Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 25
Filtrar
Mais filtros










Base de dados
Intervalo de ano de publicação
1.
Sci Adv ; 5(8): eaaw3538, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31453325

RESUMO

Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10-9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

2.
Nat Commun ; 10(1): 3009, 2019 07 08.
Artigo em Inglês | MEDLINE | ID: mdl-31285442

RESUMO

Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a sample of more than 450,000 individuals from the UK Biobank and 1600 gene expression traits from a sample of 2000 individuals as well as across-tissue gene expression from the GTEx resource. We find approximately twice as much X-linked genetic variation across the UK Biobank traits in males (mean h2SNP = 0.63%) compared to females (mean h2SNP = 0.30%), confirming the predicted DC effect. Our DC estimates for complex traits and gene expression are consistent with a small proportion of genes escaping X-inactivation in a trait- and tissue-dependent manner. Finally, we highlight examples of biologically relevant X-linked heterogeneity between the sexes that bias DC estimates if unaccounted for.


Assuntos
Genes Ligados ao Cromossomo X/genética , Loci Gênicos/genética , Variação Genética/genética , Herança Multifatorial/genética , Inativação do Cromossomo X/genética , Conjuntos de Dados como Assunto , Feminino , Estudo de Associação Genômica Ampla , Humanos , Masculino , Modelos Genéticos , Fenótipo , Fatores Sexuais
3.
Nat Commun ; 10(1): 1891, 2019 04 23.
Artigo em Inglês | MEDLINE | ID: mdl-31015401

RESUMO

Genome-wide association studies (GWASs) of medication use may contribute to understanding of disease etiology, could generate new leads relevant for drug discovery and can be used to quantify future risk of medication taking. Here, we conduct GWASs of self-reported medication use from 23 medication categories in approximately 320,000 individuals from the UK Biobank. A total of 505 independent genetic loci that meet stringent criteria (P < 10-8/23) for statistical significance are identified. We investigate the implications of these GWAS findings in relation to biological mechanism, potential drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes are 16 known therapeutic-effect target genes for medications from 9 categories. Two of the medication classes studied are for disorders that have not previously been subject to large GWAS (hypothyroidism and gastro-oesophageal reflux disease).


Assuntos
Uso de Medicamentos/estatística & dados numéricos , Genoma Humano , Estudo de Associação Genômica Ampla , Testes Farmacogenômicos/estatística & dados numéricos , Medicamentos sob Prescrição/uso terapêutico , Idoso , Bancos de Espécimes Biológicos , Doenças Cardiovasculares/tratamento farmacológico , Doenças Cardiovasculares/genética , Doenças Cardiovasculares/fisiopatologia , Bases de Dados Factuais , Feminino , Gastroenteropatias/tratamento farmacológico , Gastroenteropatias/genética , Gastroenteropatias/fisiopatologia , Loci Gênicos , Humanos , Masculino , Transtornos Mentais/tratamento farmacológico , Transtornos Mentais/genética , Transtornos Mentais/fisiopatologia , Pessoa de Meia-Idade , Doenças Musculoesqueléticas/tratamento farmacológico , Doenças Musculoesqueléticas/genética , Doenças Musculoesqueléticas/fisiopatologia , Autoadministração , Autorrelato , Reino Unido
4.
Genetics ; 211(4): 1131-1141, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30967442

RESUMO

In this Review, we focus on the similarity of the concepts underlying prediction of estimated breeding values (EBVs) in livestock and polygenic risk scores (PRS) in humans. Our research spans both fields and so we recognize factors that are very obvious for those in one field, but less so for those in the other. Differences in family size between species is the wedge that drives the different viewpoints and approaches. Large family size achievable in nonhuman species accompanied by selection generates a smaller effective population size, increased linkage disequilibrium and a higher average genetic relationship between individuals within a population. In human genetic analyses, we select individuals unrelated in the classical sense (coefficient of relationship <0.05) to estimate heritability captured by common SNPs. In livestock data, all animals within a breed are to some extent "related," and so it is not possible to select unrelated individuals and retain a data set of sufficient size to analyze. These differences directly or indirectly impact the way data analyses are undertaken. In livestock, genetic segregation variance exposed through samplings of parental genomes within families is directly observable and taken for granted. In humans, this genomic variation is under-recognized for its contribution to variation in polygenic risk of common disease, in both those with and without family history of disease. We explore the equation that predicts the expected proportion of variance explained using PRS, and quantify how GWAS sample size is the key factor for maximizing accuracy of prediction in both humans and livestock. Last, we bring together the concepts discussed to address some frequently asked questions.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Gado/genética , Herança Multifatorial , Característica Quantitativa Herdável , Animais , Big Data , Cruzamento/métodos , Humanos
5.
Am J Med Genet B Neuropsychiatr Genet ; 180(6): 439-447, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30708398

