Linkage disequilibrium and the mapping of complex human traits

Identifying Regions of the Genome Associated with Conception Rate to the First Service in Holstein Heifers Bred by Artificial Insemination and as Embryo Transfer Recipients

Heifer conception rate to the first service (HCR1) is defined as the number of heifers that become pregnant to the first breeding service compared to the heifers bred. This study aimed to identify loci associated and gene sets enriched for HCR1 for heifers that were bred by artificial insemination (AI, n = 2829) or were embryo transfer (ET, n = 2086) recipients, by completing a genome-wide association analysis and gene set enrichment analysis using SNP data (GSEA-SNP). Three unique loci, containing four positional candidate genes, were associated (p < 1 × 10-5) with HCR1 for ET recipients, while the GSEA-SNP identified four gene sets (NES ≥ 3) and sixty-two leading edge genes (LEGs) enriched for HCR1. While no loci were associated with HCR1 bred by AI, one gene set and twelve LEGs were enriched (NES ≥ 3) for HCR1 with the GSEA-SNP. This included one gene (PKD2) shared between HCR1 AI and ET services. Identifying loci associated or enriched for HCR1 provides an opportunity to use them as genomic selection tools to facilitate the selection of cattle with higher reproductive efficiency, and to better understand embryonic loss.

LncEDCH1 g.1703613 T>C regulates chicken carcass traits by targeting miR-196-2-3p

Single nucleotide polymorphisms (SNPs) are valuable genetic markers that can provide insights into the genetic diversity and variation within chicken populations. In poultry breeding, SNP analysis is widely utilized to accelerate the selection of desirable traits, improving the efficiency and effectiveness of chicken breeding programs. In our previous research, we identified an association between LncEDCH1 and muscle development. To further investigate its specific mechanism, we conducted SNP detection and performed genotyping, linkage disequilibrium, and haplotype analysis. Our research findings indicate that 16 SNPs in the LncEDCH1. Among these SNPs, g.1703497 C>T and g.1704262 C>T were significantly associated with breast muscle weight percentage, g.1703497 C>T and g.1703613 T>C were significantly associated with leg weight percentage, and g.1703497 C>T, g.1703589 T>C, g.1703613 T>C, g.1703636 C>A, g.1703768 T>C, g.1704079 C>T, g.1704250 T>C, g.1704253 G>A were significantly associated with skin yellowness. Two haplotype blocks composed of 6 SNPs that were significantly associated with wing skin yellowness, breast skin yellowness, full-bore weight, and carcass weight percentage. Furthermore, through dual-luciferase reporter assays, biotin-coupled miRNA pull-down assays, 5-ethynyl-2'-deoxyuridine (EDU) assays, immunofluorescence, and quantitative real-time polymerase chain reaction (qPCR), it has been confirmed that miR-196-2-3p inhibits the expression of LncEDCH1 directly by binding to LncEDCH1 g.1703613T>C, thereby achieving indirect regulation of muscle development. These findings provide valuable molecular markers for chicken molecular breeding and broaden our understanding of the regulatory mechanisms.

Association between SLCO1B1 genetic polymorphisms and bleeding risk in patients treated with edoxaban

Since SLCO1B1 encodes the uptake transporter OATP1B1, which can influence the pharmacokinetic and pharmacodynamic profiles of edoxaban, polymorphisms in SLCO1B1 may affect the edoxaban response. This study aimed to investigate the association between SLCO1B1 gene polymorphisms and the bleeding risk in patients receiving edoxaban. We genotyped 10 single-nucleotide polymorphisms (SNPs) from the SLCO1B1 gene in patients receiving edoxaban. We also analyzed rs3842 of ABCB1 as a confounder. The odds ratio (OR) and adjusted OR (AOR) were calculated from univariate and multivariable analysis, respectively. The area under the receiver operating characteristic curve (AUROC) was constructed for the discrimination of the model. A total of 159 patients receiving edoxaban were analyzed. Overdose and rs4149056 showed significant association with bleeding complications by around 11- and 5.5-fold, respectively. Additionally, patients with the rs4149057 variant allele (C) had a 3.9-fold increased bleeding risk compared with wild-type homozygote carriers (TT), whereas rs2306283 variant homozygote (GG) carriers had a 0.27-fold reduced bleeding risk compared with wild-type allele (A) carriers. Patients with the variant-type homozygote (CC) of ABCB1 rs3842 had a higher bleeding risk than T allele carriers (AOR = 5.3 and 5.9). The final models for multivariable analyses were acceptable based on the AUROC values (> 0.70). These findings may help predict bleeding risk in patients taking edoxaban and help personalize treatment.

Mendelian Randomization Studies in Psoriasis and Psoriatic Arthritis: A Systematic Review

Psoriasis (PSO) and psoriatic arthritis (PSA) are inflammatory diseases with complex genetic and environmental contributions. Although studies have identified environmental and clinical associations with PSO/PSA, causality is difficult to establish. Mendelian randomization (MR) employs the random assortment of genetic alleles at birth to evaluate the causal impact of exposures. We systematically reviewed 27 MR studies in PSO/PSA examining health behaviors, comorbidities, and biomarkers. Exposures, including smoking, obesity, cardiovascular disease, and Crohn's disease, were causal for PSO and PSA, whereas PSO was causally associated with several comorbidities. These findings provide insights that can guide preventive counseling and precision medicine.

Scavenger receptor class B type I genetic variants associated with disease severity in chronic hepatitis C virus infection

Analysis of host genetic polymorphisms is an increasingly important tool for understanding and predicting pathogenesis and treatment response of viral diseases. The gene locus of scavenger receptor class B type I (SR-BI), encoding a cell entry factor and receptor for hepatitis C virus (HCV), contains several genetic polymorphisms. We applied a probe extension assay to determine the frequency of six single nucleotide polymorphisms (SNPs) within the SR-BI gene locus in 374 individuals with history of HCV infection. In addition, SR-BI messenger RNA (mRNA) levels were analyzed in liver biopsy specimens of chronically infected HCV subjects. The rs5888 variant allele T was present at a higher frequency in subjects with advanced fibrosis (χ² , p = 0.016) and after adjusting for age, duration of infection and alcohol intake as confounding factors. Haplotype analysis of SNP frequencies showed that a haplotype consisting of rs61932577 variant allele C and rs5888 variant allele T was associated with an increased risk of advanced liver fibrosis (defined by an Ishak score 4-6) (adjusted odds ratio 2.81; 95% confidence interval 1.06-7.46. p = 0.038). Carriers of the rs5888 variant allele T displayed reduced SR-BI mRNA expression in liver biopsy specimens. In conclusion the rs5888 polymorphism variant is associated with decreased SR-BI expression and an increased risk of development of advanced fibrosis in chronic HCV infection. These findings provide further evidence for a role of SR-BI in HCV pathogenesis and provides a genetic marker for prediction of those infected individuals at greater risk of developing severe disease.

