bioRxivGeneticsPreprint
Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats
Apurva S. ChitreiD, Thiago Missfeldt SanchesiD, Gavrila AngiD, Nana K. Amissah, Rodolfo AvilaiD, Hannah V. BimschlegeriD, Paola CampoiD, Nazzareno CannellaiD, Denghui CheniD, Riyan ChengiD, Katarina A CoheniD, Ayteria D. CrowiD, Eric DereschewitziD, Michelle R. DoyleiD, Maya EidiD, Anthony M. GeorgeiD, Aidan P. Horvath, Keita IshiwariiD, Benjamin B. JohnsoniD, Elaine KeungiD, Christopher P. KingiD, Connor D. MartiniD, Ángel García-MartíneziD, Daniel B. MunroiD, Alesa H. NetzleyiD, , Abraham A. PalmeriD
Abstract
Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.
- organism: rat
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
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