RESUMO

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

6.
Nat Commun ; 9(1): 5407, 2018 12 20.
Artigo em Inglês | MEDLINE | ID: mdl-30573740

RESUMO

Male pattern baldness (MPB) is a sex-limited, age-related, complex trait. We study MPB genetics in 205,327 European males from the UK Biobank. Here we show that MPB is strongly heritable and polygenic, with pedigree-heritability of 0.62 (SE = 0.03) estimated from close relatives, and SNP-heritability of 0.39 (SE = 0.01) from conventionally-unrelated males. We detect 624 near-independent genome-wide loci, contributing SNP-heritability of 0.25 (SE = 0.01), of which 26 X-chromosome loci explain 11.6%. Autosomal genetic variance is enriched for common variants and regions of lower linkage disequilibrium. We identify plausible genetic correlations between MPB and multiple sex-limited markers of earlier puberty, increased bone mineral density (rg = 0.15) and pancreatic ß-cell function (rg = 0.12). Correlations with reproductive traits imply an effect on fitness, consistent with an estimated linear selection gradient of -0.018 per MPB standard deviation. Overall, we provide genetic insights into MPB: a phenotype of interest in its own right, with value as a model sex-limited, complex trait.


Assuntos
Alopecia/genética , Pleiotropia Genética , Variação Genética , Fatores Etários , Densidade Óssea , Humanos , Desequilíbrio de Ligação , Polimorfismo de Nucleotídeo Único , Reino Unido
7.
Cancer ; 124(21): 4121-4129, 2018 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-30359468

RESUMO

BACKGROUND: It has been demonstrated that fecal immunochemical test (FIT) mailing programs are effective for increasing colorectal cancer (CRC) screening. The objectives of the current study were to assess the magnitude of uptake that could be achieved with a mailed FIT program in a federally qualified health center and whether such a program can be implemented at a reasonable cost to support sustainability. METHODS: The Washington State Department of Health's partner HealthPoint implemented a direct-mail FIT program at 9 medical clinics, along with a follow-up reminder letter and automated telephone calls to those not up-to-date with recommended screening. Supplemental outreach events at selected medical clinics and a 50th birthday card screening reminder program also were implemented. The authors collected and analyzed process, effectiveness, and cost measures and conducted a systematic assessment of the short-term cost effectiveness of the interventions. RESULTS: Overall, 5178 FIT kits were mailed with 4009 follow-up reminder letters, and 8454 automated reminder telephone calls were made over 12 months. In total, 1607 FIT kits were returned within 3 months of the end of the implementation period: an overall return rate of 31% for the mailed FIT program. The average total intervention cost per FIT kit returned was $39.81, and the intervention implementation cost per kit returned was $18.76. CONCLUSIONS: The mailed FIT intervention improved CRC screening uptake among HealthPoint's patient population. This intervention was implemented for less than $40 per individual successfully screened. The findings and lessons learned can assist other clinics that serve disadvantaged populations to increase their CRC screening adherence.

