Early life stress unravels epistatic genetic associations of cortisol pathway genes with depression.

Dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis represents one of the most consistent pathophysiological findings in depressive disorders. Cortisol signaling is affected by proteins that mediate its cellular responses or alters its availability to mineralocorticoid and glucocorticoid receptors. In our study, we evaluated candidate genes that may influence the risk for depression and suicide due to its involvement in cortisol signaling. The aim of the study was to assess whether the genotypes of these genes are associated with the risk for depression, severity of depressive symptoms, suicidal ideation, and suicide attempts. And whether there is interaction between genes and early-life stress. In this study, 100 healthy controls and 140 individuals with depression were included. The subjects were clinically assessed using the 21-item GRID-Hamilton questionnaires (GRID-HAMD-21), Beck Scale for Suicidal Ideation (BSI), and the Childhood Trauma Questionnaire (CTQ). A robust multifactorial dimensionality reduction analysis was used to characterize the interactions between the genes HSD11B1, NR3C1, NR3C2, and MDR1 and early-life stress. It was found a significant association of the heterozygous genotype of the MDR1 gene rs1128503 polymorphism with reduced risk of at least one suicide attempt (OR: 0.08, p = 0.003*) and a reduction in the number of suicide attempts (ß = -0.79, p = 0.006*). Furthermore, it was found that the MDR1 rs1228503 and NR3C2 rs2070951 genes interact with early-life stress resulting in a strong association with depression (p = 0.001). Our findings suggest that polymorphisms in the MDR1 and NR3C2 genes and their interaction with childhood trauma may be important biomarkers for depression and suicidal behaviors.

Modeling within and between Sub-Genomes Epistasis of Synthetic Hexaploid Wheat for Genome-Enabled Prediction of Diseases.

Common wheat (Triticum aestivum) is a hexaploid crop comprising three diploid sub-genomes labeled A, B, and D. The objective of this study is to investigate whether there is a discernible influence pattern from the D sub-genome with epistasis in genomic models for wheat diseases. Four genomic statistical models were employed; two models considered the linear genomic relationship of the lines. The first model (G) utilized all molecular markers, while the second model (ABD) utilized three matrices representing the A, B, and D sub-genomes. The remaining two models incorporated epistasis, one (GI) using all markers and the other (ABDI) considering markers in sub-genomes A, B, and D, including inter- and intra-sub-genome interactions. The data utilized pertained to three diseases: tan spot (TS), septoria nodorum blotch (SNB), and spot blotch (SB), for synthetic hexaploid wheat (SHW) lines. The results (variance components) indicate that epistasis makes a substantial contribution to explaining genomic variation, accounting for approximately 50% in SNB and SB and only 29% for TS. In this contribution of epistasis, the influence of intra- and inter-sub-genome interactions of the D sub-genome is crucial, being close to 50% in TS and higher in SNB (60%) and SB (60%). This increase in explaining genomic variation is reflected in an enhancement of predictive ability from the G model (additive) to the ABDI model (additive and epistasis) by 9%, 5%, and 1% for SNB, SB, and TS, respectively. These results, in line with other studies, underscore the significance of the D sub-genome in disease traits and suggest a potential application to be explored in the future regarding the selection of parental crosses based on sub-genomes.

COMT and SCN9A gene variants do not contribute to chronic low back pain in Mexican-Mestizo patients.

BACKGROUND: Chronic low back pain (CLBP) is a complex condition in which genetic factors play a role in its susceptibility. Catechol-O-methyltransferase (COMT) and sodium channel NaV1.7 (SCN9A) genes are implicated in pain perception. The aim is to analyze the association of COMT and SCN9A with CLBP and their interaction, in a Mexican-Mestizo population. METHODS: A case-control study was conducted. Cases corresponded to adults of both sexes with CLBP. Controls were adults with no CLBP. Variants of SCN9A and COMT were genotyped. Allelic and genotypic frequencies and Hardy-Weinberg equilibrium (HWE) were calculated. Association was tested under codominant, dominant, and recessive models. Multifactor dimensionality reduction was developed to detect epistasis. RESULTS: Gene variants were in HWE, and there was no association under different inheritance models in the whole sample. In women, in codominant and dominant models, a trend to a high risk was observed for AA of rs4680 of COMT (OR = 1.7 [0.5-5.3] and 1.6 [0.7-3.4]) and for TT of rs4633 (OR = 1.6 [0.7-3.7] and 1.6 [0.7-3.4]). In men, a trend to low risk was observed for AG genotype of rs4680 in the same models (OR = 0.6 [0.2-1.7] and 0.7 [0.3-1.7]), and for TC genotype of rs4633 in the codominant model (OR = 0.6 [0.2-1.7]). In the interaction analysis, a model of the SCN9A and COMT variants showed a CVC of 10/10; however, the TA was 0.4141. CONCLUSION: COMT and SCN9A variants are not associated with CLBP in the analyzed Mexican-Mestizo population.

Investigating the impact of non-additive genetic effects in the estimation of variance components and genomic predictions for heat tolerance and performance traits in crossbred and purebred pig populations.

