Predicting expression-altering promoter mutations with deep learning.

Only a minority of patients with rare genetic diseases are presently diagnosed by exome sequencing, suggesting that additional unrecognized pathogenic variants may reside in noncoding sequence. In this work, we describe PromoterAI, a deep neural network that accurately identifies noncoding promoter variants that dysregulate gene expression. We show that promoter variants with predicted expression-altering consequences produce outlier expression at both the RNA and protein levels in thousands of individuals and that these variants experience strong negative selection in human populations.

Integrative GWAS and co-localisation analysis suggests novel genes associated with age-related multimorbidity.

Advancing age is the greatest risk factor for developing multiple age-related diseases. Therapeutic approaches targeting the underlying pathways of ageing, rather than individual diseases, may be an effective way to treat and prevent age-related morbidity while reducing the burden of polypharmacy. We harness the Open Targets Genetics Portal to perform a systematic analysis of nearly 1,400 genome-wide association studies (GWAS) mapped to 34 age-related diseases and traits, identifying genetic signals that are shared between two or more of these traits.

Artificial intelligence for dementia genetics and omics.

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts.

Mapping interindividual dynamics of innate immune response at single-cell resolution.

Common genetic variants across individuals modulate the cellular response to pathogens and are implicated in diverse immune pathologies, yet how they dynamically alter the response upon infection is not well understood. Here, we triggered antiviral responses in human fibroblasts from 68 healthy donors, and profiled tens of thousands of cells using single-cell RNA-sequencing. We developed GASPACHO (GAuSsian Processes for Association mapping leveraging Cell HeterOgeneity), a statistical approach designed to identify nonlinear dynamic genetic effects across transcriptional trajectories of cells.

Screening for functional regulatory variants in open chromatin using GenIE-ATAC.

Understanding the effects of genetic variation in gene regulatory elements is crucial to interpreting genome function. This is particularly pertinent for the hundreds of thousands of disease-associated variants identified by GWAS, which frequently sit within gene regulatory elements but whose functional effects are often unknown. Current methods are limited in their scalability and ability to assay regulatory variants in their endogenous context, independently of other tightly linked variants.

Genetic variants associated with psychiatric disorders are enriched at epigenetically active sites in lymphoid cells.

Multiple psychiatric disorders have been associated with abnormalities in both the innate and adaptive immune systems. The role of these abnormalities in pathogenesis, and whether they are driven by psychiatric risk variants, remains unclear. We test for enrichment of GWAS variants associated with multiple psychiatric disorders (cross-disorder or trans-diagnostic risk), or 5 specific disorders (cis-diagnostic risk), in regulatory elements in immune cells.

Multi-ancestry Mendelian randomization of omics traits revealing drug targets of COVID-19 severity.

Background: Recent omic studies prioritised several drug targets associated with coronavirus disease 2019 (COVID-19) severity. However, little evidence was provided to systematically estimate the effect of drug targets on COVID-19 severity in multiple ancestries.

Methods: In this study, we applied Mendelian randomization (MR) and colocalization approaches to understand the putative causal effects of 16,059 transcripts and 1608 proteins on COVID-19 severity in European and effects of 610 proteins on COVID-19 severity in African ancestry.

An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci.

Genome-wide association studies (GWASs) have identified many variants associated with complex traits, but identifying the causal gene(s) is a major challenge. In the present study, we present an open resource that provides systematic fine mapping and gene prioritization across 133,441 published human GWAS loci. We integrate genetics (GWAS Catalog and UK Biobank) with transcriptomic, proteomic and epigenomic data, including systematic disease-disease and disease-molecular trait colocalization results across 92 cell types and tissues.

A proteome-wide genetic investigation identifies several SARS-CoV-2-exploited host targets of clinical relevance.

Background: The virus SARS-CoV-2 can exploit biological vulnerabilities (e.g. host proteins) in susceptible hosts that predispose to the development of severe COVID-19.

A map of transcriptional heterogeneity and regulatory variation in human microglia.

Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery.

Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.

Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation.

Screening for functional transcriptional and splicing regulatory variants with GenIE.

Genome-wide association studies (GWAS) have identified numerous genetic loci underlying human diseases, but a fundamental challenge remains to accurately identify the underlying causal genes and variants. Here, we describe an arrayed CRISPR screening method, Genome engineering-based Interrogation of Enhancers (GenIE), which assesses the effects of defined alleles on transcription or splicing when introduced in their endogenous genomic locations. We use this sensitive assay to validate the activity of transcriptional enhancers and splice regulatory elements in human induced pluripotent stem cells (hiPSCs), and develop a software package (rgenie) to analyse the data.

CYRI/FAM49B negatively regulates RAC1-driven cytoskeletal remodelling and protects against bacterial infection.

Salmonella presents a global public health concern. Central to Salmonella pathogenicity is an ability to subvert host defences through strategically targeting host proteins implicated in restricting infection. Therefore, to gain insight into the host-pathogen interactions governing Salmonella infection, we performed an in vivo genome-wide mutagenesis screen to uncover key host defence proteins.

Publisher Correction: Molecular and functional variation in iPSC-derived sensory neurons.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Biallelic Loss-of-Function Variants in AIMP1 Cause a Rare Neurodegenerative Disease.

AIMP1/p43, is a noncatalytic component of the mammalian multi-tRNA synthetase complex that catalyzes the ligation of amino acids to their cognate tRNAs. AIMP1 is largely expressed in the central nervous system, where it is part of the regulatory machine of the neurofilament assembly, playing a crucial role in neuronal development and function. To date, nonsense mutations in AIMP1 have been associated with a primary neurodegenerative disorder consisting of cerebral atrophy, hypomyelination, microcephaly and epilepsy, whereas missense mutations have recently been linked to intellectual disability without neurodegeneration.

Genome-wide association study of developmental dysplasia of the hip identifies an association with .

Developmental dysplasia of the hip (DDH) is the most common skeletal developmental disease. However, its genetic architecture is poorly understood. We conduct the largest DDH genome-wide association study to date and replicate our findings in independent cohorts.

A family segregating lethal neonatal coenzyme Q deficiency caused by mutations in COQ9.

Primary CoQ deficiency is a clinically and genetically heterogeneous, autosomal recessive disorder resulting from mutations in genes involved in the synthesis of coenzyme Q (CoQ). To date, mutations in nine proteins required for the biosynthesis of CoQ cause CoQ deficiency with varying clinical presentations. In 2009 the first patient with mutations in COQ9 was reported in an infant with a neonatal-onset, primary CoQ deficiency with multi-system disease.