8.
Hum Mol Genet ; 27(20): 3641-3649, 2018 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-30124842

RESUMO

Recent genome-wide association studies (GWAS) of height and body mass index (BMI) in ∼250000 European participants have led to the discovery of ∼700 and ∼100 nearly independent single nucleotide polymorphisms (SNPs) associated with these traits, respectively. Here we combine summary statistics from those two studies with GWAS of height and BMI performed in ∼450000 UK Biobank participants of European ancestry. Overall, our combined GWAS meta-analysis reaches N âˆ¼700000 individuals and substantially increases the number of GWAS signals associated with these traits. We identified 3290 and 941 near-independent SNPs associated with height and BMI, respectively (at a revised genome-wide significance threshold of P < 1 × 10-8), including 1185 height-associated SNPs and 751 BMI-associated SNPs located within loci not previously identified by these two GWAS. The near-independent genome-wide significant SNPs explain ∼24.6% of the variance of height and ∼6.0% of the variance of BMI in an independent sample from the Health and Retirement Study (HRS). Correlations between polygenic scores based upon these SNPs with actual height and BMI in HRS participants were ∼0.44 and ∼0.22, respectively. From analyses of integrating GWAS and expression quantitative trait loci (eQTL) data by summary-data-based Mendelian randomization, we identified an enrichment of eQTLs among lead height and BMI signals, prioritizing 610 and 138 genes, respectively. Our study demonstrates that, as previously predicted, increasing GWAS sample sizes continues to deliver, by the discovery of new loci, increasing prediction accuracy and providing additional data to achieve deeper insight into complex trait biology. All summary statistics are made available for follow-up studies.

9.
Nat Genet ; 50(8): 1112-1121, 2018 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-30038396

RESUMO

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

10.
Nat Commun ; 9(1): 2941, 2018 07 27.
Artigo em Inglês | MEDLINE | ID: mdl-30054458

RESUMO

Type 2 diabetes (T2D) is a very common disease in humans. Here we conduct a meta-analysis of genome-wide association studies (GWAS) with ~16 million genetic variants in 62,892 T2D cases and 596,424 controls of European ancestry. We identify 139 common and 4 rare variants associated with T2D, 42 of which (39 common and 3 rare variants) are independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2765) with the GWAS results identifies 33 putative functional genes for T2D, 3 of which were targeted by approved drugs. A further integration of DNA methylation (n = 1980) and epigenomic annotation data highlight 3 genes (CAMK1D, TP53INP1, and ATP5G1) with plausible regulatory mechanisms, whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. Our study uncovers additional loci, proposes putative genetic regulatory mechanisms for T2D, and provides evidence of purifying selection for T2D-associated variants.

11.
JAMA Psychiatry ; 75(9): 901-910, 2018 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-29936532

RESUMO

Importance: Urban life has been proposed as an environmental risk factor accounting for the increased prevalence of schizophrenia in urban areas. An alternative hypothesis is that individuals with increased genetic risk tend to live in urban/dense areas. Objective: To assess whether adults with higher genetic risk for schizophrenia have an increased probability to live in more populated areas than those with lower risk. Design, Setting, and Participants: Four large, cross-sectional samples of genotyped individuals of European ancestry older than 18 years with known addresses in Australia, the United Kingdom, and the Netherlands were included in the analysis. Data were based on the postcode of residence at the time of last contact with the participants. Community-based samples who took part in studies conducted by the Queensland Institute for Medical Research Berghofer Medical Research Institute (QIMR), UK Biobank (UKB), Netherlands Twin Register (NTR), or QSkin Sun and Health Study (QSKIN) were included. Genome-wide association analysis and mendelian randomization (MR) were included. The study was conducted between 2016 and 2018. Exposures: Polygenic risk scores for schizophrenia derived from genetic data (genetic risk is independently measured from the occurrence of the disease). Socioeconomic status of the area was included as a moderator in some of the models. Main Outcomes and Measures: Population density of the place of residence of the participants determined from census data. Remoteness and socioeconomic status of the area were also tested. Results: The QIMR participants (15 544; 10 197 [65.6%] women; mean [SD] age, 54.4 [13.2] years) living in more densely populated areas (people per square kilometer) had a higher genetic loading for schizophrenia (r2 = 0.12%; P = 5.69 × 10-5), a result that was replicated across all 3 other cohorts (UKB: 345 246; 187 469 [54.3%] women; age, 65.7 [8.0] years; NTR: 11 212; 6727 [60.0%] women; age, 48.6 [17.5] years; and QSKIN: 15 726; 8602 [54.7%] women; age, 57.0 [7.9] years). This genetic association could account for 1.7% (95% CI, 0.8%-3.2%) of the schizophrenia risk. Estimates from MR analyses performed in the UKB sample were significant (b = 0.049; P = 3.7 × 10-7 using GSMR), suggesting that the genetic liability to schizophrenia may have a causal association with the tendency to live in urbanized locations. Conclusions and Relevance: The results of this study appear to support the hypothesis that individuals with increased genetic risk tend to live in urban/dense areas and suggest the need to refine the social stress model for schizophrenia by including genetics as well as possible gene-environment interactions.

