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1.
Genet Sel Evol ; 51(1): 20, 2019 May 10.
Artigo em Inglês | MEDLINE | ID: mdl-31077144

RESUMO

BACKGROUND: Genome-wide association studies (GWAS) are widely used to identify regions of the genome that harbor genetic determinants of quantitative traits. However, the multiple-testing burden from scanning tens of millions of whole-genome sequence variants reduces the power to identify associated variants, especially if sample size is limited. In addition, factors such as inaccuracy of imputation, complex linkage disequilibrium structures, and multiple closely-located causal variants may result in an identified causative mutation not being the most significant single nucleotide polymorphism in a particular genomic region. Therefore, the use of information from different sources, particularly variant annotations, was proposed to enhance the fine-mapping of causal variants. Here, we tested whether applying significance thresholds based on variant annotation categories increases the power of GWAS compared with a flat Bonferroni multiple-testing correction. RESULTS: Whole-genome sequence variants in dairy cattle were categorized according to type and predicted impact. Then, GWAS between markers and 17 quantitative traits were analyzed for enrichment for association of each annotation category. By using annotation categories that were determined with the variants effect predictor software and datasets indicating regions of open chromatin, "low impact" variants were found to be highly enriched. Moreover, when the variants annotated as "modifier" and not located at open chromatin regions were further classified into different types of potential regulatory elements, the high impact variants, moderate impact variants, variants located in the 3' and 5' untranslated regions, and variants located in potential non-coding RNA regions exhibited relatively more enrichment. In contrast, a similar study on human GWAS data reported that enrichment of association signals was highest with high impact variants. We observed an increase in power when these variant category-based significance thresholds were applied for GWAS results on stature in Nordic Holstein cattle, as more candidate genes from previous large GWAS meta-analysis for cattle stature were confirmed. CONCLUSIONS: Use of variant category-based genome-wide significance thresholds can marginally increase the power to detect the candidate genes in cattle. With the continued improvements in annotation of the bovine genome, we anticipate that the growing usefulness of variant category-based significance thresholds will be demonstrated.


Assuntos
Bovinos/genética , Estudo de Associação Genômica Ampla/métodos , Polimorfismo Genético , Animais , Estudo de Associação Genômica Ampla/normas , Anotação de Sequência Molecular , Locos de Características Quantitativas
2.
Mol Genet Genomic Med ; 7(5): e628, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30868767

RESUMO

BACKGROUND: 5,10-Methylentetrahydrofolate reductase (MTHFR) C677T polymorphism is one of the most studied genetic variations in the human genome. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is one of the most used techniques to characterize the point mutations in genomic sequences because of its suitability and low cost. The most widely used method for the MTHFR C677T polymorphism characterization was developed by Frosst et al. (1995) but appears to have some technical limitations. The aim of this study was to propose a novel PCR-RFLP method for the detection of this polymorphism. METHODS: In order to retrieve all published articles possibly describing any PCR-RFLP methods useful to analyze MTHFR C677T polymorphism, we performed systematic queries on PubMed, using a combination of Boolean operators (AND/OR) and MeSH terms. Amplify software was used in order to design a new primer pair following the optimal standard criteria. Primer-BLAST software was used to check primer pair's biological specificity. RESULTS: The analysis of previous literature showed that PCR-RFLP method remains the most used technique. None of the 108 primer pairs described was ideal with regard to main accepted primer pair biochemical technical parameters. The new primer pair amplifies a DNA-fragment of 513 base pair (bp) that, in the presence of the polymorphism, is cut by Hinf I enzyme in two pieces of 146 bp and 367 bp and clearly visible on 2% agarose gel. The level of expertise and the materials required are minimal and the protocol takes one day to carry out. CONCLUSION: Our original PCR-RFLP strategy, specifically designed to make the analysis optimal with respect to PCR primers and gel analysis, fits the ideal criteria compared to the widely used strategy by Frosst et al (1995) as well as any other PCR-RFLP strategies proposed for MTHFR C677T polymorphism genotyping to date.


