Pairs Of SNPs Research Articles

Genome-wide exploration of genetic interactions for bladder cancer risk.

Although GWASs have been conducted to investigate genetic variation of bladder tumorigenesis, little is known about genetic interactions that may influence bladder cancer (BC) risk. By leveraging large-scale participants from UK Biobank, we established a discovery database with 4000 Caucasian participants (2000 cases vs 2000 non-cases), a database with 1648 Caucasian participants (824 cases vs 824 non-cases) and 856 non-Caucasian participants (428 cases vs 428 non-cases) as validation. We then performed a genome-wide SNP-SNP interaction investigation related to BC risk based a machine learning approach (ie, GenEpi). Moreover, we used the selected interactions to build a BC screening model with an integrated interaction-empowered polygenic risk score (iPRS) based on Cox proportional hazard model. With Bonferroni correction, we identified 10 statistically significant pairs of SNPs, which located in 17 chromosomes. Of these, four SNP-SNP interactions were found to be positively associated with BC risk among Caucasian participants (ORs 1.57-2.03), while six SNP-SNP interactions showed negatively associated with BC risk (ORs 0.54-0.65). Only four of the SNP-SNP interactions were consistently identified in non-Caucasian participants located in ST7L-ADSS2, FHIT-CHDH, LARP4B-LHPP and RBFOX3-MPRIP. In addition, the iPRS showed a HR of 1.81 (95% CI: 1.46-2.09) compared the highest tertile to the lowest tertile, with an enhanced AUC (0.91; 95% CI:0.85-0.97) than PRS (AUC: 0.86; 95% CI:0.76-0.95; P-DeLong test = 2.2 × 10-4 ). In summary, this study identified several important SNP-SNP interactions for BC risk, and developed an iPRS model for BC screening, which may help to identify the people at high-risk state of BC before early manifestation.

Potential of genomic selection for growth, meat content and colour traits in mixed-family breeding designs for the Pacific oyster Crassostrea gigas

Selective breeding programs have been initiated worldwide for the Pacific oyster Crassostrea gigas to improve economically important traits such as growth and disease resistance. The emergence of genomic tools has allowed novel perspectives for using genomic selection (GS) in mixed-family breeding designs, which are cheaper and easier to develop than classical breeding schemes. In this study, we evaluated the potential of GS for different growth-related and shell colour traits in two independent commercially selected populations (P1 and P2), based on mixed-family designs. From ≈14.5K informative SNPs genotyped with the bi-species Axiom Affymetrix 57K oyster array, ≈12.5K were mapped on the reference genome. A strong heterogeneity of marker density between and within chromosomes was reported, with a low linkage disequilibrium (below 0.1 at 0.1 Mb) between pairs of SNPs. The within-population structure was homogenous for each population, with effective sizes of 107 for P1 and 76 for P2. Heritability was estimated for each trait and population and ranged from 0.08 ± 0.04 (for mean darkness intensity in P1) to 0.56 ± 0.08 (for the mean upper valve b* value in P2) for a pedigree-based model and from 0.04 ± 0.02 (for mean darkness intensity in P1) to 0.69 ± 0.04 (for the mean darkness intensity in P2) for a genomic-based model. Growth-related traits were generally highly genetically and positively correlated with each other, but weakly correlated with colour traits. Accuracy of prediction was generally higher with the genomic model (GBLUP) than with the classical BLUP model, with a maximum gain of accuracy (from 0.38 to 0.66) for flesh weight adjusted by total weight in P2. Accuracy of breeding values was slightly higher for colour traits for P2, with higher heritability estimates. Overall, our results indicate that GS has a good potential to be implemented in mixed-family breeding programs in a shellfish such as C. gigas.

