An integrated peach genome structural variation map uncovers genes associated with fruit traits

Abstract Background Genome structural variations (SVs) have been associated with key traits in a wide range of agronomically important species; however, SV profiles of peach and their functional impacts remain largely unexplored. Results Here, we present an integrated map of 202,273 SVs from 336 peach genomes. A substantial number of SVs have been selected during peach domestication and improvement, which together affect 2268 genes. Genome-wide association studies of 26 agronomic traits using these SVs identify a number of candidate causal variants. A 9-bp insertion in Prupe.4G186800, which encodes a NAC transcription factor, is shown to be associated with early fruit maturity, and a 487-bp deletion in the promoter of PpMYB10.1 is associated with flesh color around the stone. In addition, a 1.67 Mb inversion is highly associated with fruit shape, and a gene adjacent to the inversion breakpoint, PpOFP1, regulates flat shape formation. Conclusions The integrated peach SV map and the identified candidate genes and variants represent valuable resources for future genomic research and breeding in peach.

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Improving Polygenic Prediction in Ancestrally Diverse Populations

10.21203/rs.3.rs-133290/v1 ◽

2021 ◽

Author(s):

Hailiang Huang ◽

Yunfeng Ruan ◽

Yen-Chen Anne Feng ◽

Chia-Yen Chen ◽

Max Lam ◽

...

Keyword(s):

Association Studies ◽

Genetic Correlations ◽

Genomic Research ◽

Alternative Methods ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Size Estimation ◽

Wide Range ◽

European Populations

Abstract Polygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) were predominantly conducted in individuals of European descent, the limited transferability of PRS reduces its clinical value in non-European populations and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although they remain under-powered. Here we present a novel PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium (LD) diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures and cross-population genetic correlations in simulations, and substantially improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

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Detecting association of rare and common variants by adaptive combination of P-values

Genetics Research ◽

10.1017/s0016672315000208 ◽

2015 ◽

Vol 97 ◽

Cited By ~ 2

Author(s):

YAJING ZHOU ◽

YONG WANG

Keyword(s):

Rare Variants ◽

Association Studies ◽

Genome Wide Association Studies ◽

Common Variants ◽

Next Generation Sequencing Technology ◽

Adaptive Combination ◽

Genome Wide ◽

Wide Range ◽

Causal Variants ◽

Burden Tests

SummaryGenome-wide association studies (GWAS) can detect common variants associated with diseases. Next generation sequencing technology has made it possible to detect rare variants. Most of association tests, including burden tests and nonburden tests, mainly target rare variants by upweighting rare variant effects and downweighting common variant effects. But there is increasing evidence that complex diseases are caused by both common and rare variants. In this paper, we extend the ADA method (adaptive combination of P-values; Lin et al., 2014) for rare variants only and propose a RC-ADA method (common and rare variants by adaptive combination of P-values). Our proposed method combines the per-site P-values with the weights based on minor allele frequencies (MAFs). The RC-ADA is robust to directions of effects of causal variants and inclusion of a high proportion of neutral variants. The performance of the RC-ADA method is compared with several other association methods. Extensive simulation studies show that the RC-ADA method is more powerful than other association methods over a wide range of models.

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Improving Polygenic Prediction in Ancestrally Diverse Populations

10.1101/2020.12.27.20248738 ◽

2021 ◽

Author(s):

Yunfeng Ruan ◽

Yen-Chen Anne Feng ◽

Chia-Yen Chen ◽

Max Lam ◽

Akira Sawa ◽

...

Keyword(s):

Association Studies ◽

Genetic Correlations ◽

Genomic Research ◽

Alternative Methods ◽

Risk Scores ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Size Estimation ◽

Wide Range ◽

European Populations

ABSTRACTPolygenic risk scores (PRS) have attenuated cross-population predictive performance. As existing genome-wide association studies (GWAS) were predominantly conducted in individuals of European descent, the limited transferability of PRS reduces its clinical value in non-European populations and may exacerbate healthcare disparities. Recent efforts to level ancestry imbalance in genomic research have expanded the scale of non-European GWAS, although they remain under-powered. Here we present a novel PRS construction method, PRS-CSx, which improves cross-population polygenic prediction by integrating GWAS summary statistics from multiple populations. PRS-CSx couples genetic effects across populations via a shared continuous shrinkage prior, enabling more accurate effect size estimation by sharing information between summary statistics and leveraging linkage disequilibrium (LD) diversity across discovery samples, while inheriting computational efficiency and robustness from PRS-CS. We show that PRS-CSx outperforms alternative methods across traits with a wide range of genetic architectures and cross-population genetic correlations in simulations, and substantially improves the prediction of quantitative traits and schizophrenia risk in non-European populations.

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Strong Association between Serotonin Transporter 5-HTTVNTR Variant and Psychoactive Substance (Nicotine) Use in the Turkish Cypriot Population

Current Drug Metabolism ◽

10.2174/1389200221666200620201348 ◽

2020 ◽

Vol 21 (6) ◽

pp. 466-470

Author(s):

Emine Kandemis ◽

Gulten Tuncel ◽

Ozen Asut ◽

Sehime G. Temel ◽

Mahmut C. Ergoren

Keyword(s):

Serotonin Transporter ◽

Association Studies ◽

Strong Association ◽

Smoking Behavior ◽

Population Based ◽

Genome Wide Association Studies ◽

Genotype Distribution ◽

Psychological Traits ◽

Wide Range ◽

Turkish Cypriot

Background: The use of psychoactive substances is one of the most dangerous social problems worldwide. Nicotine dependence results from the interaction between neurobiological, environmental and genetic factors. Serotonin is a neurotransmitter that has a wide range of central nervous system activities. The serotonin transporter gene has been previously linked to psychological traits. Objective: A variable number of tandem repeats within the serotonin transporter-linked polymorphic gene region are believed to alter the transcriptional efficiency of the 5-HTT gene. Therefore, we aimed to investigate the association between this polymorphic site and smoking behavior in the Turkish Cypriot population. Methods: A total of 259 (100 smokers, 100 non-smokers and 59 ex-smokers) Turkish Cypriots were included in this population-based cross-sectional study. Genomic DNA was extracted from peripheral blood samples and the 5-HTTVNTR2 polymorphisms were determined by the PCR-RFLP. Results: The allelic frequency and genotype distribution results of this study showed a strong association (P<0.0001) between smokers and non-smokers. No statistical significance was found between non-smokers and ex-smokers. Conclusion: This is the first genetic epidemiology study to investigate the allelic frequencies of 5-HTTVNTR2 polymorphisms associated with smoking behavior in the Turkish Cypriot population. Based on the results of this study, genome-wide association studies should be designed for preventive medicine in this population.

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Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation

Genome Medicine ◽

10.1186/s13073-021-00857-3 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Shuquan Rao ◽

Yao Yao ◽

Daniel E. Bauer

Keyword(s):

Genome Editing ◽

Genetic Variants ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Functional Studies ◽

Functional Genetics ◽

Genome Wide ◽

Causal Variants ◽

Experimental Approaches

AbstractGenome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

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Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength

Nature Communications ◽

10.1038/s41467-021-23649-0 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Basel M. Al-Barghouthi ◽

Larry D. Mesner ◽

Gina M. Calabrese ◽

Daniel Brooks ◽

Steven M. Tommasini ◽

...

Keyword(s):

Cortical Bone ◽

Bone Strength ◽

Human Genetics ◽

Association Studies ◽

Systems Genetics ◽

Genome Wide Association Studies ◽

Mineral Density ◽

Diversity Outbred ◽

Wide Range ◽

Genetics Of Osteoporosis

AbstractGenome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

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CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

Nucleic Acids Research ◽

10.1093/nar/gkz1026 ◽

2019 ◽

Cited By ~ 2

Author(s):

Jianhua Wang ◽

Dandan Huang ◽

Yao Zhou ◽

Hongcheng Yao ◽

Huanhuan Liu ◽

...

Keyword(s):

Fine Mapping ◽

Genetic Variants ◽

Association Studies ◽

Complex Trait ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Genome Wide ◽

Credible Sets ◽

Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

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Genome-wide association studies of 14 agronomic traits in rice landraces

Nature Genetics ◽

10.1038/ng.695 ◽

2010 ◽

Vol 42 (11) ◽

pp. 961-967 ◽

Cited By ~ 1156

Author(s):

Xuehui Huang ◽

Xinghua Wei ◽

Tao Sang ◽

Qiang Zhao ◽

Qi Feng ◽

...

Keyword(s):

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Rice Landraces ◽

Genome Wide

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Centenary of Soil and Air Borne Wheat Karnal Bunt Disease Research: A Review

Biology ◽

10.3390/biology10111152 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1152

Author(s):

Mir Asif Iquebal ◽

Pallavi Mishra ◽

Ranjeet Maurya ◽

Sarika Jaiswal ◽

Anil Rai ◽

...

Keyword(s):

Agronomic Traits ◽

Association Studies ◽

Farmyard Manure ◽

Wheat Breeding ◽

Karnal Bunt ◽

Farm Income ◽

Resistance Locus ◽

Genome Wide Association Studies ◽

Tilletia Indica ◽

Causal Pathogen

Karnal bunt (KB) of wheat (Triticum aestivum L.), known as partial bunt has its origin in Karnal, India and is caused by Tilletia indica (Ti). Its incidence had grown drastically since late 1960s from northwestern India to northern India in early 1970s. It is a seed, air and soil borne pathogen mainly affecting common wheat, durum wheat, triticale and other related species. The seeds become inedible, inviable and infertile with the precedence of trimethylamine secreted by teliospores in the infected seeds. Initially the causal pathogen was named Tilletia indica but was later renamed Neovossia indica. The black powdered smelly spores remain viable for years in soil, wheat straw and farmyard manure as primary sources of inoculum. The losses reported were as high as 40% in India and also the cumulative reduction of national farm income in USA was USD 5.3 billion due to KB. The present review utilizes information from literature of the past 100 years, since 1909, to provide a comprehensive and updated understanding of KB, its causal pathogen, biology, epidemiology, pathogenesis, etc. Next generation sequencing (NGS) is gaining popularity in revolutionizing KB genomics for understanding and improving agronomic traits like yield, disease tolerance and disease resistance. Genetic resistance is the best way to manage KB, which may be achieved through detection of genes/quantitative trait loci (QTLs). The genome-wide association studies can be applied to reveal the association mapping panel for understanding and obtaining the KB resistance locus on the wheat genome, which can be crossed with elite wheat cultivars globally for a diverse wheat breeding program. The review discusses the current NGS-based genomic studies, assembly, annotations, resistant QTLs, GWAS, technology landscape of diagnostics and management of KB. The compiled exhaustive information can be beneficial to the wheat breeders for better understanding of incidence of disease in endeavor of quality production of the crop.

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Identification of Novel Genome-Wide Associations for Oral Inflammatory Traits

10.21203/rs.3.rs-104530/v1 ◽

2020 ◽

Author(s):

Yanjiao Jin ◽

Jie Yang ◽

Shuyue Zhang ◽

Jin Li ◽

Songlin Wang

Keyword(s):

Candidate Genes ◽

Immune Regulation ◽

Functional Annotation ◽

Inflammatory Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Protein Protein Interaction ◽

Genome Wide ◽

Causal Variants

Abstract Background: Oral diseases impact the majority of the world’s population. The following traits are common in oral inflammatory diseases: mouth ulcers, painful gums, bleeding gums, loose teeth, and toothache. Despite the prevalence of genome-wide association studies, the associations between these traits and common genomic variants, and whether pleiotropic loci are shared by some of these traits remain poorly understood. Methods: In this work, we conducted multi-trait joint analyses based on the summary statistics of genome-wide association studies of these five oral inflammatory traits from the UK Biobank, each of which is comprised of over 10,000 cases and over 300,000 controls. We estimated the genetic correlations between the five traits. We conducted fine-mapping and functional annotation based on multi-omics data to better understand the biological functions of the potential causal variants at each locus. To identify the pathways in which the candidate genes were mainly involved, we applied gene-set enrichment analysis, and further performed protein-protein interaction (PPI) analyses.Results: We identified 39 association signals that surpassed genome-wide significance, including three that were shared between two or more oral inflammatory traits, consistent with a strong correlation. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We performed fine-mapping and identified causal variants at each novel locus. Further functional annotation based on multi-omics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci, respectively. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of candidate genes at genome-wide significant loci in immune regulation.Conclusions: Our results highlighted the importance of immune regulation in the pathogenesis of oral inflammatory diseases. Some common immune-related pleiotropic loci or genetic variants are shared by multiple oral inflammatory traits. These findings will be beneficial for risk prediction, prevention, and therapy of oral inflammatory diseases.

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