Assuntos
Análise do Polimorfismo de Comprimento de Fragmentos Amplificados/métodos , Estudo de Associação Genômica Ampla/métodos , Metilenotetra-Hidrofolato Redutase (NADPH2)/genética , Polimorfismo de Nucleotídeo Único , Análise do Polimorfismo de Comprimento de Fragmentos Amplificados/normas , Estudo de Associação Genômica Ampla/normas , Humanos
3.
Hum Genet ; 138(4): 389-409, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30887117

RESUMO

Incidence rates of Mendelian diseases vary among ethnic groups, and frequencies of variant types of causative genes also vary among human populations. In this study, we examined to what extent we can predict population frequencies of recessive disorders from genomic data, and explored better strategies for variant interpretation and classification. We used a whole-genome reference panel from 3552 general Japanese individuals constructed by the Tohoku Medical Megabank Organization (ToMMo). Focusing on 32 genes for 17 congenital metabolic disorders included in newborn screening (NBS) in Japan, we identified reported and predicted pathogenic variants through variant annotation, interpretation, and multiple ways of classifications. The estimated carrier frequencies were compared with those from the Japanese NBS data based on 1,949,987 newborns from a previous study. The estimated carrier frequency based on genomic data with a recent guideline of variant interpretation for the PAH gene, in which defects cause hyperphenylalaninemia (HPA) and phenylketonuria (PKU), provided a closer estimate to that by the observed incidence than the other methods. In contrast, the estimated carrier frequencies for SLC25A13, which causes citrin deficiency, were much higher compared with the incidence rate. The results varied greatly among the 11 NBS diseases with single responsible genes; the possible reasons for departures from the carrier frequencies by reported incidence rates were discussed. Of note, (1) the number of pathogenic variants increases by including additional lines of evidence, (2) common variants with mild effects also contribute to the actual frequency of patients, and (3) penetrance of each variant remains unclear.


Assuntos
Doenças Genéticas Inatas/diagnóstico , Doenças Genéticas Inatas/genética , Doenças do Recém-Nascido/diagnóstico , Doenças do Recém-Nascido/genética , Triagem Neonatal/métodos , Grupo com Ancestrais do Continente Asiático/genética , Grupo com Ancestrais do Continente Asiático/estatística & dados numéricos , Estudos de Coortes , Feminino , Frequência do Gene , Doenças Genéticas Inatas/epidemiologia , Estudo de Associação Genômica Ampla/normas , Heterozigoto , Humanos , Incidência , Recém-Nascido , Doenças do Recém-Nascido/epidemiologia , Japão/epidemiologia , Masculino , Padrões de Referência
4.
Genetics ; 211(4): 1449-1467, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30760490

RESUMO

We leverage two complementary Drosophila melanogaster mapping panels to genetically dissect starvation resistance-an important fitness trait. Using >1600 genotypes from the multiparental Drosophila Synthetic Population Resource (DSPR), we map numerous starvation stress QTL that collectively explain a substantial fraction of trait heritability. Mapped QTL effects allowed us to estimate DSPR founder phenotypes, predictions that were correlated with the actual phenotypes of these lines. We observe a modest phenotypic correlation between starvation resistance and triglyceride level, traits that have been linked in previous studies. However, overlap among QTL identified for each trait is low. Since we also show that DSPR strains with extreme starvation phenotypes differ in desiccation resistance and activity level, our data imply multiple physiological mechanisms contribute to starvation variability. We additionally exploited the Drosophila Genetic Reference Panel (DGRP) to identify sequence variants associated with starvation resistance. Consistent with prior work these sites rarely fall within QTL intervals mapped in the DSPR. We were offered a unique opportunity to directly compare association mapping results across laboratories since two other groups previously measured starvation resistance in the DGRP. We found strong phenotypic correlations among studies, but extremely low overlap in the sets of genomewide significant sites. Despite this, our analyses revealed that the most highly associated variants from each study typically showed the same additive effect sign in independent studies, in contrast to otherwise equivalent sets of random variants. This consistency provides evidence for reproducible trait-associated sites in a widely used mapping panel, and highlights the polygenic nature of starvation resistance.


