scholarly journals POPULATION GENETIC ANALYSIS OF BRAZILIAN PEACH BREEDING GERMPLASM

2017 ◽  
Vol 39 (5) ◽  
Author(s):  
LIANE BAHR THUROW ◽  
MARIA DO CARMO BASSOLS RASEIRA ◽  
SANDRO BONOW ◽  
LUIS WILLIAN PACHECO ARGE ◽  
CAROLINE MARQUES CASTRO
Keyword(s):  
Genetic Variability ◽  
Association Studies ◽  
Subtropical Climate ◽  
Genome Wide Association Studies ◽  
Population Genetic Analysis ◽  
Average Value ◽  
Peach Breeding ◽  
Breeding Pool ◽  
High Level ◽  
Social Importance

ABSTRACT Peach has great economic and social importance in Brazil. Diverse sources of germplasm were used to introduce desirable traits in the Brazilian peach breeding pool, composed mainly by local selections and accessions selected from populations developed by the national breeding programs, adapted to subtropical climate, with low chill requirement, as well as accessions introduced from several countries. In this research, we used SSR markers, selected by their high level of polymorphism, to access genetic diversity and population structure of a set composed by 204 peach selected genotypes, based on contrasting phenotypes for valuable traits in peach breeding. A total of 80 alleles were obtained, giving an average of eight alleles per locus. In general, the average value of observed heterozygosity (0.46) was lower than the expected heterozygosity (0.63). STRUCTURE analysis assigned 162 accessions splitted into two subpopulations based mainly on their flesh type: melting (96) and non-melting (66) flesh cultivars. The remaining accessions (42) could not be assigned under the 80% membership coefficient criteria. Genetic variability was greater in melting subpopulation compared to non-melting. Additionally, 55% of the alleles present in the breeding varieties were also present in the founder varieties, indicating that founding clones are well represented in current peach cultivars and advanced selections developed. Overall, this study gives a first insight of the peach genetic variability available and evidence for population differentiation (structure) in this peach panel to be exploited and provides the basis for genome-wide association studies.

scholarly journals High Level of Uromodulin Increases the Risk of Hypertension: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Ruilian You ◽  
Lanlan Chen ◽  
Lubin Xu ◽  
Dingding Zhang ◽  
Haitao Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Inverse Variance ◽  
The Uk ◽  
High Level

Background: The association of uromodulin and hypertension has been observed in clinical studies, but not proven by a causal relationship. We conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between uromodulin and blood pressure.Methods: We selected single nucleotide polymorphisms (SNPs) related to urinary uromodulin (uUMOD) and serum uromodulin (sUMOD) from a large Genome-Wide Association Studies (GWAS) meta-analysis study and research in PubMed. Six datasets based on the UK Biobank and the International Consortium for Blood Pressure (ICBP) served as outcomes with a large sample of hypertension (n = 46,188), systolic blood pressure (SBP, n = 1,194,020), and diastolic blood pressure (DBP, n = 1,194,020). The inverse variance weighted (IVW) method was performed in uUMOD MR analysis, while methods of IVW, MR-Egger, Weighted median, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were utilized on sUMOD MR analysis.Results: MR analysis of IVM showed the odds ratio (OR) of the uUMOD to hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.04 (95% Confidence Interval (CI), 1.03-1.04, P < 0.001); the effect sizes of the uUMOD to SBP are 1.10 (Standard error (SE) = 0.25, P = 8.92E-06) and 0.03 (SE = 0.01, P = 2.70E-04) in “ieu-b-38” and “ukb-b-20175”, respectively. The β coefficient of the uUMOD to DBP is 0.88 (SE = 0.19, P = 4.38E-06) in “ieu-b-39” and 0.05 (SE = 0.01, P = 2.13E-10) in “ukb-b-7992”. As for the sUMOD, the OR of hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.01 (95% CI 1.01–1.02, all P < 0.001). The β coefficient of the SBP is 0.37 (SE = 0.07, P = 1.26E-07) in “ieu-b-38” and 0.01 (SE = 0.003, P = 1.04E-04) in “ukb-b-20175”. The sUMOD is causally associated with elevated DBP (“ieu-b-39”: β = 0.313, SE = 0.050, P = 3.43E-10; “ukb-b-7992”: β = 0.018, SE = 0.003, P = 8.41E-09).Conclusion: Our results indicated that high urinary and serum uromodulin levels are potentially detrimental in elevating blood pressure, and serve as a causal risk factor for hypertension.

