Mapping QTL underlying body weight changes that act at different times during high-fat diet challenge in collaborative cross mice

Background Over one billion people worldwide suffer from obesity, and the number is continually rising. This epidemic is partly caused by the modern lifestyle, which is defined by excessive eating of food high in calories and little physical activity. However, genetic variation sets the stage and affects how the disease develops and advances. Animal models, especially mice 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, like ultimate body weight, are often examined in quantitative trait locus (QTL) studies; time series data, such as weekly or biweekly body weight, are usually disregarded. QTL mapping utilizing biweekly body weight measurements may be particularly intriguing in examining body weight gain in obesity research and identifying more genes connected with obesity and related metabolic problems. Results This study is focused on identifying QTL 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 male and 217 female), revealed genome-wide significant QTL on different chromosomes for body weight changes over 12 weeks. This study unveiled 62 body weight QTLs, among which 28 novels 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 were previously identified. Conclusions These findings illuminate genomic regions influencing body weight in CC mice and emphasize the utility of time series data in uncovering novel genetic factors.