Assuntos
Aptidão Genética , Herança Multifatorial , Locos de Características Quantitativas , Característica Quantitativa Herdável , Estresse Fisiológico/genética , Animais , Drosophila melanogaster , Genoma de Inseto , Estudo de Associação Genômica Ampla/métodos , Estudo de Associação Genômica Ampla/normas , Inanição/genética
5.
Genetics ; 211(4): 1429-1447, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30792267

RESUMO

Due to the complexity of genotype-phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and informative than a series of univariate analyses. However, in most cases, studies of genotype-phenotype relationships have been analyzed only one trait at a time. Here, we report the results of a fully integrated multivariate genome-wide association analysis of the shape of the Drosophila melanogaster wing in the Drosophila Genetic Reference Panel. Genotypic effects on wing shape were highly correlated between two different laboratories. We found 2396 significant SNPs using a 5% false discovery rate cutoff in the multivariate analyses, but just four significant SNPs in univariate analyses of scores on the first 20 principal component axes. One quarter of these initially significant SNPs retain their effects in regularized models that take into account population structure and linkage disequilibrium. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. We exploit this fact to show that the effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. A subset of SNP effects were replicable in an unrelated panel of inbred lines. Association studies that take a phenomic approach, considering many traits simultaneously, are an important complement to the power of genomics.


Assuntos
Proteínas de Drosophila/genética , Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único , Asas de Animais/crescimento & desenvolvimento , Animais , Drosophila melanogaster , Estudo de Associação Genômica Ampla/normas , Padrões de Referência , Asas de Animais/metabolismo
6.
Genetics ; 211(4): 1395-1407, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30796011

RESUMO

In humans, most genome-wide association studies have been conducted using data from Caucasians and many of the reported findings have not replicated in other populations. This lack of replication may be due to statistical issues (small sample sizes or confounding) or perhaps more fundamentally to differences in the genetic architecture of traits between ethnically diverse subpopulations. What aspects of the genetic architecture of traits vary between subpopulations and how can this be quantified? We consider studying effect heterogeneity using Bayesian random effect interaction models. The proposed methodology can be applied using shrinkage and variable selection methods, and produces useful information about effect heterogeneity in the form of whole-genome summaries (e.g., the proportions of variance of a complex trait explained by a set of SNPs and the average correlation of effects) as well as SNP-specific attributes. Using simulations, we show that the proposed methodology yields (nearly) unbiased estimates when the sample size is not too small relative to the number of SNPs used. Subsequently, we used the methodology for the analyses of four complex human traits (standing height, high-density lipoprotein, low-density lipoprotein, and serum urate levels) in European-Americans (EAs) and African-Americans (AAs). The estimated correlations of effects between the two subpopulations were well below unity for all the traits, ranging from 0.73 to 0.50. The extent of effect heterogeneity varied between traits and SNP sets. Height showed less differences in SNP effects between AAs and EAs whereas HDL, a trait highly influenced by lifestyle, exhibited a greater extent of effect heterogeneity. For all the traits, we observed substantial variability in effect heterogeneity across SNPs, suggesting that effect heterogeneity varies between regions of the genome.


Assuntos
Grupos Étnicos/genética , Heterogeneidade Genética , Modelos Genéticos , População/genética , Característica Quantitativa Herdável , Estudo de Associação Genômica Ampla/métodos , Estudo de Associação Genômica Ampla/normas , Humanos , Polimorfismo de Nucleotídeo Único
7.
Epigenetics Chromatin ; 12(1): 1, 2019 01 02.
Artigo em Inglês | MEDLINE | ID: mdl-30602389

RESUMO

BACKGROUND: The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages. RESULTS: BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood. CONCLUSIONS: Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues.