12.
Genetics ; 209(3): 941-948, 2018 07.
Artigo em Inglês | MEDLINE | ID: mdl-29739817

RESUMO

Accurate estimation of genetic correlation requires large sample sizes and access to genetically informative data, which are not always available. Accordingly, phenotypic correlations are often assumed to reflect genotypic correlations in evolutionary biology. Cheverud's conjecture asserts that the use of phenotypic correlations as proxies for genetic correlations is appropriate. Empirical evidence of the conjecture has been found across plant and animal species, with results suggesting that there is indeed a robust relationship between the two. Here, we investigate the conjecture in human populations, an analysis made possible by recent developments in availability of human genomic data and computing resources. A sample of 108,035 British European individuals from the UK Biobank was split equally into discovery and replication datasets. Seventeen traits were selected based on sample size, distribution, and heritability. Genetic correlations were calculated using linkage disequilibrium score regression applied to the genome-wide association summary statistics of pairs of traits, and compared within and across datasets. Strong and significant correlations were found for the between-dataset comparison, suggesting that the genetic correlations from one independent sample were able to predict the phenotypic correlations from another independent sample within the same population. Designating the selected traits as morphological or nonmorphological indicated little difference in correlation. The results of this study support the existence of a relationship between genetic and phenotypic correlations in humans. This finding is of specific interest in anthropological studies, which use measured phenotypic correlations to make inferences about the genetics of ancient human populations.


Assuntos
Grupo com Ancestrais do Continente Europeu/genética , Estudo de Associação Genômica Ampla/métodos , Desequilíbrio de Ligação , Locos de Características Quantitativas , Antropologia , Evolução Biológica , Bancos de Espécimes Biológicos , Variação Genética , Genética Populacional , Genótipo , Humanos , Fenótipo , Reino Unido
13.
Genet Sel Evol ; 50(1): 10, 2018 03 24.
Artigo em Inglês | MEDLINE | ID: mdl-29571285

RESUMO

BACKGROUND: Genomic prediction and quantitative trait loci (QTL) mapping typically analyze one trait at a time but this may ignore the possibility that one polymorphism affects multiple traits. The aim of this study was to develop a multivariate Bayesian approach that could be used for simultaneously elucidating genetic architecture, QTL mapping, and genomic prediction. Our approach uses information from multiple traits to divide markers into 'unassociated' (no association with any trait) and 'associated' (associated with one or more traits). The effect of associated markers is estimated independently for each trait to avoid the assumption that QTL effects follow a multi-variate normal distribution. RESULTS: Using simulated data, our multivariate method (BayesMV) detected a larger number of true QTL (with a posterior probability > 0.9) and increased the accuracy of genomic prediction compared to an equivalent univariate method (BayesR). With real data, accuracies of genomic prediction in validation sets for milk yield traits with high-density genotypes were approximately equal to those from equivalent single-trait methods. BayesMV tended to select a similar number of single nucleotide polymorphisms (SNPs) per trait for genomic prediction compared to BayesR (i.e. those with non-zero effects), but BayesR selected different sets of SNPs for each trait, whereas BayesMV selected a common set of SNPs across traits. Despite these two dramatically different estimates of genetic architecture (i.e. different SNPs affecting each trait vs. pleiotropic SNPs), both models indicated that 3000 to 4000 SNPs are associated with a trait. The BayesMV approach may be advantageous when the aim is to develop a low-density SNP chip that works well for a number of traits. SNPs for milk yield traits identified by BayesMV and BayesR were also found to be associated with detailed milk composition. CONCLUSIONS: The BayesMV method simultaneously estimates the proportion of SNPs that are associated with a combination of traits. When applied to milk production traits, most of the identified SNPs were associated with all three traits (milk, fat and protein yield). BayesMV aims at exploiting pleiotropic QTL and selects a small number of SNPs that could be used to predict multiple traits.