Induced Pluripotent Stem Cells and Genome-Editing Tools in Determining Gene Function and Therapy for Inherited Retinal Disorders

Inherited retinal disorders (IRDs) affect millions of people worldwide and are a major cause of irreversible blindness. Therapies based on drugs, gene augmentation or transplantation approaches have been widely investigated and proposed. Among gene therapies for retinal degenerative diseases, the fast-evolving genome-editing CRISPR/Cas technology has emerged as a new potential treatment. The CRISPR/Cas system has been developed as a powerful genome-editing tool in ophthalmic studies and has been applied not only to gain proof of principle for gene therapies in vivo, but has also been extensively used in basic research to model diseases-in-a-dish. Indeed, the CRISPR/Cas technology has been exploited to genetically modify human induced pluripotent stem cells (iPSCs) to model retinal disorders in vitro, to test in vitro drugs and therapies and to provide a cell source for autologous transplantation. In this review, we will focus on the technological advances in iPSC-based cellular reprogramming and gene editing technologies to create human in vitro models that accurately recapitulate IRD mechanisms towards the development of treatments for retinal degenerative diseases.

A review of Mendelian randomization in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a relatively common and rapidly progressive neurodegenerative disease that, in the majority of cases, is thought to be determined by a complex gene-environment interaction. Exponential growth in the number of performed genome-wide association studies combined with the advent of Mendelian randomization is opening significant new opportunities to identify environmental exposures that increase or decrease the risk of amyotrophic lateral sclerosis. Each of these discoveries has the potential to shape new therapeutic interventions. However, to do so, rigorous methodological standards must be applied in the performance of Mendelian randomization. We have reviewed Mendelian randomization studies performed in amyotrophic lateral sclerosis to date. We identified 20 Mendelian randomization studies, including evaluation of physical exercise, adiposity, cognitive performance, immune function, blood lipids, sleep behaviours, educational attainment, alcohol consumption, smoking and type 2 diabetes mellitus. We have evaluated each study using gold standard methodology supported by the Mendelian randomization literature and the STROBE-Mendelian randomization checklist. Where discrepancies exist between Mendelian randomization studies, we suggest the underlying reasons. A number of studies conclude that there is a causal link between blood lipids and risk of amyotrophic lateral sclerosis; replication across different datasets and even different populations adds confidence. For other putative risk factors, such as smoking and immune function, Mendelian randomization studies have provided cause for doubt. We highlight the use of positive control analyses in choosing exposure single nucleotide polymorphisms (SNPs) to make up the Mendelian randomization instrument, use of SNP clumping to avoid false positive results due to SNPs in linkage and the importance of multiple testing correction. We discuss the implications of survival bias for study of late age of onset diseases such as amyotrophic lateral sclerosis and make recommendations to mitigate this potentially important confounder. For Mendelian randomization to be useful to the amyotrophic lateral sclerosis field, high methodological standards must be applied to ensure reproducibility. Mendelian randomization is already an impactful tool, but poor-quality studies will lead to incorrect interpretations by a field that includes non-statisticians, wasted resources and missed opportunities.

Dominance can increase genetic variance after a population bottleneck: a synthesis of the theoretical and empirical evidence

Drastic reductions in population size, or population bottlenecks, can lead to a reduction in additive genetic variance and adaptive potential. Genetic variance for some quantitative genetic traits, however, can increase after a population reduction. Empirical evaluations of quantitative traits following experimental bottlenecks indicate that non-additive genetic effects, including both allelic dominance at a given locus and epistatic interactions among loci, may impact the additive variance contributed by alleles that ultimately influences phenotypic expression and fitness. The dramatic effects of bottlenecks on overall genetic diversity have been well studied, but relatively little is known about how dominance and demographic events like bottlenecks can impact additive genetic variance. Herein, we critically examine how the degree of dominance among alleles affects additive genetic variance after a bottleneck. We first review and synthesize studies that document the impact of empirical bottlenecks on dominance variance. We then extend earlier work by elaborating on two theoretical models that illustrate the relationship between dominance and the potential increase in additive genetic variance immediately following a bottleneck. Furthermore, we investigate the parameters that influence the maximum level of genetic variation (associated with adaptive potential) after a bottleneck, including the number of founding individuals. Finally, we validated our methods using forward-time population genetic simulations of loci with varying dominance and selection levels. The fate of non-additive genetic variation following bottlenecks could have important implications for conservation and management efforts in a wide variety of taxa, and our work should help contextualize future studies (e.g., epistatic variance) in population genomics.

Genome-wide population structure inferences of human coxsackievirus-A; insights the genotypes diversity and evolution

Coxsackievirus-A (CV-A) is a causative agent of Hand Foot Mouth Disease (HFMD) worldwide. It belongs to the Human Enterovirus genus of the family Picornaviridae. The genomics data availability of CV-A samples, isolated from human host across different continental regions, provide an excellent opportunity to study its genetic composition, diversity, and evolutionary events. The complete genome sequences of 424 CV-A isolates were analyzed through a model-based population genetic approach implemented in the STRUCTURE program. Twelve genetically distinct sub-populations were identified for CV-A isolates with a marked Fst distinction of 0.76991 (P-value = 0.00000). Besides, genetically admixed strains were characterized in the G-Id, G-IIIb clusters constituted by the CV-A12 and CV-A6 enterovirus serotypes. The serotypes depicted inter/intra-genotype recombination and episodic positive selection signatures in the structural and non-structural protein-coding regions. The observed genetic composition of CV-A samples was also deduced by the phylogenetic tree analyses, where a uniform genetic structure was inferred for most of the CV-A genotypes. However, the CV-A6 serotype samples genetically stratified into three sub-populations that may lead to the emergence of new lineages in future. These informations may implicate in planning the effective strategies to combat the coxsackievirus-A-mediated infection.

Isolation and reconnection: Demographic history and multiple contact zones of the green odorous frog (Odorrana margaretae) around the Sichuan Basin

The green odorous frog (Odorrana margaretae) displays a circular distribution around the Sichuan Basin of western China and possesses multiple replicate hybrid zones between lineages with high levels of divergence. To gain an understanding of the speciation process, we obtained 1540 SNPs from 29 populations and 227 individuals using ddRAD sequencing. Population structure analysis revealed three groups within the species: the West, North & South, and East groups. Demographic inference showed that they were initially isolated at ~2 million years ago, and subsequent post-glacial expansion produced the current circular distribution with four secondary contact zones. Hybridization in those zones involved lineages with various levels of divergence and produced greatly different patterns of introgression. Contact zones between the East and North & South groups (E-S and E-N) had contrast admixture levels but both showed a general lack of potential barrier loci. Meanwhile, the reconnection of the West and North & South groups produced two contact zones along the rim of the Basin. The S-W zone had extensive admixture while the N-W zone had limited admixture within a narrow geographic distance. Both showed substantial barrier effects, and a large number of potential barrier loci were shared. We also detected strong coupling among these loci. The N-W hybrid zone involved two highly-diverged lineages (F_ST = 0.704) and many loci have reached fixation around the hybrid zone. This study system offers a unique opportunity to understand the dynamics of introgression in contact zones and the architecture of reproductive isolation at different stages of speciation.

