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Interacting Loci (interacting + locus)
Selected AbstractsA Combinatorial Searching Method for Detecting a Set of Interacting Loci Associated with Complex TraitsANNALS OF HUMAN GENETICS, Issue 5 2006Qiuying Sha Summary Complex diseases are presumed to be the results of the interaction of several genes and environmental factors, with each gene only having a small effect on the disease. Mapping complex disease genes therefore becomes one of the greatest challenges facing geneticists. Most current approaches of association studies essentially evaluate one marker or one gene (haplotype approach) at a time. These approaches ignore the possibility that effects of multilocus functional genetic units may play a larger role than a single-locus effect in determining trait variability. In this article, we propose a Combinatorial Searching Method (CSM) to detect a set of interacting loci (may be unlinked) that predicts the complex trait. In the application of the CSM, a simple filter is used to filter all the possible locus-sets and retain the candidate locus-sets, then a new objective function based on the cross-validation and partitions of the multi-locus genotypes is proposed to evaluate the retained locus-sets. The locus-set with the largest value of the objective function is the final locus-set and a permutation procedure is performed to evaluate the overall p-value of the test for association between the final locus-set and the trait. The performance of the method is evaluated by simulation studies as well as by being applied to a real data set. The simulation studies show that the CSM has reasonable power to detect high-order interactions. When the CSM is applied to a real data set to detect the locus-set (among the 13 loci in the ACE gene) that predicts systolic blood pressure (SBP) or diastolic blood pressure (DBP), we found that a four-locus gene-gene interaction model best predicts SBP with an overall p-value = 0.033, and similarly a two-locus gene-gene interaction model best predicts DBP with an overall p-value = 0.045. [source] Genes causing clefting syndromes as candidates for non-syndromic cleft lip with or without cleft palate: a family-based association studyEUROPEAN JOURNAL OF ORAL SCIENCES, Issue 6 2008Luca Scapoli Clefts of the orofacial region are among the most common congenital defects, caused by abnormal facial development during gestation. Non-syndromic cleft lip with or without cleft palate (NSCLP) is a complex trait most probably caused by multiple interacting loci, with possible additional environmental factors. As facial clefts form part of more than 300 syndromes, one strategy for identifying the genetic causes of NSCLP could be to study candidate genes responsible for clefting syndromes. Three genes were selected for this investigation: TP63, which codes for the tumour protein p63 and causes Ectrodactyly-Ectodermal dysplasia-orofacial Cleft syndrome; JAG2, a downstream gene of TP63; and MID1, which is responsible for Opitz syndrome. A linkage disequilibrium investigation was performed with intragenic single nucleotide polymorphisms on each of these genes in a sample study of 239 patients/parents trios. Evidence which suggests that JAG2 and MID1 may play a role in NSCLP was obtained. [source] PERSPECTIVE: SIGN EPISTASIS AND GENETIC COSTRAINT ON EVOLUTIONARY TRAJECTORIESEVOLUTION, Issue 6 2005Daniel M. Weinreich Abstract Epistasis for fitness means that the selective effect of a mutation is conditional on the genetic background in which it appears. Although epistasis is widely observed in nature, our understanding of its consequences for evolution by natural selection remains incomplete. In particular, much attention focuses only on its influence on the instantaneous rate of changes in frequency of selected alleles via epistatic contribution to the additive genetic variance for fitness. Thus, in this framework epistasis only has evolutionary importance if the interacting loci are simultaneously segregating in the population. However, the selective accessibility of mutational trajectories to high fitness genotypes may depend on the genetic background in which novel mutations appear, and this effect is independent of population polymorphism at other loci. Here we explore this second influence of epistasis on evolution by natural selection. We show that it is the consequence of a particular form of epistasis, which we designate sign epistasis. Sign epistasis means that the sign of the fitness effect of a mutation is under epistatic control; thus, such a mutation is beneficial on some genetic backgrounds and deleterious on others. Recent experimental innovations in microbial systems now permit assessment of the fitness effects of individual mutations on multiple genetic backgrounds. We review this literature and identify many examples of sign epistasis, and we suggest that the implications of these results may generalize to other organisms. These theoretical and empirical considerations imply that strong genetic constraint on the selective accessibility of trajectories to high fitness genotypes may exist and suggest specific areas of investigation for future research. [source] Shuttle craft: a candidate quantitative trait gene for Drosophila lifespanAGING CELL, Issue 5 2004Elena G. Pasyukova Summary Variation in longevity in natural populations is attributable to the segregation of multiple interacting loci, whose effects are sensitive to the environment. Although there has been considerable recent progress towards understanding the environmental factors and genetic pathways that regulate lifespan, little is known about the genes causing naturally occurring variation in longevity. Previously, we used deficiency complementation mapping to map two closely linked quantitative trait loci (QTL) causing female-specific variation in longevity between the Oregon (Ore) and 2b strains of Drosophila melanogaster to 35B9,C3 and 35C3 on the second chromosome. The 35B9,C3 QTL encompasses a 50-kb region including four genes, for one of which, shuttle craft (stc), mutations have been generated. The 35C3 QTL localizes to a 200-kb interval with 15 