MicroRNA in Alzheimer’s Disease: Results of interaction analysis

AbstractBackgroundMiRNA are multifunctional molecules involved in regulating posttranscriptional expression of genes. Several studies showed that miR‐107 influences expression of the BACE1 gene in the process of Aβ production. Extracellular accumulation of Aβ is well‐known hallmark of Alzheimer’s disease (AD). The product NLRP3 gene is involved in inflammasome that induces neuroinflammation a pathological process accompanying AD. The role of miR‐107 in regulation of NRLP3 is unknown.MethodWe used logistic regression model with the interaction term to test the hypothesis that interaction of SNPs from miR‐107 with SNPs from the NLRP3 gene is associated with AD. For this we used data on genotyped individuals collected in Framingham Health Study (FHS). The Cardiovascular Health Study (CHS) was used to replicate the research findings. Linkage Disequilibrium test and clumping procedure were used to reduce the number of tests and make Bonferroni correction less conservative.ResultIn the analysis of FHS data we found that the association of the rs2926616 SNP from the miR‐107 miRNA with the rs10754557 SNP from the NLRP3 gene is positive and statistically significant. The effect size β = 0.356, p‐value 6.71E‐03. This value is smaller than the p‐value threshold calculated in accordance with Bonferroni correction 7.14E‐03. This result is replicated in the analysis of CHS data with β = 0.289, and p‐value 4.76E‐02. Using FHS data we also tested the role of interaction of SNPs from the miR‐107 with SNPs from the TLR2 gene in AD and found a pair of SNPs whose interaction has statistically significant association with AD. This finding was replicated in the analysis of the CHS data where an interaction of a pair of SNPs also showed significant association with AD. Detected SNPs from this pair were in linkage disequilibrium with the pair SNPs from the CHS data.ConclusionThe results of these analyses indicate that one miRNA may influence several components of AD pathological development. This property may have important implications for developing efficient medications against AD. More studies are needed to evaluate miRNA involvement in different pathways of AD regulation, as well as in identifying factors capable in affecting such miRNA.

Computational CRISPR deep learning simulation of the likelihood of Alzheimer’s disease using chromosome 19 GWAS

AbstractBackgroundSeveral genetic variants in chromosome 19 have been determined as independent Alzheimer’s disease (AD) risk factors. It is presumed that different combinations amongst them would further impact AD risk and progression at the individual level. In order to advance AD precision medicine, it is critical to understand the underlying complex genetic mechanisms. Deep learning technology is capable of not only identifying such variants but also defining complicated interactions that could further influence disease progression.MethodWe applied a novel deep learning model to the 266,161 SNP chromosome 19 data of 313 AD and 457 cognitively unimpaired (CU) ADNI patients. By using occlusion mapping we identified the SNPs that contributed to predictive accuracy of AD vs. CU and sequentially replaced each of them with all other biologically plausible alleles to most precisely measure the impact of the variability at the SNP level. Next, we examined the possible epistatic interactions on the SNP level on AD likelihood by co‐occlusion of pairs of SNPs and investigating the additional changes on predictive accuracy.ResultRs56131196 (APOC1) emerged as the most powerful chromosome 19 AD SNP. 79.69% (51/64) of the predicted AD patients were heterozygous, i.e., AG, at this locus. In contrast, 88.89% (80/90) of the predicted CU patients had GG genotype at rs56131196. Substituting AG for GG in predicted AD participants resulted in changing the diagnostic prediction to CU in 36% of the cases. Substituting GG for AA in predicted CU participants resulted in changing the diagnostic prediction to AD in 6% of the cases. The model further identified that AG→GG replacement further affects the likelihood of AD by interactions with SNPs in other genes including APOC1/APOC1P1, TOMM40, and ERCC1/CD3EAP.ConclusionWe tested the APOC1 rs56131196 genotype risk for AD by creating a simulator analogous to CRISPR. This innovative approach could provide a potential in silico CRISPR predictive modeling and help advance personalized preventive gene therapy for AD.

Parent-offspring genotyped trios unravelling genomic regions with gametic and genotypic epistatic transmission bias on the cattle genome.

Several biological mechanisms affecting the sperm and ova fertility and viability at developmental stages of the reproductive cycle resulted in observable transmission ratio distortion (i.e., deviation from Mendelian expectations). Gene-by-gene interactions (or epistasis) could also potentially cause specific transmission ratio distortion patterns at different loci as unfavorable allelic combinations are under-represented, exhibiting deviation from Mendelian proportions. Here, we aimed to detect pairs of loci with epistatic transmission ratio distortion using 283,817 parent-offspring genotyped trios (sire-dam-offspring) of Holstein cattle. Allelic and genotypic parameterization for epistatic transmission ratio distortion were developed and implemented to scan the whole genome. Different epistatic transmission ratio distortion patterns were observed. Using genotypic models, 7, 19 and 6 pairs of genomic regions were found with decisive evidence with additive-by-additive, additive-by-dominance/dominance-by-additive and dominance-by-dominance effects, respectively. Using the allelic transmission ratio distortion model, more insight was gained in understanding the penetrance of single-locus distortions, revealing 17 pairs of SNPs. Scanning for the depletion of individuals carrying pairs of homozygous genotypes for unlinked loci, revealed 56 pairs of SNPs with recessive epistatic transmission ratio distortion patterns. The maximum number of expected homozygous offspring, with none of them observed, was 23. Finally, in this study, we identified candidate genomic regions harboring epistatic interactions with potential biological implications in economically important traits, such as reproduction.

A genetic linkage map of the threatened catfish Lophiosilurus alexandri: Inferences on effective population size

We report the first genetic linkage map of the catfish Lophiosilurus alexandri, a South American threatened and promising aquaculture catfish species. Using the progeny of three full-sib families, with 141, 74, and 49 offspring, respectively, we could genotype 2351 SNP markers using the ddRAD technology, shared by the male and the female maps constructed. The averaged, female and male maps spanned a total length of 2201.3 cM, 2481.9 cM, and 1872.8 cM, respectively, and comprehended the expected 27 linkage groups according to the karyotype information of the species (2n = 54). The recombination rate was nearly twice higher in the female than in the male map. The average map was used to estimate the historical effective population size (Ne) of the species from linkage disequilibrium between pairs of SNPs using parental individuals and revealed a remarkable drop in Ne about 20–25 generations in the past. The construction of the biggest artificial reservoir in Latin America and associated nutrient retention is pointed as a possible reason for such a reduction and suggests a reevaluation of the conservation status of the species. The current map lays the groundwork for understanding the genetic basis of economically important traits in breeding programs and will be useful for the genome assembly of this important commercial species.

Genome-wide association analysis for grain moisture content and dehydration rate on maize hybrids.

The online version contains supplementary material available at 10.1007/s11032-022-01349-x.

Association between comorbid asthma and depression and depression-related gene SNPs

ObjectiveThis study aimed to explore the correlation between depression-related gene polymorphisms and the risk of bronchial asthma combined with depression. MethodsA total of 387 patients diagnosed with bronchial asthma in our hospital were continuously enrolled in the study. The patients were divided into healthy control group, asthma group and asthma combined depression group according to the results of Self-rating Depression Scale (SDS) and Hamilton Depression Scale (HAMD). A total of 84 gene loci associated with depression were identified using the UCSC Genome Browser and Haploview 4.2 software. Chi-square test and Logistic regression analysis were used to calculate the odds ratio (OR) and confidence intervals (CIs) of each SNP (GRPERHN rs10129827, rs28762177 GG, BDFN rs6265, rs2049046 CA, TT, HTR1A rs878567, rs6295 TT) in co-dominant, dominant, and recessive genetic modes. ResultsA total of 18 loci were identified, which had at least one significant chi-square value for the distribution differences of co-dominant, dominant, and recessive model, or alleles among the three groups. Logistic analysis found that 24 of the 84 depression-associated loci had a regression relationship with asthmatic prevalence. For linkage analysis, 16 pairs of SNPs were in a highly linked state in patients with asthma, forming haploids. Compared with the healthy control group, 4 haplotypes of 3 genes were significantly associated with asthma status, including GRPERHN rs10129827, rs28762177 GG (OR = 1.258, P = 0.02582), BDFN rs6265, rs2049046 CA (OR = 1.267, P = 0.0176), TT (OR = 0.763, P = 0.008), HTR1A rs878567, rs6295 TT (OR = 1.28, P = 0.030). ConclusionThere may be an important genetic basis for bronchial asthma and depression.

