Phenotype Association Analysis Research Articles

Human adaptation to arsenic in Bolivians living in the Andes

Humans living in the Andes Mountains have been historically exposed to arsenic from natural sources, including drinking water. Enzymatic methylation of arsenic allows it to be excreted more efficiently by the human body. Adaptation to high-arsenic environments via enhanced methylation and excretion of arsenic was first reported in indigenous women in the Argentinean Andes, but whether adaptation to arsenic is a general phenomenon across native populations from the Andes Mountains remains unclear. Therefore, we evaluated whether adaptation to arsenic has occurred in the Bolivian Andes by studying indigenous groups who belong to the Aymara-Quechua and Uru ethnicities and have lived in the Bolivian Andes for generations. Our population genetics methods, including genome-wide selection scans based on linkage disequilibrium patterns and allele frequency differences, in combination with targeted and whole-genome sequencing and genotype–phenotype association analyses, detected signatures of positive selection near the gene encoding arsenite methyltransferase (AS3MT), the main arsenic methylating enzyme. This was among the strongest selection signals (top 0.5% signals via locus-specific branch length and extended haplotype homozygosity tests) at a genome-wide level in the Bolivian study groups. We found a large haplotype block of 676 kb in the AS3MT region and identified candidate functional variants for further analysis. Moreover, our analyses revealed associations between AS3MT variants and the fraction of mono-methylated arsenic in urine and showed that the Bolivian study groups had the highest frequency of alleles associated with more efficient arsenic metabolism reported so far. Our data support the idea that arsenic exposure has been a driver for human adaptation to tolerate arsenic through more efficient arsenic detoxification in different Andean populations.

Four novel candidate causal variants for deficient homozygous haplotypes in Holstein cattle

Mendelian variants can determine both insemination success and neonatal survival and thus influence fertility and rearing success of cattle. We present 24 deficient homozygous haplotype regions in the Holstein population of Switzerland and provide an overview of the previously identified haplotypes in the global Holstein breed. This study encompasses massive genotyping, whole-genome sequencing (WGS) and phenotype association analyses. We performed haplotype screenings on almost 53 thousand genotyped animals including 114 k SNP data with two different approaches. We revealed significant haplotype associations to several survival, birth and fertility traits. Within haplotype regions, we mined WGS data of hundreds of bovine genomes for candidate causal variants, which were subsequently evaluated by using a custom genotyping array in several thousand breeding animals. With this approach, we confirmed the known deleterious SMC2:p.Phe1135Ser missense variant associated with Holstein haplotype (HH) 3. For two previously reported deficient homozygous haplotypes that show negative associations to female fertility traits, we propose candidate causative loss-of-function variants: the HH13-related KIR2DS1:p.Gln159* nonsense variant and the HH21-related NOTCH3:p.Cys44del deletion. In addition, we propose the RIOX1:p.Ala133_Glu142del deletion as well as the PCDH15:p.Leu867Val missense variant to explain the unexpected low number of homozygous haplotype carriers for HH25 and HH35, respectively. In conclusion, we demonstrate that with mining massive SNP data in combination with WGS data, we can map several haplotype regions and unravel novel recessive protein-changing variants segregating at frequencies of 1 to 5%. Our findings both confirm previously identified loci and expand the spectrum of undesired alleles impairing reproduction success in Holstein cattle, the world's most important dairy breed.

Phenotypic Characterization and Association Analysis of Tomato (Solanum lycopersicum L.) Accessions.

In this study, 36 tomato accessions were subjected to variability and correlation analysis based on seventeen yield and quality traits. The traits viz., plant height, number of clusters plant-1 , number of fruits plant-1 , ascorbic acid content and single fruit weight were exhibited a high level of variability, heritability and genetic advance as per cent of mean and these traits are positive and significantly associated with yield, which is clearly indicates that these traits are highly responsive and simple selection is very appropriate. Per cent fruit set negatively associated with earliness and its exhibited moderate level of variability shows the presence of non-additive gene action. Lycopene and β-carotene were not substantially linked with any of the traits but these are highly heritable in nature, to incorporate these two traits into any breeding programme, the parents must be excellent in these particular quality parameters.

