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diff --git a/general/datasets/UCLA_BXD_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_BXD_Femur_0113_RSN/summary.rtf new file mode 100644 index 0000000..df75fa6 --- /dev/null +++ b/general/datasets/UCLA_BXD_Femur_0113_RSN/summary.rtf @@ -0,0 +1 @@ +<p>Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.</p>
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