Benchmarking phasing software with a whole-genome sequenced cattle pedigree

BackgroundAccurate haplotype reconstruction is required in many applications in quantitative and population genomics. Different phasing methods are available but their accuracy must be evaluated for samples with different properties (population structure, marker density, etc.). We herein took advantage of whole-genome sequence data available for a Holstein cattle pedigree containing 264 individuals, including 98 trios, to evaluate several population-based phasing methods. This data represents a typical example of a livestock population, with low effective population size, high levels of relatedness and long-range linkage disequilibrium.ResultsAfter stringent filtering of our sequence data, we evaluated several population-based phasing programs including one or more versions of AlphaPhase, ShapeIT, Beagle, Eagle and FImpute. To that end we used 98 individuals having both parents sequenced for validation. Their haplotypes reconstructed based on Mendelian segregation rules were considered the gold standard to assess the performance of population-based methods in two scenarios. In the first one, only these 98 individuals were phased, while in the second one, all the 264 sequenced individuals were phased simultaneously, ignoring the pedigree relationships. We assessed phasing accuracy based on switch error counts (SEC) and rates (SER), lengths of correctly phased haplotypes and the probability that there is no phasing error between a pair of SNPs as a function of their distance. For most evaluated metrics or scenarios, the best software was either ShapeIT4.1 or Beagle5.2, both methods resulting in particularly high phasing accuracies. For instance, ShapeIT4.1 achieved a median SEC of 50 per individual and a mean haplotype block length of 24.1 Mb (scenario 2). These statistics are remarkable since the methods were evaluated with a map of 8,400,000 SNPs, and this corresponds to only one switch error every 40,000 phased informative markers. When more relatives were included in the data (scenario 2), FImpute3.0 reconstructed extremely long segments without errors.ConclusionsWe report extremely high phasing accuracies in a typical livestock sample. ShapeIT4.1 and Beagle5.2 proved to be the most accurate, particularly for phasing long segments and in the first scenario. Nevertheless, most tools achieved high accuracy at short distances and would be suitable for applications requiring only local haplotypes.

Genetic diversity in some domestic and wild sheep and goats in Iran

In present study, genetic diversity of domestic and wild Iranian sheep and goats were evaluated using inbreeding coefficients (FGRM, FHOM and FROH), linkage disequilibrium (LD), and effective population size (Ne). Genomic data of Iranian sheep and goat species were obtained from the NEXTGEN project. Animals consisted of 20 domestic sheep (Ovis aries), 14 wild sheep (Ovis orientalis), 20 domestic goats (Capra hircus) and 18 wild goats (Capra aegagrus). Mutations equivalent to the IlluminaSNPchip50 K were extracted to study mutations for each animal. Based on FGRM, FHOM and FROH, higher rates of inbreeding were observed in wild species than domestic species. Wild sheep had the highest rate of inbreeding among studied populations. Our results showed a decreasing in LD with increasing in distance between pairs of SNPs so that the average LD in short distance was in the range of 0.11−0.12, and in long distance was in the range of 0.091−0.093. The analysis of LD also demonstrated higher genetic diversity in domestic sheep and goat than wild species and wild sheep had the lowest genetic diversity among studied populations. The results indicated that Ne in 13 generations ago was higher in domestic species compared to wild species. In general, present results revealed that wild species had lower genetic diversity compared to the domestic species in Iran. Meanwhile, wild sheep population is in critical conditions from genetic diversity point of view and required more attention. Designing appropriate breeding programs to improve genetic diversity in wild species, especially in wild sheep in Iran is necessary to protect them from extinction.

Estimation of the covariance structure from SNP allele frequencies

Abstract We propose two new statistics, V ̂ $\hat{V}$ and S ̂ $\hat{S}$ , to disentangle the population history of related populations from SNP frequency data. If the populations are related by a tree, we show by theoretical means as well as by simulation that the new statistics are able to identify the root of a tree correctly, in contrast to standard statistics, such as the observed matrix of F 2-statistics (distances between pairs of populations). The statistic V ̂ $\hat{V}$ is obtained by averaging over all SNPs (similar to standard statistics). Its expectation is the true covariance matrix of the observed population SNP frequencies, offset by a matrix with identical entries. In contrast, the statistic S ̂ $\hat{S}$ is put in a Bayesian context and is obtained by averaging over pairs of SNPs, such that each SNP is only used once. It thus makes use of the joint distribution of pairs of SNPs. In addition, we provide a number of novel mathematical results about old and new statistics, and their mutual relationship.