Development and validation of a forensic six-dye multiplex assay with 29 STR loci

This paper describes the development and validation of a novel 31-locus, six-dye STR multiplex system, which is designed to meet the needs of the rapidly growing Chinese forensic database. This new assay combines 20 extended-CODIS core loci (D3S1358, D5S818, TPOX, CSF1PO, TH01, vWA, D7S820, D21S11, D8S1179, D18S51, D16S539, D13S317, FGA, D1S1656, D2S441, D2S1338, D10S1248, D12S391, D19S433, and D22S1045), nine highly polymorphic loci in Chinese Han population (D3S3045, D6S1043, D6S477, D8S1132, D10S1435, D15S659, D19S253, Penta D, and Penta E), and two gender determining markers, amelogenin and Y-Indel, which could amplify DNA from extracts, as well as direct amplification from substrates. To demonstrate the suitability for forensic applications, this system was validated by precision and accuracy evaluation, concordance tests, case sample tests, sensitivity, species specificity, stability, stutter calculation, and DNA mixtures, according to the guidelines described by the Scientific Working Group on DNA Analysis Methods (SWGDAM) and regulations published by the China Ministry of Public Security. The validation results indicate the robustness and reliability of this new system, and it could be a potentially helpful tool for human identification and paternity testing in the Chinese population, as well as facilitating global forensic DNA data sharing.

Identification of Loci and Pathways Associated with Heifer Conception Rate in U.S. Holsteins

Heifer conception rate (HCR) is defined as the percentage of inseminated heifers that become pregnant at each service. The genome-wide association analyses in this study focused on identifying the loci associated with Holstein heifer (n = 2013) conception rate at first service (HCR1) and the number of times bred (TBRD) to achieve a pregnancy. There were 348 unique loci associated (p < 5 × 10⁻⁸) with HCR1 and 615 unique loci associated (p < 5 × 10⁻⁸) with TBRD. The two phenotypes shared 302 loci, and 56 loci were validated in independent cattle populations. There were 52 transcription factor binding sites (TFBS) and 552 positional candidate genes identified in the HCR1- and TBRD-associated loci. The positional candidate genes and the TFBS associated with HCR1 and TBRD were used in the ingenuity pathway analysis (IPA). In the IPA, 11 pathways, 207 master regulators and 11 upstream regulators were associated (p < 1.23 × 10⁻⁵) with HCR1 and TBRD. The validated loci associated with both HCR1 and TBRD make good candidates for genomic selection and further investigations to elucidate the mechanisms associated with subfertility and infertility.

Genome-wide association studies and genetic testing: understanding the science, success, and future of a rapidly developing field

Dog owners are increasingly interested in using commercially available testing panels to learn about the genetics of their pets, both to identify breed ancestry and to screen for specific genetic diseases. Helping owners interpret and understand results from genetic screening panels is becoming an important issue facing veterinarians. The objective of this review article is to introduce basic concepts behind genetic studies and current genetic screening tests while highlighting their value in veterinary medicine. The potential uses and limitations of commercially available genetic testing panels as screening tests are discussed, including appropriate cautions regarding the interpretation of results. Future directions, particularly with regard to the study of common complex genetic diseases, are also described.

Identification of loci associated with conception rate in primiparous Holstein cows

BACKGROUND

Subfertility is a major issue facing the dairy industry as the average US Holstein cow conception rate (CCR) is approximately 35%. The genetics underlying the physiological processes responsible for CCR, the proportion of cows able to conceive and maintain a pregnancy at each breeding, are not well characterized. The objectives of this study were to identify loci, positional candidate genes, and transcription factor binding sites (TFBS) associated with CCR and determine if there was a genetic correlation between CCR and milk production in primiparous Holstein cows. Cows were bred via artificial insemination (AI) at either observed estrus or timed AI and pregnancy status was determined at day 35 post-insemination. Additive, dominant, and recessive efficient mixed model association expedited (EMMAX) models were used in two genome-wide association analyses (GWAA). One GWAA focused on CCR at first service (CCR1) comparing cows that conceived and maintained pregnancy to day 35 after the first AI (n = 494) to those that were open after the first AI (n = 538). The second GWAA investigated loci associated with the number of times bred (TBRD) required for conception in cows that either conceived after the first AI (n = 494) or repeated services (n = 472).

RESULTS

The CCR1 GWAA identified 123, 198, and 76 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. The TBRD GWAA identified 66, 95, and 33 loci associated (P < 5 × 10- 08) in additive, dominant, and recessive models, respectively. Four of the top five loci were shared in CCR1 and TBRD for each GWAA model. Many of the associated loci harbored positional candidate genes and TFBS with putative functional relevance to fertility. Thirty-six of the loci were validated in previous GWAA studies across multiple breeds. None of the CCR1 or TBRD associated loci were associated with milk production, nor was their significance with phenotypic and genetic correlations to 305-day milk production.

CONCLUSIONS

The identification and validation of loci, positional candidate genes, and TFBS associated with CCR1 and TBRD can be utilized to improve, and further characterize the processes involved in cattle fertility.

Population-specific long-range linkage disequilibrium in the human genome and its influence on identifying common disease variants

Despite the availability of large-scale sequencing data, long-range linkage disequilibrium (LRLD) has not been extensively studied. The theoretical aspects of LRLD estimates were studied to determine the best estimation method for the sequencing data of three different populations of African (AFR), European (EUR), and East-Asian (EAS) descent from the 1000 Genomes Project. Genome-wide LRLDs excluding centromeric regions revealed clear population specificity, presenting substantially more population-specific LRLDs than coincident LRLDs. Clear relationships between the functionalities of the regions in LRLDs denoted long-range interactions in the genome. The proportions of gene regions were increased in LRLD variants, and the coding sequence (CDS)-CDS LRLDs showed obvious functional similarities between genes in LRLDs. Application to theoretical case-control associations confirmed that the LRLDs in genome-wide association studies (GWASs) could contribute to false signals, although the impacts might not be severe in most cases. LRLDs with variants with functional similarity exist in the human genome indicating possible gene-gene interactions, and they differ depending on populations. Based on the current study, LRLDs should be examined in GWASs to identify true signals. More importantly, population specificity in LRLDs should be examined in relevant studies.

