CONTRIBUTION TO LINKAGE AND ASSOCIATION MAPPING OF TRAIT LOCI IN LIVESTOCK.

Until recently, breeding values were estimated based on phenotypes measured on the individual and its relatives, and the notion that the covariance between breeding values is proportionate to the kinship coefficient. Advances in genomics now allow for direct analysis of the genome and identification of the loci that determine the breeding values of individuals. As a consequence, marker assisted selection and genomic selection have become more effective and are replacing conventional selection. The identification of loci influencing the traits of interest requires the use of advanced statistical methods that are constantly evolving. In the context of this thesis, we have (i) contributed to the development of gene mapping methods, (ii) applied these methods to map loci influencing both metric and meristic traits, and (iii) contributed to the development of methods for the integration of genomic information in livestock breeding and management. The mapping methods that we have helped developing distinguish themselves mainly by the fact that (i) they exploit haplotype information (by means of a hidden markov model) which should increase the linkage disequilibrium with causative variants and hence detection power, (ii) they can simultaneously extract linkage information within families, and linkage disequilibrium information across the population, and (iii) they correct for population stratification by means of a random polygenic effect, and (iv) they can be applied to binary as well as quantitative traits. We have applied these and other methods to map loci influencing (i) quantitative hematological parameters in a porcine line-cross, and (ii) binary traits including diseases in bovine and non-syntenic Copy Number Variants in cattle, horse and human. In fine, we have contributed to the development of methods for the utilization of marker information in animal selection and production. We have extended the haplotype-based mapping method to allow imputation and have evaluated the utility of this approach in scenarios mimicking reality. We have also contributed to the development of a method to quantify somatic cell counts in the milk of individual cows by genotyping a sample of milk from the farm’s tank (hence a mixture of milk from all cows on the farm) Our work has resulted in the development of a software package (“GLASCOW”) that is increasingly used by the community to map genes influencing complex traits, primarily binary. By using this tool, we have contributed to the localization of several trait loci in pig, cattle, horse and human. We have contributed to the development of approaches that reduce the costs of genomic analyses in livestock by, on the one hand, complementing real SNP genotypes with genotypes obtained in silico by means imputation, and, on the other hand, by developing a method to deconvolute genotypes obtained on DNA pools

Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well

Mapping genes underlying ethnic differences in tuberculosis risk by linkage disequilibrium in the South African coloured population of the Western Cape

Includes bibliographical references.The South Africa Coloured population of the Western Cape is the result of unions between Europeans, Africans (Bantu and Khoisan), and various other populations (Malaysian or Indonesian descent). The world-wide burden of tuberculosis remains an enormous problem, and is particularly severe in this population. In general, admixed populations that have arisen in historical times can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Despite numerous successful genome-wide association studies, detecting variants that have low disease risk still poses a challenge. Furthermore, admixture association studies for multi-way admixed populations pose constant challenges, including the choice of an accurate ancestral panel to infer ancestry and for imputing missing genotypes to identify possible genetic variants causing susceptibility to disease. This thesis addresses some of these challenges. We first developed PROXYANC, an approach to select the best proxy ancestral populations for admixed populations. From the simulation of a multi-way admixed population, we demonstrated the ability and accuracy of PROXYANC in selecting the best proxy ancestry and illustrated the importance of the choice of ancestries in both estimating admixture proportions and imputing missing genotypes. We applied this approach to the South African Coloured population, to refine both the choice of ancestral populations and their genetic contributions. We also demonstrated that the ancestral allele frequency differences correlated with increased linkage disequilibrium in the SAC, and that the increased LD originates from admixture events rather than population bottlenecks. Secondly, we conducted a study to determine whether ancestry-specific genetic contributions affect tuberculosis risk. We additionally conducted imputation genome-wide association studies and a meta-analysis incorporating previous genome-wide association studies of tuberculosis

Polygenicity and Epistasis Underlie Fitness-Proximal Traits in the Caenorhabditis elegans Multiparental Experimental Evolution (CeMEE) Panel