Vitamin D receptor gene polymorphisms and risk of breast cancer in Iranian women

ObjectivesVitamin D deficiency is a driving force of common cancers like breast cancer. Vitamin D receptor (VDR) can play a tumor suppressor role by helping the precise function of vitamin D in cells such as modulation TGF-β signaling pathway. This study aimed to investigate the association of VDR gene variants and susceptibility to breast cancer in Iranian women. MethodsGenomic DNAs were isolated from blood samples of 161 women with breast cancer and 150 healthy women. After amplification of five positions of VDR gene, the prepared amplicons were digested with TaqI, ApaI, BsmI, Cdx2, and FokI restriction enzymes. ResultsSubsequently, the digested products were electrophoresed on the 1.5% agarose gel. Odds ratios (ORs) for breast cancer were calculated for genotypes and estimated haplotypes. Binary logistic regression analysis showed FokI (rs2228570), BsmI (rs1544410), and ApaI (rs7975232) polymorphisms had the significant distribution in patients than to the normal group. Analysis of linkage disequilibrium for all pairs of SNPs showed that D′-value between SNP TaqI and SNP BsmI was significantly (p ≤ 0.05). We observed that four major haplotypes of ApaI, BsmI, FokI, Cdx2, and TaqI SNPs significantly were in high frequency than predicted frequency. Among these four haplotypes, CGTAT haplotype was in a higher significant association than others with breast cancer risk (p-value = 0.0001). ConclusionOur results showed that FokI, BsmI, and ApaI of VDR polymorphisms associated with the risk of breast cancer in Iranian population.

Negative linkage disequilibrium between amino acid changing variants reveals interference among deleterious mutations in the human genome.

Evolutionary forces like Hill-Robertson interference and negative epistasis can lead to deleterious mutations being found on distinct haplotypes. However, the extent to which these forces depend on the selection and dominance coefficients of deleterious mutations and shape genome-wide patterns of linkage disequilibrium (LD) in natural populations with complex demographic histories has not been tested. In this study, we first used forward-in-time simulations to predict how negative selection impacts LD. Under models where deleterious mutations have additive effects on fitness, deleterious variants less than 10 kb apart tend to be carried on different haplotypes relative to pairs of synonymous SNPs. In contrast, for recessive mutations, there is no consistent ordering of how selection coefficients affect LD decay, due to the complex interplay of different evolutionary effects. We then examined empirical data of modern humans from the 1000 Genomes Project. LD between derived alleles at nonsynonymous SNPs is lower compared to pairs of derived synonymous variants, suggesting that nonsynonymous derived alleles tend to occur on different haplotypes more than synonymous variants. This result holds when controlling for potential confounding factors by matching SNPs for frequency in the sample (allele count), physical distance, magnitude of background selection, and genetic distance between pairs of variants. Lastly, we introduce a new statistic HR(j) which allows us to detect interference using unphased genotypes. Application of this approach to high-coverage human genome sequences confirms our finding that nonsynonymous derived alleles tend to be located on different haplotypes more often than are synonymous derived alleles. Our findings suggest that interference may play a pervasive role in shaping patterns of LD between deleterious variants in the human genome, and consequently influences genome-wide patterns of LD.

Long-range linkage disequilibrium in French beef cattle breeds

BackgroundLinkage disequilibrium (LD) is a key parameter to study the history of populations and to identify and fine map quantitative trait loci (QTL) and it has been studied for many years in animal populations. The advent of new genotyping technologies has allowed whole-genome LD studies in most cattle populations. However, to date, long-range LD (LRLD) between distant variants on the genome has not been investigated in detail in cattle. Here, we present the first comprehensive study of LRLD in French beef cattle by analysing data on 672 Charolais (CHA), 462 Limousine (LIM) and 326 Blonde d’Aquitaine (BLA) individuals that were genotyped on the Illumina BovineHD Beadchip. Furthermore, whole-genome LD and haplotype block structure were analysed in these three breeds.ResultsWe computed linkage disequilibrium (r2) values for 5.9, 5.6 and 6.0 billion pairs of SNPs on the 29 autosomes of CHA, LIM and BLA, respectively. Mean r2 values drop to less than 0.1 for distances between SNPs greater than 120 kb. However, for the first time, we detected the existence of LRLD in the three main French beef breeds. In total, 598, 266, and 795 LRLD events (r2 ≥ 0.6) were detected in CHA, LIM and BLA, respectively. Each breed had predominantly population-specific LRLD interactions, although shared LRLD events occurred in a number of regions (55 LRLD events were shared between two breeds and nine between the three breeds). Examples of possible functional gene interactions and QTL co-location were observed with some of these LRLD events, which suggests epistatic selection.ConclusionsWe identified long-range linkage disequilibrium for the first time in French beef cattle populations. Epistatic selection may be the main source of the observed LRLD events, but other forces may also be involved. LRLD information should be accounted for in genome-wide association studies.

Genome-wide conditional association study reveals the influences of lifestyle cofactors on genetic regulation of body surface area in MESA population.

