Tomasz Konopka

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR-Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.

Near-haploid human cell lines are instrumental for genetic screens and genome engineering as gene inactivation is greatly facilitated by the absence of a second gene copy. However, no completely haploid human cell line has been described, hampering the genetic accessibility of a subset of genes. The near-haploid human cell line HAP1 contains a single copy of all chromosomes except for a heterozygous 30-megabase fragment of Chromosome 15. This large fragment encompasses 330 genes and is integrated on the long arm of Chromosome 19. Here, we employ a CRISPR/Cas9-based genome engineering strategy to excise this sizeable chromosomal fragment and to efficiently and reproducibly derive clones that retain their haploid state. Importantly, spectral karyotyping and single-nucleotide polymorphism (SNP) genotyping revealed that engineered-HAPloid (eHAP) cells are fully haploid with no gross chromosomal aberrations induced by Cas9. Furthermore, whole-genome sequence and transcriptome analysis of the parental HAP1 and an eHAP cell line showed that transcriptional changes are limited to the excised Chromosome 15 fragment. Together, we demonstrate the feasibility of efficiently engineering megabase deletions with the CRISPR/Cas9 technology and report the first fully haploid human cell line.

Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in &lt;<a href="https://doi.org/10.48550/arXiv.1802.03426" target="_top">doi:10.48550/arXiv.1802.03426</a>&gt;. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).

Little is known about how RNA editing operates in cancer. Transcriptome analysis of 68 normal and cancerous breast tissues revealed that the editing enzyme ADAR acts uniformly, on the same loci, across tissues. In controlled ADAR expression experiments, the editing frequency increased at all loci with ADAR expression levels according to the logistic model. Loci-specific "editabilities," i.e., propensities to be edited by ADAR, were quantifiable by fitting the logistic function to dose-response data. The editing frequency was increased in tumor cells in comparison to normal controls. Type I interferon response and ADAR DNA copy number together explained 53% of ADAR expression variance in breast cancers. ADAR silencing using small hairpin RNA lentivirus transduction in breast cancer cell lines led to less cell proliferation and more apoptosis. A-to-I editing is a pervasive, yet reproducible, source of variation that is globally controlled by 1q amplification and inflammation, both of which are highly prevalent among human cancers.

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery.