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Hairy vetch (Vicia villosa Roth), a winter-hardy annual legume, is a promising cover crop. To fully leverage its potential, seed production and field performance of V. villosa must be improved to facilitate producer adoption. Two classic domestication traits, seed dormancy (hard seed) and dehiscence (pod shatter), are selection targets in an ongoing breeding program. This study reports a genome-wide association study of 1,019 V. villosa individuals evaluated at two sites (Knox City, Texas and Corvallis, Oregon) for the proportion of dormant seed, visual pod dehiscence scores, and two dehiscence surrogate measures (force to dehiscence and pod spiraling score). Trait performance varied between sites, but reliability (related to heritability) across sites was strong (dormant seed proportion: 0.68; dehiscence score: 0.61; spiraling score: 0.42; force to dehiscence: 0.41). A major locus controlling seed dormancy was found (q- value: 1.29 × 10−5 ; chromosome 1: position: 63611165), which can be used by breeding programs to rapidly reduce dormancy in breeding populations. No significant dehiscence score QTL was found, primarily due to the high dehiscence rates in Corvallis, Oregon. Since Oregon is a potentially major V. villosa seed production region, further dehiscence resistance screening is necessary. [ABSTRACT FROM AUTHOR]

Hairy vetch (Vicia villosa Roth), a winter-hardy annual legume, is a promising cover crop. To fully leverage its potential, seed production and field performance of V. villosa must be improved to facilitate producer adoption. Two classic domestication traits, seed dormancy (hard seed) and dehiscence (pod shatter), are selection targets in an ongoing breeding program. This study reports a genome-wide association study of 1,019 V. villosa individuals evaluated at two sites (Knox City, Texas and Corvallis, Oregon) for the proportion of dormant seed, visual pod dehiscence scores, and two dehiscence surrogate measures (force to dehiscence and pod spiraling score). Trait performance varied between sites, but reliability (related to heritability) across sites was strong (dormant seed proportion: 0.68; dehiscence score: 0.61; spiraling score: 0.42; force to dehiscence: 0.41). A major locus controlling seed dormancy was found (q-value: 1.29 × 10−5; chromosome 1: position: 63611165), which can be used by breeding programs to rapidly reduce dormancy in breeding populations. No significant dehiscence score QTL was found, primarily due to the high dehiscence rates in Corvallis, Oregon. Since Oregon is a potentially major V. villosa seed production region, further dehiscence resistance screening is necessary

Collie eye anomaly (CEA) encompasses a spectrum of different ophthalmic phenotypes from clinically inconsequential choroidal hypoplasia to blindness from coloboma of the optic nerve head (ONH). A previous study found a 7.8-kb deletion in intron 4 of the NHEJ1 gene to be associated with CEA. A genetic test based on this association is recommended for many breeds, including the Nova Scotia Duck Tolling Retriever (NSDTR). Collection of ONH coloboma-affected NSDTR showed lack of concordance of the NHEJ1 intronic deletion with ONH coloboma. Using genomewide single nucleotide polymorphism (SNP) genotyping in 7 ONH coloboma-affected NSDTR cases and 47 unaffected NSDTR controls with no ophthalmic signs, one SNP, located on chromosome 7, demonstrated genomewide significance. However, high genomic inflation may have confounded the results. Therefore, the genomewide association study was repeated using EMMAX to control for population structure in the cohort of 7 cases and 47 controls. However, no regions of the genome were significantly associated with ONH coloboma. These results failed to document significant association with the CEA locus. Due to the complex genetic etiology of ONH coloboma, the NHEJ1 intronic deletion test results should be carefully considered when making breeding decisions. If the goal is to select for visually competent dogs, our data suggest that eye examinations of puppies would be more effective as a guide in selection of breeding pairs than relying solely on currently available genetic tests.

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27 581 individuals of European descent over 65 years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5 × 10(-8) ) and 39 suggestive (P-value< 5 × 10(-5) ) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β = 0.47, SE = 0.08, P-value = 5.20 × 10(-10) ). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength.