Low genetic variation is associated with low mutation rate in the giant duckweed

Mutation rate and effective population size (Ne) jointly determine intraspecific genetic diversity, but the role of mutation rate is often ignored. Here we investigate genetic diversity, spontaneous mutation rate and Ne in the giant duckweed (Spirodela polyrhiza). Despite its large census population size, whole-genome sequencing of 68 globally sampled individuals reveals extremely low intraspecific genetic diversity. Assessed under natural conditions, the genome-wide spontaneous mutation rate is at least seven times lower than estimates made for other multicellular eukaryotes, whereas Ne is large. These results demonstrate that low genetic diversity can be associated with large-Ne species, where selection can reduce mutation rates to very low levels. This study also highlights that accurate estimates of mutation rate can help to explain seemingly unexpected patterns of genome-wide variation.

Microhaplotypes in forensic genetics

Microhaplotype loci (microhaps, MHs) are a novel type of molecular marker of less than 300 nucleotides, defined by two or more closely linked SNPs associated in multiple allelic combinations. The value of these markers is enhanced by massively parallel sequencing (MPS), which allows the sequencing of both parental haplotypes at each of the many multiplexed loci. This review describes the features of these multi-SNP markers and documents their value in forensic genetics, focusing on individualization, biogeographic ancestry inference, and mixture deconvolution. Foreseeable applications also include missing person identification, relationship testing, and medical diagnostic applications. The technique is not restricted to humans.

The Rise and Fall and Rise of Linkage Analysis as a Technique for Finding and Characterizing Inherited Influences on Disease Expression

For many years, family-based studies using linkage analysis represented the primary approach for identifying disease genes. This strategy is responsible for the identification of the greatest number of genes proven to cause human disease. However, technical advancements in next generation sequencing and high throughput genotyping, coupled with the apparent simplicity of association testing, led to the rejection of family-based studies and of linkage analysis. At present, genetic association methods, using case-control comparisons, have become the exclusive approach for detecting disease-related genes, particularly those underlying common, complex diseases. In this chapter, we present a historical overview of linkage analysis, including a description of how the approach works, as well as its strengths and weaknesses. We discuss how the transition from family-based studies to population comparison association studies led to a critical loss of information with respect to genetic etiology and inheritance, and we present historical and contemporary examples of linkage analysis "success stories" in identifying genes contributing to the development of human disease. Currently, linkage analysis is re-emerging as a useful approach for identifying disease genes, determining genetic parameters, and resolving genetic heterogeneity. We posit that the combination of linkage analysis, association testing, and high throughput sequencing provides a powerful approach for identifying disease-causing genes.

First description and evaluation of SNPs in the ADH and ALDH genes in a population of alcoholics in Central-West Brazil

Worldwide, different studies have reported an association of alcohol-use disorder (AUD) with different types of Single Nucleotide Polymorphisms (SNPs) in the genes for aldehyde dehydrogenase (ALDH) and alcohol dehydrogenase (ADH). In Brazil, there is little information about the occurrence of these SNPs in the AUD population and an absence of studies characterizing the population in the Central-West Region of Brazil. Actually, in Brazil, there are more than 4 million people with AUD. Despite the major health hazards of AUD, information on alcohol consumption and its consequences are not well understood. Therefore, it is extremely important to characterize these SNPs for the better understanding of AUD as a genetic disease in the Brazilian population. The present study, unlike other studies in other countries, is done with a subject population that shows a significant amount of racial homogenization. We evaluated the presence of SNPs in the ADH (ADH1B, ADH1C, and ADH4) and ALDH (ALDH2) genes in alcohol users of Goiânia, State of Goiás - Brazil, and then we established a possible relationship with AUD by allelic and genotypic study. This study was conducted with a population of people with AUD (n = 99) from Goiás Alcohol Dependence Recovery Center (GO CEREA) and Psychosocial Care Center for Alcohol and Drugs (CAPS AD), and with a population of people without AUD as controls (n = 100). DNA was extracted from whole-blood samples and the genotyping was performed using TaqMan^® SNP genotyping assays. For characterization and evaluation of SNPs in the population, genotype frequency, allele frequency, haplotype frequency, Hardy-Weinberg equilibrium, and linkage disequilibrium were analyzed. Statistical analyses were calculated by GENEPOP 4.5 and Haploview software. The allele 1 was considered as "wild" (or *1) and allele 2 as mutant (or *2). Significant differences were found for ADH1B*, ADH4*2, and ALDH2*2 SNPs when the genotype and allele frequencies were analyzed. In addition, four haplotypes were observed between ADH1B*2 and ADH1C*2 through linkage disequilibrium analysis. The genetic variants may be associated with protection against AUD in the population studied.

Association mapping unveils favorable alleles for grain iron and zinc concentrations in lentil (Lens culinaris subsp. culinaris)

Lentil is a major cool-season grain legume grown in South Asia, West Asia, and North Africa. Populations in developing countries of these regions have micronutrient deficiencies; therefore, breeding programs should focus more on improving the micronutrient content of food. In the present study, a set of 96 diverse germplasm lines were evaluated at three different locations in India to examine the variation in iron (Fe) and zinc (Zn) concentration and identify simple sequence repeat (SSR) markers that associate with the genetic variation. The genetic variation among genotypes of the association mapping (AM) panel was characterized using a genetic distance-based and a general model-based clustering method. The model-based analysis identified six subpopulations, which satisfactorily explained the genetic structure of the AM panel. AM analysis identified three SSRs (PBALC 13, PBALC 206, and GLLC 563) associated with grain Fe concentration explaining 9% to 11% of phenotypic variation and four SSRs (PBALC 353, SSR 317-1, PLC 62, and PBALC 217) were associated with grain Zn concentration explaining 14%, to 21% of phenotypic variation. These identified SSRs exhibited consistent performance across locations. These candidate SSRs can be used in marker-assisted genetic improvement for developing Fe and Zn fortified lentil varieties. Favorable alleles and promising genotypes identified in this study can be utilized for lentil biofortification.