scholarly journals Characterization of cocaine addiction-like behavior in heterogeneous stock rats

2021 ◽  
Author(s):  
Giordano de Guglielmo ◽  
Lieselot Carrette ◽  
Marsida Kallupi ◽  
Molly Brennan ◽  
Brent Boomhower ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Association Studies ◽  
Twin Studies ◽  
Progressive Ratio ◽  
Individual Variability ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Heterogeneous Stock ◽  
Cocaine Use ◽  
Specific Effects

Twin studies suggest that approximately 50% of the vulnerability to cocaine use disorder is determined by genetic factors, but genome-wide association studies (GWAS) in humans have only begun to identify specific genes that confer this risk. The identification of a set of single nucleotide polymorphisms (SNPs) associated with increased vulnerability to develop compulsive cocaine use represents a major goal for understanding of the genetic risk factors to cocaine use disorder and facilitating the identification of novel druggable targets. Here we characterized addiction-like behaviors in heterogeneous stock (HS) rats, a unique outbred strain of rats characterized by high genetic variability that has been developed to mimic genetic variability in humans. HS rats were allowed to self-administer cocaine 6h/daily for 14 days. Animals were also screened for compulsive cocaine use, using progressive-ratio (PR) and responding despite adverse consequences (contingent foot shocks). To minimize cohort-specific effects, we used large cohorts (n = 46-60) and normalized the level of responding within cohorts using a Z-score. To take advantage of the three behaviors related to compulsive intake and further identify subjects that are consistently vulnerable vs. resilient to compulsive cocaine use we computed an Addiction index by averaging normalized responding (Z-scores) for the three behavioral tests. Results showed high individual variability between vulnerable and resilient rats that is likely to facilitate detection of gene variants associated with vulnerable vs. resilient individuals. Such data will have considerable translational value for designing pharmacogenetic studies in humans.

scholarly journals Functional genomic characterization of the FTO locus in African Americans

2019 ◽  
Vol 51 (11) ◽  
pp. 517-528 ◽  
Author(s):  
Richard Gill ◽  
George Stratigopoulos ◽  
Joseph H. Lee ◽  
Rudolph L. Leibel
Keyword(s):  
Fine Mapping ◽  
Association Studies ◽  
Haplotype Diversity ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Nucleotide Polymorphisms ◽  
Atherosclerosis Risk In Communities ◽  
Individual Level ◽  
Genome Wide ◽  
High Level

Background: SNPs in the first intron of the fat mass and obesity-associated ( FTO) gene represent the strongest genome-wide associations with adiposity [body mass index (BMI)]; the molecular basis for these associations is under intense investigation. In European populations, the focus of most genome-wide association studies conducted to date, the single nucleotide polymorphisms (SNPs) have indistinguishable associations due to the high level of linkage disequilibrium (LD). However, in African American (AA) individuals, reduced LD and increased haplotype diversity permit finer distinctions among obesity-associated SNPs. Such distinctions are important to mechanistic inferences and for selection of disease SNPs relevant to specific populations. Methods: To identify specific FTO SNP(s) directly related to adiposity, we performed: 1) haplotype analyses of individual-level data in 3,335 AAs from the Atherosclerosis Risk in Communities Cohort (ARIC) study; as well as 2) statistical fine-mapping using summary statistics from a study of FTO in over 20 000 AAs and over 1000 functional genomic annotations. Results: Our haplotype analyses suggest that in AAs at least two distinct signals underlie the intron 1 FTO-adiposity signal. Fine mapping showed that two SNPs have the highest posterior probability of association (PPA) with BMI: rs9927317 (PPA = 0.94) and rs62033405 (PPA = 0.99). These variants overlap possible enhancer sites and the 5′-regions of transcribed genes in the substantia nigra, chondrocytes, and white adipocytes. Conclusions: We found two SNPs in FTO with the highest probability of direct association with BMI in AAs, as well as tissue-specific mechanisms by which these variants may contribute to the pathogenesis of obesity.

