A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families

Background

Genome-wide association studies (GWAS) have become a common approach to identifying single nucleotide polymorphisms (SNPs) associated with complex diseases. As complex diseases are caused by the joint effects of multiple genes, while the effect of individual gene or SNP is modest, a method considering the joint effects of multiple SNPs can be more powerful than testing individual SNPs. The multi-SNP analysis aims to test association based on a SNP set, usually defined based on biological knowledge such as gene or pathway, which may contain only a portion of SNPs with effects on the disease. Therefore, a challenge for the multi-SNP analysis is how to effectively select a subset of SNPs with promising association signals from the SNP set.

Results

We developed the Optimal P-value Threshold Pedigree Disequilibrium Test (OPTPDT). The OPTPDT uses general nuclear families. A variable p-value threshold algorithm is used to determine an optimal p-value threshold for selecting a subset of SNPs. A permutation procedure is used to assess the significance of the test. We used simulations to verify that the OPTPDT has correct type I error rates. Our power studies showed that the OPTPDT can be more powerful than the set-based test in PLINK, the multi-SNP FBAT test, and the p-value based test GATES. We applied the OPTPDT to a family-based autism GWAS dataset for gene-based association analysis and identified MACROD2-AS1 with genome-wide significance (p-value= 2.5 × 10^− 6).

Conclusions

Our simulation results suggested that the OPTPDT is a valid and powerful test. The OPTPDT will be helpful for gene-based or pathway association analysis. The method is ideal for the secondary analysis of existing GWAS datasets, which may identify a set of SNPs with joint effects on the disease.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1620-3) contains supplementary material, which is available to authorized users.     

Water requirements of beef production can be reduced by genetic selection

Growing concerns regarding sustainability in agriculture include the availability of drinking water, which is putting pressure on livestock production, especially the beef sector, for more efficient practices. Thus, genetic parameters were estimated for traits related to water intake and water use efficiency in Senepol cattle. Senepol females (n = 925) and males (n = 191) were evaluated in performance tests carried out from 2014 to 2019. Daily dry matter intake (DMI) and water intake (WI) were recorded by electronic feed and water bunks (Intergado Ltd.). Other traits assessed included average daily gain (ADG); mid-test metabolic BW (BW^0.75); residual water intake based on ADG (RWI_ADG), estimated as the residual of the linear regression equation of WI on ADG and BW^0.75; residual water intake based on DMI (RWI_DMI), estimated as the residual of the linear regression equation of WI on DMI and BW^0.75 (RWI_DMI); water conversion ratio (= WI/ADG); gross water efficiency (GWE = ADG/WI); residual feed intake estimated as the residual of the linear regression equation of DMI on ADG and BW^0.75 (RFI); feed conversion ratio (= DMI/ADG) and gross feed efficiency. Genetic (co)variances were estimated with bivariate analyses. The heritabilities for WI, RWI_ADG and RWI_DMI were 0.38, 0.36 and 0.33, respectively. Water conversion ratio, RWI_ADG and RWI_DMI showed positive genetic and phenotypic correlations with WI, whereas GWE was negatively correlated with WI, suggesting that traits related to water use efficiency may be useful to identify cattle with reduced WI. Water intake showed positive genetic (r = 0.79) and phenotypic (r = 0.60) correlations with DMI, suggesting the use of WI to estimate DMI in future studies. Both RWI_ADG and RWI_DMI were genetically correlated with RFI (0.67 and 0.57, respectively) and ADG (0.49 and 0.44, respectively), showing that RWI is positively associated with feed efficiency, but has an antagonistic relationship with growth. This antagonism, however, may be managed using selection indexes. Genetic improvement of water use efficiency in Senepol cattle is possible through selection and may reduce the water requirements of beef production systems.     

Stability of Bivariate GWAS Biomarker Detection

Given the difficulty and effort required to confirm candidate causal SNPs detected in genome-wide association studies (GWAS), there is no practical way to definitively filter false positives. Recent advances in algorithmics and statistics have enabled repeated exhaustive search for bivariate features in a practical amount of time using standard computational resources, allowing us to use cross-validation to evaluate the stability. We performed 10 trials of 2-fold cross-validation of exhaustive bivariate analysis on seven Wellcome–Trust Case–Control Consortium GWAS datasets, comparing the traditional test for association, the high-performance GBOOST method and the recently proposed GSS statistic (Available at http://bioinformatics.research.nicta.com.au/software/gwis/). We use Spearman''s correlation to measure the similarity between the folds of cross validation. To compare incomplete lists of ranks we propose an extension to Spearman''s correlation. The extension allows us to consider a natural threshold for feature selection where the correlation is zero.This is the first reported cross-validation study of exhaustive bivariate GWAS feature selection. We found that stability between ranked lists from different cross-validation folds was higher for GSS in the majority of diseases. A thorough analysis of the correlation between SNP-frequency and univariate score demonstrated that the test for association is highly confounded by main effects: SNPs with high univariate significance replicably dominate the ranked results. We show that removal of the univariately significant SNPs improves replicability but risks filtering pairs involving SNPs with univariate effects. We empirically confirm that the stability of GSS and GBOOST were not affected by removal of univariately significant SNPs.These results suggest that the GSS and GBOOST tests are successfully targeting bivariate association with phenotype and that GSS is able to reliably detect a larger set of SNP-pairs than GBOOST in the majority of the data we analysed. However, the test for association was confounded by main effects.     

Meta-analysis of spineless cactus feeding to meat lambs: performance and development of mathematical models to predict dry matter intake and average daily gain

Spineless cactus is a useful feed for various animal species in arid and semiarid regions due to its adaptability to dry and harsh soil, high efficiency of water use and carbohydrates storage. This meta-analysis was carried out to assess the effect of spineless cactus on animal performance, and develop and evaluate equations to predict dry matter intake (DMI) and average daily gain (ADG) in meat lambs. Equations for predicting DMI and ADG as a function of animal and diet characteristics were developed using data from eight experiments. The dataset was comprised of 40 treatment means from 289 meat lambs, in which cactus was included from 0 to 75% of the diet dry matter (DM). Accuracy and precision were evaluated by cross-validation using the mean square error of prediction (MSEP), which was decomposed into mean bias, systematic bias and random error; concordance correlation coefficient, which was decomposed into accuracy (C_b) and precision (ρ); and coefficient of determination (R²). In addition, the data set was used to evaluate the predicting accuracy and precision of the main lamb feeding systems (Agricultural and Food Research Council, Small Ruminant Nutritional System, National Research Council and Institut National de la Recherche Agronomique) and also two Brazilian studies. The DMI, CP intake (CPI), metabolizable energy (ME) intake and ADG increased when cactus was included up to 499 g/kg DM (P<0.001). In contrast, animals fed high levels of cactus (>500 g/kg DM) had a decreased DMI, CPI and NDF intake, but increased feed efficiency (P<0.001) and similar ADG compared with those without cactus addition. The DMI was positively correlated with initial BW, final BW, concentrate and ADG, while it was negatively correlated with cactus inclusion and ME of the diet. On other hand, ADG was positively correlated with DMI, initial and mean BW and concentrate, and it was negatively correlated with cactus inclusion. The two developed equations had high accuracy (C_b of 0.95 for DMI and 0.94 for ADG) and the random error of MSEP was 99% for both equations. The precision of both equations was moderate, with R² values of 0.53 and 0.50 and ρ values of 0.73 and 0.71 for DMI and ADG, respectively. In conclusion, the developed equation to predict DMI had moderate precision and high accuracy, nonetheless, it was more efficient than those reported in the literature. The proposed equations can be a useful alternative to estimate intake and performance of lambs fed cactus.     

Integration of Mouse and Human Genome-Wide Association Data Identifies KCNIP4 as an Asthma Gene

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.     

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k₁ (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k₁ and α. QTLs within genomic regions mapped for k₁ are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k₁ were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k₁ did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.     