OmicsOne: associate omics data with phenotypes in one-click

BackgroundThe rapid advancements of high throughput “omics” technologies have brought a massive amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset and the discovery of interesting genes, proteins, lipids, glycans, metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed for data analysis and visualization. However, it still lacks an efficient way to investigate the phenotypes with multiple omics data. Here, we present OmicsOne as an interactive web-based framework for rapid phenotype association analysis of multi-omic data by integrating quality control, statistical analysis, and interactive data visualization on ‘one-click’.Materials and methodsOmicsOne was applied on the previously published proteomic and glycoproteomic data sets of high-grade serous ovarian carcinoma (HGSOC) and the published proteome data set of lung squamous cell carcinoma (LSCC) to confirm its performance. The data was analyzed through six main functional modules implemented in OmicsOne: (1) phenotype profiling, (2) data preprocessing and quality control, (3) knowledge annotation, (4) phenotype associated features discovery, (5) correlation and regression model analysis for phenotype association analysis on individual features, and (6) enrichment analysis for phenotype association analysis on interested feature sets.ResultsWe developed an integrated software solution, OmicsOne, for the phenotype association analysis on multi-omics data sets. The application of OmicsOne on the public data set of ovarian cancer data showed that the software could confirm the previous observations consistently and discover new evidence for HNRNPU and a glycopeptide of HYOU1 as potential biomarkers for HGSOC data sets. The performance of OmicsOne was further demonstrated in the Tumor and NAT comparison study on the proteome data set of LSCC.ConclusionsOmicsOne can effectively simplify data analysis and reveal the significant associations between phenotypes and potential biomarkers, including genes, proteins, and glycopeptides, in minutes to assist users to understand aberrant biological processes.

A Genome-Wide Association Study Identifies Novel Risk Loci for Sarcopenia in a Taiwanese Population.

PurposeA genome-wide association study (GWAS) of sarcopenia unraveled the importance of genetic contribution to decline in muscle. The current study investigated sarcopenia-related single nucleotide polymorphisms (SNPs) in Asian older adults, and further constructed a genotype score that tests the combined effect of these SNPs on risk of sarcopenia.Patients and MethodsNinety-six subjects aged 60 or above were recruited from the database of annual geriatric health examination at Tri-Service General Hospital during 2020. Eligible criteria included: 1) not having severe comorbidities; 2) agreed to join the Taiwan Precision Medicine Initiative project; and 3) having sufficient information of required sarcopenic measurements. Genotype–phenotype association analysis was performed to find SNPs that were significantly associated with each of three sarcopenic indices (low muscle mass, muscle strength, and physical performance). Subsequently, these SNPs comprised a sarcopenia-related genotype score that summed up the number of SNPs carrying unfavorable allele(s).ResultsTwelve SNPs revealed suggestive genome-wide significance with the three sarcopenic indices, and eight of them revealed a relationship with more than one index. Low muscle strength was the item that had the most (eight) related SNPs. Among them, rs10282247 affects cholesterol binding and rs7022373 participates in cellular apoptosis. In addition, higher genotype score demonstrated higher risk of sarcopenia (≥4 points: OR=630.6; 2–3 points: OR=408, p-value<0.001).ConclusionSeveral newly discovered SNPs suggest that genetic contribution plays a part in the pathogenesis of sarcopenia. Further studies are warranted to verify the underlying mechanisms. Moreover, a genotype score provides an estimate of the combined effect of genetic association with sarcopenia, which may modestly improve clinical risk classification.

Predicting the herbal medicine triggering innate anti-tumor immunity from a system pharmacology perspective

Although the main focus of immuno-oncology has been manipulating the adaptive immune system, tumor associated macrophages (TAMs) are the main infiltrating component in the tumor microenvironment (TME) and play a critical role in cancer progression. TAMs are mainly divided into two different subtypes: macrophages with antitumor or killing activity are called M1 while tumor-promoting or healing macrophages are named M2. Therefore, controlling the polarization of TAMs is an important strategy for cancer treatment, but there is no particularly effective means to regulate the polarization process. Here, combined systems pharmacology targets and pathways analysis strategy, we uncovered Scutellariae Radix (SR) has the potential to regulate TAMs polarization to inhibit the growth of non-small cell lung cancer (NSCLC). Firstly, systems pharmacology approach was used to reveal the active components of SR targeting macrophages in TME through compound target prediction and target-microenvironment phenotypic association analysis. Secondly, in vitro experiment verified that WBB (wogonin, baicalein and baicalin), major active ingredients of SR are significantly related to macrophages and survival, initiated macrophages programming to M1-like macrophages to promoted the apoptosis of tumor cells. Finally, we evidenced that WBB effectively inhibited tumor growth in LLC (Lewis lung carcinoma) tumor-bearing mice and increased the infiltration of M1-type macrophages in TME. Overall, the systems pharmacology strategy offers a paradigm to understand the mechanism of polypharmacology of natural products targeting TME.

Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

BackgroundSleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.MethodsThe study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.ResultsWe identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10−8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.ConclusionsWe have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

A SNP within the PMCH gene as a molecular marker associated with fertility traits in Angus and Brangus beef heifers raised under a desert environment.

Components of the GH/IGF1 endocrine axis regulate growth and reproductive traits in cattle. The pro-melanin-concentrating hormone (PMCH) gene located within chromosome 5 belongs to this axis. Objective herein was to evaluate PMCH single-nucleotide polymorphisms (SNPs) as molecular markers associated with age at first calving, calving interval, and age at second calving in Angus and Brangus beef heifers raised in desert conditions. Five SNPs within the PMCH gene were included in the study. Three of these SNPs had minor allele frequency > 10% and only one SNP did not deviate from Hardy-Weinberg equilibrium. A genotype to phenotype association analyses was performed using a mixed-effects model which included phenotype as the response variable, SNP genotype, breed, year of birth and age of dam as fixed terms, and sire as a random effect. Genotypes from the SNP rs135033882 were found to be associated (P < 0.05) with all evaluated fertility traits, and the term breed resulted as a significant source of variation only for age at second calving. The allele A was the favorable allele because it decreased the age at first calving 98.6days, the calving interval 85.3days, and the age at second calving 183.1days, in Angus and Brangus heifers. In conclusion, we proposed a SNP within the PMCH gene as a potential candidate marker associated with reproductive performance in Angus and Brangus beef heifers raised in a desert climate.

Identification of Candidate Genes for Root Traits Using Genotype-Phenotype Association Analysis of Near-Isogenic Lines in Hexaploid Wheat (Triticum aestivum L.).

Global wheat (Triticum aestivum L.) production is constrained by different biotic and abiotic stresses, which are increasing with climate change. An improved root system is essential for adaptability and sustainable wheat production. In this study, 10 pairs of near-isogenic lines (NILs)—targeting four genomic regions (GRs) on chromosome arms 4BS, 4BL, 4AS, and 7AL of hexaploid wheat—were used to phenotype root traits in a semi-hydroponic system. Seven of the 10 NIL pairs significantly differed between their isolines for 11 root traits. The NIL pairs targeting qDSI.4B.1 GR varied the most, followed by the NIL pair targeting qDT.4A.1 and QHtscc.ksu-7A GRs. For pairs 5–7 targeting qDT.4A.1 GR, pair 6 significantly differed in the most root traits. Of the 4 NIL pairs targeting qDSI.4B.1 GR, pairs 2 and 4 significantly differed in 3 and 4 root traits, respectively. Pairs 9 and 10 targeting QHtscc.ksu-7A GR significantly differed in 1 and 4 root traits, respectively. Using the wheat 90K Illumina iSelect array, we identified 15 putative candidate genes associated with different root traits in the contrasting isolines, in which two UDP-glycosyltransferase (UGT)-encoding genes, TraesCS4A02G185300 and TraesCS4A02G442700, and a leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding gene, TraesCS4A02G330900, also showed important functions for root trait control in other crops. This study characterized, for the first time, that these GRs control root traits in wheat, and identified candidate genes, although the candidate genes will need further confirmation and validation for marker-assisted wheat breeding.

Short communication: Genotype-phenotype association analysis revealed different utilization ability of 2'-fucosyllactose in Bifidobacterium genus

The oligosaccharide 2'-fucosyllactose (2'FL) in human breast milk selectively promotes the proliferation of bifidobacteria. One hundred fifty-one Bifidobacterium strains were evaluated for their capacity to utilize 2'FL based on the combination of phenotype and genotype association analysis. Through genotype analysis, 37 strains were predicted to have the ability to use 2'FL, including Bifidobacteriumbifidum, Bifidobacteriumbreve, Bifidobacteriumlongum ssp. longum, Bifidobacteriumlongum ssp. infantis, and Bifidobacteriumdentium, whereas Bifidobacteriumadolescentis, Bifidobacteriumanimalis, Bifidobacteriumpseudocatenulatum, and Bifidobacteriumangulatum could not use 2'FL. For in vitro utilization, there were noteworthy differences for 2'FL usage among different species, which were 100% consistent with genotype prediction. The results indicated that 2'FL utilization ability differed even within the same species, and Bifidobacterium followed the currently well-known pathway to utilize 2'FL, which could provide guidance to develop personalized prebiotics for different bifidobacteria via gene-trait matching analysis.