Assuntos
Metilação de DNA , Epigenômica/normas , Variação Genética , Estudo de Associação Genômica Ampla/normas , Adolescente , Fatores Etários , Criança , Pré-Escolar , Feminino , Humanos , Masculino , Monócitos/metabolismo , Mucosa Bucal/metabolismo
8.
Genet Sel Evol ; 51(1): 1, 2019 Jan 17.
Artigo em Inglês | MEDLINE | ID: mdl-30654735

RESUMO

BACKGROUND: The use of whole-genome sequence (WGS) data for genomic prediction and association studies is highly desirable because the causal mutations should be present in the data. The sequencing of 935 sheep from a range of breeds provides the opportunity to impute sheep genotyped with single nucleotide polymorphism (SNP) arrays to WGS. This study evaluated the accuracy of imputation from SNP genotypes to WGS using this reference population of 935 sequenced sheep. RESULTS: The accuracy of imputation from the Ovine Infinium® HD BeadChip SNP (~ 500 k) to WGS was assessed for three target breeds: Merino, Poll Dorset and F1 Border Leicester × Merino. Imputation accuracy was highest for the Poll Dorset breed, although there were more Merino individuals in the sequenced reference population than Poll Dorset individuals. In addition, empirical imputation accuracies were higher (by up to 1.7%) when using larger multi-breed reference populations compared to using a smaller single-breed reference population. The mean accuracy of imputation across target breeds using the Minimac3 or the FImpute software was 0.94. The empirical imputation accuracy varied considerably across the genome; six chromosomes carried regions of one or more Mb with a mean imputation accuracy of < 0.7. Imputation accuracy in five variant annotation classes ranged from 0.87 (missense) up to 0.94 (intronic variants), where lower accuracy corresponded to higher proportions of rare alleles. The imputation quality statistic reported from Minimac3 (R2) had a clear positive relationship with the empirical imputation accuracy. Therefore, by first discarding imputed variants with an R2 below 0.4, the mean empirical accuracy across target breeds increased to 0.97. Although accuracy of genomic prediction was less affected by filtering on R2 in a multi-breed population of sheep with imputed WGS, the genomic heritability clearly tended to be lower when using variants with an R2 ≤ 0.4. CONCLUSIONS: The mean imputation accuracy was high for all target breeds and was increased by combining smaller breed sets into a multi-breed reference. We found that the Minimac3 software imputation quality statistic (R2) was a useful indicator of empirical imputation accuracy, enabling removal of very poorly imputed variants before downstream analyses.


Assuntos
Estudo de Associação Genômica Ampla/normas , Ovinos/genética , Software/normas , Sequenciamento Completo do Genoma/normas , Animais , Estudo de Associação Genômica Ampla/veterinária , Polimorfismo de Nucleotídeo Único , Sequenciamento Completo do Genoma/veterinária
9.
Genet Sel Evol ; 51(1): 2, 2019 Jan 24.
Artigo em Inglês | MEDLINE | ID: mdl-30678638

RESUMO

BACKGROUND: Use of whole-genome sequence data (WGS) is expected to improve identification of quantitative trait loci (QTL). However, this requires imputation to WGS, often with a limited number of sequenced animals for the target population. The objective of this study was to investigate imputation to WGS in two pig lines using a multi-line reference population and, subsequently, to investigate the effect of using these imputed WGS (iWGS) for GWAS. METHODS: Phenotypes and genotypes were available on 12,184 Large White pigs (LW-line) and 4943 Dutch Landrace pigs (DL-line). Imputed 660 K and 80 K genotypes for the LW-line and DL-line, respectively, were imputed to iWGS using Beagle v.4.1. Since only 32 LW-line and 12 DL-line boars were sequenced, 142 animals from eight commercial lines were added. GWAS were performed for each line using the 80 K and 660 K SNPs, the genotype scores of iWGS SNPs that had an imputation accuracy (Beagle R2) higher than 0.6, and the dosage scores of all iWGS SNPs. RESULTS: For the DL-line (LW-line), imputation of 80 K genotypes to iWGS resulted in an average Beagle R2 of 0.39 (0.49). After quality control, 2.5 × 106 (3.5 × 106) SNPs had a Beagle R2 higher than 0.6, resulting in an average Beagle R2 of 0.83 (0.93). Compared to the 80 K and 660 K genotypes, using iWGS led to the identification of 48.9 and 64.4% more QTL regions, for the DL-line and LW-line, respectively, and the most significant SNPs in the QTL regions explained a higher proportion of phenotypic variance. Using dosage instead of genotype scores improved the identification of QTL, because the model accounted for uncertainty of imputation, and all SNPs were used in the analysis. CONCLUSIONS: Imputation to WGS using the multi-line reference population resulted in relatively poor imputation, especially when imputing from 80 K (DL-line). In spite of the poor imputation accuracies, using iWGS instead of a lower density SNP chip increased the number of detected QTL and the estimated proportion of phenotypic variance explained by these QTL, especially when dosage scores were used instead of genotype scores. Thus, iWGS, even with poor imputation accuracy, can be used to identify possible interesting regions for fine mapping.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Suínos/genética , Sequenciamento Completo do Genoma/métodos , Animais , Estudo de Associação Genômica Ampla/normas , Estudo de Associação Genômica Ampla/veterinária , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Sequenciamento Completo do Genoma/normas , Sequenciamento Completo do Genoma/veterinária
10.
Genetics ; 211(4): 1179-1189, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30692194