BACKGROUND: Non-additive genetic effects are often ignored in livestock genetic evaluations. However, fitting them in the models could improve the accuracy of genomic breeding values. Furthermore, non-additive genetic effects contribute to heterosis, which could be optimized through mating designs. Traits related to fitness and adaptation, such as heat tolerance, tend to be more influenced by non-additive genetic effects. In this context, the primary objectives of this study were to estimate variance components and assess the predictive performance of genomic prediction of breeding values based on alternative models and two independent datasets, including performance records from a purebred pig population and heat tolerance indicators recorded in crossbred lactating sows. RESULTS: Including non-additive genetic effects when modelling performance traits in purebred pigs had no effect on the residual variance estimates for most of the traits, but lower additive genetic variances were observed, especially when additive-by-additive epistasis was included in the models. Furthermore, including non-additive genetic effects did not improve the prediction accuracy of genomic breeding values, but there was animal re-ranking across the models. For the heat tolerance indicators recorded in a crossbred population, most traits had small non-additive genetic variance with large standard error estimates. Nevertheless, panting score and hair density presented substantial additive-by-additive epistatic variance. Panting score had an epistatic variance estimate of 0.1379, which accounted for 82.22% of the total genetic variance. For hair density, the epistatic variance estimates ranged from 0.1745 to 0.1845, which represent 64.95-69.59% of the total genetic variance. CONCLUSIONS: Including non-additive genetic effects in the models did not improve the accuracy of genomic breeding values for performance traits in purebred pigs, but there was substantial re-ranking of selection candidates depending on the model fitted. Except for panting score and hair density, low non-additive genetic variance estimates were observed for heat tolerance indicators in crossbred pigs.

The impact of epistasis in the heterosis and combining ability analyses.

The current theoretical knowledge concerning the influence of epistasis on heterosis is based on a simplified multiplicative model. The objective of this study was to assess how epistasis affects the heterosis and combining ability analyses, assuming additive model, hundreds of genes, linkage disequilibrium (LD), dominance, and seven types of digenic epistasis. We developed the quantitative genetics theory for supporting the simulation of the individual genotypic values in nine populations, the selfed populations, the 36 interpopulation crosses, 180 doubled haploids (DHs), and their 16,110 crosses, assuming 400 genes on 10 chromosomes of 200 cM. Epistasis only affects population heterosis if there is LD. Only additive × additive and dominance × dominance epistasis can affect the components of the heterosis and combining ability analyses of populations. Epistasis can have a negative impact on the heterosis and combining ability analysis of populations, leading to wrong inferences regarding the identification of superior and most divergent populations. However, this depends on the type of epistasis, percentage of epistatic genes, and magnitude of their effects. Except for duplicate genes with cumulative effects and non-epistatic genic interaction, there was a decrease in the average heterosis by increasing the percentage of epistatic genes and the magnitude of their effects. The same results are generally true for the combining ability analysis of DHs. The combining ability analyses of subsets of 20 DHs showed no significant average impact of epistasis on the identification of the most divergent ones, regardless of the number of epistatic genes and magnitude of their effects. However, a negative effect on the assessment of the superior DHs can occur assuming 100% of epistatic genes, but depending on the epistasis type and the epistatic effect magnitude.

Genome-enabled prediction through quantile random forest for complex traits / Predição genômica por meio do random forest quantílitico para características complexas

Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a response variable and extracting information from different quantiles instead of just predicting the mean. This evaluated the performance of the QRF in the genomic prediction for complex traits (epistasis and dominance). In addition, compare the accuracies obtained with those derived from the G-BLUP. The simulation created an F2 population with 1,000 individuals and genotyped for 4,010 SNP markers. Besides, twelve traits were simulated from a model considering additive and non-additive effects, QTL (Quantitative trait loci) numbers ranging from eight to 120, and heritability of 0.3, 0.5, or 0.8. For training and validation, the 5-fold cross-validation approach was used. For each fold, the accuracies of all the proposed models were calculated: QRF in five different quantiles and three G-BLUP models (additive effect, additive and epistatic effects, additive and dominant effects). Finally, the predictive performance of these methodologies was compared. In all scenarios, the QRF accuracies were equal to or greater than the methodologies evaluated and proved to be an alternative tool to predict genetic values in complex traits.

Quantile Random Forest (QRF) é uma metodologia não paramétrica, que combina as vantagens do Random Forest (RF) e da Regressão Quantílica (QR). Especificamente, essa abordagem pode explorar funções não lineares, determinando a distribuição de probabilidade de uma variável resposta e extraindo informações de diferentes quantis em vez de apenas prever a média. O objetivo deste trabalho foi avaliar o desempenho do QRF em predizer o valor genético genômico para características com arquitetura genética não aditiva (epistasia e dominância). Adicionalmente, as acurácias obtidas foram comparadas com aquelas advindas do G-BLUP. A simulação criou uma população F2 com 1.000 indivíduos genotipados para 4.010 marcadores SNP. Além disso, doze características foram simuladas a partir de um modelo considerando efeitos aditivos e não aditivos, com número de QTL (Quantitative trait loci) variando de oito a 120 e herdabilidade de 0,3, 0,5 ou 0,8. Para treinamento e validação foi usada a abordagem da validação cruzada 5-fold. Para cada um dos folds foram calculadas as acurácias de todos os modelos propostos: QRF em cinco quantis diferentes e três modelos do G-BLUP (com efeito aditivo, aditivo e epistático, aditivo e dominante). Por fim, o desempenho preditivo dessas metodologias foi comparado. Em todos os cenários, as acurácias do QRF foram iguais ou superiores às metodologias avaliadas e mostrou ser uma ferramenta alternativa para predizer valores genéticos em características complexas.