Assuntos
Mapeamento Cromossômico/veterinária , Genômica/métodos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Algoritmos , Animais , Teorema de Bayes , Bovinos , Simulação por Computador , Feminino , Leite , Modelos Genéticos
14.
Nat Hum Behav ; 2(12): 948-954, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30988446

RESUMO

Preference for mates with similar phenotypes; that is, assortative mating, is widely observed in humans1-5 and has evolutionary consequences6-8. Under Fisher's classical theory6, assortative mating is predicted to induce a signature in the genome at trait-associated loci that can be detected and quantified. Here, we develop and apply a method to quantify assortative mating on a specific trait by estimating the correlation (θ) between genetic predictors of the trait from single nucleotide polymorphisms on odd- versus even-numbered chromosomes. We show by theory and simulation that the effect of assortative mating can be quantified in the presence of population stratification. We applied this approach to 32 complex traits and diseases using single nucleotide polymorphism data from ~400,000 unrelated individuals of European ancestry. We found significant evidence of assortative mating for height (θ = 3.2%) and educational attainment (θ = 2.7%), both of which were consistent with theoretical predictions. Overall, our results imply that assortative mating involves multiple traits and affects the genomic architecture of loci that are associated with these traits, and that the consequence of mate choice can be detected from a random sample of genomes.


Assuntos
Genoma Humano , Casamento , Alelos , Estatura/genética , Escolaridade , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Genoma Humano/genética , Humanos , Masculino , Polimorfismo de Nucleotídeo Único/genética , Característica Quantitativa Herdável
15.
Mamm Genome ; 27(1-2): 81-97, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26613780

RESUMO

Dairy cattle are an interesting model for gaining insights into the genes responsible for the large variation between and within mammalian species in the protein and fat content of their milk and their milk volume. Large numbers of phenotypes for these traits are available, as well as full genome sequence of key founders of modern dairy cattle populations. In twenty target QTL regions affecting milk production traits, we imputed full genome sequence variant genotypes into a population of 16,721 Holstein and Jersey cattle with excellent phenotypes. Association testing was used to identify variants within each target region, and gene expression data were used to identify possible gene candidates. There was statistical support for imputed sequence variants in or close to BTRC, MGST1, SLC37A1, STAT5A, STAT5B, PAEP, VDR, CSF2RB, MUC1, NCF4, and GHDC associated with milk production, and EPGN for calving interval. Of these candidates, analysis of RNA-Seq data demonstrated that PAEP, VDR, SLC37A1, GHDC, MUC1, CSF2RB, and STAT5A were highly differentially expressed in mammary gland compared to 15 other tissues. For nine of the other target regions, the most significant variants were in non-coding DNA. Genomic predictions in a third dairy breed (Australian Reds) using sequence variants in only these candidate genes were for some traits more accurate than genomic predictions from 632,003 common SNP on the Bovine HD array. The genes identified in this study are interesting candidates for improving milk production in cattle and could be investigated for novel biological mechanisms driving lactation traits in other mammals.


Assuntos
Cromossomos de Mamíferos/química , Indústria de Laticínios , Lactação/genética , Leite/metabolismo , Locos de Características Quantitativas , Característica Quantitativa Herdável , Animais , Cruzamento , Bovinos , Mapeamento Cromossômico , Gorduras na Dieta/metabolismo , Feminino , Estudo de Associação Genômica Ampla , Genótipo , Glândulas Mamárias Animais/anatomia & histologia , Glândulas Mamárias Animais/metabolismo , Análise em Microsséries , Leite/química , Fenótipo , Polimorfismo de Nucleotídeo Único
16.
Biol Reprod ; 94(1): 19, 2016 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-26607721