The deposited article is a pre-print version and it has not been submitted to peer reviewing. This article version was provided by bioRxiv and is the preprint first posted online Mar. 26, 2017. This publication hasn't any creative commons license associated. The deposited article version contains attached the supplementary materials within the pdf.Understanding the genetic basis of complex traits remains a major challenge in biology. Polygenicity, phenotypic plasticity and epistasis contribute to phenotypic variance in ways that are rarely clear. This uncertainty can be problematic for estimating heritability, for predicting individual phenotypes from genomic data, and for parameterizing models of phenotypic evolution. Here we report an advanced recombinant inbred line (RIL) quantitative trait locus (QTL) mapping panel for the hermaphroditic nematode Caenorhabditis elegans, the C. elegans multiparental experimental evolution (CeMEE) panel. The CeMEE panel, comprising 507 RILs at present, was created by hybridization of 16 wild isolates, experimental evolution for 140-190 generations, and inbreeding by selfing for 13-16 generations. The panel contains 22% of single nucleotide polymorphisms known to segregate in natural populations, and complements existing C. elegans mapping resources by providing fine resolution and high nucleotide diversity across >95% of the genome. We apply it to study the genetic basis of two fitness components, fertility and hermaphrodite body size at time of reproduction, with high broad sense heritability in the CeMEE. While simulations show we should detect common alleles with additive effects as small as 5%, at gene-level resolution, the genetic architectures of these traits does not feature such alleles. We instead find that a significant fraction of trait variance, approaching 40% for fertility, can be explained by sign epistasis with main effects below the detection limit. In congruence, phenotype prediction from genomic similarity, while generally poor (r2 < 10%), requires modeling epistasis for optimal accuracy, with most variance attributed to the rapidly evolving chromosome arms.National Science Foundation grant: (PHY-1125915); National Institutes of Health grants: (R25-GM-067110, R01-GM-089972, R01-GM-121828); Gordon and Betty Moore Foundation grant: (2919.01); Human Frontiers Science Program (RGP0045/2010); European Research Council grant: (FP7/2007-2013/243285); Agence Nationale de la Recherche grant: (ANR-14-ACHN-0032-01).info:eu-repo/semantics/publishedVersio

Genetic variation and health in rural Caribbean village

Bwa Mawego is a small-scale horticultural community (~500 people) on the island of Dominica that has been the site of a longitudinal health research project for more than 30 years. Cardiovascular diseases and metabolic health are growing local concerns. Here we analyze longitudinal growth data, cardiometabolic metrics, and genome-wide single nucleotide polymorphism (SNP) data from this population to investigate sources of variation in anthropometric and cardiometabolic outcomes. Mixed effect heritability models indicate that (1) variation in body mass index (BMI) is significantly shaped by genetic variation, and (2) variation between longitudinal BMI curves has not been consistently impacted by secular environmental trends from 1997 2017. In order to assess genetic variation in more detail, we first characterize the population structure and admixture in this Caribbean community using high-density SNP data and global reference samples in the Human Genome Diversity Panel. We detect four distinct family clusters and admixture from African, European, and Amerindian ancestral populations that occurred 5-6 generations ago (~130-150 years). Amerindian haplotypes represented in Bwa Mawego associate with deeply diverged lineages in Karitiana and Surui peoples, highlighting the regionally variable nature of admixture throughout the Caribbean and unique historical outcomes in Dominica. Genome-wide association tests of cardiometabolic phenotypes identify a genomic region of interest downstream of the ANK3 gene that associates with BMI in Bwa Mawego, after controlling for confounding variation from ancestral population structure and relatedness. Any functional relationship between ANK3 and BMI is currently uncharacterized, and there is unique potential to further explore complex gene-environment-phenotype landscapes in Bwa Mawego.Includes bibliographical reference