Comprehensive SNP Scan of DNA Repair and DNA Damage Response Genes Reveal Multiple Susceptibility Loci Conferring Risk to Tobacco Associated Leukoplakia and Oral Cancer

Polymorphic variants of DNA repair and damage response genes play major role in carcinogenesis. These variants are suspected as predisposition factors to Oral Squamous Cell Carcinoma (OSCC). For identification of susceptible variants affecting OSCC development in Indian population, the “maximally informative” method of SNP selection from HapMap data to non-HapMap populations was applied. Three hundred twenty-five SNPs from 11 key genes involved in double strand break repair, mismatch repair and DNA damage response pathways were genotyped on a total of 373 OSCC, 253 leukoplakia and 535 unrelated control individuals. The significantly associated SNPs were validated in an additional cohort of 144 OSCC patients and 160 controls. The rs12515548 of MSH3 showed significant association with OSCC both in the discovery and validation phases (discovery P-value: 1.43E-05, replication P-value: 4.84E-03). Two SNPs (rs12360870 of MRE11A, P-value: 2.37E-07 and rs7003908 of PRKDC, P-value: 7.99E-05) were found to be significantly associated only with leukoplakia. Stratification of subjects based on amount of tobacco consumption identified SNPs that were associated with either high or low tobacco exposed group. The study reveals a synergism between associated SNPs and lifestyle factors in predisposition to OSCC and leukoplakia.     

Identification of polymorphisms influencing feed intake and efficiency in beef cattle

Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI (P < 0.05). The largest single SNP allele substitution effect for RFI was -0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI (r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle.     

Timing of eating during transition impacts feedlot cattle diet and liveweight gain

The timing of eating, relative to when feed is offered, is affected by the social rank of feedlot cattle due to limited feed bunk space. As cattle can select feed based on dietary preference, the timing of eating for cattle in feedlot may be associated with the ingested diet composition. Our objectives were to determine the nutritive value and timing of feed ingested by 100 feedlot cattle during transition and the association of timing of eating with feeding behaviours and average daily gain (ADG). Cattle behaviour and timing of eating were determined on 100 feedlot cattle using accelerometer-based ear tag sensors from days 3 to 6 post feedlot induction (observation period), and the ongoing impact of this period on ADG was determined for the full feed period (75 days). To determine eating patterns at the time of feed offer, cattle were grouped according to the number of days they were recorded as eating within 1 h of feed being offered across 4 observation days, G⁰: not present across 4 days, G¹: present for 1 day, G²: 2 days, G³: 3 days and G⁴: present for each of the 4 days. Total mixed ration (TMR) samples were collected for nutritive value analysis from four locations along the feed bunk from the time feed was offered and at hourly intervals thereafter for 7 h each day during the observation period. The composition of feed in the bunk changed across the 7 h of measurement (P < 0.05). The DM and CP of feed increased from 65 to 70% and 15 to 16%, respectively, and the NDF decreased from 36 to 32%. Thus, the preferred TMR feed component was the fibrous dietary fraction. However, the overall composition of the ingested diet for 7 h post feeding was similar between groups. Cattle in G⁰ had reduced eating time (0.7 vs 4.8%; P < 0.001), rumination time (4.5 vs 19.5%; P < 0.001) and ADG (1.0 vs 1.3 kg/d; P < 0.05) across the study, as compared with cattle in G⁴. Offering a more fibrous ration during feedlot transition, and customised cattle segregation and/or customised feeding regimes based on sensor derived feeding behaviour profiles during acclimation to feedlot can optimise ADG, animal welfare and feedlot profit.     

Developing and validating a model to predict the dry matter intake of grazing lactating beef cows

Current techniques for measuring the dry matter intake (DMI) of grazing lactating beef cows are invasive, time consuming and expensive making them impractical for use on commercial farms. This study was undertaken to explore the potential to develop and validate a model to predict DMI of grazing lactating beef cows, which could be applied in a commercial farm setting, using non-invasive animal measurements. The calibration dataset used to develop the model was comprised of 94 measurements recorded on 106 beef or beef–dairy crossbred cows (maternal origin). The potential of body measurements, linear type scoring, grazing behaviour and thermal imaging to predict DMI in combination with known biologically plausible adjustment variables and energy sinks was investigated. Multivariable regression models were constructed for each independent variable using SAS PROC REG and contained milk yield, BW, parity, calving day and maternal origin (dairy or beef). Of the 94 variables tested, 32 showed an association with DMI (P < 0.25) upon multivariable analysis. These variables were incorporated into a backwards linear regression model using SAS PROC REG. Variables were retained in this model if P < 0.05. Five variables; width at pins, full body depth, ruminating mastications, central ligament and rump width score, were retained in the model in addition to milk yield, BW, parity, calving day and maternal origin. The inclusion of these variables in the model increased the predictability of DMI by 0.23 (R² = 0.68) when compared to a model containing milk yield, BW, parity, calving day and maternal origin only. This model was applied to data recorded on an independent dataset; a herd of 60 lactating beef cows two years after the calibration study. The R² for the validation was 0.59. Estimates of DMI are required for measuring feed efficiency. While acknowledging challenges in applicability, the findings suggest a model such as that developed in this study may be used as a tool to more easily and less invasively estimate DMI on large populations of commercial beef cows, and therefore measure feed efficiency.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.     

Evaluation of panicle residue from broom sorghum as a feed ingredient in finishing diets for lambs

Sorghum panicle residue (SPR), a by-product of Sorghum vulgare, obtained in the manufacture of brooms and wisks, has potential as a partial substitute for grain in growing-finishing diets for feedlot lambs. Accordingly, 48 Pelibuey×Katahdin lambs (initial weight=16.2±4.3 kg) were used in an 84-d growth-performance trial to evaluate its comparative feeding value. Lambs were blocked by weight and assigned within weight groupings to 12 pens (4 lambs per pen). The SPR was finely ground before it was incorporated into the diet. The basal diet contained 60% whole grain sorghum (WGS; DM basis). Dietary treatments consisted in the replacement of WGS with 0, 50, or 100% SPR. Replacement of WGS with SPR decreased (linear effect, P=0.04) average daily gain (ADG), and tended to increase (linear effect, P=0.06) dry matter intake (DMI). Replacement of WGS with SPR decreased (linear effect, P<0.01) gain efficiency (ADG : DMI), and observed dietary net energy (NE), as well as hot carcass weight, dressing percentage, kidney–pelvic–heart fat, and back fat thickness (linear effect, P⩽.05) Other carcass characteristics and wholesale cuts as a percentage of cold carcass weight were not affected by dietary treatments. It is concluded that SPR is a palatable feed ingredient for inclusion in finishing diets for feedlot lambs. The comparative NE values for SPR are 1.50 and 0.91 Mcal/kg for maintenance and gain, respectively, 75% the NE value of WGS. These NE values reflect the greater fiber content of SPR. To the extent that dietary energy density limits energy intake (and hence daily weight gain), appropriate constraints on level of SPR incorporation is warranted.     

Supplementing a yeast-derived product to enhance productive and health responses of beef steers

This experiment evaluated the impacts of supplementing a yeast-derived product (Celmanax; Church & Dwight Co., Inc., Princeton, NJ, USA) on productive and health responses of beef steers, and was divided into a preconditioning (days 4 to 30) and feedlot receiving phase (days 31 to 69). In all, 84 Angus × Hereford steers were weaned on day 0 (BW=245±2 kg; age=186±2 days), and maintained in a single group from days 0 to 3. On day 4, steers were allocated according to weaning BW and age to a 21-pen drylot (4 steers/pen). Pens were randomly assigned to (n=7 pens/treatment): (1) no Celmanax supplementation during the study, (2) Celmanax supplementation (14 g/steer daily; as-fed) from days 14 to 69 or (3) Celmanax supplementation (14 g/steer daily; as-fed) from days 31 to 69. Steers had free-choice access to grass-alfalfa hay, and were also offered a corn-based concentrate beginning on day 14. Celmanax was mixed daily with the concentrate. On day 30, steers were road-transported for 1500 km (24 h). On day 31, steers returned to their original pens for the 38-day feedlot receiving. Shrunk BW was recorded on days 4, 31 and 70. Feed intake was evaluated daily (days 14 to 69). Steers were observed daily (days 4 to 69) for bovine respiratory disease (BRD) signs. Blood samples were collected on days 14, 30, 31, 33, 35, 40, 45, 54 and 69, and analyzed for plasma cortisol, haptoglobin, IGF-I, and serum fatty acids. Preconditioning results were analyzed by comparing pens that received (CELM) or not (CONPC) Celmanax during the preconditioning phase. Feedlot receiving results were analyzed by comparing pens that received Celmanax from days 14 to 69 (CELPREC), days 31 to 69 (CELRECV) or no Celmanax supplementation (CON). During preconditioning, BRD incidence was less (P=0.03) in CELM v. CONPC. During feedlot receiving, average daily gain (ADG) (P=0.07) and feed efficiency (P=0.08) tended to be greater in CELPREC and CELRECV v. CON, whereas dry matter intake was similar (P⩾0.29) among treatments. No other treatment effects were detected (P⩾0.20). Collectively, Celmanax supplementation reduced BRD incidence during the 30-day preconditioning. Moreover, supplementing Celmanax tended to improve ADG and feed efficiency during the 38-day feedlot receiving, independently of whether supplementation began during preconditioning or after feedlot entry. These results suggest that Celmanax supplementation benefits preconditioning health and feedlot receiving performance in beef cattle.     