RESUMO

High-throughput measurements of molecular phenotypes provide an unprecedented opportunity to model cellular processes and their impact on disease. These highly structured datasets are usually strongly confounded, creating false positives and reducing power. This has motivated many approaches based on principal components analysis (PCA) to estimate and correct for confounders, which have become indispensable elements of association tests between molecular phenotypes and both genetic and nongenetic factors. Here, we show that these correction approaches induce a bias, and that it persists for large sample sizes and replicates out-of-sample. We prove this theoretically for PCA by deriving an analytic, deterministic, and intuitive bias approximation. We assess other methods with realistic simulations, which show that perturbing any of several basic parameters can cause false positive rate (FPR) inflation. Our experiments show the bias depends on covariate and confounder sparsity, effect sizes, and their correlation. Surprisingly, when the covariate and confounder have [Formula: see text], standard two-step methods all have [Formula: see text]-fold FPR inflation. Our analysis informs best practices for confounder correction in genomic studies, and suggests many false discoveries have been made and replicated in some differential expression analyses.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Fenótipo , Análise de Componente Principal/métodos , Animais , Estudo de Associação Genômica Ampla/normas , Humanos , Modelos Genéticos , Análise de Componente Principal/normas , Locos de Características Quantitativas , Reprodutibilidade dos Testes
11.
Genet Epidemiol ; 43(4): 356-364, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-30657194

RESUMO

When interpreting genome-wide association peaks, it is common to annotate each peak by searching for genes with plausible relationships to the trait. However, "all that glitters is not gold"-one might interpret apparent patterns in the data as plausible even when the peak is a false positive. Accordingly, we sought to see how human annotators interpreted association results containing a mixture of peaks from both the original trait and a genetically uncorrelated "synthetic" trait. Two of us prepared a mix of original and synthetic peaks of three significance categories from five different scans along with relevant literature search results and then we all annotated these regions. Three annotators also scored the strength of evidence connecting each peak to the scanned trait and the likelihood of further studying that region. While annotators found original peaks to have stronger evidence (p Bonferroni = 0.017) and higher likelihood of further study ( p Bonferroni = 0.006) than synthetic peaks, annotators often made convincing connections between the synthetic peaks and the original trait, finding these connections 55% of the time. These results show that it is not difficult for annotators to make convincing connections between synthetic association signals and genes found in those regions.


Assuntos
Curadoria de Dados , Interpretação Estatística de Dados , Reações Falso-Positivas , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Curadoria de Dados/métodos , Curadoria de Dados/normas , Curadoria de Dados/estatística & dados numéricos , Decepção , Estudo de Associação Genômica Ampla/normas , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único
12.
Genes Genet Syst ; 93(6): 255-258, 2019 Jan 19.
Artigo em Inglês | MEDLINE | ID: mdl-30568067

RESUMO

The Siberian weasel (Mustela sibirica) is widely distributed in mainland Asia, but its introduction into Japan and subsequent expansion have affected the Japanese weasel (M. itatsi). To provide a useful tool for population genetic studies and control of M. sibirica, we developed 10 polymorphic microsatellite markers. Among 40 individuals of M. sibirica collected in Hubei Province, China, the number of alleles per locus varied from 2 to 19, with the observed heterozygosity ranging from 0.050 to 1.000 and the expected heterozygosity ranging from 0.049 to 0.920. None of the loci deviated from Hardy-Weinberg equilibrium. These markers will be useful in further studies investigating the population structure and natural history of M. sibirica, and may thus provide new insights for the efficient management of this species.


