Health and population effects of rare gene knockouts in adult humans with related parents.

Examining complete gene knockouts within a viable organism can inform on gene function. We sequenced the exomes of 3222 British adults of Pakistani heritage with high parental relatedness, discovering 1111 rare-variant homozygous genotypes with predicted loss of function (knockouts) in 781 genes. We observed 13.7% fewer homozygous knockout genotypes than we expected, implying an average load of 1.6 recessive-lethal-equivalent loss-of-function (LOF) variants per adult. When genetic data were linked to the individuals' lifelong health records, we observed no significant relationship between gene knockouts and clinical consultation or prescription rate. In this data set, we identified a healthy PRDM9-knockout mother and performed phased genome sequencing on her, her child, and control individuals. Our results show that meiotic recombination sites are localized away from PRDM9-dependent hotspots. Thus, natural LOF variants inform on essential genetic loci and demonstrate PRDM9 redundancy in humans.The study was funded by the Wellcome Trust (WT102627 and WT098051), Barts Charity (845/1796), Medical Research Council (MR/M009017/1). This paper presents independent research funded by the National Institute for Health Research (NIHR) under its Collaboration for Applied Health Research and Care (CLAHRC) for Yorkshire and Humber. Core support for Born in Bradford is also provided by the Wellcome Trust (WT101597). V.N. was supported by the Wellcome Trust PhD Studentship (WT099769). D.G.M. and K.K. were supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM104371. E.R.M. is funded by NIHR Cambridge Biomedical Research Centre. H.H. is supported by awards to establish the Farr Institute of Health Informatics Research, London, from the Medical Research Council, Arthritis Research UK, British Heart Foundation, Cancer Research UK, Chief Scientist Office, Economic and Social Research Council, Engineering and Physical Sciences Research Council, NIHR, National Institute for Social Care and Health Research, and Wellcome Trust.This is the author accepted manuscript. The final version is available from the American Association for the Advancement of Science via https://doi.org/10.1126/science.aac862

Mutations in the voltage-gated potassium channel gene KCNH1 cause Temple-Baraitser syndrome and epilepsy (vol 47, pg 73, 2015)

"Mutations in the voltage-gated potassium channel gene KCNH1 cause Temple-Baraitser syndrome and epilepsy" published in Nature Genetics (2015), volume 47, pp.73-77

Recessive mutations in POLR1C cause a leukodystrophy by impairing biogenesis of RNA polymerase III

A small proportion of 4H (Hypomyelination, Hypodontia and Hypogonadotropic Hypogonadism) or RNA polymerase III (POLR3)-related leukodystrophy cases are negative for mutations in the previously identified causative genes POLR3A and POLR3B. Here we report eight of these cases carrying recessive mutations in POLR1C, a gene encoding a shared POLR1 and POLR3 subunit, also mutated in some Treacher Collins syndrome (TCS) cases. Using shotgun proteomics and ChIP sequencing, we demonstrate that leukodystrophy-causative mutations, but not TCS mutations, in POLR1C impair assembly and nuclear import of POLR3, but not POLR1, leading to decreased binding to POLR3 target genes. This study is the first to show that distinct mutations in a gene coding for a shared subunit of two RNA polymerases lead to selective modification of the enzymes’ availability leading to two different clinical conditions and to shed some light on the pathophysiological mechanism of one of the most common hypomyelinating leukodystrophies, POLR3-related leukodystrophy

Achieving high-sensitivity for clinical applications using augmented exome sequencing

daSNVs in ACMG genes where inadequate coverage was observed among at least one platform, using WES/ACE data normalized to both 12 Gb and 100× mean coverage. (XLSX 312 kb

Performance of methods to detect genetic variants from bisulphite sequencing data in a non-model species

The profiling of epigenetic marks like DNA methylation has become a central aspect of studies in evolution and ecology. Bisulphite sequencing is commonly used for assessing genome-wide DNA methylation at single nucleotide resolution but these data can also provide information on genetic variants like single nucleotide polymorphisms (SNPs). However, bisulphite conversion causes unmethylated cytosines to appear as thymines, complicating the alignment and subsequent SNP calling. Several tools have been developed to overcome this challenge, but there is no independent evaluation of such tools for non-model species, which often lack genomic references. Here, we used whole-genome bisulphite sequencing (WGBS) data from four female great tits (Parus major) to evaluate the performance of seven tools for SNP calling from bisulphite sequencing data. We used SNPs from whole-genome resequencing data of the same samples as baseline SNPs to assess common performance metrics like sensitivity, precision, and the number of true positive, false positive, and false negative SNPs for the full range of variant and genotype quality values. We found clear differences between the tools in either optimizing precision (Bis-SNP), sensitivity (biscuit), or a compromise between both (all other tools). Overall, the choice of SNP caller strongly depends on which performance parameter should be maximized and whether ascertainment bias should be minimized to optimize downstream analysis, highlighting the need for studies that assess such differences.Peer reviewe