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations

전장유전체연관분석과 표현형 예측 연구를 위한 선형혼합모형

학위논문 (석사)-- 서울대학교 대학원 : 농업생명과학대학 농생명공학부, 2019. 2. 김희발.With the advance of sequencing and genotyping technologies, a large amount of genomic data has been accumulated and is available for biological studies. Along with the development of statistical models and computational capabilities, sizable genomic data can be analyzed thoroughly. Processing large genomic data via statistical computation enables discerning the relationship between genotypes and phenotypes. In this thesis, the main concern was how differences in genotypes are related to phenotypes. I conducted genome-wide association study to discover genetic variants correlated with phenotypes. Also, I constructed prediction models to precisely estimate phenotypes from genotypes. In the studies, various linear mixed models were applied to calculate the effects of genetic variants. In chapter 2, genome-wide association study on intramuscular fat content of pig was performed. Statistically significant single nucleotide polymorphisms were found and annotated to genes. Genes related to mitogen-activated protein kinase pathway were identified as candidate genes affecting the intramuscular fat content of pigs. In chapter 3, genomic prediction models using haplotype alleles were constructed. The models attempt to predict carcass weight in Hanwoo. Different haplotype defining methods were implemented and the prediction accuracies of them were compared. As a result, genomic prediction accuracy was higher when haplotype alleles were used compared to when individual SNPs were used. In chapter 4, models predicting human height from genotype were developed. I designed a genomic best linear unbiased prediction model adjusted with parental height. In addition, variables having highest effects on height were selected using bootstrap resampling. Models using only the selected variables were tested, and consequently I could obtain a model with high prediction ability. Through these studies, I could understand how linear mixed models can be applied to explain relationships between genotypic variation and phenotypic variation. The findings of this dissertation will help to extend the use of linear mixed models for understanding the genetic architectures in animals and human.염기서열분석과 유전형질분석 기술의 발전으로 생물학적 연구에 이용할 수 있는 많은 양의 데이터가 축적되었다. 뿐만 아니라 통계적 모형이 발달하고 큰 데이터를 계산하는 능력이 향상되면서 방대한 양의 유전정보에 대한 보다 정밀한 분석이 가능해졌다. 통계적 계산을 활용한 유전정보의 분석으로부터 유전형질과 표현형 간의 관계를 밝혀낼 수 있다. 본 졸업논문에서는 유전형질의 차이가 어떻게 표현형과 관련이 있는지를 주로 다루고 있다. 우선, 전장유전체연관분석을 통해 표현형과 연관성이 높은 유전 변이를 찾아내고자 하였다. 또한, 유전형질로부터 표현형을 정확하게 예측할 수 있는 모형을 개발하고자 하였다. 표현형에 대한 유전 변이들의 효과를 추정하기 위해서 다양한 선형혼합모형을 적용하였다. 2장에서는 돼지의 근내지방도에 대해서 전장유전체연관분석을 실시하였다. 이로부터 통계적으로 유의한 효과를 가지는 단일염기다형성들을 발견했고, 유의한 단일염기다형성이 포함되어 있거나 물리적으로 가까이 있는 유전자들을 찾아내었다. 찾아진 유전자들 중, 마이토겐 활성화 단백질 키나제 경로와 관련된 유전자들을 돼지의 근내지방도에 영향을 주는 후보 유전자들로 제시하였다. 3장에서는 한우의 유전자형으로부터 도체중을 예측하기 위해 반수체의 대립 형질을 이용한 유전체 예측을 진행하였다. 다양한 방법으로 반수체를 정의하였고, 이로부터 얻어진 대립 형질을 사용했을 때 유전체 예측의 정확도를 비교하였다. 이 때, 반수체를 이용하였을 때의 정확도가 개개의 단일염기다형성을 이용했을 때의 정확도보다 높게 나타났다. 4장에서는 사람의 유전자형으로부터 키를 예측하는 모형을 설계하였다. 예측 모형으로는 부모의 키로 보정된 최적선형불편추정 모형을 사용하였다. 더불어 부트스트랩 재추출을 활용하여 키에 미치는 영향이 큰 단일염기다형성을 선택하였다. 선택된 단일염기다형성만을 변수로 사용하는 모형을 검증한 결과, 예측력이 높게 나타났다. 위의 연구들을 통해 유전자형에서의 변이와 표현형에서의 변이 사이의 관계를 설명하기 위해 선형혼합모형을 어떻게 적용할 수 있는지 이해할 수 있었다. 연구에서 얻어진 결과는 동물과 사람의 유전적 구조를 이해하기 위한 선형혼합모형의 적용을 확장하는 것에 활용될 수 있다.Abstract ⅰ Table of Contents ⅳ List of Figures ⅵ List of Tables ⅷ Chapter 1. Literature Review 1 1.1 Linear Mixed Models 2 1.2 Genome-Wide Association Study 2 1.3 Genomic Prediction 7 Chapter 2. Identification of genes related to intramuscular fat content of pig using genome-wide association study 13 2.1 Abstract 14 2.2 Introduction 15 2.3 Materials and Method 17 2.4 Results 20 2.5 Discussion 26 Chapter 3. Genomic prediction accuracies using haplotypes defined by different methods in Hanwoo 53 3.1 Abstract 54 3.2 Introduction 56 3.3 Materials and Method 59 3.4 Results 64 3.5 Discussion 72 Chapter 4. A height prediction model using selected genetic markers and parental heights in Korean 75 2.1 Abstract 76 2.2 Introduction 77 2.3 Materials and Method 79 2.4 Results and Discussion 83 Reference 91 국문초록 99Maste