RESUMO

Despite the importance of fertility in humans and livestock, there has been little success dissecting the genetic basis of fertility. Our hypothesis was that genes differentially expressed in the endometrium and corpus luteum on Day 13 of the estrous cycle between cows with either good or poor genetic merit for fertility would be enriched for genetic variants associated with fertility. We combined a unique genetic model of fertility (cattle that have been selected for high and low fertility and show substantial difference in fertility) with gene expression data from these cattle and genome-wide association study (GWAS) results in ∼20,000 cattle to identify quantitative trait loci (QTL) regions and sequence variants associated with genetic variation in fertility. Two hundred and forty-five QTL regions and 17 sequence variants associated primarily with prostaglandin F2alpha, steroidogenesis, mRNA processing, energy status, and immune-related processes were identified. Ninety-three of the QTL regions were validated by two independent GWAS, with signals for fertility detected primarily on chromosomes 18, 5, 7, 8, and 29. Plausible causative mutations were identified, including one missense variant significantly associated with fertility and predicted to affect the protein function of EIF4EBP3. The results of this study enhance our understanding of 1) the contribution of the endometrium and corpus luteum transcriptome to phenotypic fertility differences and 2) the genetic architecture of fertility in dairy cattle. Including these variants in predictions of genomic breeding values may improve the rate of genetic gain for this critical trait.


Assuntos
Corpo Lúteo/metabolismo , Fertilidade/genética , Fertilidade/fisiologia , Expressão Gênica/genética , Variação Genética/genética , Variação Genética/fisiologia , Animais , Bovinos , Cromossomos/genética , Dinoprosta/biossíntese , Dinoprosta/genética , Endométrio/metabolismo , Endométrio/fisiologia , Fator de Iniciação 4F em Eucariotos/metabolismo , Feminino , Estudo de Associação Genômica Ampla , Locos de Características Quantitativas , RNA Mensageiro/biossíntese , RNA Mensageiro/genética , Transcriptoma
17.
Genet Sel Evol ; 47: 34, 2015 Apr 30.
Artigo em Inglês | MEDLINE | ID: mdl-25926276

RESUMO

BACKGROUND: Genomic prediction of breeding values from dense single nucleotide polymorphisms (SNP) genotypes is used for livestock and crop breeding, and can also be used to predict disease risk in humans. For some traits, the most accurate genomic predictions are achieved with non-linear estimates of SNP effects from Bayesian methods that treat SNP effects as random effects from a heavy tailed prior distribution. These Bayesian methods are usually implemented via Markov chain Monte Carlo (MCMC) schemes to sample from the posterior distribution of SNP effects, which is computationally expensive. Our aim was to develop an efficient expectation-maximisation algorithm (emBayesR) that gives similar estimates of SNP effects and accuracies of genomic prediction than the MCMC implementation of BayesR (a Bayesian method for genomic prediction), but with greatly reduced computation time. METHODS: emBayesR is an approximate EM algorithm that retains the BayesR model assumption with SNP effects sampled from a mixture of normal distributions with increasing variance. emBayesR differs from other proposed non-MCMC implementations of Bayesian methods for genomic prediction in that it estimates the effect of each SNP while allowing for the error associated with estimation of all other SNP effects. emBayesR was compared to BayesR using simulated data, and real dairy cattle data with 632 003 SNPs genotyped, to determine if the MCMC and the expectation-maximisation approaches give similar accuracies of genomic prediction. RESULTS: We were able to demonstrate that allowing for the error associated with estimation of other SNP effects when estimating the effect of each SNP in emBayesR improved the accuracy of genomic prediction over emBayesR without including this error correction, with both simulated and real data. When averaged over nine dairy traits, the accuracy of genomic prediction with emBayesR was only 0.5% lower than that from BayesR. However, emBayesR reduced computing time up to 8-fold compared to BayesR. CONCLUSIONS: The emBayesR algorithm described here achieved similar accuracies of genomic prediction to BayesR for a range of simulated and real 630 K dairy SNP data. emBayesR needs less computing time than BayesR, which will allow it to be applied to larger datasets.


Assuntos
Algoritmos , Cruzamento , Genômica/métodos , Animais , Teorema de Bayes , Bovinos , Masculino , Modelos Genéticos , Modelos Estatísticos , Polimorfismo de Nucleotídeo Único
18.
Genet Sel Evol ; 47: 29, 2015 Apr 17.
Artigo em Inglês | MEDLINE | ID: mdl-25887988