Genome-enabled prediction through quantile random forest for complex traits / Predição genômica por meio do random forest quantílitico para características complexas

ABSTRACT: Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a response variable and extracting information from different quantiles instead of just predicting the mean. This evaluated the performance of the QRF in the genomic prediction for complex traits (epistasis and dominance). In addition, compare the accuracies obtained with those derived from the G-BLUP. The simulation created an F2 population with 1,000 individuals and genotyped for 4,010 SNP markers. Besides, twelve traits were simulated from a model considering additive and non-additive effects, QTL (Quantitative trait loci) numbers ranging from eight to 120, and heritability of 0.3, 0.5, or 0.8. For training and validation, the 5-fold cross-validation approach was used. For each fold, the accuracies of all the proposed models were calculated: QRF in five different quantiles and three G-BLUP models (additive effect, additive and epistatic effects, additive and dominant effects). Finally, the predictive performance of these methodologies was compared. In all scenarios, the QRF accuracies were equal to or greater than the methodologies evaluated and proved to be an alternative tool to predict genetic values in complex traits.

RESUMO: Quantile Random Forest (QRF) é uma metodologia não paramétrica, que combina as vantagens do Random Forest (RF) e da Regressão Quantílica (QR). Especificamente, essa abordagem pode explorar funções não lineares, determinando a distribuição de probabilidade de uma variável resposta e extraindo informações de diferentes quantis em vez de apenas prever a média. O objetivo deste trabalho foi avaliar o desempenho do QRF em predizer o valor genético genômico para características com arquitetura genética não aditiva (epistasia e dominância). Adicionalmente, as acurácias obtidas foram comparadas com aquelas advindas do G-BLUP. A simulação criou uma população F2 com 1.000 indivíduos genotipados para 4.010 marcadores SNP. Além disso, doze características foram simuladas a partir de um modelo considerando efeitos aditivos e não aditivos, com número de QTL (Quantitative trait loci) variando de oito a 120 e herdabilidade de 0,3, 0,5 ou 0,8. Para treinamento e validação foi usada a abordagem da validação cruzada 5-fold. Para cada um dos folds foram calculadas as acurácias de todos os modelos propostos: QRF em cinco quantis diferentes e três modelos do G-BLUP (com efeito aditivo, aditivo e epistático, aditivo e dominante). Por fim, o desempenho preditivo dessas metodologias foi comparado. Em todos os cenários, as acurácias do QRF foram iguais ou superiores às metodologias avaliadas e mostrou ser uma ferramenta alternativa para predizer valores genéticos em características complexas.

The interplay between HLA-B and NLRP3 polymorphisms may be associated with the genetic susceptibility of gout.

BACKGROUND: HLA and NLRP3 play an important role in the development of various autoimmune and autoinflammatory diseases. Gout is an autoinflammatory disease associated with multiple genetic and environmental factors. The objective of the present study was to evaluate the interaction and association between genetic polymorphisms of HLA-B and the NLRP3 gene in Mexican patients with gout. METHODS AND RESULTS: Eighty-one patients with gout were included and compared with 95 healthy subjects. The polymorphisms rs4349859, rs116488202, rs2734583 and rs3099844 (within the HLA-B region) and rs3806268 and rs10754558 of the NLRP3 gene were genotyped using TaqMan probes in a Rotor-Gene device. The interactions were determined using the multifactorial dimensionality reduction (MDR) method, while the associations were determined through logistic regression models. The MDR analysis revealed significant interactions between the rs116488202 and rs10754558 polymorphisms with an entropy value of 4.31% (p < 0.0001). Significant risk associations were observed with rs4349859 and rs116488202 polymorphisms (p < 0.01); however, no significant associations were observed with the polymorphisms of the NLRP3 gene. CONCLUSIONS: The results suggest that HLA-B polymorphisms and their interaction with NLRP3 may contribute to the genetic susceptibility of gout.

Slow Protein Dynamics Elicits New Enzymatic Functions by Means of Epistatic Interactions.

Protein evolution depends on the adaptation of these molecules to different functional challenges. This occurs by tuning their biochemical, biophysical, and structural traits through the accumulation of mutations. While the role of protein dynamics in biochemistry is well recognized, there are limited examples providing experimental evidence of the optimization of protein dynamics during evolution. Here we report an NMR study of four variants of the CTX-M ß-lactamases, in which the interplay of two mutations outside the active site enhances the activity against a cephalosporin substrate, ceftazidime. The crystal structures of these enzymes do not account for this activity enhancement. By using NMR, here we show that the combination of these two mutations increases the backbone dynamics in a slow timescale and the exposure to the solvent of an otherwise buried ß-sheet. The two mutations located in this ß-sheet trigger conformational changes in loops located at the opposite side of the active site. We postulate that the most active variant explores alternative conformations that enable binding of the more challenging substrate ceftazidime. The impact of the mutations in the dynamics is context-dependent, in line with the epistatic effect observed in the catalytic activity of the different variants. These results reveal the existence of a dynamic network in CTX-M ß-lactamases that has been exploited in evolution to provide a net gain-of-function, highlighting the role of alternative conformations in protein evolution.

A Random Forest-Based Genome-Wide Scan Reveals Fertility-Related Candidate Genes and Potential Inter-Chromosomal Epistatic Regions Associated With Age at First Calving in Nellore Cattle.

This study aimed to perform a genome-wide association analysis (GWAS) using the Random Forest (RF) approach for scanning candidate genes for age at first calving (AFC) in Nellore cattle. Additionally, potential epistatic effects were investigated using linear mixed models with pairwise interactions between all markers with high importance scores within the tree ensemble non-linear structure. Data from Nellore cattle were used, including records of animals born between 1984 and 2015 and raised in commercial herds located in different regions of Brazil. The estimated breeding values (EBV) were computed and used as the response variable in the genomic analyses. After quality control, the remaining number of animals and SNPs considered were 3,174 and 360,130, respectively. Five independent RF analyses were carried out, considering different initialization seeds. The importance score of each SNP was averaged across the independent RF analyses to rank the markers according to their predictive relevance. A total of 117 SNPs associated with AFC were identified, which spanned 10 autosomes (2, 3, 5, 10, 11, 17, 18, 21, 24, and 25). In total, 23 non-overlapping genomic regions embedded 262 candidate genes for AFC. Enrichment analysis and previous evidence in the literature revealed that many candidate genes annotated close to the lead SNPs have key roles in fertility, including embryo pre-implantation and development, embryonic viability, male germinal cell maturation, and pheromone recognition. Furthermore, some genomic regions previously associated with fertility and growth traits in Nellore cattle were also detected in the present study, reinforcing the effectiveness of RF for pre-screening candidate regions associated with complex traits. Complementary analyses revealed that many SNPs top-ranked in the RF-based GWAS did not present a strong marginal linear effect but are potentially involved in epistatic hotspots between genomic regions in different autosomes, remarkably in the BTAs 3, 5, 11, and 21. The reported results are expected to enhance the understanding of genetic mechanisms involved in the biological regulation of AFC in this cattle breed.

Significance of linkage disequilibrium and epistasis on genetic variances in noninbred and inbred populations.

BACKGROUND: The influence of linkage disequilibrium (LD), epistasis, and inbreeding on genotypic variance continues to be an important area of investigation in genetics and evolution. Although the current knowledge about biological pathways and gene networks indicates that epistasis is important in determining quantitative traits, the empirical evidence for a range of species and traits is that the genotypic variance is most additive. This has been confirmed by some recent theoretical studies. However, because these investigations assumed linkage equilibrium, considered only additive effects, or used simplified assumptions for two- and higher-order epistatic effects, the objective of this investigation was to provide additional information about the impact of LD and epistasis on genetic variances in noninbred and inbred populations, using a simulated dataset. RESULTS: In general, the most important component of the genotypic variance was additive variance. Because of positive LD values, after 10 generations of random crosses there was generally a decrease in all genetic variances and covariances, especially the nonepistatic variances. Thus, the epistatic variance/genotypic variance ratio is inversely proportional to the LD level. Increasing inbreeding increased the magnitude of the additive, additive x additive, additive x dominance, and dominance x additive variances, and decreased the dominance and dominance x dominance variances. Except for duplicate epistasis with 100% interacting genes, the epistatic variance/genotypic variance ratio was proportional to the inbreeding level. In general, the additive x additive variance was the most important component of the epistatic variance. Concerning the genetic covariances, in general, they showed lower magnitudes relative to the genetic variances and positive and negative signs. The epistatic variance/genotypic variance ratio was maximized under duplicate and dominant epistasis and minimized assuming recessive and complementary epistasis. Increasing the percentage of epistatic genes from 30 to 100% increased the epistatic variance/genotypic variance ratio by a rate of 1.3 to 12.6, especially in inbred populations. The epistatic variance/genotypic variance ratio was maximized in the noninbred and inbred populations with intermediate LD and an average allelic frequency of the dominant genes of 0.3 and in the noninbred and inbred populations with low LD and an average allelic frequency of 0.5. CONCLUSIONS: Additive variance is in general the most important component of genotypic variance. LD and inbreeding have a significant effect on the magnitude of the genetic variances and covariances. In general, the additive x additive variance is the most important component of epistatic variance. The maximization of the epistatic variance/genotypic variance ratio depends on the LD level, degree of inbreeding, epistasis type, percentage of interacting genes, and average allelic frequency.

Mitochondrial Genetics Reinforces Multiple Layers of Interaction in Alzheimer's Disease.

Nuclear DNA has been the main source of genome-wide loci association in neurodegenerative diseases, only partially accounting for the heritability of Alzheimer's Disease (AD). In this context, mitochondrial DNA (mtDNA) is gaining more attention. Here, we investigated mitochondrial genes and genetic variants that may influence mild cognitive impairment and AD, through an integrative analysis including differential gene expression and mitochondrial genome-wide epistasis. We assessed the expression of mitochondrial genes in different brain tissues from two public RNA-Seq databases (GEO and GTEx). Then, we analyzed mtDNA from the ADNI Cohort and investigated epistasis regarding mitochondrial variants and levels of Aß1-42, TAU, and Phosphorylated TAU (PTAU) from cognitively healthy controls, and both mild cognitive impairment (MCI) and AD cases. We identified multiple differentially expressed mitochondrial genes in the comparisons between cognitively healthy individuals and AD patients. We also found increased protein levels in MCI and AD patients when compared to healthy controls, as well as novel candidate networks of mtDNA epistasis, which included variants in all mitochondrially-encoded oxidative phosphorylation complexes, 12S rRNA and MT-DLOOP. Our results highlight layers of potential interactions involving mitochondrial genetics and suggest specific molecular alterations as potential biomarkers for AD.

Epistasis Between Two Gene Variants of Leptin and Vascular Endothelial Growth Factor Genes in the Development of Primary Knee Osteoarthritis.

BACKGROUND: The association of leptin (LEP) and vascular endothelial growth factor A (VEGFA) genes with the susceptibility to knee osteoarthritis (OA) has been analyzed; however, the epistasis between them has not been investigated. OBJECTIVE: The objective of the study was to analyze the association of LEP and VEGFA variants and their interaction with primary knee OA in a Mexican Mestizo population. METHODS: A case-control study was developed. Cases were ≥40 years, BMI ≤27 kg/m2, with primary knee OA and radiologic Grade ≥2. Controls were participants with no knee OA and a radiologic Grade < 2. The rs2167270 of LEP and rs2010963 of VEGFA were genotyped. Genotypic association was tested under codominant, dominant, and recessive models. Uni- and multi-variate analyses were developed through non-conditional logistic regression. The multifactor dimensionality reduction algorithm was developed to detect epistasis. RESULTS: Participants comprised 103 cases and 179 controls. Allelic and genotypic distributions did not show differences between the groups. Notwithstanding, a statistically significant interaction was observed between the LEP and VEGFA genes (p = 0.02) with a testing accuracy of 0.5199 and cross-validation consistency of 10/10. This interaction model confers an increased risk to knee OA (OR [95% CI] = 1.8 [1.1-2.9]). CONCLUSION: Interaction between LEP and VEGFA is related with genetic susceptibility to developing primary knee OA.

Brazilian Multiethnic Association Study of Genetic Variant Interactions among FOS, CASP8, MMP2 and CRISPLD2 in the Risk of Nonsyndromic Cleft Lip with or without Cleft Palate.

Associations of CRISPLD2 (cysteine-rich secretory protein LCCL domain containing 2) and genes belonging to its activation pathway, including FOS (Fos proto-oncogene), CASP8 (caspase 8) and MMP2 (matrix metalloproteinase 2), with nonsyndromic orofacial cleft risk, have been reported, but the results are yet unclear. The aim of this study was to evaluate single nucleotide polymorphisms (SNPs) in FOS, CASP8 and MMP2 and to determine their SNP-SNP interactions with CRISPLD2 variants in the risk of nonsyndromic cleft lip with or without cleft palate (NSCL±P) in the Brazilian population. The SNPs rs1046117 (FOS), rs3769825 (CASP8) and rs243836 (MMP2) were genotyped using TaqMan allelic discrimination assays in a case-control sample containing 801 NSCL±P patients (233 nonsyndromic cleft lip only (NSCLO) and 568 nonsyndromic cleft lip and palate (NSCLP)) and 881 healthy controls via logistic regression analysis adjusted for the effects of sex and genomic ancestry proportions with a multiple comparison p value set at ≤0.01. SNP-SNP interactions with rs1546124, rs8061351, rs2326398 and rs4783099 in CRISPLD2 were performed with the model-based multifactor dimensionality reduction test complemented with a 1000 permutation-based strategy. Although the association between FOS rs1046117 and risk of NSCL±P reached only nominal p values, NSCLO risk was significantly higher in carriers of the FOS rs1046117 C allele (OR: 1.28, 95% CI: 1.10-1.64, p = 0.004), TC heterozygous genotype (OR: 1.59, 95% CI: 1.16-2.18, p = 0.003), and in the dominant model (OR: 1.50, 95% CI: 1.10-2.02, p = 0.007). Individually, no significant associations between cleft risk and the SNPs in CASP8 and MMP2 were observed. SNP-SNP interactions involving CRISPLD2 variants and rs1046117 (FOS), rs3769825 (CASP8) and rs243836 (MMP2) yielded several significant p values, mostly driven by FOS rs1046117 and CASP8 rs3769825 in NSCL±P, FOS rs1046117 in NSCLO and CRISPLD2 rs8061351 in NSCLP. Our study is the first in the Brazilian population to reveal the association of FOS rs1046117 with NSCLO risk, and to support that CRISPLD2, CASP8, FOS and MMP2 interactions may be related to the pathogenesis of this common craniofacial malformation.

Genome-wide interaction study reveals epistatic interactions for beef lipid-related traits in Nellore cattle.

Gene-gene interactions cause hidden genetic variation in natural populations and could be responsible for the lack of replication that is typically observed in complex traits studies. This study aimed to identify gene-gene interactions using the empirical Hilbert-Schmidt Independence Criterion method to test for epistasis in beef fatty acid profile traits of Nellore cattle. The dataset contained records from 963 bulls, genotyped using a 777 962k SNP chip. Meat samples of Longissimus muscle, were taken to measure fatty acid composition, which was quantified by gas chromatography. We chose to work with the sums of saturated (SFA), monounsaturated (MUFA), polyunsaturated (PUFA), omega-3 (OM3), omega-6 (OM6), SFA:PUFA and OM3:OM6 fatty acid ratios. The SNPs in the interactions where P < 10 - 8 were mapped individually and used to search for candidate genes. Totals of 602, 3, 13, 23, 13, 215 and 169 candidate genes for SFAs, MUFAs, PUFAs, OM3s, OM6s and SFA:PUFA and OM3:OM6 ratios were identified respectively. The candidate genes found were associated with cholesterol, lipid regulation, low-density lipoprotein receptors, feed efficiency and inflammatory response. Enrichment analysis revealed 57 significant GO and 18 KEGG terms ( P < 0.05), most of them related to meat quality and complementary terms. Our results showed substantial genetic interactions associated with lipid profile, meat quality, carcass and feed efficiency traits for the first time in Nellore cattle. The knowledge of these SNP-SNP interactions could improve understanding of the genetic and physiological mechanisms that contribute to lipid-related traits and improve human health by the selection of healthier meat products.