BackgroundThe risk of alcohol-related liver cirrhosis increases with increasing alcohol consumption, but many people with very high intake escape from liver disease. We postulate that susceptibility to alcoholic cirrhosis has a complex genetic component and propose that this can be dissected through a large and sufficiently powered genomewide association study (GWAS).MethodsThe GenomALC Consortium comprises researchers from Australia, France, Germany, Switzerland, United Kingdom, and United States, with a joint aim of exploring the genetic and genomic basis of alcoholic cirrhosis. For this National Institutes of Health/National Institute on Alcohol Abuse and Alcoholism funded study, we are recruiting high-risk drinkers who are either cases (with alcoholic cirrhosis) or controls (drinking comparable amounts over similar time, but free of significant liver disease). Extensive phenotypic data are obtained using semistructured interviews and patient records, and blood samples are collected.ResultsWe have successfully recruited 859 participants including 538 matched case-control samples as of September 2014, using study-specific inclusion-exclusion criteria and data collection protocols. Of these, 580 are cases (442 men and 138 women) and 279 are controls (205 men and 74 women). Duration of excessive drinking was slightly greater in cases than controls and was significantly less in women than men. Cases had significantly lower lifetime alcohol intake than controls. Both cases and controls had a high prevalence of reported parental alcohol problems, but cases were significantly more likely to report that a father with alcohol problems had died from liver disease (odds ratio 2.53, 95% confidence interval 1.31 to 4.87, p = 0.0055).ConclusionsRecruitment of participants for a GWAS of alcoholic cirrhosis has proved feasible across countries with multiple sites. Affected patients often consume less alcohol than unaffected ones, emphasizing the existence of individual vulnerability factors. Cases are more likely to report liver disease in a father with alcohol problems than controls, consistent with a potential genetic component to the risk of alcoholic cirrhosis.

Recent advances indicate that bone and energy metabolism are closely related. However, little direct evidence on causality has been provided in humans. We aimed to assess the association of three bone‐related biomarkers—25 hydroxyvitamin D (25OHD), parathyroid hormone (PTH), and osteocalcin (OCN)—with several metabolic phenotypes and investigate any causal relevance to the associations using a Mendelian randomization (MR) study. Serum 25OHD, PTH, and total OCN were measured at baseline in 5169 eligible Chinese participants in Changfeng study. Partial correlation and bivariate GREML analysis were used to estimate phenotypic and genetic correlations, respectively. Multiple linear regression and logistic regression were used to assess linear associations. Genomewide association analysis (GWAS) was performed. Bidirectional two‐sample MR analyses were conducted to examine causal relationships between OCN and body mass index (BMI), diastolic blood pressure (DBP), triglyceride (TG), high‐density lipoprotein cholesterol (HDL‐C), glycated hemoglobin A1c (HbA1c), and type 2 diabetes (T2DM), using our GWAS result of OCN and GWAS statistics from Biobank Japan project (BBJ) and the largest meta‐analysis of T2DM GWAS in East Asian population. Circulating OCN was significantly associated with higher DBP and HDL‐C and decreased TG, blood glucose level, insulin resistance, liver fat content, bone mineral density, BMI, and a favorable body fat distribution pattern. GWAS identified one novel serum PTH locus and two novel serum OCN loci, explaining 0.81% and 1.98% of variances of PTH and OCN levels, respectively. MR analysis suggested a causal effect of T2DM on lower circulating OCN concentration (causal effect: −0.03; −0.05 to −0.01; p = 0.006 for T2DM_BBJ and −0.03; −0.05 to −0.01; p = 0.001 for T2DM_EAS). These findings indicate that T2DM might impact bone remodeling and provide a resource for understanding complex relationships between osteocalcin and metabolic (and related) traits in humans. © 2021 American Society for Bone and Mineral Research (ASBMR). [ABSTRACT FROM AUTHOR]

Abstract: The increasing affordability of sequencing and genotyping technologies has transformed the field of molecular ecology in recent decades. By correlating marker variants with trait variation using association analysis, large‐scale genotyping and phenotyping of individuals from wild populations has enabled the identification of genomic regions that contribute to phenotypic differences among individuals. Such “gene mapping” studies are enabling us to better predict evolutionary potential and the ability of populations to adapt to challenges, such as changing environment. These studies are also allowing us to gain insight into the evolutionary processes maintaining variation in natural populations, to better understand genotype‐by‐environment and epistatic interactions and to track the dynamics of allele frequency change at loci contributing to traits under selection. Gene mapping in the wild using genomewide association scans (GWAS) do, however, come with a number of methodological challenges, not least the population structure in space and time inherent to natural populations. We here provide an overview of these challenges, summarize the exciting methodological advances and applications of association mapping in natural populations reported in this special issue and provide some guidelines for future “wild GWAS” research. [ABSTRACT FROM AUTHOR]