RESUMO

BACKGROUND: Genomic selection is increasingly widely practised, particularly in dairy cattle. However, the accuracy of current predictions using GBLUP (genomic best linear unbiased prediction) decays rapidly across generations, and also as selection candidates become less related to the reference population. This is likely caused by the effects of causative mutations being dispersed across many SNPs (single nucleotide polymorphisms) that span large genomic intervals. In this paper, we hypothesise that the use of a nonlinear method (BayesR), combined with a multi-breed (Holstein/Jersey) reference population will map causative mutations with more precision than GBLUP and this, in turn, will increase the accuracy of genomic predictions for selection candidates that are less related to the reference animals. RESULTS: BayesR improved the across-breed prediction accuracy for Australian Red dairy cattle for five milk yield and composition traits by an average of 7% over the GBLUP approach (Australian Red animals were not included in the reference population). Using the multi-breed reference population with BayesR improved accuracy of prediction in Australian Red cattle by 2 - 5% compared to using BayesR with a single breed reference population. Inclusion of 8478 Holstein and 3917 Jersey cows in the reference population improved accuracy of predictions for these breeds by 4 and 5%. However, predictions for Holstein and Jersey cattle were similar using within-breed and multi-breed reference populations. We propose that the improvement in across-breed prediction achieved by BayesR with the multi-breed reference population is due to more precise mapping of quantitative trait loci (QTL), which was demonstrated for several regions. New candidate genes with functional links to milk synthesis were identified using differential gene expression in the mammary gland. CONCLUSIONS: QTL detection and genomic prediction are usually considered independently but persistence of genomic prediction accuracies across breeds requires accurate estimation of QTL effects. We show that accuracy of across-breed genomic predictions was higher with BayesR than with GBLUP and that BayesR mapped QTL more precisely. Further improvements of across-breed accuracy of genomic predictions and QTL mapping could be achieved by increasing the size of the reference population, including more breeds, and possibly by exploiting pleiotropic effects to improve mapping efficiency for QTL with small effects.


Assuntos
Bovinos/genética , Genômica/métodos , Locos de Características Quantitativas , Animais , Teorema de Bayes , Cruzamento , Mapeamento Cromossômico , Fenótipo
19.
BMC Genomics ; 15: 246, 2014 Mar 28.
Artigo em Inglês | MEDLINE | ID: mdl-24678841

RESUMO

BACKGROUND: Selection signatures aim to identify genomic regions underlying recent adaptations in populations. However, the effects of selection in the genome are difficult to distinguish from random processes, such as genetic drift. Often associations between selection signatures and selected variants for complex traits is assumed even though this is rarely (if ever) tested. In this paper, we use 8 breeds of domestic cattle under strong artificial selection to investigate if selection signatures are co-located in genomic regions which are likely to be under selection. RESULTS: Our approaches to identify selection signatures (haplotype heterozygosity, integrated haplotype score and FST) identified strong and recent selection near many loci with mutations affecting simple traits under strong selection, such as coat colour. However, there was little evidence for a genome-wide association between strong selection signatures and regions affecting complex traits under selection, such as milk yield in dairy cattle. Even identifying selection signatures near some major loci was hindered by factors including allelic heterogeneity, selection for ancestral alleles and interactions with nearby selected loci. CONCLUSIONS: Selection signatures detect loci with large effects under strong selection. However, the methodology is often assumed to also detect loci affecting complex traits where the selection pressure at an individual locus is weak. We present empirical evidence to suggests little discernible 'selection signature' for complex traits in the genome of dairy cattle despite very strong and recent artificial selection.


Assuntos
Herança Multifatorial , Característica Quantitativa Herdável , Seleção Genética , Animais , Cruzamento , Bovinos , Estudos de Associação Genética , Genoma , Estudo de Associação Genômica Ampla , Genômica , Haplótipos , Homozigoto , Leite , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas
20.
Genet Sel Evol ; 45: 43, 2013 Oct 29.
Artigo em Inglês | MEDLINE | ID: mdl-24168700

RESUMO

BACKGROUND: The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor. METHODS: Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin. RESULTS: Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies. CONCLUSIONS: The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.


Assuntos
Bovinos/classificação , Bovinos/genética , Estudo de Associação Genômica Ampla/métodos , Locos de Características Quantitativas , Alelos , Animais , Peso Corporal/genética , Cruzamento , Cromossomos , Frequência do Gene , Variação Genética , Genoma , Genótipo , Crescimento/genética , Haplótipos , Fenótipo , Polimorfismo de Nucleotídeo Único , Seleção Genética , Especificidade da Espécie
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA