Genome-wide heritability analysis of severe malaria susceptibility and resistance reveals evidence of polygenic inheritance

Summary Statistics ◽

Cell Type ◽

Protein Coding ◽

Polygenic Inheritance ◽

Genome Wide ◽

Cell Type Specific ◽

Malaria Susceptibility ◽

Susceptibility And Resistance

ABSTRACTObjectiveEstimating SNP-heritability (h2g) of severe malaria/resistance and its distribution across the genome might shed new light in to the underlying biology.MethodWe investigated h2g of severe malaria susceptibility and resistance from genome-wide association study (GWAS) dataset (sample size =11, 657). We partitioned the h2g in to chromosomes, allele frequencies and annotations. We further examined none-cell type specific and cell type specific enrichments from GWAS-summary statistics.ResultsWe estimated the h2g of severe malaria at 0.21 (se=0.05, p=2.7×10−5), 0.20 (se =0.05, p=7.5×10−5) and 0.17 (se =0.05, p= 7.2×10−4) in Gambian, Kenyan and Malawi populations, respectively. The h2g attributed to the GWAS significant SNPs and the well-known sickle cell (HbS) variant was approximately 0.07 and 0.03, respectively. We prepared African population reference panel and obtained comparable h2g estimate (0.21 (se = 0.02, p< 1×10−5)) from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in protein coding genic SNPs while summary statistics analysis suggests pattern of enrichment in multiple categories.ConclusionWe report for the first time that the heritability of malaria susceptibility and resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Overall, our results suggest that malaria susceptibility and resistance is a polygenic trait. Further studies with larger sample sizes are needed to better understand the underpinning genetics of resistance and susceptibility to severe malaria.

Genome-wide heritability analysis of severe malaria resistance reveals evidence of polygenic inheritance

Human Molecular Genetics ◽

10.1093/hmg/ddz258 ◽

2019 ◽

Vol 29 (1) ◽

pp. 168-176

Author(s):

Delesa Damena ◽

Emile R Chimusa

Keyword(s):

Severe Malaria ◽

Allelic Frequency ◽

Relationship Matrix ◽

Summary Statistics ◽

Cell Type ◽

Polygenic Inheritance ◽

Genome Wide ◽

A Genome ◽

Abstract Background: Estimating single nucleotide polymorphism (SNP)-heritability (h2g) of severe malaria resistance and its distribution across the genome might shed new light in to the underlying biology. Method: We investigated h2g of severe malaria resistance from a genome-wide association study (GWAS) dataset (sample size = 11 657). We estimated the h2g and partitioned in to chromosomes, allele frequencies and annotations using the genetic relationship-matrix restricted maximum likelihood approach. We further examined non-cell type-specific and cell type-specific enrichments from GWAS-summary statistics. Results: The h2g of severe malaria resistance was estimated at 0.21 (se = 0.05, P = 2.7 × 10−5), 0.20 (se = 0.05, P = 7.5 × 10−5) and 0.17 (se = 0.05, P = 7.2 × 10−4) in Gambian, Kenyan and Malawi populations, respectively. A comparable range of h2g [0.21 (se = 0.02, P < 1 × 10−5)] was estimated from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in genic SNPs while summary statistics analysis suggests evidences of enrichment in multiple categories. Supporting the polygenic inheritance, the h2g of severe malaria resistance is distributed across the chromosomes and allelic frequency spectrum. However, the h2g is disproportionately concentrated on three chromosomes (chr 5, 11 and 20), suggesting cost-effectiveness of targeting these chromosomes in future malaria genomic sequencing studies. Conclusion: We report for the first time that the heritability of malaria resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Further studies with larger sample sizes are needed to better understand the underpinning genetics of severe malaria resistance.

Partitioning heritability by functional category using GWAS summary statistics

10.1101/014241 ◽

2015 ◽

Cited By ~ 9

Author(s):

Hilary Kiyo Finucane ◽

Brendan Bulik-Sullivan ◽

Alexander Gusev ◽

Gosia Trynka ◽

Yakir Reshef ◽

...

Keyword(s):

Association Studies ◽

Smoking Behavior ◽

Complex Diseases ◽

New Method ◽

Age At Menarche ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Cell Type ◽

Genome Wide ◽

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

A compendium of uniformly processed human gene expression and splicing quantitative trait loci

Nature Genetics ◽

10.1038/s41588-021-00924-w ◽

2021 ◽

Vol 53 (9) ◽

pp. 1290-1299

Author(s):

Nurlan Kerimov ◽

James D. Hayhurst ◽

Kateryna Peikova ◽

Jonathan R. Manning ◽

Peter Walter ◽

...

Keyword(s):

Gene Expression ◽

Quantitative Trait ◽

Target Genes ◽

Cell Types ◽

Summary Statistics ◽

Genome Wide ◽

Cell Type Specific ◽

Trait Locus ◽

Complex Human Traits

AbstractMany gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

echolocatoR: an automated end-to-end statistical and functional genomic fine-mapping pipeline

10.1101/2020.10.22.351221 ◽

2020 ◽

Cited By ~ 2

Author(s):

Brian M. Schilder ◽

Jack Humphrey ◽

Towfique Raj

Keyword(s):

Linkage Disequilibrium ◽

Fine Mapping ◽

R Package ◽

Functional Genomic ◽

Summary Statistics ◽

Cell Type ◽

High Confidence ◽

Genome Wide ◽

Cell Type Specific ◽

End To End

AbstractSummaryecholocatoR integrates a diverse suite of statistical and functional fine-mapping tools in order to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium (LD) panels, quantitative trait loci (QTL) datasets, genome-wide annotations, cell type-specific epigenomics, thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations.Availability and implementationecholocatoR is an open-source R package available through GitHub under the MIT license: https://github.com/RajLabMSSM/echolocatoR

A Nonsense Variant in Hephaestin Like 1 (HEPHL1) Is Responsible for Congenital Hypotrichosis in Belted Galloway Cattle

Genes ◽

10.3390/genes12050643 ◽

2021 ◽

Vol 12 (5) ◽

pp. 643

Author(s):

Thibaud Kuca ◽

Brandy M. Marron ◽

Joana G. P. Jacinto ◽

Julia M. Paris ◽

Christian Gerspach ◽

...

Keyword(s):

Homozygosity Mapping ◽

Mendelian Inheritance ◽

Large Animal Model ◽

Large Animal ◽

Loss Of Function ◽

Protein Coding ◽

Positional Candidate ◽

Genome Wide ◽

A Genome

Genodermatosis such as hair disorders mostly follow a monogenic mode of inheritance. Congenital hypotrichosis (HY) belong to this group of disorders and is characterized by abnormally reduced hair since birth. The purpose of this study was to characterize the clinical phenotype of a breed-specific non-syndromic form of HY in Belted Galloway cattle and to identify the causative genetic variant for this recessive disorder. An affected calf born in Switzerland presented with multiple small to large areas of alopecia on the limbs and on the dorsal part of the head, neck, and back. A genome-wide association study using Swiss and US Belted Galloway cattle encompassing 12 cases and 61 controls revealed an association signal on chromosome 29. Homozygosity mapping in a subset of cases refined the HY locus to a 1.5 Mb critical interval and subsequent Sanger sequencing of protein-coding exons of positional candidate genes revealed a stop gain variant in the HEPHL1 gene that encodes a multi-copper ferroxidase protein so-called hephaestin like 1 (c.1684A>T; p.Lys562*). A perfect concordance between the homozygous presence of this most likely pathogenic loss-of-function variant and the HY phenotype was found. Genotyping of more than 700 purebred Swiss and US Belted Galloway cattle showed the global spread of the mutation. This study provides a molecular test that will permit the avoidance of risk matings by systematic genotyping of relevant breeding animals. This rare recessive HEPHL1-related form of hypotrichosis provides a novel large animal model for similar human conditions. The results have been incorporated in the Online Mendelian Inheritance in Animals (OMIA) database (OMIA 002230-9913).

Genome-wide association study indicates two novel resistance loci for severe malaria

Nature ◽

10.1038/nature11334 ◽

2012 ◽

Vol 489 (7416) ◽

pp. 443-446 ◽

Cited By ~ 148

Author(s):

Christian Timmann ◽

Thorsten Thye ◽

Maren Vens ◽

Jennifer Evans ◽

Jürgen May ◽

...

Keyword(s):

Association Study ◽

Severe Malaria ◽

Genome Wide Association ◽

Genome Wide

Identification of Potential Pleiotropic Genes for Immune and Skeletal Diseases Using Multivariate MetaCCA Analysis

Current Genomics ◽

10.2174/1389202923666211223115214 ◽

2021 ◽

Vol 23 ◽

Author(s):

Pei He ◽

Rong- Rong Cao ◽

Fei- Yan Deng ◽

Shu- Feng Lei

Keyword(s):

Association Study ◽

Canonical Correlation ◽

Genetic Factors ◽

Summary Statistics ◽

Immune Disease ◽

Histocompatibility Complex ◽

Genome Wide ◽

Genetic Mechanisms ◽

Shared Genetic

Background: Immune and skeletal systems physiologically and pathologically interact with each other. The immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia and fracture) Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. Versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA. Results: About 157 (p<8.19E-6), 319 (p<3.90E-6) and 77 (p<9.72E-6) potential pleiotropic genes were identified shared by two immune disease, four skeletal diseases, and all of the six diseases, respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal diseases, including HLA-B, TSBP1 and TSBP1-AS1 (p<E-300) were located in the major histocompatibility complex (MHC) region. Nineteen of 77 putative pleiotropic genes identified by metaCCA analysis were associated with at least one disease in the VEGAS2 analysis. Specifically, majority (18) of these 19 putative validated pleiotropic genes were associated with RA. Conclusion: The metaCCA method identified some pleiotropic genes shared by the immune and skeletal diseases. These findings help to improve our understanding of the shared genetic mechanisms and signaling pathways underlying immune and skeletal diseases.

