Person:

Coulter, Michael Edward

Although autism has a clear genetic component, the high genetic heterogeneity of the disorder has been a challenge for the identification of causative genes. We used homozygosity analysis to identify probands from nonconsanguineous families that showed evidence of distant shared ancestry, suggesting potentially recessive mutations. Whole-exome sequencing of 16 probands revealed validated homozygous, potentially pathogenic recessive mutations that segregated perfectly with disease in 4/16 families. The candidate genes (UBE3B, CLTCL1, NCKAP5L, ZNF18) encode proteins involved in proteolysis, GTPase-mediated signaling, cytoskeletal organization, and other pathways. Furthermore, neuronal depolarization regulated the transcription of these genes, suggesting potential activity-dependent roles in neurons. We present a multidimensional strategy for filtering whole-exome sequence data to find candidate recessive mutations in autism, which may have broader applicability to other complex, heterogeneous disorders.

Abstract Single cell whole-genome sequencing (scWGS) is providing novel insights into the nature of genetic heterogeneity in normal and diseased cells. However, the whole-genome amplification process required for scWGS introduces biases into the resulting sequencing that can confound downstream analysis. Here, we present a statistical method, with an accompanying package PaSD-qc (Power Spectral Density-qc), that evaluates the properties and quality of single cell libraries. It uses a modified power spectral density to assess amplification uniformity, amplicon size distribution, autocovariance and inter-sample consistency as well as to identify chromosomes with aberrant read-density profiles due either to copy alterations or poor amplification. These metrics provide a standard way to compare the quality of single cell samples as well as yield information necessary to improve variant calling strategies. We demonstrate the usefulness of this tool in comparing the properties of scWGS protocols, identifying potential chromosomal copy number variation, determining chromosomal and subchromosomal regions of poor amplification, and selecting high-quality libraries from low-coverage data for deep sequencing. The software is available free and open-source at https://github.com/parklab/PaSDqc.

Human genetics of neonatal brain malformations has identified dozens of genes required for brain development that regulate diverse cellular processes. Recent evidence shows that somatic mutations, mutations that are only present in some cells of the body, can also cause brain malformations and disease. We have studied the function of a recently identified microcephaly and cerebellar hypoplasia gene, CHMP1A, and found that it is required for exosome-mediated secretion of sonic hedgehog (SHH). SHH is an essential growth factor in the developing brain, and our results reveal a novel mechanism for SHH secretion in the vertebrate brain. Somatic mutations are caused by incorrect repair of damaged DNA. Cockayne syndrome and xeroderma pigmentosum are disorders of DNA damage repair that cause microcephaly and early neurodegeneration. Using whole genome sequencing, we measured somatic mutation rate in post-mortem single cortical neurons from patients with these disorders and found a dramatic increase in the number of somatic mutations compared to normal individuals.