Genome Wide Interaction Studies Identify Sex-Specific Risk Alleles for Nonsyndromic Orofacial Clefts

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is the most common craniofacial birth defect in humans and is notable for its apparent sexual dimorphism where approximately twice as many males are affected as females. The sources of this disparity are largely unknown, but interactions between genetic and sex effects are likely contributors. We examined gene-by-sex (G x S) interactions in a worldwide sample of 2,142 NSCL/P cases and 1,700 controls recruited from 13 countries. First, we performed genome-wide joint tests of the genetic (G) and G x S effects genome-wide using logistic regression assuming an additive genetic model and adjusting for 18 principal components of ancestry. We further interrogated loci with suggestive results from the joint test (p < 1.00 × 10−5) by examining the G x S effects from the same model. Out of the 133 loci with suggestive results (p < 1.00 × 10−5) for the joint test, we observed one genome-wide significant G x S effect in the 10q21 locus (rs72804706; p = 6.69 × 10−9; OR = 2.62 [1.89, 3.62]) and 16 suggestive G x S effects. At the intergenic 10q21 locus, the risk of NSCL/P is estimated to increase with additional copies of the minor allele for females, but the opposite effect for males. Our observation that the impact of genetic variants on NSCL/P risk differs for males and females may further our understanding of the genetic architecture of NSCL/P and the sex differences underlying clefts and other birth defects.

Genetic variability of traits recorded during 100-day stationary performance test and inbreeding level in Polish warmblood stallions

The objectives of this study were to estimate direct heritability of 30 conformation and performance traits evaluated during 100-day stationary performance test and to predict the genetic effects in Polish Warmblood stallions. Inbreeding coefficients were estimated as well. Moreover, phenotypic and genetic trends were derived. The data were extracted from the database of the Polish Horse Breeding Association. The analysis included 494 warmblood stallions, which performed during 100-day test in the years 2002–2008 at two Polish Training Centres. Pedigree data comprised 8 512 individuals. Restricted maximum likelihood was employed to estimate parameters under an additive genetic model (including fixed effects: age of stallion, breed, year and place of performance test). Nonzero inbreeding coefficients were estimated for 88 stallions with performance records as well as for 458 unrecorded ancestors. Average inbreeding level for the stallions with records was 0.29 %, whereas for all inbred individuals – 1.69 %. The average completeness of the pedigrees, expressed as Cassell coefficient, for the recorded stallions was 42.47 %. The heritability estimates varied from 0.14 (character) to 0.87 (total index). Relatively high heritabilities were found for jumping-ability traits. In general, the genetic trends for studied traits were negligibly positive.

Maternal genetic effects on body weight and breast morphological traits in duck population under selection

Direct and maternal additive genetic and mitochondrial variances of duck meat performance traits were estimated using AI-REML algorithm. Records of 3 099 (5 010 pedigreed birds) from six consecutive generations were included. The following four traits were investigated: body weight at 3rd week, body weight at 7th week, sternum crest length at 7th week (in cm), and breast muscles thickness at 7th week (in cm). The data were analysed via three single trait linear animal models: I – additive genetic model, II – model extended to additive maternal effects; III– as model II with mitochondrial effects as random. Adequacy of the models was examined by Akaike´s information criterion (AIC). Relatively high direct additive heritability estimates were obtained for body weight at 3rd week (0.4326–0.4546) and body weight at 7th week (0.5322–0.6088) whereas lower estimates were obtained for sternum crest length (0.1756–0.2744) and breast muscles thickness (0.1369–0.2932). The maternal heritabilities were moderate and also considerably depended on the model used. For all of the studied traits a negative covariance between direct and maternal genetic effects was found. Mitochondrial heritabilities were very low. Generally, on the basis of criteria employed, the model III can be suggested for analysis of body weight whereas for other traits model II seems to be suitable.

Spatial analysis methods for forest genetic trials

Spatial analysis, using separable autoregressive processes of residuals, is increasingly used in agricultural variety yield trial analysis. Interpretation of the sample variogram has become a tool for the detection of global trend and "extraneous" variation aligned with trial rows and columns. We applied this methodology to five selected forest genetic trials using an individual tree additive genetic model. We compared the base design model with post-blocking, a first-order autoregressive model of residuals (AR1), that model with an independent error term (AR1η), a combined base and autoregressive model, an autoregressive model only within replicates and an autoregressive model applied at the plot level. Post-blocking gave substantial improvements in log-likelihood over the base model, but the AR1η model was even better. The independent error term was necessary with the individual tree additive genetic model to avoid substantial positive bias in estimates of additive genetic variance in the AR1 model and blurred patterns of variation. With the combined model, the design effects were eliminated, or their significance was greatly reduced. Applying the AR1η model to individual trees was better than applying it at the plot level or applying it on a replicate-by-replicate basis. The relative improvements achieved in genetic response to selection did not exceed 6%. Examination of the spatial distribution of the residuals and the variogram of the residuals allowed the identification of the spatial patterns present. While additional significant terms could be fitted to model some of the spatial patterns and stationary variograms were attained in some instances, this resulted in only marginal increases in genetic gain. Use of a combined model is recommended to enable improved analysis of experimental data.

Genetic and Nongenetic Bases for the L-Shaped Distribution of Quantitative Trait Loci Effects

The L-Shaped distribution of estimated QTL effects (R2) has long been reported. We recently showed that a metabolic mechanism could account for this phenomenon. But other nonexclusive genetic or nongenetic causes may contribute to generate such a distribution. Using analysis and simulations of an additive genetic model, we show that linkage disequilibrium between QTL, low heritability, and small population size may also be involved, regardless of the gene effect distribution. In addition, a comparison of the additive and metabolic genetic models revealed that estimates of the QTL effects for traits proportional to metabolic flux are far less robust than for additive traits. However, in both models the highest R2's repeatedly correspond to the same set of QTL.

Design and analysis of experiments on random drift and inbreeding depression.

While the genetic consequences of inbreeding and small population size are of fundamental importance in many areas of biology, empirical research on these phenomena has proceeded in the absence of a well-developed statistical methodology. The usual approach is to compare observed means and variances with the expectations of Wright's neutral, additive genetic model for quantitative characters. If the observations deviate from the expectations more than can be accounted for by sampling variance of the parameter estimates, the null hypothesis is routinely rejected in favor of alternatives invoking evolutionary forces such as selection or nonadditive gene action. This is a biased procedure because it treats sequential samples from the same populations as independent, and because it ignores the fact that the expectations of the neutral additive genetic model will rarely be realized when only a finite number of lines are studied. Even when genes are perfectly additive and neutral, the variation among the properties of founder populations, the random development of linkage disequilibrium within lines, and the variance in inbreeding between lines reduce the likelihood that Wright's expectations will be realized in any particular set of lines. Under most experimental designs, these sources of variation are much too large to be ignored. Formulas are presented for the variance-covariance structure of the realized within- and between-line variance under the neutral additive genetic model. These results are then used to develop statistical tests for detecting the operation of selection and/or inbreeding depression in small populations. A number of recommendations are made for the optimal design of experiments on drift and inbreeding, and a method is suggested for the correction of data for general environmental effects. In general, it appears that we can best understand the response of populations to inbreeding and finite population size by studying a very large number (&gt;100) of self-fertilizing or full-sib mated lines in parallel with one or more stable control populations.