scholarly journals Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways

2021 ◽  
Vol 12 ◽  
Author(s):  
Delesa Damena ◽  
Francis E. Agamah ◽  
Peter O. Kimathi ◽  
Ntumba E. Kabongo ◽  
Hundaol Girma ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Severe Malaria ◽  
Resistance Genes ◽  
Population Genetic ◽  
Association Studies ◽  
Chromatin Interaction ◽  
Genome Wide Association Studies ◽  
Biological Functions ◽  
Population Genetic Analysis ◽  
Genome Wide

Recent genome-wide association studies (GWASs) of severe malaria have identified several association variants. However, much about the underlying biological functions are yet to be discovered. Here, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics (N = 17,000) meta-analysed across 11 populations in malaria endemic regions. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping, and gene-based association analyses to identify candidate severe malaria resistance genes. We further applied rare variant analysis to raw GWAS datasets (N = 11,000) of three malaria endemic populations including Kenya, Malawi, and Gambia and performed various population genetic structures of the identified genes in the three populations and global populations. We performed network and pathway analyses to investigate their shared biological functions. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci, while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signalling elements, and neuronal systems. Our population genetic analysis revealed that the minor allele frequencies (MAF) of the single nucleotide polymorphisms (SNPs) residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes, highlighting the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways.

scholarly journals Genetic variability in response to Aβ deposition influences Alzheimer’s risk

2018 ◽  
Author(s):  
Dervis A. Salih ◽  
Sevinc Bayram ◽  
Manuel S. Guelfi ◽  
Regina Reynolds ◽  
Maryam Shoai ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variability ◽  
Disease Risk ◽  
Late Onset ◽  
Association Studies ◽  
Amyloid Deposition ◽  
Genome Wide Association Studies ◽  
Statistical Comparison ◽  
Microglial Response

AbstractGenetic analysis of late-onset Alzheimer’s disease risk has previously identified a network of largely microglial genes that form a transcriptional network. In transgenic mouse models of amyloid deposition we have previously shown that the expression of many of the mouse orthologs of these genes are co-ordinately up-regulated by amyloid deposition. Here we investigate whether systematic analysis of other members of this mouse amyloid-responsive network predicts other Alzheimer’s risk loci. This statistical comparison of the mouse amyloid-response network with Alzheimer’s disease genome-wide association studies identifies 5 other genetic risk loci for the disease (OAS1, CXCL10, LAPTM5, ITGAM and LILRB4). This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer’s risk.One Sentence SummaryIdentification of 5 new risk loci for Alzheimer’s by statistical comparison of mouse Aβ microglial response with gene-based SNPs from human GWAS

scholarly journals Assessing the role of blood pressure in amyotrophic lateral sclerosis: a Mendelian randomization study

2021 ◽  
Author(s):  
Kailin Xia ◽  
Linjing Zhang ◽  
Lu Tang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Blood Pressure ◽  
Amyotrophic Lateral Sclerosis ◽  
Protective Factor ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Inverse Variance ◽  
High Level ◽  
Lateral Sclerosis

Abstract Background Observational studies have suggested a close but controversial relationship between blood pressure (BP) and amyotrophic lateral sclerosis (ALS). However, it remains unclear whether this association is causal. The authors employed a bidirectional two-sample Mendelian randomization (MR) approach to investigate whether there is a causal relationship between BP and ALS. Genetic proxies for systolic blood pressure (SBP), diastolic blood pressure (DBP), antihypertension drugs (AHDs), ALS, and their corresponding genome-wide association studies (GWAS) summary datasets were obtained from the updated largest studies. Inverse variance weighted (IVW) method was adopted as the main approach to examine the effect of BP on ALS and four other MR methods for sensitivity analyses. To exclude the interference between SBP and DBP, multivariable MR was used. Results We found that genetically determined increased DBP was a protective factor for ALS (OR = 0.978, 95% CI 0.960–0.996, P = 0.017), and increased SBP was an independent risk factor for ALS (OR = 1.014, 95% CI 1.003–1.025, P = 0.015). The high level of targeted protein of Calcium channel blocker (CCB) showed a causative relationship with ALS (OR = 0.985, 95% CI 0.971-1.000, P = 0.049). No evidence was revealed that ALS caused results change of BP measurements. Conclusions This study demonstrated that an increase in DBP is a protective factor for ALS, and increased SBP is independently risk for ALS, which may be related to sympathetic excitability. Blood pressure management is important in ALS, in which CCB may be a promising candidate.