Body surface area (BSA) is an important trait used for many clinical purposes. People’s BSA may vary due to genetic background, race, and different lifestyle factors (such as walking, exercise, reading, smoking, transportation, etc.). GWAS of BSA was conducted on 5,324 subjects of four ethnic populations of European-American, African-American, Hispanic-American, and Chinese-American from the Multi-Ethnic Study of Atherocloris (MESA) data using unconditional and conditional full genetic models. In this study, fifteen SNPs were identified (Experiment-wise PEW < 1×10−5) using unconditional full genetic model, of which thirteen SNPs had individual genetic effects and seven SNPs were involved in four pairs of epistasis interactions. Seven single SNPs and eight pairs of epistasis SNPs were additionally identified using exercise, smoking, and transportation cofactor-conditional models. By comparing association analysis results from unconditional and cofactor conditional models, we observed three different scenarios: (i) genetic effects of several SNPs did not affected by cofactors, e.g., additive effect of gene CREB5 (a≙ –0.013 for T/T and 0.013 for G/G, −Log10 PEW = 8.240) did not change in the cofactor models; (ii) genetic effects of several SNPs affected by cofactors, e.g., the genetic additive effect (a≙ 0.012 for A/A and –0.012 for G/G, −Log10 PEW = 7.185) of SNP of the gene GRIN2A was not significant in transportation cofactor model; and (iii) genetic effects of several SNPs suppressed by cofactors, e.g., additive (a≙ –0.018 for G/G and 0.018 for C/C, −Log10 PEW = 19.737) and dominance (d≙ –0.038 for G/C, −Log10 PEW = 27.734) effects of SNP of gene ERBB4 was identified using only transportation cofactor model. Gene ontology analysis showed that several genes are related to the metabolic pathway of calcium compounds, coronary artery disease, type-2 Diabetes, Alzheimer disease, childhood obesity, sleeping duration, Parkinson disease, and cancer. This study revealed that lifestyle cofactors could contribute, suppress, increase or decrease the genetic effects of BSA associated genes.

Novel approach for parallelizing pairwise comparison problems as applied to detecting segments identical by decent in whole-genome data.

MotivationPairwise comparison problems arise in many areas of science. In genomics, datasets are already large and getting larger, and so operations that require pairwise comparisons—either on pairs of SNPs or pairs of individuals—are extremely computationally challenging. We propose a generic algorithm for addressing pairwise comparison problems that breaks a large problem (of order n2 comparisons) into multiple smaller ones (each of order n comparisons), allowing for massive parallelization.ResultsWe demonstrated that this approach is very efficient for calling identical by descent (IBD) segments between all pairs of individuals in the UK Biobank dataset, with a 250-fold savings in time and 750-fold savings in memory over the standard approach to detecting such segments across the full dataset. This efficiency should extend to other methods of IBD calling and, more generally, to other pairwise comparison tasks in genomics or other areas of science.Availability and ImplementationA GitHub page is available at https://github.com/emmanuelsapin with the code to generate data needed for the implementation

Genome-wide association study for beef fatty acid profile using haplotypes in Nellore cattle

The objective of this study was to identify genomic regions associated with beef fatty acid (FA) profile in Nellore cattle finished in feedlot, using haplotype based analyzes. Also, the metabolic pathway enrichment analysis was performed to seek for genes with known functions, close to the haplotype blocks, associated with the evaluated traits, providing subsidies for a better understanding of how the genes affect this trait. A total of 963 Nellore bulls with phenotype for FA, were genotyped using the Illumina BovineHD BeadChip. Samples from the Longissimus thoracis muscle were taken for FAs profile measurement by gas chromatography using a SP-2560 capillary column. Haplotype blocks were defined based on the linkage disequilibrium (LD), where pairs of SNPs are in strong LD if the confidence interval is equal to or greater than 95% with D’ equal to 0.98 and the lower limit is above 0.70. The model used to estimate the haplotypes effects for the sum of beef fatty acid groups included the fixed effects of contemporary group, animal age at slaughter (as linear covariable), haplotypes (as linear regression over the number of haplotype copies: 0, 1 e 2), and the additive genetic effect as random (polygenic effect). Genome-wide association analyzes were performed for each haplotype block (single marker association) by a Restricted Maximum Likelihood model (REML) using ASREML v. 4.3 software. A total of 15, 15, 4, 3, 6, 5, and 10 haplotypes were significantly associated (FDR< 0.10) with monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), total amount of saturated fatty acids (SFA), PUFA:SFA ratio, omega 3 (n3), omega 6 (n6), and n6:n3 ratio, respectively. The statistically significant haplotypes harbored 38 genes, among which we highlighted those involved in lipid biosynthesis and metabolism, low-density lipoprotein oxidation, transport of fatty acids and cholesterol, adipocyte functions, biosynthesis of glycoprotein hormones, regulation of serum triglyceride and high-density lipoprotein-cholesterol levels, and adipogenesis. In addition, several novel regions were identified, including a putative quantitative trait locus for lipid metabolism and energy homeostasis. The enrichment analysis by DAVID tool revealed 14 significant (P< 0.05) terms related to fatty acids such as cellular response to retinoic acid, glycerol transport, regulation of Notch signaling pathway, and Ras signaling pathway. These results would contribute to the improvement of nutritional and health value of beef lipids in indicine cattle by including information from causal mutations in genetic evaluation through weighted their effects differently in genomic predictions.

