gene interactions may involve. Knowledge derived from QTL mapping will help us to uncover understanding of biology in complex traits and diseases and enhance power of genetic association study. In the context of study of complex diseases, we focused on expression QTL and methylation QTL, presenting major findings and technique considerations, including experimental platform, sample quality, size, and heterogeneity, as well as analytical procedure and significance criteria. Lastly, we discussed the current and future use of QTL data in study of complex diseases.
KW - Complex diseases
KW - DNA methylation
KW - eQTL
KW - mQTL
KW - pQTL
UR - https://www.scopus.com/pages/publications/105007644934
U2 - 10.1007/978-94-007-5558-1_5
DO - 10.1007/978-94-007-5558-1_5
M3 - Chapter
T3 - Translational Bioinformatics
SP - 61
EP - 82
BT - Translational Bioinformatics
PB - Springer Nature
ER -