scholarly journals A novel computational methodology for GWAS multi-locus analysis based on graph theory and machine learning

2021 ◽  
Author(s):  
Subrata Saha ◽  
Himanshu Narayan Singh ◽  
Ahmed Soliman ◽  
Sanguthevar Rajasekaran
Keyword(s):  
Machine Learning ◽  
Graph Theory ◽  
Complex Traits ◽  
Developmental Disorders ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Current Form ◽  
Gwas Dataset ◽  
Genome Wide ◽  
High Level

Background: Current form of genome-wide association studies (GWAS) is inadequate to accurately explain the genetics of complex traits due to the lack of sufficient statistical power. It explores each variant individually, but current studies show that multiple variants with varying effect sizes actually act in a concerted way to develop a complex disease. To address this issue, we have developed an algorithmic framework that can effectively solve the multi-locus problem in GWAS with a very high level of confidence. Our methodology consists of three novel algorithms based on graph theory and machine learning. It identifies a set of highly discriminating variants that are stable and robust with little (if any) spuriousness. Consequently, likely these variants should be able to interpret missing heritability of a convoluted disease as an entity. Results: To demonstrate the efficacy of our proposed algorithms, we have considered astigmatism case-control GWAS dataset. Astigmatism is a common eye condition that causes blurred vision because of an error in the shape of the cornea. The cause of astigmatism is not entirely known but a sizable inheritability is assumed. Clinical studies show that developmental disorders (such as, autism) and astigmatism co-occur in a statistically significant number of individuals. By performing classical GWAS analysis, we didn't find any genome-wide statistically significant variants. Conversely, we have identified a set of stable, robust, and highly predictive variants that can together explain the genetics of astigmatism. We have performed a set of biological enrichment analyses based on gene ontology (GO) terms, disease ontology (DO) terms, biological pathways, network of pathways, and so forth to manifest the accuracy and novelty of our findings. Conclusions: Rigorous experimental evaluations show that our proposed methodology can solve GWAS multi-locus problem effectively and efficiently. It can identify signals from the GWAS dataset having small number of samples with a high level of accuracy. We believe that the proposed methodology based on graph theory and machine learning is the most comprehensive one compared to any other machine learning based tools in this domain.

scholarly journals Genetic variability in response to amyloid beta deposition influences Alzheimer’s disease risk

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Dervis A Salih ◽  
Sevinc Bayram ◽  
Sebastian Guelfi ◽  
Regina H Reynolds ◽  
Maryam Shoai ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variability ◽  
Disease Risk ◽  
Association Studies ◽  
Amyloid Deposition ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide

Abstract Genome-wide association studies of late-onset Alzheimer’s disease risk have previously identified genes primarily expressed in microglia that form a transcriptional network. Using transgenic mouse models of amyloid deposition, we previously showed that many of the mouse orthologues of these risk genes are co-expressed and associated with amyloid pathology. In this new study, we generate an improved RNA-seq-derived network that is expressed in amyloid-responsive mouse microglia and we statistically compare this with gene-level variation in previous human Alzheimer’s disease genome-wide association studies to predict at least four new risk genes for the disease (OAS1, LAPTM5, ITGAM/CD11b and LILRB4). Of the mouse orthologues of these genes Oas1a is likely to respond directly to amyloid at the transcriptional level, similarly to established risk gene Trem2, because the increase in Oas1a and Trem2 transcripts in response to amyloid deposition in transgenic mice is significantly higher than both the increase of the average microglial transcript and the increase in microglial number. In contrast, the mouse orthologues of LAPTM5, ITGAM/CD11b and LILRB4 (Laptm5, Itgam/CD11b and Lilra5) show increased transcripts in the presence of amyloid plaques similar in magnitude to the increase of the average microglial transcript and the increase in microglia number, except that Laptm5 and Lilra5 transcripts increase significantly quicker than the average microglial transcript as the plaque load becomes dense. This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer’s disease risk, and identification of these genes may help to predict the risk of developing Alzheimer’s disease. These findings also provide further insights into the mechanisms underlying Alzheimer’s disease for potential drug discovery.

scholarly journals Functional analysis of genome-wide dataset from 17000 individuals identifies multiple candidate malaria resistance genes enriched in malaria pathogenic pathways

2020 ◽  
Author(s):  
Delesa Damena ◽  
Francis Agamah ◽  
Peter O Kimathi ◽  
Ntumba E Kabongo ◽  
Hundaol Girma ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Severe Malaria ◽  
Resistance Genes ◽  
Population Genetic ◽  
Association Studies ◽  
Chromatin Interaction ◽  
Genome Wide Association Studies ◽  
Biological Functions ◽  
Population Genetic Analysis ◽  
Genome Wide

Recent genome-wide association studies (GWASs) of severe malaria have identified several association variants. However, much about the underlying biological functions are yet to be discovered. Here, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics(N=17,000) meta-analyzed across eleven populations in malaria endemic regions. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping and gene-based association analyses to identify candidate severe malaria resistance genes. We performed network and pathway analyses to investigate their shared biological functions. We further applied rare variant analysis to raw GWAS datasets (N=11,000) of three malaria endemic populations including Kenya, Malawi and Gambia and performed various population genetic structures of the identified genes in the three populations and global populations. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signaling elements and neuronal systems. Our population genetic analysis revealed that the minor allele frequencies (MAF) of the single nucleotide polymorphisms (SNPs) residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes; highlighting the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways.

TLR1 and PRKAA1 Gene Polymorphisms in the Development of Atrophic Gastritis and Gastric Cancer

2018 ◽  
Vol 27 (4) ◽  
pp. 363-369 ◽  
Author(s):  
Gintare Dargiene ◽  
Greta Streleckiene ◽  
Jurgita Skieceviciene ◽  
Marcis Leja ◽  
Alexander Link ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Atrophic Gastritis ◽  
Genetic Polymorphisms ◽  
Association Studies ◽  
Control Group ◽  
Similar Distribution ◽  
Genome Wide Association Studies ◽  
Increased Risk ◽  
Infection Susceptibility ◽  
H Pylori

Background & Aims: Previous genome-wide association studies showed that genetic polymorphisms in toll-like receptor 1 (TLR1) and protein kinase AMP-activated alpha 1 catalytic subunit (PRKAA1) genes were associated with gastric cancer (GC) or increased Helicobacter pylori (H. pylori) infection susceptibility. The aim of this study was to evaluate the association between TLR1 and PRKAA1 genes polymorphisms and H.pylori infection, atrophic gastritis (AG) or GC in the European population.Methods: Single-nucleotide polymorphisms (SNPs) were analysed in 511 controls, 340 AG patients and 327 GC patients. TLR1 C>T (rs4833095) and PRKAA1 C>T (rs13361707) were genotyped by the real-time polymerase chain reaction. H. pylori status was determined by testing for anti-H. pylori IgG antibodies in the serum.Results: The study included 697 (59.2%) H. pylori positive and 481 (40.8%) H. pylori negative cases. We observed similar distribution of TLR1 and PRKAA1 alleles and genotypes in H. pylori positive and negative cases. TLR1 and PRKAA1 SNPs were not linked with the risk of AG. TC genotype of TLR1 gene was more prevalent in GC patients compared to the control group (29.7% and 22.3% respectively, p=0.002). Carriers of TC genotype had a higher risk of GC (aOR=1.89, 95% CI: 1.26–2.83, p=0.002). A similar association was observed in a dominant inheritance model for TLR1 gene SNP, where comparison of CC+TC vs. TT genotypes showed an increased risk of GC (aOR=1.86, 95% CI: 1.26–2.75, p=0.002). No association between genetic polymorphism in PRKAA1 gene and GC was observed.Conclusions: TLR1 rs4833095 SNP was associated with an increased risk of GC in a European population, while PRKAA1 rs13361707 genetic variant was not linked with GC. Both genetic polymorphisms were not associated with H. pylori infection susceptibility or the risk of AG.

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