Background Conventional meta-analysis based on genetic markers may be less powerful for heterogeneous samples. In this study, we introduced a new meta-analysis for 4 genomewide association studies on alcohol dependence that integrated the information of putative causal variants. Methods A total of 12,481 subjects in 4 independent cohorts were analyzed, including 1 European American cohort (1,409 cases with alcohol dependence and 1,518 controls), 1 European Australian cohort (a total of 6,438 family subjects with 1,645 probands), 1 African American cohort from SAGE + COGA (681 cases and 508 controls), and 1 African American cohort from Yale (1,429 cases and 498 controls). The genomewide association analysis was conducted for each cohort, and then, a new meta-analysis was performed to derive the combined p-values. cis-Acting expression of quantitative locus ( cis-eQTL) analysis of each risk variant in human tissues and RNA expression analysis of each risk gene in rat brain served as functional validation. Results In meta-analysis of European American and European Australian cohorts, we found 10 top-ranked single nucleotide polymorphisms (SNPs) ( p < 10−6) that were associated with alcohol dependence. They included 6 at SERINC2 (3.1 × 10−8 ≤ p ≤ 9.6 × 10−8), 1 at STK40 ( p = 1.3 × 10−7), 2 at KIAA0040 (3.3 × 10−7 ≤ p ≤ 5.2 × 10−7), and 1 at IPO11 ( p = 6.9 × 10−7). In meta-analysis of 2 African American cohorts, we found 2 top-ranked SNPs including 1 at SLC6A11 ( p = 2.7 × 10−7) and 1 at CBLN2 ( p = 7.4 × 10−7). In meta-analysis of all 4 cohorts, we found 2 top-ranked SNPs in PTP4A1- PHF3 locus (6.0 × 10−7 ≤ p ≤ 7.2 × 10−7). In an African American cohort only, we found 1 top-ranked SNP at PLD1 ( p = 8.3 × 10−7; OR = 1.56). Many risk SNPs had positive cis-eQTL signals, and all these risk genes except KIAA0040 were found to express in both rat and mouse brains. Conclusions We found multiple genes that were significantly or suggestively associated with alcohol dependence. They are among the most appropriate for follow-up as contributors to risk for alcohol dependence. [ABSTRACT FROM AUTHOR]

Unraveling the genomic processes at play during variety diversification is of fundamental interest for understanding evolution, but also of applied interest in crop science. It can indeed provide knowledge on the genetic bases of traits for crop improvement and germplasm diversity management. Apple is one of the most important fruit crops in temperate regions, having both great economic and cultural values. Sweet dessert apples are used for direct consumption, while bitter cider apples are used to produce cider. Several important traits are known to differentiate the two variety types, in particular fruit size, biennial versus annual fruit bearing, and bitterness, caused by a higher content in polyphenols. Here, we used an Illumina 8k SNP chip on two core collections, of 48 dessert and 48 cider apples, respectively, for identifying genomic regions responsible for the differences between cider and dessert apples. The genome-wide level of genetic differentiation between cider and dessert apples was low, although 17 candidate regions showed signatures of divergent selection, displaying either outlier FST values or significant association with phenotypic traits (bitter versus sweet fruits). These candidate regions encompassed 420 genes involved in a variety of functions and metabolic pathways, including several colocalizations with QTLs for polyphenol compounds. [ABSTRACT FROM AUTHOR]

Background We conducted a genomewide association study ( GWAS) for maximum number of alcoholic drinks consumed in a 24-hour period ('MaxDrinks'), in 2 independent samples comprised of over 9,500 subjects, following up on our GWAS for alcohol dependence ( AD) in European Americans ( EAs) and African Americans ( AAs). Methods The samples included our GWAS samples (Yale- UPenn) recruited for studies of the genetics of drug or AD, and a publicly available sample: the Study of Addiction: Genetics and Environment ( SAGE). Genomewide association analysis was performed for ~890,000 single nucleotide polymorphisms ( SNPs) using linear association random effects models. EAs and AAs were separately analyzed. Results The results confirmed significant associations of the well-known functional loci at ADH1B with MaxDrinks in EAs (rs1229984 Arg48His p = 5.96 × 10−15) and AAs (rs2066702 Arg370Cys, p = 2.50 × 10−10). The region of significant association on chromosome 4 was extended to LOC100507053 in AAs but not EAs. We also identified potentially novel significant common SNPs for MaxDrinks in EAs in the Yale- UPenn sample: rs1799876 at SERPINC1 on chromosome 1 (4.00 × 10−8) and rs2309169 close to ANKRD36 on chromosome 2 ( p = 5.58 × 10−9). After adjusting for the peak SNP rs1229984 on ADH1B, rs1799876 was nearly significant ( p = 1.99 × 10−7) and rs2309169 remained highly significant (2.12 × 10−9). Conclusions The results provide further support that ADH1B modulates alcohol consumption. Future replications of potential novel loci are warranted. This is the largest MaxDrinks GWAS to date, the first in AAs. [ABSTRACT FROM AUTHOR]