Genetic parameters controlling the inheritance of glaucousness and yield traits in bread wheat / Parâmetros genéticos que controlam a herança de glaucosidade e características de produção em trigo mole

Wheat breeders frequently use generation mean analysis to obtain information on the type of gene action involved in inheriting a trait to choose the helpful breeding procedure for trait improvement. The present study was carried out to study the inter-allelic and intra-allelic gene action and inheritance of glaucousness, earliness and yield traits in a bread wheat cross between divergent parents in glaucousness and yield traits; namely Mut-2 (P1) and Sakha 93 (P2). The experimental material included six populations, i.e. P1, P2, F1, F2, BC1, and BC2 for this wheat cross. A randomized complete block design with three replications was used, and a six parameters model was applied. Additive effects were generally more critical than dominance for all studied traits, except for plant height (PH) and grain yield/plant (GYPP). The duplicate epistasis was observed in spike length; SL, spikes/plant; SPP and days to heading; DTH. All six types of allelic and non-allelic interaction effects controlled SL, GYPP, DTH and glaucousness. All three types of epistasis, i.e. additive x additive, additive x dominance, and dominance x dominance, are essential in determining the inheritance of four traits (SL, GYPP, DTH and glaucousness). Dominance × dominance effects were higher in magnitude than additive × dominance and additive × additive in most traits. The average degree of dominance was minor than unity in six traits (glaucousness, grains/spike, spike weight, days to maturity, 100-grain weight and SL), indicating partial dominance and selection for these traits might be more effective in early generations. Meanwhile, the remaining traits (PH, SPP, GYPP and DTH) had a degree of dominance more than unity, indicating that overdominance gene effects control such traits and it is preferable to postpone selection to later generations. The highest values of [...].(AU)

Os criadores de trigo frequentemente usam a análise da média de geração para obter informações sobre o tipo de ação do gene envolvida na herança de uma característica para escolher o procedimento de melhoramento útil para o aprimoramento da característica. O presente estudo foi conduzido para estudar a ação do gene interalélico e intraalélico e a herança de características de glaucosidade, precocidade e produção em um cruzamento de trigo mole entre pais divergentes em glaucosidade e características de produção; nomeadamente Mut-2 (P1) e Sakha 93 (P2). O material experimental incluiu seis populações, ou seja, P1, P2, F1, F2, BC1 e BC2 para este cruzamento de trigo. O delineamento experimental foi em blocos ao acaso com três repetições e aplicado um modelo de seis parâmetros. Os efeitos aditivos foram geralmente mais críticos do que a dominância para todas as características estudadas, exceto para altura da planta (AP) e rendimento de grãos / planta (GYPP). A epistasia duplicada foi observada no comprimento da ponta; SL, espigas / planta; SPP e dias para o cabeçalho; DTH. Todos os seis tipos de efeitos de interação alélica e não alélica controlaram SL, GYPP, DTH e glaucosidade. Todos os três tipos de epistasia, ou seja, aditivo x aditivo, aditivo x dominância e dominância x dominância, são essenciais na determinação da herança de quatro características (SL, GYPP, DTH e glaucosidade). Os efeitos de dominância × dominância foram maiores em magnitude do que aditivo × dominância e aditivo × aditivo na maioria das características. O grau médio de dominância foi menor do que a unidade em seis características (glaucosidade, grãos / espiga, peso da espiga, dias até a maturidade, peso de 100 grãos e SL), indicando dominância parcial, e a seleção para essas características pode ser mais eficaz nas gerações iniciais. Enquanto isso, os traços restantes (PH, SPP, GYPP e [...].(AU)

Genetic parameters controlling the inheritance of glaucousness and yield traits in bread wheat / Parâmetros genéticos que controlam a herança de glaucosidade e características de produção em trigo mole

Wheat breeders frequently use generation mean analysis to obtain information on the type of gene action involved in inheriting a trait to choose the helpful breeding procedure for trait improvement. The present study was carried out to study the inter-allelic and intra-allelic gene action and inheritance of glaucousness, earliness and yield traits in a bread wheat cross between divergent parents in glaucousness and yield traits; namely Mut-2 (P1) and Sakha 93 (P2).The experimental material included six populations, i.e. P1, P2, F1, F2, BC1, and BC2 for this wheat cross. A randomized complete block design with three replications was used, and a six parameters model was applied. Additive effects were generally more critical than dominance for all studied traits, except for plant height (PH) and grain yield/plant (GYPP). The duplicate epistasis was observed in spike length; SL, spikes/plant; SPP and days to heading; DTH. All six types of allelic and non-allelic interaction effects controlled SL, GYPP, DTH and glaucousness. All three types of epistasis, i.e. additive x additive, additive x dominance, and dominance x dominance, are essential in determining the inheritance of four traits (SL, GYPP, DTH and glaucousness). Dominance × dominance effects were higher in magnitude than additive × dominance and additive × additive in most traits. The average degree of dominance was minor than unity in six traits (glaucousness, grains/spike, spike weight, days to maturity, 100-grain weight and SL), indicating partial dominance and selection for these traits might be more effective in early generations. Meanwhile, the remaining traits (PH, SPP, GYPP and DTH) had a degree of dominance more than unity, indicating that overdominance gene effects control such traits and it is preferable to postpone selection to later generations. The highest values of narrow-sense heritability and genetic advance were recorded by glaucousness trait followed by SL and SPP, indicating that selection in segregating generations would be more effective than other traits.

