Leveraging human musculoskeletal development to identify causal disease variants

Harvard University, Cambridge MA

Investigators

Abstract

Project Summary/Abstract There exists a major gap in our knowledge on what genes and regulatory regions control the differences in skeletal morphology between humans, and our best studied model system, the mouse. This is despite the human skeletons’ importance to walking/running, tool use, and childbirth, and that congenital, trauma-induced, and aging diseases of the skeleton are very common. This gap has not been spanned by the recent efforts of large scale consortia (e.g., ENCODE), which have been generating extensive functional genomics datasets on human and mouse fetal and adult tissues to shed light on organ biology, but which have neglected the skeleton and its cell types. Here, we propose to remedy this situation and take a first step to fill the gap in knowledge through our proposal to conduct targeted studies on the human fetal skeleton, at site-specific anatomical levels, using the functional genomic techniques of single cell multiomics, to detect expressed transcripts/genes and regulatory elements per cell for each tissue, and spatial transcriptomics for each anatomical region to detect gene expression at high definition histologically. Importantly, we will generate transcriptomic and epigenomic maps for all the large joints in the post-cranial body, which will then be intersected with actual human disease-causing genetic variation from Genome-wide Association Studies to find causal variants. These will be tested in a high throughput assay to examine each regulatory variants impacts on gene expression. In Aim 1, single cell multiomics will be performed on human joints for the shoulder, elbow, wrist, interphalangeal joint of the hand, ankle, interphalangeal joints of the foot, and lumbar sacral joint to map the transcriptome plus epigenome of each cell type at each joint. These data will be combined with identical data we generated on the hip and knee, thus covering all large joints of the post-cranium. All of these datasets are compared across three timepoints to build human-specific maps, noting similarities and differences in transcriptomic and epigenomic usage, reflecting differences in the attainment of morphological differences in anatomical regions. In Aim 2, high-definition spatial transcriptomics will be performed on the same anatomical regions as in Aim 1 on human samples to reconstruct tissue (histological) level gene expression at single cell resolution. These data are then compared across time- points to build human-specific maps, noting similarities and differences in genic usage at the cell type, and anatomical-specific levels. In Aim 3, we propose to use a high throughout reporter assay, called the Massively Parallel Reporter Assay, to test the regulatory functions of thousands of human variants (involved in normal or disease biology) residing in musculoskeletal cell type regulatory regions. This approach will generate a compendium of human regulatory elements with effects on such cell type gene regulation, and in doing so will shed light on the complex regulatory architecture underlying normal human biology (e.g., the shape of the birth canal or our bipedal knee) and common human skeletal diseases such hip dysplasia or osteoarthritis.