Assessment of the Interaction of Aggregatin Protein with Amyloid-Beta (Aβ) at the Molecular Level via In Silico Analysis

Alzheimer's disease is a major neurodegenerative illness whose prevalence is increasing worldwide but the molecular mechanism remains unclear. There is some scientific evidence that the molecular complexity of Alzheimer's pathophysiology is associated with the formation of extracellular amyloid-beta plaques in the brain. A novel cross- phenotype association analysis of imaging genetics reported a brain atrophy susceptibility gene, namely FAM222A and the protein Aggregatin encoded by FAM222A interacts with amyloid-beta (A?)-peptide (1-42) through its N-terminal A? binding domain and facilitates A? aggregation. The function of Aggregatin protein is unknown, and its three-dimensional structure has not been analyzed experimentally yet. Our goal was to investigate the interaction of Aggregatin with A? in detail by in silico analysis, including the 3D structure prediction analysis of Aggregatin protein by homology modeling. Our analysis verified the interaction of the C-terminal domain of model protein with the N-terminal domain of A?. This is the first attempt to demonstrate the interaction of Aggregatin with the A?. These results confirmed in vitro and in vivo study reports claiming FAM222A helping to ease the aggregating of the A?-peptide.

System biology analysis reveals the role of voltage-dependent anion channel in mitochondrial dysfunction during non-alcoholic fatty liver disease progression into hepatocellular carcinoma.

Non‐alcoholic fatty liver disease (NAFLD) is one of the most common causes of hepatocellular carcinoma (HCC), but the underlying mechanisms behind the correlation of NAFLD with HCC are unclear. We aimed to uncover the genes and potential mechanisms that drive this progression. This study uncovered the genes and potential mechanisms through a multiple ’omics integration approach. Quantitative proteomics combined with phenotype‐association analysis was performed. To investigate the potential mechanisms, a comprehensive transcriptome/lipidome/phenome‐wide association analysis was performed in genetic reference panel BXD mice strains. The quantitative proteomics combined with phenotype‐association results showed that VDAC1 was significantly increased in tumor tissues and correlated with NAFLD‐related traits. Gene co‐expression network analysis indicated that VDAC1 is involved in mitochondria dysfunction in the tumorigenic/tumor progression. The association between VDAC1 and mitochondria dysfunction can be explained by the fact that VDAC1 was associated with mitochondria membrane lipids cardiolipin (CL) composition shift. VDAC1 was correlated with the suppression of mature specie CL(LLLL) and elevation level of nascent CL species. Such profiling shift was supported by the significant positive correlation between VDAC1 and PTPMT1, as well as negative correlation with CL remodeling enzyme Tafazzin (TAZ). This study confirmed that the expression of VADC1 was dysregulated in NAFLD‐driven HCC and associated with NAFLD progression. The VDAC1‐driven mitochondria dysfunction is associated with cardiolipin composition shift, which causes alteration of mitochondria membrane properties.

Integrative analyses prioritize GNL3 as a risk gene for bipolar disorder.

Genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) associated with bipolar disorder (BD), but what the causal variants are and how they contribute to BD is largely unknown. In this study, we used FUMA, a GWAS annotation tool, to pinpoint potential causal variants and genes from the latest BD GWAS findings, and performed integrative analyses, including brain expression quantitative trait loci (eQTL), gene coexpression network, differential gene expression, protein-protein interaction, and brain intermediate phenotype association analysis to identify the functions of a prioritized gene and its connection to BD. Convergent lines of evidence prioritized protein-coding gene G Protein Nucleolar 3 (GNL3) as a BD risk gene, with integrative analyses revealing GNL3's roles in cell proliferation, neuronal functions, and brain phenotypes. We experimentally revealed that BD-related eQTL SNPs rs10865973, rs12635140, and rs4687644 regulate GNL3 expression using dual luciferase reporter assay and CRISPR interference experiment in human neural progenitor cells. We further identified that GNL3 knockdown and overexpression led to aberrant neuronal proliferation and differentiation, using two-dimensional human neural cell cultures and three-dimensional forebrain organoid model. This study gathers evidence that BD-related genetic variants regulate GNL3 expression which subsequently affects neuronal proliferation and differentiation.

Verification of a ZBTB16 variant in polycystic ovary syndrome patients

Research questionThis study investigated whether rs1784692 is a risk factor for polycystic ovary syndrome (PCOS) in Han Chinese women. DesignA case-control study was conducted in Han Chinese women, involving 526 PCOS patients and 522 control participants. A TaqMan MGB probe assay was used to genotype the variant rs1784692. Dominant and additive models were employed for genotype–phenotype association analysis in the PCOS and control samples. ResultsThe minor allele C of rs1784692 is protective against PCOS (odds ratio [OR] 0.556, 95% confidence interval [CI] 0.408–0.759, P = 1.83 × 10–4), even after adjustment for body mass index (BMI) and age (ORadj 0.539, 95% CI 0.391–0.743, Padj= 1.62 × 10–4). Genotype–phenotype analysis of the dominant model showed that mean BMI in the CC+CT group was higher than in the TT group in the PCOS group (27.12 ± 5.82 versus 24.57 ± 4.52, P = 1.0 × 10–3), but not in the control groups, indicating that the minor allele C of rs1784692 associates with BMI in women with PCOS. The mean LH (luteinizing hormone) concentration in the CC+CT group was lower than in the TT group in PCOS and control participants (9.33 ± 5.08 versus 10.93 ± 5.91, P = 0.036; 4.39 ± 1.66 versus 4.89 ± 2.07, P = 0.021). Genotype–phenotype analysis of additive model showed that mean BMI in TC group was higher than in the TT group in PCOS patients compared with control participants (27.14 ± 5.81 versus 24.57 ± 4.52, P = 3.06 × 10–3). ConclusionsThe SNP rs1784692 in gene ZBTB16 is protective against PCOS but is associated with increased BMI in Han Chinese women with PCOS.

Genome-Wide Association Analysis Identifies Candidate Genes Regulating Seed Number Per Silique in Arabidopsis thaliana.

Seed weight and number ultimately determine seed yield. Arabidopsis seed number comprised of silique number and seed number per silique (SNS). Comparing seed development and weight, determinants of seed number remain largely uncharacterized. In this study, taking advantage of 107 available Arabidopsis accessions, genome-wide association analysis (GWAS) was employed to identify the candidate genes regulating SNS. GWAS-based genotype and phenotype association analysis identified 38 most significant SNPs marker sites that were mapped to specific chromosomal positions and allowed us to screen for dozens of candidate genes. One of them (PIN3) was selected for functional validation based on gene expression analysis. It is a positive regulator of Arabidopsis SNS. Although silique length of PIN3 loss of function mutant was not significantly changed, its SNS and seed density (SD) were significantly reduced as compared with the wild type. Notably, PIN3 overexpression lines driven by a placenta-specific promoter STK exhibited significantly shorter siliques, slightly reduced SNS, but significant increased SD compared with wild type, suggesting that PIN3 positively regulates SD through inducing ovule primordia initiation regardless of the placenta size. Ovule initiation determines the maximal possibility of SNS, and new genes and mechanism regulating SNS through modulating ovule initiation is worth further investigated.

Hierarchical Canonical Correlation Analysis Reveals Phenotype, Genotype, and Geoclimate Associations in Plants.

The local environment of the geographical origin of plants shaped their genetic variations through environmental adaptation. While the characteristics of the local environment correlate with the genotypes and other genomic features of the plants, they can also be indicative of genotype-phenotype associations providing additional information relevant to environmental dependence. In this study, we investigate how the geoclimatic features from the geographical origin of the Arabidopsis thaliana accessions can be integrated with genomic features for phenotype prediction and association analysis using advanced canonical correlation analysis (CCA). In particular, we propose a novel method called hierarchical canonical correlation analysis (HCCA) to combine mutations, gene expressions, and DNA methylations with geoclimatic features for informative coprojections of the features. HCCA uses a condition number of the cross-covariance between pairs of datasets to infer a hierarchical structure for applying CCA to combine the data. In the experiments on Arabidopsis thaliana data from 1001 Genomes and 1001 Epigenomes projects and climatic, atmospheric, and soil environmental variables combined by CLIMtools, HCCA provided a joint representation of the genomic data and geoclimate data for better prediction of the special flowering time at 10°C (FT10) of Arabidopsis thaliana. We also extended HCCA with information from a protein-protein interaction (PPI) network to guide the feature learning by imposing network modules onto the genomic features, which are shown to be useful for identifying genes with more coherent functions correlated with the geoclimatic features. The findings in this study suggest that environmental data comprise an important component in plant phenotype analysis. HCCA is a useful data integration technique for phenotype prediction, and a better understanding of the interactions between gene functions and environment as more useful functional information is introduced by coprojections of multiple genomic datasets.

A flexible copula-based approach for the analysis of secondary phenotypes in ascertained samples.

Data collected for a genome-wide association study of a primary phenotype are often used for additional genome-wide association analyses of secondary phenotypes. However, when the primary and secondary traits are dependent, naïve analyses of secondary phenotypes may induce spurious associations in non-randomly ascertained samples. Previously, retrospective likelihood-based methods have been proposed to correct for sampling biases arising in secondary trait association analyses. However, most methods have been introduced to handle studies featuring a case-control design based on a binary primary phenotype. As such, these methods are not directly applicable to more complicated study designs such as multiple-trait studies, where the sampling mechanism also depends on the secondary phenotype, or extreme-trait studies, where individuals with extreme primary phenotype values are selected. To accommodate these more complicated sampling mechanisms, only a few prospective likelihood approaches have been proposed. These approaches assume a normal distribution for the secondary phenotype (or the latent secondary phenotype) and a bivariate normal distribution for the primary-secondary phenotype dependence. In this paper, we propose a unified copula-based approach to appropriately detect genetic variant/secondary phenotype association in the presence of selected samples. Primary phenotype is either binary or continuous and the secondary phenotype is continuous although not necessary normal. We use both prospective and retrospective likelihoods to account for the sampling mechanism and use a copula model to allow for potentially different dependence structures between the primary and secondary phenotypes. We demonstrate the effectiveness of our approach through simulation studies and by analyzing data from the Avon Longitudinal Study of Parents and Children cohort.

Genome-Wide Association Analyses of Equine Metabolic Syndrome Phenotypes in Welsh Ponies and Morgan Horses.

Equine metabolic syndrome (EMS) is a complex trait for which few genetic studies have been published. Our study objectives were to perform within breed genome-wide association analyses (GWA) to identify associated loci in two high-risk breeds, coupled with meta-analysis to identify shared and unique loci between breeds. GWA for 12 EMS traits identified 303 and 142 associated genomic regions in 264 Welsh ponies and 286 Morgan horses, respectively. Meta-analysis demonstrated that 65 GWA regions were shared across breeds. Region boundaries were defined based on a fixed-size or the breakdown of linkage disequilibrium, and prioritized if they were: shared between breeds or across traits (high priority), identified in a single GWA cohort (medium priority), or shared across traits with no SNPs reaching genome-wide significance (low priority), resulting in 56 high, 26 medium, and seven low priority regions including 1853 candidate genes in the Welsh ponies; and 39 high, eight medium, and nine low priority regions including 1167 candidate genes in the Morgans. The prioritized regions contained protein-coding genes which were functionally enriched for pathways associated with inflammation, glucose metabolism, or lipid metabolism. These data demonstrate that EMS is a polygenic trait with breed-specific risk alleles as well as those shared across breeds.

Phenotypic association and heritability analysis in bread wheat (Triticum aestivum L.) genotypes

Phenotypic association and heritability analysis in bread wheat (Triticum aestivum L.) genotypes

Feather colour affects the aggressive behaviour of chickens with the same genotype on the dominant white (I) locus.

Aggression in chickens is a serious economic and animal welfare issue in poultry farming. Pigmentation traits have been documented to be associated with animal behaviour. Chicken pecking behaviour has been found to be related to feather colour, with premelanosome protein 17 (PMEL17) being one of the candidate genes. In the present study, we performed a genotypic and phenotypic association analysis between chicken plumage colour (red and white) and aggressive behaviour in an F1 hybrid group generated by crossing the autosomal dominant white-feathered breed White Leghorn (WL) and the red-feathered breed Rhode Island Red (RIR). In genetic theory, all the progeny should have white feathers because WL is homozygous autosomal dominant for white feathers. However, we found a few red-feathered female chickens. We compared the aggressiveness between the red and white females to determine whether the feather colour alone affected the behaviour, given that the genetic background should be the same except for feather colour. The aggressiveness was recorded 5 days after sexual maturity at 26 weeks. Generally, white plumage hens showed significantly higher aggressiveness compared to the red ones in chasing, attacking, pecking, and threatening behaviour traits. We assessed three candidate feather colour genes—PMEL17, solute carrier family 45 member 2 (SLC45A2), and SRY-box 10 (SOX10)—to determine the genetic basis for the red and white feather colour in our hybrid population; there was no association between the three loci and feather colour. The distinct behavioural findings observed herein provide clues to the mechanisms underlying the association between phenotype and behaviour in chickens. We suggest that mixing red and white chickens together might reduce the occurrence of aggressive behaviours.