Background The risk of alcohol-related liver cirrhosis increases with increasing alcohol consumption, but many people with very high intake escape from liver disease. We postulate that susceptibility to alcoholic cirrhosis has a complex genetic component and propose that this can be dissected through a large and sufficiently powered genomewide association study ( GWAS). Methods The Genom ALC Consortium comprises researchers from Australia, France, Germany, Switzerland, United Kingdom, and United States, with a joint aim of exploring the genetic and genomic basis of alcoholic cirrhosis. For this National Institutes of Health/National Institute on Alcohol Abuse and Alcoholism funded study, we are recruiting high-risk drinkers who are either cases (with alcoholic cirrhosis) or controls (drinking comparable amounts over similar time, but free of significant liver disease). Extensive phenotypic data are obtained using semistructured interviews and patient records, and blood samples are collected. Results We have successfully recruited 859 participants including 538 matched case-control samples as of September 2014, using study-specific inclusion-exclusion criteria and data collection protocols. Of these, 580 are cases (442 men and 138 women) and 279 are controls (205 men and 74 women). Duration of excessive drinking was slightly greater in cases than controls and was significantly less in women than men. Cases had significantly lower lifetime alcohol intake than controls. Both cases and controls had a high prevalence of reported parental alcohol problems, but cases were significantly more likely to report that a father with alcohol problems had died from liver disease (odds ratio 2.53, 95% confidence interval 1.31 to 4.87, p = 0.0055). Conclusions Recruitment of participants for a GWAS of alcoholic cirrhosis has proved feasible across countries with multiple sites. Affected patients often consume less alcohol than unaffected ones, emphasizing the existence of individual vulnerability factors. Cases are more likely to report liver disease in a father with alcohol problems than controls, consistent with a potential genetic component to the risk of alcoholic cirrhosis. [ABSTRACT FROM AUTHOR]

Genome-wide association studies explore the relationship between genome variability and disease susceptibility with either population- or family-based data. Here, we have evaluated the utility of combining population- and family-based statistical association tests and have proposed a method for reducing the burden of multiple testing.Unrelated singleton and parent-offspring trio cases and controls from the Genetics of Kidneys in Diabetes study were analyzed for genetic association with diabetic nephropathy (DN) in type 1 diabetics. The Cochran-Armitage test for trend and the family-based association test were employed using either unrelated cases and controls or trios, respectively. In addition to combining single nucleotide polymorphism (SNP) p-values across these tests via Fisher’s method, we employed a novel screening approach to rank SNPs based on conditional power for more efficient testing.Using either the population-based or family-based subset alone predictably limited resolution to detect DN SNPs. For 384,197 SNPs passing quality control (QC), none achieved strict genome-wide significance (1.4 x 10-7) using 1171 singletons (577/594 cases/controls) or 1738 pooled singletons and offspring probands (841/897). Similarly, none of the 352,004 SNPs passing QC in 567 family trios (264/303 case/control proband trios) reached genome-wide significance. Testing the top 10 SNPs ranked using aggregated conditional power resulted in two SNPs reaching genome-wide significance, rs11645147 on chromosome 16 (p=1.74 x 10-4 < 0.05/10=0.005) and rs7866522 on chromosome 9 (p=0.0033).Efficient usage of mixed designs incorporating both unrelated and family-based data may help to uncover associations otherwise difficult to detect in the presence of massive multiple testing corrections. Capitalizing on the strengths of both types while using screening approaches may be useful especially in light of large-scale, next-generation sequencing and rare variant studies.

Osteochondrosis (OC) is an orthopedic syndrome of the joints that occurs in children and adolescents and domestic animals, particularly pigs, horses, and dogs. OC is the most frequent cause of leg weakness in rapidly growing pigs causing animal welfare issues and economic losses. In this study, a genomewide association study (GWAS) was performed using the Porcine 60k SNPChip in animals of the breed Large White (n=298) to identify chromosome regions and candidate genes associated with OC lesion scores. A total of 19 SNPs on chromosomes (SSC) 3, 5, 8, 10, 14 and 18 were significantly associated with OC lesion scores (p-values ≤ 10-5). The SNPs MARC0098684, MARC00840086, MARC0093124 and ASGA0062794 at SSC14 36.1 to 38.2 Mb encompass a region of six linkage disequilibrium (LD) blocks. The most significant SNP ASGA0062794 is located in a LD block spanning 465 kb and covering the gene encoding T-box transcription factor 5 (TBX5). A SNP (c.54T>C) identified in TBX5 was significantly associated with OC lesions scores in a single marker analysis. TBX5 c.54T>C showed highest linkage disequilibrium with ASGA00627974 (r2=0.96) and superior association with OC lesion scores over other SNPs when included in the genome scan, whereas its treatment as an additional fixed effect in the GWAS statistical model led to a drop of significance of nearby markers. Moreover, real time PCR showed different transcript abundance of TBX5 in healthy and defect cartilage. The results imply that the association signal obtained on SCC14 is largely attributable to TBX5 c.54T>C likely to be in linkage disequilibrium with a regulatory polymorphism of TBX5. The transcription factor TBX5 interacts with GJA5 and MEF2C both being involved in vascularization. This study provides evidence for epistatic interaction of TBX5 and MEF2C, thus supporting deficiency of blood supply to growth cartilage as being fundamental for the initiation of osteochondrosis.