Prioritizing tests of epistasis through hierarchical representation of genomic redundancies

Epistasis is defined as a statistical interaction between two or more genomic loci in terms of their association with a phenotype of interest. Epistatic loci that are identified using data from Genome-Wide Association Studies (GWAS) provide insights into the interplay among multiple genetic factors, with applications including assessment of susceptibility to complex diseases, decision making in precision medicine, and gaining insights into disease mechanisms. Since the number of genomic loci assayed by GWAS is extremely large (usually in the order of millions), identification of epistatic loci is a statistically difficult and computationally intensive problem. Even when only pairwise interactions are considered, the size of the search space ranges from hundreds of millions to billions of locus pairs. The large number of statistical tests performed also makes sufficient type one error correction imperative. Consequently, efficient algorithms are required to filter the tests that are performed and evaluate large GWAS data sets in a reasonable amount of computation time. It has been observed that many pairwise tests are redundant due to correlations in their genotype values across samples, known as linkage disequilibrium. However, algorithms that have been developed for efficient identification of epistatic loci do not systematically exploit linkage disequilibrium. Here, we propose a new algorithm for fast epistasis detection based on hierarchical representation of linkage disequilibrium (LinDen). We utilize redundancies in genotype patterns between neighboring loci to generate a hierarchical structure and execute a branch-and-bound search to prioritize loci testing based on approximations of a test statistic for pairs of locus groups. The hierarchical organization of tests performed by LinDen allows for efficient scaling based on the screened loci. We test LinDen comprehensively on three data sets obtained from the Wellcome Trust Case Control Consortium: type two diabetes, psoriasis, and hypertension. Our results show that, as compared other state-of-the-art tools for fast epistasis detection, LinDen drastically reduces the number of tests performed while discovering statistically significant locus pairs. LinDen is implemented in C++ and is available as open source at http://compbio.case.edu/linden/.

Effects of genetic variants of the bovine WNT8A gene on nine important growth traits in beef cattle

WNT-β-catenin-TCF pathway is involved in carcinogenesis and foetal development. As a member of the WNT gene family, Wnt8A encodes secreted signalling proteins and responds to many biological processes.However, similar research on the effects of genetic variations of Wnt8A gene on growth traits is lacking. Therefore, in this study, polymorphisms of Wnt8A were detected in 396 animals from Chinese Qinchuan cattle using DNA pool sequencing and PCR-RFLP methods. Four novel single-nucleotide polymorphisms (SNPs) of Wnt8A gene were identified, including three mutations in introns (g.T-445C, g.G244C and g.G910A) and one in exon (g.T4922C). Additionally, we examined the associations of four SNPs with growth traits. The results revealed that SNP2 (g.G244C) was significantly associated with shoulder height, hip height, body length, hip width, and body weight (P < 0.05). SNP3 (g.G910A) also displayed notable effects on hip width (P < 0.05). Meanwhile, the haplotype combination CC-GC-GA-CC was strongly associated with heavier, taller and longer animals (P < 0.05). These results show that the Wnt8A gene may be a potential candidate gene, and the SNPs could be used as molecular markers in early marker-assisted selection in beef cattle breeding programmes.

Genetic analysis of indel markers in three loci associated with Parkinson's disease

The causal mutations and genetic polymorphisms associated with susceptibility to Parkinson’s disease (PD) have been extensively described. To explore the potential contribution of insertion (I)/deletion (D) polymorphisms (indels) to the risk of PD in a Chinese population, we performed genetic analyses of indel loci in ACE, DJ-1, and GIGYF2 genes. Genomic DNA was extracted from venous blood of 348 PD patients and 325 age- and sex-matched controls without neurodegenerative disease. Genotyping of the indel loci was performed by fragment length analysis after PCR and DNA sequencing. Our results showed a statistically significant association for both allele X (alleles without 5) vs. 5 (odds ratio = 1.378, 95% confidence interval = 1.112–1.708, P = 0.003) and genotype 5/X+X/X vs. 5/5 (odds ratio = 1.681, 95% confidence interval = 1.174–2.407, P = 0.004) in the GIGYF2 locus; however, no significant differences were detected for the ACE and DJ-1 indels. After stratification by gender, no significant differences were observed in any indels. These results indicate that the GIGYF2 indel may be associated with increased risk of PD in northern China.

The Bos taurus-Bos indicus balance in fertility and milk related genes

Numerical approaches to high-density single nucleotide polymorphism (SNP) data are often employed independently to address individual questions. We linked independent approaches in a bioinformatics pipeline for further insight. The pipeline driven by heterozygosity and Hardy-Weinberg equilibrium (HWE) analyses was applied to characterize Bos taurus and Bos indicus ancestry. We infer a gene co-heterozygosity network that regulates bovine fertility, from data on 18,363 cattle with genotypes for 729,068 SNP. Hierarchical clustering separated populations according to Bos taurus and Bos indicus ancestry. The weights of the first principal component were subjected to Normal mixture modelling allowing the estimation of a gene’s contribution to the Bos taurus-Bos indicus axis. We used deviation from HWE, contribution to Bos indicus content and association to fertility traits to select 1,284 genes. With this set, we developed a co-heterozygosity network where the group of genes annotated as fertility-related had significantly higher Bos indicus content compared to other functional classes of genes, while the group of genes associated with milk production had significantly higher Bos taurus content. The network analysis resulted in capturing novel gene associations of relevance to bovine domestication events. We report transcription factors that are likely to regulate genes associated with cattle domestication and tropical adaptation. Our pipeline can be generalized to any scenarios where population structure requires scrutiny at the molecular level, particularly in the presence of a priori set of genes known to impact a phenotype of evolutionary interest such as fertility.

Editing the genome of hiPSC with CRISPR/Cas9: disease models

The advent of human-induced pluripotent stem cell (hiPSC) technology has provided a unique opportunity to establish cellular models of disease from individual patients, and to study the effects of the underlying genetic aberrations upon multiple different cell types, many of which would not normally be accessible. Combining this with recent advances in genome editing techniques such as the clustered regularly interspaced short palindromic repeat (CRISPR) system has provided an ability to repair putative causative alleles in patient lines, or introduce disease alleles into a healthy “WT” cell line. This has enabled analysis of isogenic cell pairs that differ in a single genetic change, which allows a thorough assessment of the molecular and cellular phenotypes that result from this abnormality. Importantly, this establishes the true causative lesion, which is often impossible to ascertain from human genetic studies alone. These isogenic cell lines can be used not only to understand the cellular consequences of disease mutations, but also to perform high throughput genetic and pharmacological screens to both understand the underlying pathological mechanisms and to develop novel therapeutic agents to prevent or treat such diseases. In the future, optimising and developing such genetic manipulation technologies may facilitate the provision of cellular or molecular gene therapies, to intervene and ultimately cure many debilitating genetic disorders.

Multi-marker linkage disequilibrium mapping of quantitative trait loci

Single nucleotide polymorphisms (SNPs), the most common genetic markers in genome-wide association studies, are usually in linkage disequilibrium (LD) with each other within a small genomic region. Both single- and two-marker-based LD mapping methods have been developed by taking advantage of the LD structures. In this study, a more general LD mapping framework with an arbitrary number of markers has been developed to further improve LD mapping and its detection power. This method is referred as multi-marker linkage disequilibrium mapping (mmLD). For the parameter estimation, we implemented a two-phase estimation procedure: first, haplotype frequencies were estimated for known markers; then, haplotype frequencies were updated to include the unknown quantitative trait loci based on estimates from the first step. For the hypothesis testing, we proposed a novel sequential likelihood ratio test procedure, which iteratively removed haplotypes with zero frequency and subsequently determined the proper degree of freedom. To compare the proposed mmLD method with other existing mapping methods, e.g. the adjusted single-marker LD mapping and the SKAT_C, we performed extensive simulations under various scenarios. The simulation results demonstrated that the mmLD has the same or higher power than the existing methods, while maintaining the correct type I errors. We further applied the mmLD to a public data set, 'GAW17', to investigate its applicability. The result showed the good performance of mmLD. We concluded that this improved mmLD method will be useful for future genome-wide association studies and genetic association analyses.