genes, including three genes for which mutations exist (reduced (rd), guftagu (gft) and ms(2)35Ci). Here, we report quantitative complementation tests to mutations at these four positional candidate genes, and show that ms(2)35Ci and stc are novel candidate quantitative trait genes affecting variation in Drosophila longevity. Complementation tests with stc alleles reveal sex- and allele-specific failure to complement, and complementation effects are dependent on the genetic background, indicating considerable epistasis for lifespan. In addition, a homozygous viable stc allele has a sex-specific effect on lifespan. stc encodes an RNA polymerase II transcription factor, and is an attractive candidate gene for the regulation of longevity and variation in longevity, because it is required for motoneuron development and is expressed throughout development. Quantitative genetic analysis of naturally occurring variants with subtle effects on lifespan can identify novel candidate genes and pathways important in the regulation of longevity. [source] Grey plumage colouration in the duck is genetically determined by the alleles on two different, interacting lociANIMAL GENETICS, Issue 1 2010Y. Gong Summary Based on the observation of a grey phenotype in the F1 generation from a cross between two white plumage duck varieties, the white Kaiya and the white Liancheng, we hypothesized a possible interaction between two autosomal loci that determine grey plumage. Using the parental and F1 individuals, seven testing combinations including five different F1 intercrosses (F2) and two different backcrosses (BC1 and BC2) were designed to test our hypothesis. It was demonstrated by chi-squared analysis that six test matings produced offspring in the expected ratios between the grey and white, with P- values ranging from 0.50 to 0.99. Another mating, where all white offspring were expected, produced 33 white individuals. These results verified that the interaction between two loci produced the grey phenotype. The C locus, which carries the recessive allele (c), was previously thought to be the only gene responsible for white plumage in the duck. This is the first report that an allele (t), carried by the white Liancheng at a different autosomal locus, also determines white plumage in ducks. Furthermore, the dominant alleles at both loci can interact with each other to produce the grey phenotype, and a new dark phenotype, observed in some F2 individuals, can be attributed to the dosage effect of the T allele. [source] Evaluation of the NK2 Homeobox 1 Gene (NKX2-1) as a Hirschsprung's Disease Locus THIS ARTICLE HAS BEEN RETRACTEDANNALS OF HUMAN GENETICS, Issue 2 2008M.-M. Garcia-Barceló Summary Hirschsprung's disease (HSCR, colonic aganglionosis) is an oligogenic entity that usually requires mutations in RET and other interacting loci. Decreased levels of RET expression may lead to the manifestation of HSCR. We previously showed that RET transcription was decreased due to alteration of the NKX2,1 binding site by two HSCR-associated RET promoter single nucleotide polymorphisms (SNPs). This prompted us to investigate whether DNA alterations in NKX2-1 could play a role in HSCR by affecting the RET -regulatory properties of the NKX2,1 protein. Our initial study on 86 Chinese HSCR patients revealed a Gly322Ser amino acid substitution in the NKX2,1 protein. In this study, we have examined 102 additional Chinese and 70 Caucasian patients and 194 Chinese and 60 Caucasian unselected, unrelated, subjects as controls. The relevance of the DNA changes detected in NKX2-1 by direct sequencing were evaluated using bioinformatics, reporter and binding-assays, mouse neurosphere culture, immunohistochemistry and immunofluorescence techniques. Met3Leu and Pro48Pro were identified in 2 Caucasian and 1 Chinese patients respectively. In vitro analysis showed that Met3Leu reduced the activity of the RET promoter by 100% in the presence of the wild-type or HSCR-associated RET promoter SNP alleles. The apparent binding affinity of the NKX2,1 mutated protein was not decreased. The Met3Leu mutation may affect the interaction of NKX2,1 with its protein partners. The absence of NKX2-1 expression in mouse but not in human gut suggests that the role of NKX2,1 in gut development differs between the two species. NKX2-1 mutations could contribute to HSCR by affecting RET expression through defective interactions with other transcription factors. [source] An Empirical Bayes Method for Estimating Epistatic Effects of Quantitative Trait LociBIOMETRICS, Issue 2 2007Shizhong Xu Summary The genetic variance of a quantitative trait is often controlled by the segregation of multiple interacting loci. Linear model regression analysis is usually applied to estimating and testing effects of these quantitative trait loci (QTL). Including all the main effects and the effects of interaction (epistatic effects), the dimension of the linear model can be extremely high. Variable selection via stepwise regression or stochastic search variable selection (SSVS) is the common procedure for epistatic effect QTL analysis. These methods are computationally intensive, yet they may not be optimal. The LASSO (least absolute shrinkage and selection operator) method is computationally more efficient than the above methods. As a result, it has been widely used in regression analysis for large models. However, LASSO has never been applied to genetic mapping for epistatic QTL, where the number of model effects is typically many times larger than the sample size. In this study, we developed an empirical Bayes method (E-BAYES) to map epistatic QTL under the mixed model framework. We also tested the feasibility of using LASSO to estimate epistatic effects, examined the fully Bayesian SSVS, and reevaluated the penalized likelihood (PENAL) methods in mapping epistatic QTL. Simulation studies showed that all the above methods performed satisfactorily well. However, E-BAYES appears to outperform all other methods in terms of minimizing the mean-squared error (MSE) with relatively short computing time. Application of the new method to real data was demonstrated using a barley dataset. [source] | ||||||||||