Powerful Bivariate Genome-Wide Association Analyses Suggest the SOX6 Gene Influencing Both Obesity and Osteoporosis Phenotypes in Males

Background

Current genome-wide association studies (GWAS) are normally implemented in a univariate framework and analyze different phenotypes in isolation. This univariate approach ignores the potential genetic correlation between important disease traits. Hence this approach is difficult to detect pleiotropic genes, which may exist for obesity and osteoporosis, two common diseases of major public health importance that are closely correlated genetically.

Principal Findings

To identify such pleiotropic genes and the key mechanistic links between the two diseases, we here performed the first bivariate GWAS of obesity and osteoporosis. We searched for genes underlying co-variation of the obesity phenotype, body mass index (BMI), with the osteoporosis risk phenotype, hip bone mineral density (BMD), scanning ∼380,000 SNPs in 1,000 unrelated homogeneous Caucasians, including 499 males and 501 females. We identified in the male subjects two SNPs in intron 1 of the SOX6 (SRY-box 6) gene, rs297325 and rs4756846, which were bivariately associated with both BMI and hip BMD, achieving p values of 6.82×10⁻⁷ and 1.47×10⁻⁶, respectively. The two SNPs ranked at the top in significance for bivariate association with BMI and hip BMD in the male subjects among all the ∼380,000 SNPs examined genome-wide. The two SNPs were replicated in a Framingham Heart Study (FHS) cohort containing 3,355 Caucasians (1,370 males and 1,985 females) from 975 families. In the FHS male subjects, the two SNPs achieved p values of 0.03 and 0.02, respectively, for bivariate association with BMI and femoral neck BMD. Interestingly, SOX6 was previously found to be essential to both cartilage formation/chondrogenesis and obesity-related insulin resistance, suggesting the gene''s dual role in both bone and fat.

Conclusions

Our findings, together with the prior biological evidence, suggest the SOX6 gene''s importance in co-regulation of obesity and osteoporosis.     

A region on BTA14 that includes the positional candidate genes LYPLA1, XKR4 and TMEM68 is associated with feed intake and growth phenotypes in cattle(1)

Feed cost for beef cattle is the largest expense incurred by cattle producers. The development of genetic markers to enhance selection of more efficient animals that require less feed while still achieving acceptable levels of production has the potential to substantially reduce production costs. A genome‐wide marker association approach based on the Illumina BovineSNP50 BeadChip? was used to identify genomic regions affecting average daily feed intake (ADFI), average daily gain (ADG) and residual feed intake traits in a population of 1159 crossbred steers. This approach identified a region on BTA14 from 22.02 to 23.92 Mb containing several single‐nucleotide polymorphisms (SNPs) that have significant association with at least one of the traits. Two genes in this region, lysophospholipase 1 (LYPLA1) and transmembrane protein 68 (TMEM68), appeared to be logical positional and functional candidate genes. LYPLA1 deacylates ghrelin, a hormone involved in the regulation of appetite in the rat stomach, while TMEM68 is expressed in bovine rumen, abomasum, intestine and adipose tissue in cattle, and likely affects lipid biosynthetic processes. SNPs lying in or near these two genes were identified by sequencing a subset of animals with extreme phenotypes. A total of 55 SNPs were genotyped and tested for association with the same population of steers. After correction for multiple testing, five markers within 22.79–22.84 Mb, located downstream of TMEM68, and between TMEM68 and the neighbouring gene XKR4, were significant for both ADFI and ADG. Genetic markers predictive of feed intake and weight gain phenotypes in this population of cattle may be useful for the identification and selection of animals that consume less feed, although further evaluation of these markers for effects on other production traits and validation in additional populations will be required.     

Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation

The ability to establish genetic risk models is critical for early identification and optimal treatment of breast cancer. For such a model to gain clinical utility, more variants must be identified beyond those discovered in previous genome-wide association studies (GWAS). This is especially true for women at high risk because of family history, but without BRCA1/2 mutations. This study incorporates three datasets in a GWAS analysis of women with Ashkenazi Jewish (AJ) homogeneous ancestry. Two independent discovery cohorts comprised 239 and 238 AJ women with invasive breast cancer or preinvasive ductal carcinoma in situ and strong family histories of breast cancer, but lacking the three BRCA1/2 founder mutations, along with 294 and 230 AJ controls, respectively. An independent, third cohort of 203 AJ cases with familial breast cancer history and 263 healthy controls of AJ women was used for validation. A total of 19 SNPs were identified as associated with familial breast cancer risk in AJ women. Among these SNPs, 13 were identified from a panel of 109 discovery SNPs, including an FGFR2 haplotype. In addition, six previously identified breast cancer GWAS SNPs were confirmed in this population. Seven of the 19 markers were significant in a multivariate predictive model of familial breast cancer in AJ women, three novel SNPs [rs17663555(5q13.2), rs566164(6q21), and rs11075884(16q22.2)], the FGFR2 haplotype, and three previously published SNPs [rs13387042(2q35), rs2046210(ESR1), and rs3112612(TOX3)], yielding moderate predictive power with an area under the curve (AUC) of the ROC (receiver-operator characteristic curve) of 0.74. Population-specific genetic variants in addition to variants shared with populations of European ancestry may improve breast cancer risk prediction among AJ women from high-risk families without founder BRCA1/2 mutations.     

Feedlot performance and immune function analysis of implanted and non-implanted steers selected for alcohol dehydrogenase 1 C (ADH1C) genotype and fed a low vitamin A diet

Previous studies have shown that the interaction between limiting vitamin A (VA) and an alcohol dehydrogenase 1 C (ADH1C) variant in beef cattle results in increased intramuscular fat in the longissimus thoracis muscle in one genotype when fed low dietary VA. Although quality grade is important for increased profitability and improving taste characteristics of beef products, limiting VA too drastically can impair animal welfare. The objectives of this study were to determine if this marker-assisted management strategy would be effective, and whether any impairment in immune function would occur in a feedlot setting. Mixed breed beef steers (n=2000) were sorted into 40 feedlot pens so that all combinations of ADH1C genotype (TT or CT), VA level (50% or 100% of recommended) and hormonal implant status (implanted (IMP) or non-implanted (NI)) were equally represented within the population. The VA×ADH1C interaction was not observed. An implant status × ADH1C interaction was observed with average daily gain (ADG; P=0.03). Steers that were IMP and CT had higher ADG than IMP TT (CT=1.69 and TT=1.62 kg/day), whereas both genotypes in the NI steers were lower (CT=1.29 and TT=1.32 kg/day). Implant status was shown to affect dry matter intake (DMI; IMP=8.55 and NI=7.87 kg; P<0.01), total days-on-feed (IMP=164.4 and NI 210.5 days; P<0.01), USDA yield grade (YIELD; IMP=2.40 and NI=2.77; P<0.01), marbling score (MARB; IMP=392 and NI=455; P<0.01), longissimus thoracis area (LTA; IMP=85.0 and NI=80.7 cm²; P=0.01) and backfat thickness (FAT; IMP=8.0 and NI 10.0 mm; P<0.01). Overall, IMP animals finished on fewer total days-on-feed with higher ADG, DMI, larger LTA, and lower YIELD, MARB and FAT. To investigate immune function parameters, crossbred steers (n=18) were selected from a prior feeding trial so that all combinations of ADH1C (TT, CT and CC) and VA (25% or 75%) were equally represented. Blood cell count analysis and peripheral blood mononuclear cell proliferation and stimulation assays were conducted. None of these immune parameters were affected by VA level. Treatment and mortality records were examined in the 2000 steer population, where no correlations with ADH1C, implant status or VA level were observed. Due to no VA × ADH1C interaction, this nutrigenetic marker-assisted management strategy is not effective at this time in commercial beef cattle feedlots, however, supplementing VA at a level as low as 25% of recommended in finishing rations would likely not result in signs of immune dysfunction.     