The Decay of Disease Association with Declining Linkage Disequilibrium: A Fine Mapping Theorem

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise linkage disequilibrium, r². A complete derivation of this relationship from a general disease model is shown. Quite interestingly, this relationship holds across all modes of inheritance. Extensive Monte Carlo simulations using a disease genetics model applied to chromosomes subjected to a standard model of recombination are employed to better understand the variation around this fine mapping theorem due to sampling effects. We also use this relationship to provide a framework for estimating properties of a non-interrogated causal site using data at closely linked markers. Lastly, we apply this way of examining association data from high-density genotyping in a large, publicly-available data set investigating extreme BMI. We anticipate that understanding the patterns of disease association decay with declining linkage disequilibrium from a causal site will enable more powerful fine mapping methods and provide new avenues for identifying causal sites/genes from fine-mapping studies.

New Software for the Fast Estimation of Population Recombination Rates (FastEPRR) in the Genomic Era

Genetic recombination is a very important evolutionary mechanism that mixes parental haplotypes and produces new raw material for organismal evolution. As a result, information on recombination rates is critical for biological research. In this paper, we introduce a new extremely fast open-source software package (FastEPRR) that uses machine learning to estimate recombination rate ρ (=4Ner) from intraspecific DNA polymorphism data. When ρ>10 and the number of sampled diploid individuals is large enough (≥50), the variance of ρFastEPRR remains slightly smaller than that of ρLDhat. The new estimate ρcomb (calculated by averaging ρFastEPRR and ρLDhat) has the smallest variance of all cases. When estimating ρFastEPRR, the finite-site model was employed to analyze cases with a high rate of recurrent mutations, and an additional method is proposed to consider the effect of variable recombination rates within windows. Simulations encompassing a wide range of parameters demonstrate that different evolutionary factors, such as demography and selection, may not increase the false positive rate of recombination hotspots. Overall, accuracy of FastEPRR is similar to the well-known method, LDhat, but requires far less computation time. Genetic maps for each human population (YRI, CEU, and CHB) extracted from the 1000 Genomes OMNI data set were obtained in less than 3 d using just a single CPU core. The Pearson Pairwise correlation coefficient between the ρFastEPRR and ρLDhat maps is very high, ranging between 0.929 and 0.987 at a 5-Mb scale. Considering that sample sizes for these kinds of data are increasing dramatically with advances in next-generation sequencing technologies, FastEPRR (freely available at http://www.picb.ac.cn/evolgen/) is expected to become a widely used tool for establishing genetic maps and studying recombination hotspots in the population genomic era.

Association between Eight Functional Polymorphisms and Haplotypes in the Cholesterol Ester Transfer Protein (CETP) Gene and Dyslipidemia in National Minority Adults in the Far West Region of China

We have investigated the relationship between the polymorphisms and haplotypes in the CETP gene, and dyslipidemia among the Xinjiang Kazak and Uyghur populations in China. A total of 712 patients with dyslipidemia and 764 control subjects of CETP gene polymorphism at rs12149545, rs3764261, rs1800775, rs711752, rs708272, rs289714, rs5882, and rs1801706 loci were studied by the Snapshot method, linkage disequilibrium analysis and haplotype construction. The results are as follows: (1) the minor allele of eight loci of frequencies in the two groups were different from other results of similar studies in other countries; (2) In the linear regression analysis, the HDL-C levels of rs708272 TT, rs1800775 AA, rs289714 CC and rs711752 AA genotypes were significantly higher than those of other genotypes, however, the rs3764261 GG and rs12149545 GG genotypes were significantly lower than those of other genotypes in the two ethnic groups. The HDL-C levels of the rs12149545 GG genotype were lower than those of other genotypes; (3) in the control group, the rs708272 CT genotype of TG levels were lower than in the CC genotype, the T genotype of LDL-C levels were lower than in the CC genotype, and the HDL-C levels were higher than in the CT genotype; the rs1800775 AC genotype of TG levels were higher than in the AA genotype, the rs711752 AG genotype of TG levels were lower than in the GG genotype, the AA genotype LDL-C levels were lower than in the GG genotype, and the HDL-C levels were higher than in the AG genotype; the rs1800775 AC genotype of TG levels were higher than in the AA genotype. In the dyslipidemia group, the rs708272 TT genotype of TC and LDL-C levels were higher than in the CT genotype and the rs3764261 TT genotype of TC levels were higher than in the GG genotype. The rs711752 AA genotype of TC and LDL-C levels were higher than in the AG genotype, and the rs12149545 AA genotype of TC and LDL-C levels were higher than in the GG genotype; (4) perfect Linkage Disequilibrium was observed for two sets of two SNPs: rs3764261 and rs12149545; rs711752 and rs708272. (5) Using SHEsis software analysis, the five A/T/A/A/T/C/A/G, A/T/A/A/T/T/G/A, G/G/A/G/C/C/G/G, G/G/C/G/C/C/A/G and G/G/C/G/C/T/G/G haplotypes were between dyslipidemia group and control group statistically significantly different (p < 0.05 in each case). The polymorphism of CETP genes rs708272, rs3764261, rs1800775, rs711752, rs12149545 was closely related to the dyslipidemia in the Xinjiang Uyghur and Kazakh ethnic groups; and the rs708272 T, rs3764261 T, rs711752 A, and rs12149545 A alleles could reduce risk of dyslipidemia in the Uyghur and Kazakh populations, however, the rs1800775 C allele showed risk factors.

Genetic linkage analysis in the age of whole-genome sequencing

For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data.