Enteric ruminant methane is the most important greenhouse gas emitted from the pastoral agricultural systems. Genetic improvement of livestock provides a cumulative and permanent impact on performance, and using high-density SNP panels can increase the speed of improvement for most traits. In this study, a data set of 1,726 dairy cows, collected since 1990, was used to calculate a predicted methane emission (PME) trait from feed and energy intake and requirements based on milk yield, live weight, feed intake, and condition score data. Repeated measurements from laser methane detector (LMD) data were also available from 57 cows. The estimated heritabilities for PME, milk yield, DMI, live weight, condition score, and LMD data were 0.13, 0.25, 0.11, 0.92, 0.38, and 0.05, respectively. There was a high genetic correlation between DMI and PME. No SNP reached the Bonferroni significance threshold for the PME traits. One SNP was within the 3 best SNP for PME at wk 10, 20, 30, and 40. Genomic prediction accuracies between dependent variable and molecular breeding value ranged between 0.26 and 0.30. These results are encouraging; however, more work is required before a PME trait can be implemented in a breeding program. [ABSTRACT FROM AUTHOR]

A primary challenge in identifying replicable pharmacogenomic markers from clinical genomewide association study (GWAS) trials in oncology is the difficulty in performing a second large clinical trial with the same drugs and dosage regimen. We sought to overcome this challenge by incorporating GWAS results from cell-based studies using the same chemotherapy as a clinical cohort.In this study, we test whether the overlap between genetic variants identified in a preclinical study and a clinical study on capecitabine is more than expected by chance. A GWAS of capecitabine-induced cytotoxicity was performed in 164 lymphoblastoid cell lines derived from the CEU HapMap population and compared with a GWAS of hand-foot syndrome (HFS), the most frequent capecitabine-induced adverse drug reaction, in Spanish breast and colorectal cancer patients (n=160) treated with capecitabine.We observed an overlap of 16 single nucleotide polymorphisms associated with capecitabine-induced cytotoxicity (P<0.001) in lymphoblastoid cell lines and HFS (P<0.05) in patients, which is a greater overlap than expected by chance (genotype-phenotype permutation empirical P=0.015). Ten tag single nucleotide polymorphisms, which cover the overlap loci, were genotyped in a second patient cohort (n=85) and one of them, rs9936750, was associated with capecitabine-induced HFS (P=0.0076).The enrichment results imply that cellular models of capecitabine-induced cytotoxicity may capture components of the underlying polygenic architecture of related toxicities in patients. [ABSTRACT FROM AUTHOR]

A preliminary attempt at collecting tools and utilities for genetic data as an R package called gap is described. Genomewide association is then described as a specific example, linking the work of Risch and Merikangas (1996), Long and Langley (1997) for family-based and population-based studies, and the counterpart for case-cohort design established by Cai and Zeng (2004). Analysis of staged design as outlined by Skol et al. (2006) and associate methods are discussed. The package is flexible, customizable, and should prove useful to researchers especially in its application to genomewide association studies.

Objectives: Nonalcoholic fatty liver disease (NAFLD) ranges from simple steatosis to hepatic inflammation to cirrhosis. We sought to identify common genetic variants contributing to NAFLD, using CT measured fatty liver (FL), and alanine aminotransferase levels (ALT), as a biochemical marker of hepatic inflammation. Methods: We employed a correlated meta-analysis (CMA) to test whether combining FL and ALT genomewide association (GWA) results, using ∼2.5 million imputed SNPs, could enhance ability to detect variants influencing both traits. Results: Variants of the ERLIN1-CHUK-CWF19L1 gene cluster were associated with concomitant variation of FL and ALT. Nine variants (rs2862954, rs1408579, rs10883451, rs11597086, rs11591741, rs17729876, rs17668255, rs17668357, rs12784396) displayed genomewide significant associations at loci concomitantly influencing FL and ALT (2.47 × 10−9 ≤ CMA-p ≤ 4.29 × 10−10) as compared with the suggestive significance of marginal tests (4.11 × 10−5 ≤ GWA-p ≤ 2.34 × 10−6). For example, the missense variant in ERLIN1-rs2862954 was genomewide significant (CMA-p = 4.88 × 10−10) for the combination of FL and ALT, while the respective univariate associations were suggestive (FL:p = 5.74 × 10−6, ALT:p = 3.71 × 10−6). Further we investigated whether the concomitant associations were driven mainly by ALT levels. When we adjusted FL by ALT, the correlated associations diminished but did not vanish (CMA-p ≤ 3.3 × 10−7). Our findings suggest ERLIN1-CHUK-CWF19L1 variants are associated with early stage of FL accumulation (measured by CT) to hepatic inflammation (ALT levels), and the association enhances when accounting for the correlations between their scans. Conclusions: CMA approach enhanced the ability to identify novel variants of the ERLIN1-CHUK-CWF19L1 influencing both simple steatosis and hepatic steatosis with inflammation, which suggest that this gene cluster may regulate the susceptibility of NAFLD in a wide spectrum of disease. [ABSTRACT FROM AUTHOR]

