Associations between single nucleotide polymorphisms in 33 candidate genes and meat quality traits in commercial pigs

This study aimed to evaluate the effects of single nucleotide polymorphisms (SNPs) in candidate genes for meat quality using a custom 96‐SNP panel (Illumina Vera Code GoldenGate Assay) on 15 traits collected from 400 commercial pigs. Meat quality measurements included muscle pH, color (L*, a* and b*), drip loss, cooking loss, peak shear force and six sensory traits including appearance (outside and inside), tenderness, juiciness, flavor and overall liking as well as carcass weight and probe yield. Thirty‐five SNPs with minor allele frequencies > 0.10 remained for the multimarker association using the GLM procedure of sas 9.2. Results showed that 20 SNPs were significantly associated with at least one of the traits with either additive or dominance or both effects (P < 0.05). Among these significant SNPs, five of them in ADIPOQ, FTO, TNF, LEPR and AMPD1 had an effect on more than three traits simultaneously; those in MC4R, CAST, DGAT1 and MYF6 had an effect on two traits, while the others were associated with one trait. The results suggest that these markers could be incorporated into commercial pigs for marker‐assisted selection and breeding programs for carcass and meat quality trait improvement.     

Next generation modeling in GWAS: comparing different genetic architectures

The continuous advancement in genotyping technology has not been accompanied by the application of innovative statistical methods, such as multi-marker methods (MMM), to unravel genetic associations with complex traits. Although the performance of MMM has been widely explored in a prediction context, little is known on their behavior in the quantitative trait loci (QTL) detection under complex genetic architectures. We shed light on this still open question by applying Bayes A (BA) and Bayesian LASSO (BL) to simulated and real data. Both methods were compared to the single marker regression (SMR). Simulated data were generated in the context of six scenarios differing on effect size, minor allele frequency (MAF) and linkage disequilibrium (LD) between QTLs. These were based on real SNP genotypes in chromosome 21 from the Spanish Bladder Cancer Study. We show how the genetic architecture dramatically affects the behavior of the methods in terms of power, type I error and accuracy of estimates. Markers with high MAF are easier to detect by all methods, especially if they have a large effect on the phenotypic trait. A high LD between QTLs with either large or small effects differently affects the power of the methods: it impairs QTL detection with BA, irrespectively of the effect size, although boosts that of small effects with BL and SMR. We demonstrate the convenience of applying MMM rather than SMR because of their larger power and smaller type I error. Results from real data when applying MMM suggest novel associations not detected by SMR.     

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

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

Niche construction initiates the evolution of mutualistic interactions

Niche construction theory explains how organisms' niche modifications may feed back to affect their evolutionary trajectories. In theory, the evolution of other species accessing the same modified niche may also be affected. We propose that this niche construction may be a general mechanism driving the evolution of mutualisms. Drosophilid flies benefit from accessing yeast‐infested fruits, but the consequences of this interaction for yeasts are unknown. We reveal high levels of variation among strains of Saccharomyces cerevisiae in their ability to modify fruits and attract Drosophila simulans. More attractive yeasts are dispersed more frequently, both in the lab and in the field, and flies associated with more attractive yeasts have higher fecundity. Although there may be multiple natural yeast and fly species interactions, our controlled assays in the lab and field provide evidence of a mutualistic interaction, facilitated by the yeast's niche modification.     

Selection for complex traits leaves little or no classic signatures of selection

Background

Selection signatures aim to identify genomic regions underlying recent adaptations in populations. However, the effects of selection in the genome are difficult to distinguish from random processes, such as genetic drift. Often associations between selection signatures and selected variants for complex traits is assumed even though this is rarely (if ever) tested. In this paper, we use 8 breeds of domestic cattle under strong artificial selection to investigate if selection signatures are co-located in genomic regions which are likely to be under selection.

Results

Our approaches to identify selection signatures (haplotype heterozygosity, integrated haplotype score and F_ST) identified strong and recent selection near many loci with mutations affecting simple traits under strong selection, such as coat colour. However, there was little evidence for a genome-wide association between strong selection signatures and regions affecting complex traits under selection, such as milk yield in dairy cattle. Even identifying selection signatures near some major loci was hindered by factors including allelic heterogeneity, selection for ancestral alleles and interactions with nearby selected loci.

Conclusions

Selection signatures detect loci with large effects under strong selection. However, the methodology is often assumed to also detect loci affecting complex traits where the selection pressure at an individual locus is weak. We present empirical evidence to suggests little discernible ‘selection signature’ for complex traits in the genome of dairy cattle despite very strong and recent artificial selection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-246) contains supplementary material, which is available to authorized users.     

ObStruct: A Method to Objectively Analyse Factors Driving Population Structure Using Bayesian Ancestry Profiles

Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin) correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present ObStruct, a novel tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods. ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct''s ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses.     

Dynein light intermediate chains maintain spindle bipolarity by functioning in centriole cohesion

Cytoplasmic dynein 1 (dynein) is a minus end–directed microtubule motor protein with many cellular functions, including during cell division. The role of the light intermediate chains (LICs; DYNC1LI1 and 2) within the complex is poorly understood. In this paper, we have used small interfering RNAs or morpholino oligonucleotides to deplete the LICs in human cell lines and Xenopus laevis early embryos to dissect the LICs’ role in cell division. We show that although dynein lacking LICs drives microtubule gliding at normal rates, the LICs are required for the formation and maintenance of a bipolar spindle. Multipolar spindles with poles that contain single centrioles were formed in cells lacking LICs, indicating that they are needed for maintaining centrosome integrity. The formation of multipolar spindles via centrosome splitting after LIC depletion could be rescued by inhibiting Eg5. This suggests a novel role for the dynein complex, counteracted by Eg5, in the maintenance of centriole cohesion during mitosis.     

The Genetic Architecture of Climatic Adaptation of Tropical Cattle

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.     

Prediction of heterosis in crosses between inbred lines of Drosophila melanogaster

Summary The aim of the experiment was to determine if the estimated genetic distance between two populations could be used to predict the amount of heterosis that would occur when they were crossed. Eight lines of known relatedness to each other were produced by eight generations of sib mating and sub-lining. This produced lines that varied in coefficient of coancestry from zero to 0.78. Fourteen reciprocal crosses of these lines were used to measure heterosis for larval viability and adult fecundity. Gene frequencies at six polymorphic enzyme loci were used to estimate the genetic distances between lines, which were then compared with the known degrees of coancestry. The estimated genetic differences were poorly correlated with the known coancestry coefficients (r=0.4), possibly due to the small number of loci typed. Also genetic distances were only about 1/3 of what was expected. Selection acting on blocks of genes linked to the enzyme loci probably prevented the expected increase in homozygosity. Coancestry coefficient was correlated with heterosis (r=0.44–0.71). This level of correlation implied differences in heterosis among parent lines with the same level of coancestry. This variability is expected if a small number of loci explain most of the heterosis. The average level of heterosis was less than expected after eight generations of sib mating. This is most likely due to selection opposing the increase in homozygosity caused by inbreeding. The combination of these two imperfect correlations resulted in no significant correlation between genetic distance estimated from markers and heterosis.