Assuntos
Repetições de Microssatélites , Mustelidae/genética , Animais , Estudo de Associação Genômica Ampla/normas , Espécies Introduzidas , Polimorfismo Genético
13.
Genetics ; 211(2): 483-494, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30578273

RESUMO

With growing human genetic and epidemiologic data, there has been increased interest for the study of gene-by-environment (G-E) interaction effects. Still, major questions remain on how to test jointly a large number of interactions between multiple SNPs and multiple exposures. In this study, we first compared the relative performance of four fixed-effect joint analysis approaches using simulated data, considering up to 10 exposures and 300 SNPs: (1) omnibus test, (2) multi-exposure and genetic risk score (GRS) test, (3) multi-SNP and environmental risk score (ERS) test, and (4) GRS-ERS test. Our simulations explored both linear and logistic regression while considering three statistics: the Wald test, the Score test, and the likelihood ratio test (LRT). We further applied the approaches to three large sets of human cohort data (n = 37,664), focusing on type 2 diabetes (T2D), obesity, hypertension, and coronary heart disease with smoking, physical activity, diets, and total energy intake. Overall, GRS-based approaches were the most robust, and had the highest power, especially when the G-E interaction effects were correlated with the marginal genetic and environmental effects. We also observed severe miscalibration of joint statistics in logistic models when the number of events per variable was too low when using either the Wald test or LRT test. Finally, our real data application detected nominally significant interaction effects for three outcomes (T2D, obesity, and hypertension), mainly from the GRS-ERS approach. In conclusion, this study provides guidelines for testing multiple interaction parameters in modern human cohorts including extensive genetic and environmental data.


Assuntos
Predisposição Genética para Doença , Estudo de Associação Genômica Ampla/métodos , Modelos Genéticos , Algoritmos , Estudo de Associação Genômica Ampla/normas , Humanos , Polimorfismo de Nucleotídeo Único
14.
Mol Autism ; 9: 63, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30559955

RESUMO

Background: Animal models for neurodevelopmental disorders (NDD) generally rely on a single genetic mutation on a fixed genetic background. Recent human genetic studies however indicate that a clinical diagnosis with ASDAutism Spectrum Disorder (ASD) is almost always associated with multiple genetic fore- and background changes. The translational value of animal model studies would be greatly enhanced if genetic insults could be studied in a more quantitative framework across genetic backgrounds. Methods: We used the Collaborative Cross (CC), a novel mouse genetic reference population, to investigate the quantitative genetic architecture of mouse behavioral phenotypes commonly used in animal models for NDD. Results: Classical tests of social recognition and grooming phenotypes appeared insufficient for quantitative studies due to genetic dilution and limited heritability. In contrast, digging, locomotor activity, and stereotyped exploratory patterns were characterized by continuous distribution across our CC sample and also mapped to quantitative trait loci containing genes associated with corresponding phenotypes in human populations. Conclusions: These findings show that the CC can move animal model studies beyond comparative single gene-single background designs, and point out which type of behavioral phenotypes are most suitable to quantify the effect of developmental etiologies across multiple genetic backgrounds.


Assuntos
Transtorno do Espectro Autista/genética , Genética Comportamental/métodos , Estudo de Associação Genômica Ampla/métodos , Animais , Genética Comportamental/normas , Estudo de Associação Genômica Ampla/normas , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Herança Multifatorial , Locos de Características Quantitativas , Padrões de Referência
15.
Genetics ; 209(2): 401-408, 2018 06.
Artigo em Inglês | MEDLINE | ID: mdl-29674520

