PT  - JOURNAL ARTICLE
AU  - Danny Arends
AU  - Deike Hesse
AU  - Stefan Kärst
AU  - Sebastian Heise
AU  - Shijie Lyu
AU  - Paula Korkuc
AU  - Manuel Delpero
AU  - Megan K. Mulligan
AU  - Pjotr Prins
AU  - Gudrun A. Brockmann
TI  - LMM-MQM time series mapping - An application in a murine advanced intercross line identifies novel growth QTLs
AID  - 10.1101/2022.01.23.477441
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.01.23.477441
4099  - http://biorxiv.org/content/early/2022/01/25/2022.01.23.477441.short
4100  - http://biorxiv.org/content/early/2022/01/25/2022.01.23.477441.full
AB  - The Berlin Fat Mouse Inbred line 860 (BFMI860) is a mouse model for juvenile obesity. Previously, a recessive major effect locus (jObes1) was identified on chromosome 3 explaining around 26% of the body weight variance in an BFMI860xC57BL/6NCrl advanced intercross line. The aim of this study was to discover additional QTL.Time series body weight data were modeled using linear mixed models (LMM), while a multiple QTL mapping (MQM) approach compensated for the jObes1 locus effect. LMM-MQM identified five additional loci significantly associated with body weight. Variance explained by the jObes1 locus increased to 38.1% when using LMM-MQM mapping, while the additional loci explained between 2.0% and 3.9% of the body weight variance. Several positional candidate genes within the novel QTL regions were found in KEGG pathways for insulin signaling and insulin resistance. Strong distortion with preference for the BFMI allele was observed within a newly identified QTL containing the well-known Foxo1 regulator of adipocyte differentiation.Here, we present a novel method for QTL detection in time series data: LMM-MQM time series mapping. We show that our method is more powerful in detecting QTLs compared to single timepoint mapping approaches. Thus, the time series structure should be considered for optimal detection of small effect QTLs. LMM-MQM time series mapping can be used to find genetic determinants of all kind of “phenotypes over time” be it lactation curves in cattle, plant biomass, drug clearance in human clinical trials, or cognitive decline during disease.