Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease.

A major fraction of loci identified by genome-wide association studies (GWASs) mediate alternative splicing, but mechanistic interpretation is hindered by the technical limitations of short-read RNA sequencing (RNA-seq), which cannot directly link splicing events to full-length protein isoforms. Long-read RNA-seq represents a powerful tool to characterize transcript isoforms, and recently, infer protein isoform existence. Here, we present an approach that integrates information from GWASs, splicing quantitative trait loci (sQTLs), and PacBio long-read RNA-seq in a disease-relevant model to infer the effects of sQTLs on the ultimate protein isoform products they encode. We demonstrate the utility of our approach using bone mineral density (BMD) GWAS data. We identified 1,863 sQTLs from the Genotype-Tissue Expression (GTEx) project in 732 protein-coding genes that colocalized with BMD associations (H4PP ≥ 0.75). We generated PacBio Iso-Seq data (N = ∼22 million full-length reads) on human osteoblasts, identifying 68,326 protein-coding isoforms, of which 17,375 (25%) were unannotated. By casting the sQTLs onto protein isoforms, we connected 809 sQTLs to 2,029 protein isoforms from 441 genes expressed in osteoblasts. Overall, we found that 74 sQTLs influenced isoforms likely impacted by nonsense-mediated decay and 190 that potentially resulted in the expression of unannotated protein isoforms. Finally, we functionally validated colocalizing sQTLs in TPM2, in which siRNA-mediated knockdown in osteoblasts showed two TPM2 isoforms with opposing effects on mineralization but exhibited no effect upon knockdown of the entire gene. Our approach should be to generalize across diverse clinical traits and to provide insights into protein isoform activities modulated by GWAS loci.

Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations.

Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.

Multi-scale cortical bone traits vary in females and males from two mouse models of genetic diversity.

Understanding the genetic basis of cortical bone traits can allow for the discovery of novel genes or biological pathways regulating bone health. Mice are the most widely used mammalian model for skeletal biology and allow for the quantification of traits that cannot easily be evaluated in humans, such as osteocyte lacunar morphology. The goal of our study was to investigate the effect of genetic diversity on multi-scale cortical bone traits of 3 long bones in skeletally-mature mice. We measured bone morphology, mechanical properties, material properties, lacunar morphology, and mineral composition of mouse bones from 2 populations of genetic diversity. Additionally, we compared how intrabone relationships varied in the 2 populations. Our first population of genetic diversity included 72 females and 72 males from the 8 inbred founder strains used to create the Diversity Outbred (DO) population. These 8 strains together span almost 90% of the genetic diversity found in mice (Mus musculus). Our second population of genetic diversity included 25 genetically unique, outbred females and 25 males from the DO population. We show that multi-scale cortical bone traits vary significantly with genetic background; heritability values range from 21% to 99% indicating genetic control of bone traits across length scales. We show for the first time that lacunar shape and number are highly heritable. Comparing the 2 populations of genetic diversity, we show that each DO mouse does not resemble a single inbred founder, but instead the outbred mice display hybrid phenotypes with the elimination of extreme values. Additionally, intrabone relationships (eg, ultimate force vs. cortical area) were mainly conserved in our 2 populations. Overall, this work supports future use of these genetically diverse populations to discover novel genes contributing to cortical bone traits, especially at the lacunar length scale.