RESUMO

Due to issues of practicality and confidentiality of genomic data sharing on a large scale, typically only meta- or mega-analyzed genome-wide association study (GWAS) summary data, not individual-level data, are publicly available. Reanalyses of such GWAS summary data for a wide range of applications have become more and more common and useful, which often require the use of an external reference panel with individual-level genotypic data to infer linkage disequilibrium (LD) among genetic variants. However, with a small sample size in only hundreds, as for the most popular 1000 Genomes Project European sample, estimation errors for LD are not negligible, leading to often dramatically increased numbers of false positives in subsequent analyses of GWAS summary data. To alleviate the problem in the context of association testing for a group of SNPs, we propose an alternative estimator of the covariance matrix with an idea similar to multiple imputation. We use numerical examples based on both simulated and real data to demonstrate the severe problem with the use of the 1000 Genomes Project reference panels, and the improved performance of our new approach.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Genoma Humano , Estudo de Associação Genômica Ampla/normas , Humanos , Desequilíbrio de Ligação , Polimorfismo de Nucleotídeo Único , Padrões de Referência , Reprodutibilidade dos Testes
16.
Genome ; 61(6): 449-456, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29688035

RESUMO

Genotyping-by-sequencing (GBS) potentially offers a cost-effective alternative for SNP discovery and genotyping. Here, we report the exploration of GBS in tetraploid potato. Both ApeKI and PstI/MspI enzymes were used for library preparation on eight diverse potato genotypes. ApeKI yielded more markers than PstI/MspI but provided a lower read coverage per marker, resulting in more missing data and limiting effective genotyping to the tetraploid mode. We then assessed the accuracy of these SNPs by comparison with SolCAP data (5824 data points in diploid mode and 3243 data points in tetraploid mode) and found the match rates between genotype calls was 90.4% and 81.3%, respectively. Imputation of missing data did not prove very accurate because of incomplete haplotype discovery, suggesting caution in setting the allowance for missing data. To further assess the quality of GBS-derived data, a genome-wide association analysis was performed for flower color on 318 clones (with ApeKI). A strong association signal on chromosome 2 was obtained with the most significant SNP located in the middle of the dihydroflavonol 4-reductase (DFR) gene. We conclude that an appropriate choice of enzyme for GBS library preparation makes it possible to obtain high-quality SNPs in potato and will be helpful for marker-assisted genomics.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Técnicas de Genotipagem/métodos , Polimorfismo de Nucleotídeo Único , Análise de Sequência de DNA/métodos , Solanum tuberosum/genética , Estudo de Associação Genômica Ampla/normas , Técnicas de Genotipagem/normas , Análise de Sequência de DNA/normas , Tetraploidia
17.
Proc Natl Acad Sci U S A ; 115(22): E4970-E4979, 2018 05 29.
Artigo em Inglês | MEDLINE | ID: mdl-29686100

RESUMO

Identifying causal effects in nonexperimental data is an enduring challenge. One proposed solution that recently gained popularity is the idea to use genes as instrumental variables [i.e., Mendelian randomization (MR)]. However, this approach is problematic because many variables of interest are genetically correlated, which implies the possibility that many genes could affect both the exposure and the outcome directly or via unobserved confounding factors. Thus, pleiotropic effects of genes are themselves a source of bias in nonexperimental data that would also undermine the ability of MR to correct for endogeneity bias from nongenetic sources. Here, we propose an alternative approach, genetic instrumental variable (GIV) regression, that provides estimates for the effect of an exposure on an outcome in the presence of pleiotropy. As a valuable byproduct, GIV regression also provides accurate estimates of the chip heritability of the outcome variable. GIV regression uses polygenic scores (PGSs) for the outcome of interest which can be constructed from genome-wide association study (GWAS) results. By splitting the GWAS sample for the outcome into nonoverlapping subsamples, we obtain multiple indicators of the outcome PGSs that can be used as instruments for each other and, in combination with other methods such as sibling fixed effects, can address endogeneity bias from both pleiotropy and the environment. In two empirical applications, we demonstrate that our approach produces reasonable estimates of the chip heritability of educational attainment (EA) and show that standard regression and MR provide upwardly biased estimates of the effect of body height on EA.