Compositional epistasis detection using a few prototype disease models.

We study computational approaches for detecting SNP-SNP interactions that are characterized by a set of “two-locus, two-allele, two-phenotype and complete-penetrance” disease models. We argue that existing methods, which use data to determine a best-fitting disease model for each pair of SNPs prior to screening, may be too greedy. We present a less greedy strategy which, for each given pair of SNPs, limits the number of candidate disease models to a set of prototypes determined a priori.

High-throughput genotyping in onion reveals structure of genetic diversity and informative SNPs useful for molecular breeding

Onion is an economically important crop cultivated worldwide since ancient times. Over the centuries, domestication and outbreeding have had a significant influence on its genetic pool, leading to a high degree of biodiversity. In this study, using kompetitive allele-specific PCR (KASP) genotyping technology, we explored the genetic variation of 73 onion accessions (including wild species, commercial, and local varieties) from different areas of the world. The SNP dataset inspection returned 375 polymorphic loci with a very low percentage of non-calling sites (0.03%). Eight-nine percent of the onions amplified all polymorphic loci and were considered for a population structure analysis. The ΔK method suggested four populations and enabled the identification of genepools, reflecting the geographical origin of the samples. Through statistical studies, our SNP set has proven to be successful, revealing population-specific alleles and potential candidates for use in future breeding programs. Notably, 74 loci were associated with phenotypic traits (bulbing photoperiod, bulb shape, or bulb color), and 3 loci were identified as putative targets of selection associated with onion improvement. Fifty-three pairs of SNPs were co-inherited, and among them, 17 were both trait-associated and in linkage disequilibrium. In conclusion, the data generated in this study allowed the survey of genetic variability in a heterogeneous and scantily examined germplasm, with repercussions on its exploitation in breeding programs.

Gene-Gene Interactions among SPRYs for Nonsyndromic Cleft Lip/Palate

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a common birth defect with a complex genetic architecture. Gene-gene interactions have been increasingly regarded as contributing to the etiology of NSCL/P. A recent genome-wide association study revealed that a novel single-nucleotide polymorphism at SPRY1 in 4q28.1 showed a significant association with NSCL/P. In the current study, we explored the role of 3 SPRY genes in the etiology of NSCL/P by detecting gene-gene interactions: SPRY1, SPRY2, and SPRY4—with SPRY3 excluded due to its special location on the X chromosome. We selected markers in 3 SPRY genes to test for gene-gene interactions using 1,908 case-parent trios recruited from an international consortium established for a genome-wide association study of nonsyndromic oral clefts. As the trios came from populations with different ancestries, subgroup analyses were conducted among Europeans and Asians. Cordell’s method based on conditional logistic regression models was applied to test for potential gene-gene interactions via the statistical package TRIO in R software. Gene-gene interaction analyses yielded 10 pairs of SNPs in Europeans and 6 pairs in Asians that achieved significance after Bonferroni correction. The significant interactions were confirmed in the 10,000-permutation tests (empirical P = 0.003 for the most significant interaction). The study identified gene-gene interactions among SPRY genes among 1,908 NSCL/P trios, which revealed the importance of potential gene-gene interactions for understanding the genetic architecture of NSCL/P. The evidence of gene-gene interactions in this study also provided clues for future biological studies to further investigate the mechanism of how SPRY genes participate in the development of NSCL/P.