Os criadores de trigo frequentemente usam a análise da média de geração para obter informações sobre o tipo de ação do gene envolvida na herança de uma característica para escolher o procedimento de melhoramento útil para o aprimoramento da característica. O presente estudo foi conduzido para estudar a ação do gene interalélico e intraalélico e a herança de características de glaucosidade, precocidade e produção em um cruzamento de trigo mole entre pais divergentes em glaucosidade e características de produção; nomeadamente Mut-2 (P1) e Sakha 93 (P2). O material experimental incluiu seis populações, ou seja, P1, P2, F1, F2, BC1 e BC2 para este cruzamento de trigo. O delineamento experimental foi em blocos ao acaso com três repetições e aplicado um modelo de seis parâmetros. Os efeitos aditivos foram geralmente mais críticos do que a dominância para todas as características estudadas, exceto para altura da planta (AP) e rendimento de grãos / planta (GYPP). A epistasia duplicada foi observada no comprimento da ponta; SL, espigas/planta; SPP e dias para o cabeçalho; DTH. Todos os seis tipos de efeitos de interação alélica e não alélica controlaram SL, GYPP, DTH e glaucosidade. Todos os três tipos de epistasia, ou seja, aditivo x aditivo, aditivo x dominância e dominância x dominância, são essenciais na determinação da herança de quatro características (SL, GYPP, DTH e glaucosidade). Os efeitos de dominância × dominância foram maiores em magnitude do que aditivo × dominância e aditivo × aditivo na maioria das características. O grau médio de dominância foi menor do que a unidade em seis características (glaucosidade, grãos / espiga, peso da espiga, dias até a maturidade, peso de 100 grãos e SL), indicando dominância parcial, e a seleção para essas características pode ser mais eficaz nas gerações iniciais. Enquanto isso, os traços restantes (PH, SPP, GYPP e DTH) tiveram um grau de dominância maior do que a unidade, indicando que os efeitos do gene de superdominância controlam tais traços e é preferível adiar a seleção para gerações posteriores. Os maiores valores de herdabilidade no sentido restrito e avanço genético foram registrados pelo traço de glaucosidade seguido por SL e SPP, indicando que a seleção em gerações segregadas seria mais eficaz do que outros caracteres.

Genetic parameters controlling the inheritance of glaucousness and yield traits in bread wheat / Parâmetros genéticos que controlam a herança de glaucosidade e características de produção em trigo mole

Wheat breeders frequently use generation mean analysis to obtain information on the type of gene action involved in inheriting a trait to choose the helpful breeding procedure for trait improvement. The present study was carried out to study the inter-allelic and intra-allelic gene action and inheritance of glaucousness, earliness and yield traits in a bread wheat cross between divergent parents in glaucousness and yield traits; namely Mut-2 (P1) and Sakha 93 (P2). The experimental material included six populations, i.e. P1, P2, F1, F2, BC1, and BC2 for this wheat cross. A randomized complete block design with three replications was used, and a six parameters model was applied. Additive effects were generally more critical than dominance for all studied traits, except for plant height (PH) and grain yield/plant (GYPP). The duplicate epistasis was observed in spike length; SL, spikes/plant; SPP and days to heading; DTH. All six types of allelic and non-allelic interaction effects controlled SL, GYPP, DTH and glaucousness. All three types of epistasis, i.e. additive x additive, additive x dominance, and dominance x dominance, are essential in determining the inheritance of four traits (SL, GYPP, DTH and glaucousness). Dominance × dominance effects were higher in magnitude than additive × dominance and additive × additive in most traits. The average degree of dominance was minor than unity in six traits (glaucousness, grains/spike, spike weight, days to maturity, 100-grain weight and SL), indicating partial dominance and selection for these traits might be more effective in early generations. Meanwhile, the remaining traits (PH, SPP, GYPP and DTH) had a degree of dominance more than unity, indicating that overdominance gene effects control such traits and it is preferable to postpone selection to later generations. The highest values of [...].

Os criadores de trigo frequentemente usam a análise da média de geração para obter informações sobre o tipo de ação do gene envolvida na herança de uma característica para escolher o procedimento de melhoramento útil para o aprimoramento da característica. O presente estudo foi conduzido para estudar a ação do gene interalélico e intraalélico e a herança de características de glaucosidade, precocidade e produção em um cruzamento de trigo mole entre pais divergentes em glaucosidade e características de produção; nomeadamente Mut-2 (P1) e Sakha 93 (P2). O material experimental incluiu seis populações, ou seja, P1, P2, F1, F2, BC1 e BC2 para este cruzamento de trigo. O delineamento experimental foi em blocos ao acaso com três repetições e aplicado um modelo de seis parâmetros. Os efeitos aditivos foram geralmente mais críticos do que a dominância para todas as características estudadas, exceto para altura da planta (AP) e rendimento de grãos / planta (GYPP). A epistasia duplicada foi observada no comprimento da ponta; SL, espigas / planta; SPP e dias para o cabeçalho; DTH. Todos os seis tipos de efeitos de interação alélica e não alélica controlaram SL, GYPP, DTH e glaucosidade. Todos os três tipos de epistasia, ou seja, aditivo x aditivo, aditivo x dominância e dominância x dominância, são essenciais na determinação da herança de quatro características (SL, GYPP, DTH e glaucosidade). Os efeitos de dominância × dominância foram maiores em magnitude do que aditivo × dominância e aditivo × aditivo na maioria das características. O grau médio de dominância foi menor do que a unidade em seis características (glaucosidade, grãos / espiga, peso da espiga, dias até a maturidade, peso de 100 grãos e SL), indicando dominância parcial, e a seleção para essas características pode ser mais eficaz nas gerações iniciais. Enquanto isso, os traços restantes (PH, SPP, GYPP e [...].