Assuntos
Pleiotropia Genética , Variação Genética , Estudo de Associação Genômica Ampla , Fatores Socioeconômicos , Estatura/fisiologia , Escolaridade , Estudo de Associação Genômica Ampla/normas , Estudo de Associação Genômica Ampla/estatística & dados numéricos , Humanos , Avaliação de Resultados (Cuidados de Saúde)
18.
Genetics ; 209(2): 389-400, 2018 06.
Artigo em Inglês | MEDLINE | ID: mdl-29588288

RESUMO

High-throughput sequencing methods that multiplex a large number of individuals have provided a cost-effective approach for discovering genome-wide genetic variation in large populations. These sequencing methods are increasingly being utilized in population genetic studies across a diverse range of species. Two side-effects of these methods, however, are (1) sequencing errors and (2) heterozygous genotypes called as homozygous due to only one allele at a particular locus being sequenced, which occurs when the sequencing depth is insufficient. Both of these errors have a profound effect on the estimation of linkage disequilibrium (LD) and, if not taken into account, lead to inaccurate estimates. We developed a new likelihood method, GUS-LD, to estimate pairwise linkage disequilibrium using low coverage sequencing data that accounts for undercalled heterozygous genotypes and sequencing errors. Our findings show that accurate estimates were obtained using GUS-LD, whereas underestimation of LD results if no adjustment is made for the errors.


Assuntos
Algoritmos , Estudo de Associação Genômica Ampla/métodos , Desequilíbrio de Ligação , Análise de Sequência de DNA/normas , Animais , Confiabilidade dos Dados , Cervos/genética , Estudo de Associação Genômica Ampla/normas , Genótipo , Heterozigoto
19.
Genome Biol ; 19(1): 21, 2018 02 15.
Artigo em Inglês | MEDLINE | ID: mdl-29448949

RESUMO

The accurate description of ancestry is essential to interpret, access, and integrate human genomics data, and to ensure that these benefit individuals from all ancestral backgrounds. However, there are no established guidelines for the representation of ancestry information. Here we describe a framework for the accurate and standardized description of sample ancestry, and validate it by application to the NHGRI-EBI GWAS Catalog. We confirm known biases and gaps in diversity, and find that African and Hispanic or Latin American ancestry populations contribute a disproportionately high number of associations. It is our hope that widespread adoption of this framework will lead to improved analysis, interpretation, and integration of human genomics data.


Assuntos
Estudo de Associação Genômica Ampla/normas , Genômica/normas , Grupos de Populações Continentais , Variação Genética , Humanos
20.
Sci Rep ; 8(1): 220, 2018 01 09.
Artigo em Inglês | MEDLINE | ID: mdl-29317680

RESUMO

Performance of a recently developed test for association between multivariate phenotypes and sets of genetic variants (MURAT) is demonstrated using measures of bone mineral density (BMD). By combining individual-level whole genome sequenced data from the UK10K study, and imputed genome-wide genetic data on individuals from the Study of Osteoporotic Fractures (SOF) and the Osteoporotic Fractures in Men Study (MrOS), a data set of 8810 individuals was assembled; tests of association were performed between autosomal gene-sets of genetic variants and BMD measured at lumbar spine and femoral neck. Distributions of p-values obtained from analyses of a single BMD phenotype are compared to those from the multivariate tests, across several region definitions and variant weightings. There is evidence of increased power with the multivariate test, although no new loci for BMD were identified. Among 17 genes highlighted either because there were significant p-values in region-based association tests or because they were in well-known BMD genes, 4 windows in 2 genes as well as 6 single SNPs in one of these genes showed association at genome-wide significant thresholds with the multivariate phenotype test but not with the single-phenotype test, Sequence Kernel Association Test (SKAT).


Assuntos
Densidade Óssea/genética , Estudo de Associação Genômica Ampla/normas , Fraturas por Osteoporose/genética , Polimorfismo de Nucleotídeo Único , Idoso , Exoma , Feminino , Colo do Fêmur/patologia , Estudo de Associação Genômica Ampla/métodos , Humanos , Vértebras Lombares/patologia , Masculino , Fraturas por Osteoporose/patologia , Fenótipo
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