Mapping quantitative trait loci underlying body weight changes that act at different times during high-fat diet...

Over one billion people worldwide suffer from obesity, and the number is continually rising. This epidemic is partly caused by the modern lifestyle. Animal models, especially mouse models, are crucial to identifying the genetic components of complex disorders and exploring the potential applications of these genetic findings. The body weight of the animals used in research is often measured regularly to monitor their health. Only endpoint measurements, such as ultimate body weight, are frequently examined in quantitative trait locus (QTL) studies; time series data, including weekly or biweekly body weight, are usually disregarded. QTL mapping using biweekly body weight measurements may be particularly intriguing in examining body weight gain in obesity research and identifying more genes associated with obesity and related metabolic disorders. This study is focused on identifying quantitative trait loci (QTLs) underlying body weight changes by analyzing biweekly weight measurements in collaborative cross (CC) mice maintained on a high-fat diet for 12 weeks. QTL analysis, utilizing 525 mice from 55 CC lines (308 males and 217 females), revealed genome-wide significant QTLs on different chromosomes for body weight changes over 12 weeks. This study unveiled 62 body weight QTLs, among which 28 novel QTLs associated with defined traits were observed and found not reported previously. In addition, 34 more QTLs were fine-mapped, as the genomic interval positions of these had been previously identified. These findings highlight genomic regions that influence body weight in CC mice, underscoring the value of time series data in identifying novel genetic factors.