The advent of economically viable high-throughput genetic and genomic techniques has equipped animal geneticists with an unprecedented ability to generate massive amounts of molecular data. As a result, large lists of genes differentially expressed in many experimental conditions of interests have been reported and, likewise, the association of an ever growing number of DNA variants with phenotypes of importance is now a routine endeavor. Although these studies have greatly improved our understanding of the genetic basis of complex phenotypes, they have also revealed the difficulty in explaining more than a fraction of the genetic variance. Inspired by this data-rich and knowledge-poor dichotomy, systems biology aims at the formal integration of seemingly disparate datasets allowing for a holistic view where key properties of the systems emerge as an intuitive feature and enable the generation of testable hypotheses. Herein, we present 2 examples of integrating molecular data anchored in the power of gene network inference. The first example is concerned with the onset of puberty in Bos indicus-influenced cows bred in Australia. Using the results from genomewide association studies across a range of phenotypes, we developed what we termed an association weight matrix to generate a gene network underlying phenotypes of puberty in cattle. The network was mined for the minimal set of transcription factor genes whose predicted target spanned the majority of the topology of the entire network. The second example deals with piebald, a pigmentation phenotype in Merino sheep. Two networks were developed: a regulatory network and an epistatic network. The former is inferred based on promoter sequence analysis of differentially expressed genes. The epistatic network is built from 2-locus models among all pairwise associated polymorphisms. At the intersection between these 2 networks, we revealed a set of genes and gene-gene interactions of validated and de novo predicted relevance to the piebald phenotype. We argue that these new approaches are holistic and therefore more appropriate than traditional approaches for investigating genetic mechanisms underlying complex phenotypes of importance in livestock species. [ABSTRACT FROM AUTHOR]

Understanding individual differences in the susceptibility to metabolic side effects as a response to antipsychotic therapy is essential to optimize the treatment of schizophrenia. Here, we perform genomewide association studies (GWAS) to search for genetic variation affecting the susceptibility to metabolic side effects. The analysis sample consisted of 738 schizophrenia patients, successfully genotyped for 492K single nucleotide polymorphisms (SNPs), from the genomic subsample of the Clinical Antipsychotic Trial of Intervention Effectiveness study. Outcomes included 12 indicators of metabolic side effects, quantifying antipsychotic-induced change in weight, blood lipids, glucose and hemoglobin A1c, blood pressure and heart rate. Our criterion for genomewide significance was a pre-specified threshold that ensures, on average, only 10% of the significant findings are false discoveries. A total of 21 SNPs satisfied this criterion. The top finding indicated that a SNP in Meis homeobox 2 (MEIS2) mediated the effects of risperidone on hip circumference (q=0.004). The same SNP was also found to mediate risperidone's effect on waist circumference (q=0.055). Genomewide significant finding were also found for SNPs in PRKAR2B, GPR98, FHOD3, RNF144A, ASTN2, SOX5 and ATF7IP2, as well as in several intergenic markers. PRKAR2B and MEIS2 both have previous research indicating metabolic involvement, and PRKAR2B has previously been shown to mediate antipsychotic response. Although our findings require replication and functional validation, this study shows the potential of GWAS to discover genes and pathways that potentially mediate adverse effects of antipsychotic medication. [ABSTRACT FROM AUTHOR]

The article discusses a study which aims to describe the use of twin studies in attention-deficit/hyperactivity disorder (ADHD) research and their identification of alternative phenotypes that are suitable for development risk assessment and intervention targets. It states that research groups use twin studies to identify endophenotypes for ADHD. The study reveals that failure of genomewide association studies of ADHD to identify replicable associations for heritable variation.