Relationship between Adiponectin Gene Polymorphisms and Late-Onset Alzheimer's Disease

In recent years, researchers have found that adiponectin (ANP) plays an important role in the pathogenesis of Alzheimer's disease (AD), and low serum concentrations of ANP are associated with AD. Higher plasma ANP level have a protective effect against the development of cognitive decline, suggesting that ANP may affect AD onset. Meanwhile, accumulating evidence supports the crucial role of ANP in the pathogenesis of AD. To study the relationship between ANP gene polymorphisms (rs266729, -11377C>G and rs1501299, G276T) and late-onset AD (LOAD), we carried out a case-control study that included 201 LOAD patients and 257 healthy control subjects. Statistically significant differences were detected in the genotype and allelotype frequency distributions of rs266729 and rs1501299 between the LOAD group and the control group, with a noticeable increase in the G and T allelotype frequency distributions in the LOAD group (P < 0.05). Logistic regression analysis using recessive model and additive model revealed that the rs266729 GG and rs1501299 TT genotypes are associated with a greater risk of LOAD. Haplotype analysis identified four haplotypes: CG, CT, GG, and GT. The frequencies of the CT and GG haplotypes were not significantly different (P > 0.05) between the LOAD group and control group, whereas the CG and GT haplotypes were significantly different (P < 0.05), suggesting a negative correlation between the CG haplotype and LOAD onset (OR = 0.74, 95% CI = 0.57–0.96, P = 0.022), and a positive correlation between the GT haplotype and LOAD onset (OR = 2.29, 95% CI = 1.42–3.68, P = 0.005). Therefore, we speculated that the rs266729 and rs1501299 of ANP gene polymorphisms and the GT and CG haplotypes were associated with LOAD.

Comparison of high-resolution human leukocyte antigen haplotype frequencies in different ethnic groups: Consequences of sampling fluctuation and haplotype frequency distribution tail truncation

High-resolution haplotype frequency estimations and descriptive metrics are becoming increasingly popular for accurately describing human leukocyte antigen diversity. In this study, we compared sample sets of publically available haplotype frequencies from different populations to characterize the consequences of unequal sample size on haplotype frequency estimation. We found that for low samples sizes (a few thousand), haplotype frequencies were overestimated, affecting all descriptive metrics of the underlying distribution, such as most frequent haplotype, the number of haplotypes, and the mean/median frequency. This overestimation was a result of random sample fluctuation and truncation of the tail end of the frequency distribution that comprises the least frequent haplotypes. Finally, we simulated balanced datasets through resampling and contrasted the disparities of descriptive metrics among equal and unequal datasets. This simulation resulted in the global description of the most frequent human leukocyte antigen haplotypes worldwide.

A graphical weighted power improving multiplicity correction approach for SNP selections

Controlling for the multiplicity effect is an essential part of determining statistical significance in large-scale single-locus association genome scans on Single Nucleotide Polymorphisms (SNPs). Bonferroni adjustment is a commonly used approach due to its simplicity, but is conservative and has low power for large-scale tests. The permutation test, which is a powerful and popular tool, is computationally expensive and may mislead in the presence of family structure. We propose a computationally efficient and powerful multiple testing correction approach for Linkage Disequilibrium (LD) based Quantitative Trait Loci (QTL) mapping on the basis of graphical weighted-Bonferroni methods. The proposed multiplicity adjustment method synthesizes weighted Bonferroni-based closed testing procedures into a powerful and versatile graphical approach. By tailoring different priorities for the two hypothesis tests involved in LD based QTL mapping, we are able to increase power and maintain computational efficiency and conceptual simplicity. The proposed approach enables strong control of the familywise error rate (FWER). The performance of the proposed approach as compared to the standard Bonferroni correction is illustrated by simulation and real data. We observe a consistent and moderate increase in power under all simulated circumstances, among different sample sizes, heritabilities, and number of SNPs. We also applied the proposed method to a real outbred mouse HDL cholesterol QTL mapping project where we detected the significant QTLs that were highlighted in the literature, while still ensuring strong control of the FWER.

Using haplotypes for the prediction of allelic identity to fine-map QTL: characterization and properties

BACKGROUND

Numerous methods have been developed over the last decade to predict allelic identity at unobserved loci between pairs of chromosome segments along the genome. These loci are often unobserved positions tested for the presence of quantitative trait loci (QTL). The main objective of this study was to understand from a theoretical standpoint the relation between linkage disequilibrium (LD) and allelic identity prediction when using haplotypes for fine mapping of QTL. In addition, six allelic identity predictors (AIP) were also compared in this study to determine which one performed best in theory and application.

RESULTS

A criterion based on a simple measure of matrix distance was used to study the relation between LD and allelic identity prediction when using haplotypes. The consistency of this criterion with the accuracy of QTL localization, another criterion commonly used to compare AIP, was evaluated on a set of real chromosomes. For this set of chromosomes, the criterion was consistent with the mapping accuracy of a simulated QTL with either low or high effect. As measured by the matrix distance, the best AIP for QTL mapping were those that best captured LD between a tested position and a QTL. Moreover the matrix distance between a tested position and a QTL was shown to decrease for some AIP when LD increased. However, the matrix distance for AIP with continuous predictions in the [0,1] interval was algebraically proven to decrease less rapidly up to a lower bound with increasing LD in the simplest situations, than the discrete predictor based on identity by state between haplotypes (IBS hap), for which there was no lower bound. The expected LD between haplotypes at a tested position and alleles at a QTL is a quantity that increases naturally when the tested position gets closer to the QTL. This behavior was demonstrated with pig and unrelated human chromosomes.

CONCLUSIONS

When the density of markers is high, and therefore LD between adjacent loci can be assumed to be high, the discrete predictor IBS hap is recommended since it predicts allele identity correctly when taking LD into account.

Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses

Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it.

Rioux J, Hauser S, Oksenberg J. HLA diversity in the 1000 genomes dataset

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC), only the top 10 most frequent haplotypes are in the 1% frequency range whereas thousands of haplotypes are present at lower frequencies. Given the limitation of both the coverage and the read length of the sequences generated by the 1000 Genomes Project, the highly variable positions that define HLA alleles may be difficult to identify. We used classical Sanger sequencing techniques to type the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 genes in the available 1000 Genomes samples and combined the results with the 103,310 variants in the MHC region genotyped by the 1000 Genomes Project. Using pairwise identity-by-descent distances between individuals and principal component analysis, we established the relationship between ancestry and genetic diversity in the MHC region. As expected, both the MHC variants and the HLA phenotype can identify the major ancestry lineage, informed mainly by the most frequent HLA haplotypes. To some extent, regions of the genome with similar genetic or similar recombination rate have similar properties. An MHC-centric analysis underlines departures between the ancestral background of the MHC and the genome-wide picture. Our analysis of linkage disequilibrium (LD) decay in these samples suggests that overestimation of pairwise LD occurs due to a limited sampling of the MHC diversity. This collection of HLA-specific MHC variants, available on the dbMHC portal, is a valuable resource for future analyses of the role of MHC in population and disease studies.

Holm multiple correction for large-scale gene-shape association mapping

Background

Linkage Disequilibrium (LD) is a powerful approach for the identification and characterization of morphological shape, which usually involves multiple genetic markers. However, multiple testing corrections substantially reduce the power of the associated tests. In addition, the principle component analysis (PCA), used to quantify the shape variations into several principal phenotypes, further increases the number of tests. As a result, a powerful multiple testing correction for simultaneous large-scale gene-shape association tests is an essential part of determining statistical significance. Bonferroni adjustments and permutation tests are the most popular approaches to correcting for multiple tests within LD based Quantitative Trait Loci (QTL) models. However, permutations are extremely computationally expensive and may mislead in the presence of family structure. The Bonferroni correction, though simple and fast, is conservative and has low power for large-scale testing.