Haplotype Assembly and Small Variant Calling using Emerging Sequencing Technologies

Short read DNA sequencing technologies from Illumina have made sequencing a human genome significantly more affordable, greatly accelerating studies of biological function and the association of genetic variants to disease. These technologies are frequently used to detect small genetic variants such as single nucleotide variants (SNVs) using a reference genome. However, short read sequencing technologies have several limitations. First, the human genome is diploid and short reads contain limited information for assembling haplotypes, or the sequences of alleles on homologous chromosomes. Moreover, there is significant input DNA required, which poses challenges for analyzing single cells. Further, there is limited ability to detect genetic variants inside long duplicated sequences that occur in the genome. As a result, there has been widespread development of novel methods to overcome these deficiencies using short reads. These include clone based sequencing, linked read sequencing, and proximity ligation sequencing, as well as various single cell sequencing methods. There are also entirely new sequencing technologies from Pacific Biosciences and Oxford Nanopore Technologies that produce significantly longer reads. While these emerging methods and technologies demonstrate improvements compared to short reads, they also have properties and error modalities that pose unique computational challenges. Moreover, there is a shortage of bioinformatics methods for accurate small variant detection and haplotype assembly using these approaches compared to short reads. This dissertation aims to address this problem with the introduction of several new algorithms for highly accurate haplotype assembly and SNV calling. First, it introduces HapCUT2, an algorithm that can rapidly assemble haplotypes using a broad range of sequencing technologies. Second, it introduces an algorithm for variant calling and haplotyping using SISSOR, a recently introduced microfluidics based technology for sequencing single cells. Finally, it introduces Longshot, an algorithm for detecting and phasing SNVs using error-prone long read technologies. In each case, the algorithms are benchmarked using multiple real whole-genome sequencing datasets and are found to be highly accurate. The methods introduced in this dissertation contribute to the goal of sequencing diploid genomes accurately and completely for a broad range of scientific and clinical purposes

Discovering genetic drivers in acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation

University of Minnesota Ph.D. dissertation. May 2019. Major: Biomedical Informatics and Computational Biology. Advisors: Caleb Kennedy, Claudia Neuhauser. 1 computer file (PDF); x, 128 pages + 2 supplementary tablesAcute graft-versus-host disease (GVHD) is one of the major complications after allogeneic hematopoietic stem cell transplantation (allo-HCT) that cause non-relapse morbidity and mortality. Although the increasing matching rate of the human leukocyte antigen (HLA) genes between donor and recipient (DR) has significantly reduced the risk of GVHD, clinically significant GVHD remains as a transplantation challenge, even in HLA-identical transplants. Candidate gene studies and genome-wide association studies have revealed susceptible individual genes and gene pairs from DR pairs that are associated with acute GVHD; however, the roles of genetic disparities between donor and recipient remain to be understood. To identify genetic factors linked to acute GVHD, we investigated the classical HLA and non-HLA genes and conducted a genome-wide clinical outcome association study. Assessment of 4,646 antigen recognition domain (ARD)-matched unrelated donor allo-HCT cases showed that the frequency of mismatches outside the ARD in HLA genes is very low when the DR pairs are matched at ARD. Due to the low frequency of amino acid mismatches in the non-ARD region and their reportedly weak alloimmune reactions, we suggest that the non-ARD sequence mismatches within the ARD-matched DR pairs have limited influence on the development of acute GVHD, and may not be a primary factor. The genome-wide clinical outcome association study between DR pairs observed multiple autosomal minor histocompatibility antigens (MiHAs) restricted by HLA typing, though their association with acute GVHD outcome was not statistically significant. This result suggests that HLA mismatching outweighs other genetic mismatches as contributors to acute GVHD risk. In the cases of female donors to male recipients, we identified the significant association of the Y chromosome-specific peptides encoded by PCDH11Y, USP9Y, UTY, and NLGN4Y with the acute GVHD outcome. Additionally, we developed a machine learning-based genetic variant selection algorithm for ultra-high dimensional transplant genomic studies. The algorithm successfully selected a set of genes from over 1 M genetic variants, all of which have evidence to be linked to the transplant-related complications. This work offers evidence and guidance for further research in acute GVHD and allo-HCT and provides useful bioinformatics and data mining tools for transplant genomic studies