Background: Understanding individual differences in the development of extrapyramidal side effects (EPS) as a response to antipsychotic therapy is essential to individualize treatment. Methods: We performed genomewide association studies to search for genetic susceptibility to EPS. Our sample consisted of 738 schizophrenia patients, genotyped for 492K single nucleotide polymorphisms (SNPs). We studied three quantitative measures of antipsychotic adverse drug reactions—the Simpson-Angus Scale (SAS) for Parkinsonism, the Barnes Akathisia Rating Scale, and the Abnormal Involuntary Movement Scale (AIMS)—as well as a clinical diagnosis of probable tardive dyskinesia. Results: Two SNPs for SAS, rs17022444 and rs2126709 with p = 1.2 × 10−10 and p = 3.8 × 10−7, respectively, and one for AIMS, rs7669317 with p = 7.7 × 10−8, reached genomewide significance (Q value < .1). rs17022444 and rs7669317 were located in intergenic regions and rs2126709 was located in ZNF202 on 11q24. Fourteen additional signals were potentially interesting (Q value < .5). The ZNF202 is a transcriptional repressor controlling, among other genes, PLP1, which is the major protein in myelin. Mutations in PLP1 cause Pelizaeus-Merzbacher disease, which has Parkinsonism as an occurring symptom. Altered mRNA expression of PLP1 is associated with schizophrenia. Conclusions: Although our findings require replication and validation, this study demonstrates the potential of genomewide association studies to discover genes and pathways that mediate adverse effects of antipsychotics. [Copyright &y& Elsevier]

Genomewide association (GWA) studies assay hundreds of thousands of single nucleotide polymorphisms (SNPs) simultaneously across the entire genome and associate them with diseases, other biological or clinical traits. The association analysis usually tests each SNP as an independent entity and ignores the biological information such as linkage disequilibrium. Although the Bonferroni correction and other approaches have been proposed to address the issue of multiple comparisons as a result of testing many SNPs, there is a lack of understanding of the distribution of an association test statistic when an entire genome is considered together. In other words, there are extensive efforts in hypothesis testing, and almost no attempt in estimating the density under the null hypothesis. By estimating the true null distribution, we can apply the result directly to hypothesis testing; better assess the existing approaches of multiple comparisons; and evaluate the impact of linkage disequilibrium on the GWA studies. To this end, we estimate the empirical null distribution of an association test statistic in GWA studies using simulated population data. We further propose a convenient and accurate method based on adaptive spline to estimate the empirical value in GWA studies and validate our findings using a real data set. Our method enables us to fully characterize the null distribution of an association test that not only can be used to test the null hypothesis of no association, but also provides important information about the impact of density of the genetic markers on the significance of the tests. Our method does not require users to perform computationally intensive permutations, and hence provides a timely solution to an important and difficult problem in GWA studies. [ABSTRACT FROM AUTHOR]

Abstract: Advances in genotyping technologies have facilitated the advent of the genomewide association studies in large study populations and thereby led to the identification of an impressive—and still increasing—number of genetic variants with significant impact on the risk of widespread lifestyle health problems such as obesity, diabetes, and cardiovascular disease. Yet, the scientific community is a long way from reaching a comprehensive picture of the heritable components of these diseases and advancing from plain statistical significance into a biological understanding where the true contribution to a trait is recognized. Increasingly large study populations, denser single-nucleotide polymorphism mapping, deep sequencing, and raised awareness of the importance of structural variants may add to the known genetic variance underlying common complex disorders; however, genetic variance alone probably cannot account for disease susceptibility without the addition of pre- and postnatal environmental and/or behavioral factors. Moreover, an interaction between genetic and environmental factors may hinder the detection of genetic effects if not accounted for, e.g., in genomewide association studies, and prospective cohort studies have hence been proposed to surpass the classic case–control design. With a focus on obesity we describe some of the recently reported gene–environment interactions for polymorphisms identified in the FTO and INSIG2 genes. Ultimately, a thorough understanding of the gene–environment interactions underlying a common complex condition such as obesity may suggest novel treatment or intervention strategies to complement the harmful effect of detrimental genetic variation and thus may assist in improving the quality of life for affected individuals. [Copyright &y& Elsevier]

Abundant evidence from family, adoption, and twin studies point to large genetic contributions to individual differences in vulnerability to develop dependence on one or more addictive substances. Twin data suggest that most of this genetic vulnerability is shared by individuals who are dependent on a variety of addictive substances. Molecular genetic studies, especially genomewide and candidate gene association studies, have elucidated common haplotypes in dozens of genes that appear to make polygenic contributions to vulnerability to developing dependence. Most genes that harbor currently identified addiction-associated haplotypes are expressed in the brain. Haplotypes in many of the same genes are identified in genomewide association studies that compare allele frequencies in substance dependent vs. control individuals from European, African, and Asian racial/ethnic backgrounds. Many of these addiction-associated haplotypes display pleiotropic influences on a variety of related brain-based phenotypes that display 1) substantial heritability and 2) clinical cooccurence with substance dependence. [ABSTRACT FROM AUTHOR]