Results

We propose a new multiple testing approach, constructed by combining an Intersection Union Test (IUT) with the Holm correction, which strongly controls the family-wise error rate (FWER) without any additional assumptions on the joint distribution of the test statistics or dependence structure of the markers. The power improvement for the Holm correction, as compared to the standard Bonferroni correction, is examined through a simulation study. A consistent and moderate increase in power is found under the majority of simulated circumstances, including various sample sizes, Heritabilities, and numbers of markers. The power gains are further demonstrated on real leaf shape data from a natural population of poplar, Populus szechuanica var tietica, where more significant QTL associated with morphological shape are detected than under the previously applied Bonferroni adjustment.

Conclusion

The Holm correction is a valid and powerful method for assessing gene-shape association involving multiple markers, which not only controls the FWER in the strong sense but also improves statistical power.

Genome-wide association studies of agronomic and quality traits in a set of German winter barley (Hordeum vulgare L.) cultivars using Diversity Arrays Technology (DArT)

A set of about 100 winter barley (Hordeum vulgare L.) cultivars, comprising diverse and economically important German barley elite germplasm released during the last six decades, was previously genotypically characterized by single nucleotide polymorphism (SNP) markers using the Illumina GoldenGate BeadArray Technology to detect associations with phenotypic data estimated in three-year field trials at 12 locations. In order to identify further associations and to obtain information on whether the marker type influences the outcome of association genetics studies, the set of winter barley cultivars was re-analyzed using Diversity Arrays Technology (DArT) markers. As with the analysis of the SNPs, only polymorphic markers present at an allele frequency >5% were included to detect associations in a mixed linear model (MLM) approach using the TASSEL software (P ≤ 0.001). The population structure and kinship matrix were estimated on 72 simple sequence repeats (SSRs) covering the whole barley genome. The respective average linkage disequilibrium (LD) analyzed with DArT markers was estimated at 5.73 cM. A total of 52 markers gave significant associations with at least one of the traits estimated which, therefore, may be suitable for marker-assisted breeding. In addition, by comparing the results to those generated using the Illumina GoldenGate BeadArray Technology, it turned out that a different number of associations for respective traits is detected, depending on the marker system. However, as only a few of the respective DArT and Illumina markers are present in a common map, no comprehensive comparison of the detected associations was feasible, but some were probably detected in the same chromosomal regions. Because of the identification of additional marker-trait associations, it may be recommended to use both marker techniques in genome-wide association studies.

Identification of bovine NPC1 gene cSNPs and their effects on body size traits of Qinchuan cattle

NPC1 gene is an important gene closely related to the Niemann-Pick type C (NPC). Mutations in the NPC1 gene tend to cause Niemann-Pick type C, a lysosomal storage disorder. Previous studies have shown that NPC1 protein plays an important role in subcellular lipid transport, homeostasis, platelet function and formation, which are basic metabolic activities in the process of development. In this study, to explore the association between the NPC1 gene variation and body size traits in Qinchuan cattle, we detected four novel coding single nucleotide polymorphisms (cSNPs) in the bovine NPC1 gene, including one missense mutation (SNP1) and three synonymous mutations (SNP2, SNP3 and SNP4). Population genetic analyses of 518 individuals and association correlations between cSNPs and bovine body size traits were conducted in this research. A missense mutation at SNP1 locus was found to be significantly related to the heart girth, hip width and body weight (P<0.01 or P<0.05, 3.5-year-old). Two synonymous mutations at SNP2 and SNP3 loci also showed significant effects on hip width (P<0.05, 3.5-year-old). One synonymous mutation at SNP4 locus showed significant effect on body weight (P<0.05, 2.0-year-old). Combined haplotypes H2H6 and H6H6 showed significant effects on body size traits such as heart girth, hip width, and body weight (3.5-year-old, P<0.01 or P<0.05). This study provides evidence that the NPC1 gene might be involved in the regulation of bovine growth and body development, and may be considered as a candidate gene for marker assisted selection (MAS) in beef cattle breeding industry.

Genome-wide two-marker linkage disequilibrium mapping of quantitative trait loci

BACKGROUND

In a natural population, the alleles of multiple tightly linked loci on the same chromosome co-segregate and are passed non-randomly from generation to generation. Capitalizing on this phenomenon, a group of mapping methods, commonly referred to as the linkage disequilibrium-based mapping (LD mapping), have been developed recently for detecting genetic associations. However, most current LD mapping methods mainly employed single-marker analysis, overlooking the rich information contained within adjacent linked loci.

RESULTS

We extend the single-marker LD mapping to include two linked loci and explicitly incorporate their LD information into genetic mapping models (tmLD). We establish the theoretical foundations for the tmLD mapping method and also provide a thorough examination of its statistical properties. Our simulation studies demonstrate that the tmLD mapping method significantly improves the detection power of association compared to the single-marker based and also haplotype based mapping methods. The practical usage and properties of the tmLD mapping method were further elucidated through the analysis of a large-scale dental caries GWAS data set. It shows that the tmLD mapping method can identify significant SNPs that are missed by the traditional single-marker association analysis and haplotype based mapping method. An R package for our proposed method has been developed and is freely available.

CONCLUSIONS

The proposed tmLD mapping method is more powerful than single marker mapping generally used in GWAS data analysis. We recommend the usage of this improved method over the traditional single marker association analysis.

Additive genetic variation in schizophrenia risk is shared by populations of African and European descent

To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence.

Association analysis for quality traits in a diverse panel of Chinese sesame (Sesamum indicum L.) germplasm

The main objective of this study was to evaluate the potential of a sesame (Sesamum indicum L.) panel for association analysis, and investigate the genetic basis of oil content (OC), protein content, oleic acid concentration, and linoleic acid concentration using association mapping. A panel of 216 sesame accessions was phenotyped in a multi-environment trial and fingerprinted with 608 polymorphic loci produced by 79 primers, including simple sequence repeats (SSRs), sequence-related amplified polymorphisms (SRAPs), and amplified fragment length polymorphisms (AFLPs). Population structure analysis revealed two subgroups in the population. The Q model performed better for its ability to re-identify associations for the four traits at highly significant P-values compared to the other three mixed models. And a total of 35 and 25 associations for the four traits in 2010 and 2011 were identified, respectively, with the Q model after Bonferroni correction. Among those associations, only one for OC was re-identified in two environments, and several markers associated simultaneously with multiple traits were discovered. These results suggest the power and stability of the Q model for association analysis of nutritional traits in this sesame panel for its slight population stratification and familial relationship, which could aid in dissecting complex traits, and could help to develop strategies for improving nutritional quality.