In vivo single-cell profiling of lncRNAs during Ebola virus infection

10.1101/2022.01.12.476002 ◽

2022 ◽

Author(s):

Luisa Santus ◽

Raquel García-Pérez ◽

Maria Sopena-Rios ◽

Aaron E Lin ◽

Gordon C Adams ◽

...

Keyword(s):

Viral Infection ◽

Single Cell ◽

Ebola Virus ◽

Cell Type ◽

Protein Coding ◽

Expression Variation ◽

Lncrna Expression ◽

Ebov Infection ◽

Long non-coding RNAs (lncRNAs) are pivotal mediators of systemic immune response to viral infection, yet most studies concerning their expression and functions upon immune stimulation are limited to in vitro bulk cell populations. This strongly constrains our understanding of how lncRNA expression varies at single-cell resolution, and how their cell-type specific immune regulatory roles may differ compared to protein-coding genes. Here, we perform the first in-depth characterization of lncRNA expression variation at single-cell resolution during Ebola virus (EBOV) infection in vivo. Using bulk RNA-sequencing from 119 samples and 12 tissue types, we significantly expand the current macaque lncRNA annotation. We then profile lncRNA expression variation in immune circulating single-cells during EBOV infection and find that lncRNAs' expression in fewer cells is a major differentiating factor from their protein-coding gene counterparts. Upon EBOV infection, lncRNAs present dynamic and mostly cell-type specific changes in their expression profiles especially in monocytes, the main cell type targeted by EBOV. Such changes are associated with gene regulatory modules related to important innate immune responses such as interferon response and purine metabolism. Within infected cells, several lncRNAs have positively and negatively correlated expression with viral load, suggesting that expression of some of these lncRNAs might be directly hijacked by EBOV to attack host cells. This study provides novel insights into the roles that lncRNAs play in the host response to acute viral infection and paves the way for future lncRNA studies at single-cell resolution.

Capturing cell type-specific chromatin structural patterns by applying topic modeling to single-cell Hi-C data

10.1101/534800 ◽

2019 ◽

Cited By ~ 2

Author(s):

Hyeon-Jin Kim ◽

Galip Gürkan Yardımcı ◽

Giancarlo Bonora ◽

Vijay Ramani ◽

Jie Liu ◽

...

Keyword(s):

Single Cell ◽

Topic Modeling ◽

Biological Information ◽

Chromatin Interaction ◽

Cell Type ◽

3D Genome ◽

Genome Wide ◽

Significant Barrier ◽

Chromatin Structural ◽

AbstractSingle-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate twelve different single-cell combinatorial indexed Hi-C (sciHi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 25,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sciHi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics.

Distinct CoREST complexes act in a cell-type-specific manner

Nucleic Acids Research ◽

10.1093/nar/gkz1050 ◽

2019 ◽

Author(s):

Igor Mačinković ◽

Ina Theofel ◽

Tim Hundertmark ◽

Kristina Kovač ◽

Stephan Awe ◽

...

Keyword(s):

Gene Expression ◽

Germ Line ◽

Protein Complexes ◽

Specific Gene ◽

S2 Cells ◽

Cell Type ◽

Specific Gene Expression ◽

Genome Wide ◽

A Cell ◽

Abstract CoREST has been identified as a subunit of several protein complexes that generate transcriptionally repressive chromatin structures during development. However, a comprehensive analysis of the CoREST interactome has not been carried out. We use proteomic approaches to define the interactomes of two dCoREST isoforms, dCoREST-L and dCoREST-M, in Drosophila. We identify three distinct histone deacetylase complexes built around a common dCoREST/dRPD3 core: A dLSD1/dCoREST complex, the LINT complex and a dG9a/dCoREST complex. The latter two complexes can incorporate both dCoREST isoforms. By contrast, the dLSD1/dCoREST complex exclusively assembles with the dCoREST-L isoform. Genome-wide studies show that the three dCoREST complexes associate with chromatin predominantly at promoters. Transcriptome analyses in S2 cells and testes reveal that different cell lineages utilize distinct dCoREST complexes to maintain cell-type-specific gene expression programmes: In macrophage-like S2 cells, LINT represses germ line-related genes whereas other dCoREST complexes are largely dispensable. By contrast, in testes, the dLSD1/dCoREST complex prevents transcription of germ line-inappropriate genes and is essential for spermatogenesis and fertility, whereas depletion of other dCoREST complexes has no effect. Our study uncovers three distinct dCoREST complexes that function in a lineage-restricted fashion to repress specific sets of genes thereby maintaining cell-type-specific gene expression programmes.