Genetic parameters controlling the inheritance of glaucousness and yield traits in bread wheat

Abstract Wheat breeders frequently use generation mean analysis to obtain information on the type of gene action involved in inheriting a trait to choose the helpful breeding procedure for trait improvement. The present study was carried out to study the inter-allelic and intra-allelic gene action and inheritance of glaucousness, earliness and yield traits in a bread wheat cross between divergent parents in glaucousness and yield traits; namely Mut-2 (P1) and Sakha 93 (P2). The experimental material included six populations, i.e. P1, P2, F1, F2, BC1, and BC2 for this wheat cross. A randomized complete block design with three replications was used, and a six parameters model was applied. Additive effects were generally more critical than dominance for all studied traits, except for plant height (PH) and grain yield/plant (GYPP). The duplicate epistasis was observed in spike length; SL, spikes/plant; SPP and days to heading; DTH. All six types of allelic and non-allelic interaction effects controlled SL, GYPP, DTH and glaucousness. All three types of epistasis, i.e. additive x additive, additive x dominance, and dominance x dominance, are essential in determining the inheritance of four traits (SL, GYPP, DTH and glaucousness). Dominance × dominance effects were higher in magnitude than additive × dominance and additive × additive in most traits. The average degree of dominance was minor than unity in six traits (glaucousness, grains/spike, spike weight, days to maturity, 100-grain weight and SL), indicating partial dominance and selection for these traits might be more effective in early generations. Meanwhile, the remaining traits (PH, SPP, GYPP and DTH) had a degree of dominance more than unity, indicating that overdominance gene effects control such traits and it is preferable to postpone selection to later generations. The highest values of narrow-sense heritability and genetic advance were recorded by glaucousness trait followed by SL and SPP, indicating that selection in segregating generations would be more effective than other traits.

Resumo Os criadores de trigo frequentemente usam a análise da média de geração para obter informações sobre o tipo de ação do gene envolvida na herança de uma característica para escolher o procedimento de melhoramento útil para o aprimoramento da característica. O presente estudo foi conduzido para estudar a ação do gene interalélico e intraalélico e a herança de características de glaucosidade, precocidade e produção em um cruzamento de trigo mole entre pais divergentes em glaucosidade e características de produção; nomeadamente Mut-2 (P1) e Sakha 93 (P2). O material experimental incluiu seis populações, ou seja, P1, P2, F1, F2, BC1 e BC2 para este cruzamento de trigo. O delineamento experimental foi em blocos ao acaso com três repetições e aplicado um modelo de seis parâmetros. Os efeitos aditivos foram geralmente mais críticos do que a dominância para todas as características estudadas, exceto para altura da planta (AP) e rendimento de grãos / planta (GYPP). A epistasia duplicada foi observada no comprimento da ponta; SL, espigas/planta; SPP e dias para o cabeçalho; DTH. Todos os seis tipos de efeitos de interação alélica e não alélica controlaram SL, GYPP, DTH e glaucosidade. Todos os três tipos de epistasia, ou seja, aditivo x aditivo, aditivo x dominância e dominância x dominância, são essenciais na determinação da herança de quatro características (SL, GYPP, DTH e glaucosidade). Os efeitos de dominância × dominância foram maiores em magnitude do que aditivo × dominância e aditivo × aditivo na maioria das características. O grau médio de dominância foi menor do que a unidade em seis características (glaucosidade, grãos / espiga, peso da espiga, dias até a maturidade, peso de 100 grãos e SL), indicando dominância parcial, e a seleção para essas características pode ser mais eficaz nas gerações iniciais. Enquanto isso, os traços restantes (PH, SPP, GYPP e DTH) tiveram um grau de dominância maior do que a unidade, indicando que os efeitos do gene de superdominância controlam tais traços e é preferível adiar a seleção para gerações posteriores. Os maiores valores de herdabilidade no sentido restrito e avanço genético foram registrados pelo traço de glaucosidade seguido por SL e SPP, indicando que a seleção em gerações segregadas seria mais eficaz do que outros caracteres.

Mapping Resistance to Argentinean Fusarium (Graminearum) Head Blight Isolates in Wheat.

Fusarium head blight (FHB) of wheat, caused by Fusarium graminearum (Schwabe), is a destructive disease worldwide, reducing wheat yield and quality. To accelerate the improvement of scab tolerance in wheat, we assessed the International Triticeae Mapping Initiative mapping population (ITMI/MP) for Type I and II resistance against a wide population of Argentinean isolates of F. graminearum. We discovered a total of 27 additive QTLs on ten different (2A, 2D, 3B, 3D, 4B, 4D, 5A, 5B, 5D and 6D) wheat chromosomes for Type I and Type II resistances explaining a maximum of 15.99% variation. Another four and two QTLs for thousand kernel weight in control and for Type II resistance, respectively, involved five different chromosomes (1B, 2D, 6A, 6D and 7D). Furthermore, three, three and five QTLs for kernel weight per spike in control, for Type I resistance and for Type II resistance, correspondingly, involved ten chromosomes (2A, 2D, 3B, 4A, 5A, 5B, 6B, 7A, 7B, 7D). We were also able to detect five and two epistasis pairs of QTLs for Type I and Type II resistance, respectively, in addition to additive QTLs that evidenced that FHB resistance in wheat is controlled by a complex network of additive and epistasis QTLs.