Variance components methods have been used in various aspects of genetic analysis for many decades. This article discusses their application to data on quantitative traits for the estimation of polygenic and environmental variances as well as, for the detection of quantitative trait loci using methods of linkage and association. Multivariate approaches are discussed, along with regression-based related methods. Additionally, examples of the application of these methods from the literature are presented. [ABSTRACT FROM AUTHOR]

Widely used measures of the environment, especially the family environment of children, show genetic influence in dozens of twin and adoption studies. This phenomenon is known as gene-environment correlation in which genetically driven influences of individuals affect their environments. We conducted the first genome-wide association (GWA) analysis of an environmental measure. We used a measure called CHAOS which assesses ‘environmental confusion’ in the home, a measure that is more strongly associated with cognitive development in childhood than any other environmental measure. CHAOS was assessed by parental report when the children were 3 years and again when the children were 4 years; a composite CHAOS measure was constructed across the 2 years. We screened 490,041 autosomal single-nucleotide polymorphisms (SNPs) in a two-stage design in which children in low chaos families ( N = 469) versus high chaos families ( N = 369) from 3,000 families of 4-year-old twins were screened in Stage 1 using pooled DNA. In Stage 2, following SNP quality control procedures, 41 nominated SNPs were tested for association with family chaos by individual genotyping an independent representative sample of 3,529. Despite having 99% power to detect associations that account for more than 0.5% of the variance, none of the 41 nominated SNPs met conservative criteria for replication. Similar to GWA analyses of other complex traits, it is likely that most of the heritable variation in environmental measures such as family chaos is due to many genes of very small effect size. [ABSTRACT FROM AUTHOR]

Little is known for certain about the genetics of schizophrenia. The advent of genomewide association has been widely anticipated as a promising means to identify reproducible DNA sequence variation associated with this important and debilitating disorder. A total of 738 cases with DSM-IV schizophrenia (all participants in the CATIE study) and 733 group-matched controls were genotyped for 492 900 single-nucleotide polymorphisms (SNPs) using the Affymetrix 500K two-chip genotyping platform plus a custom 164K fill-in chip. Following multiple quality control steps for both subjects and SNPs, logistic regression analyses were used to assess the evidence for association of all SNPs with schizophrenia. We identified a number of promising SNPs for follow-up studies, although no SNP or multimarker combination of SNPs achieved genomewide statistical significance. Although a few signals coincided with genomic regions previously implicated in schizophrenia, chance could not be excluded. These data do not provide evidence for the involvement of any genomic region with schizophrenia detectable with moderate sample size. However, a planned genomewide association study for response phenotypes and inclusion of individual phenotype and genotype data from this study in meta-analyses hold promise for eventual identification of susceptibility and protective variants.Molecular Psychiatry (2008) 13, 570–584; doi:10.1038/mp.2008.25; published online 18 March 2008 [ABSTRACT FROM AUTHOR]

General cognitive ability ( g), which refers to what cognitive abilities have in common, is an important target for molecular genetic research because multivariate quantitative genetic analyses have shown that the same set of genes affects diverse cognitive abilities as well as learning disabilities. In this first autosomal genome-wide association scan of g, we used a two-stage quantitative trait locus (QTL) design with pooled DNA to screen more than 500 000 single nucleotide polymorphisms (SNPs) on microarrays, selecting from a sample of 7000 7-year-old children. In stage 1, we screened for allele frequency differences between groups pooled for low and high g. In stage 2, 47 SNPs nominated in stage 1 were tested by individually genotyping an independent sample of 3195 individuals, representative of the entire distribution of g scores in the full 7000 7-year-old children. Six SNPs yielded significant associations across the normal distribution of g, although only one SNP remained significant after a false discovery rate of 0.05 was imposed. However, none of these SNPs accounted for more than 0.4% of the variance of g, despite 95% power to detect associations of that size. It is likely that QTL effect sizes, even for highly heritable traits such as cognitive abilities and disabilities, are much smaller than previously assumed. Nonetheless, an aggregated ‘SNP set’ of the six SNPs correlated 0.11 ( P < 0.00000003) with g. This shows that future SNP sets that will incorporate many more SNPs could be useful for predicting genetic risk and for investigating functional systems of effects from genes to brain to behavior. [ABSTRACT FROM AUTHOR]