Grazed grass herbage intake and performance of beef heifers with predetermined phenotypic residual feed intake classification

Data were collected on 85 Simmental and Simmental × Holstein–Friesian heifers. During the indoor winter period, they were offered grass silage ad libitum and 2 kg of concentrate daily, and individual dry matter intake (DMI) and growth was recorded over 84 days. Individual grass herbage DMI was determined at pasture over a 6-day period, using the n-alkane technique. Body condition score, skeletal measurements, ultrasonic fat and muscle depth, visual muscularity score, total tract digestibility, blood hormones, metabolites and haematology variables and activity behaviour were measured for all heifers. Phenotypic residual feed intake (RFI) was calculated for each animal as the difference between actual DMI and expected DMI during the indoor winter period. Expected DMI was calculated for each animal by regressing average daily DMI on mid-test live weight (LW)^0.75 and average daily gain (ADG) over an 84-day period. Standard deviations above and below the mean were used to group animals into high (>0.5 s.d.), medium (±0.5 s.d.) and low (<0.5 s.d.) RFI. Overall mean (s.d.) values for DMI (kg/day), ADG (kg), feed conversion ratio (FCR) kg DMI/kg ADG and RFI (kg dry matter/day) were 5.82 (0.73), 0.53 (0.18), 12.24 (4.60), 0.00 (0.43), respectively, during the RFI measurement period. Mean DMI (kg/day) and ADG (kg) during the grazing season was 9.77 (1.77) and 0.77 (0.14), respectively. The RFI groups did not differ (P > 0.05) in LW, ADG or FCR at any stage of measurement. RFI was positively correlated (r = 0.59; P < 0.001) with DMI during the RFI measurement period but not with grazed grass herbage DMI (r = 0.06; P = 0.57). Low RFI heifers had 0.07 greater (P < 0.05) concentration of plasma creatinine than high RFI heifers and, during the grazed herbage intake period, spent less time standing and more time lying (P < 0.05) than high RFI heifers. However, low and high RFI groups did not differ (P > 0.05) in ultrasonic backfat thickness or muscle depth, visual muscle scores, skeletal size, total tract digestibility or blood hormone and haematology variables at any stage of the experiment. Despite a sizeable difference in intake of grass silage between low and high RFI heifers during the indoor winter period, there were no detectable differences between RFI groupings for any economically important performance traits measured when animals were offered ensiled or grazed grass herbage.     

Association between putative functional variants in the PSMB9 gene and risk of melanoma – re‐analysis of published melanoma genome‐wide association studies

To mine possibly hidden causal single‐nucleotide polymorphisms (SNPs) of melanoma, we investigated the association of SNPs in 76 M/G1 transition genes with melanoma risk using our published genome‐wide association study (GWAS) data set with 1804 melanoma cases and 1026 cancer‐free controls. We found multiple SNPs with P < 0.01 and performed validation studies for 18 putative functional SNPs in PSMB9 in two other GWAS data sets. Two SNPs (rs1351383 and rs2127675) were associated with melanoma risk in the GenoMEL data set (P = 0.013 and 0.004, respectively), but failed in validation using the Australian data set. Genotype–phenotype analysis revealed these two SNPs were significantly correlated with mRNA expression level of PSMB9. Further experiments revealed that SNP rs2071480, which is in high LD with rs1351383 and rs2127675, may have a weak effect on the promoter activity of PSMB9. Taken together, our data suggested that functional variants in PSMB9 may contribute to melanoma susceptibility.     

Insight in Genome-Wide Association of Metabolite Quantitative Traits by Exome Sequence Analyses

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. ¹H Nuclear Magnetic Resonance (¹H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10⁻³²), PRODH with proline (P-value  = 1.11×10⁻¹⁹), SLC16A9 with carnitine level (P-value  = 4.81×10⁻¹⁴) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10⁻¹⁹) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10⁻⁸), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10⁻⁸) and 2p12 locus with valine (P-value  = 3.49×10⁻⁸). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution ¹H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.