Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates

Wavelet-based coherence between large-scale resting-state networks : neurodynamics marker for autism?

Neurodynamics is poorly understood and has raised interest of neuroscientists over the past decade. When a brain pathology cannot be described through structural or functional brain analyses, neurodynamics based descriptors might be the only option to understand a pathology and maybe predict its symptomatic evolution. For example, adolescents or adults with autism have shown mixed results when their intrinsic structural and functional connectivity parameters in the brain at rest were assessed. To visualize neurodynamics parameters we use wavelet coherence maps, which show when and at which frequency two large-scale resting-state networks (RSNs) co-vary and display phase-locked behavior. Here the wavelet-based coherence coefficients are extracted from fMRI of adolescents with and without autism. More specifically, we introduce a novel metric: ‘time of in- phase coherence’ between pairs of resting-state networks. Results show that wavelet coherence maps can be used as neurodynamics maps, and that features such as ‘time of in-phase coherence’ can be calculated between pairs of resting-state networks. This wavelet-based metric shows actually weaker coherent patterns between the ventral stream and the executive control network in patient with autism.\u3cbr/\u3e

Brain resting-state networks in adolescents with high-functioning autism : analysis of spatial connectivity and temporal neurodynamics

Introduction\u3cbr/\u3eAutism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity.\u3cbr/\u3e\u3cbr/\u3eMaterials and Methods\u3cbr/\u3eWe performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics.\u3cbr/\u3e\u3cbr/\u3eResults\u3cbr/\u3eControls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices.\u3cbr/\u3e\u3cbr/\u3eConclusion\u3cbr/\u3eThe results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state

Using an Inbred Horse Breed in a High Density Genome-Wide Scan for Genetic Risk Factors of Insect Bite Hypersensitivity (IBH)

While susceptibility to hypersensitive reactions is a common problem amongst humans and animals alike, the population structure of certain animal species and breeds provides a more advantageous route to better understanding the biology underpinning these conditions. The current study uses Exmoor ponies, a highly inbred breed of horse known to frequently suffer from insect bite hypersensitivity, to identify genomic regions associated with a type I and type IV hypersensitive reaction. A total of 110 cases and 170 controls were genotyped on the 670K Axiom Equine Genotyping Array. Quality control resulted in 452,457 SNPs and 268 individuals being tested for association. Genome-wide association analyses were performed using the GenABEL package in R and resulted in the identification of two regions of interest on Chromosome 8. The first region contained the most significant SNP identified, which was located in an intron of the DCC netrin 1 receptor gene. The second region identified contained multiple top SNPs and encompassed the PIGN, KIAA1468, TNFRSF11A, ZCCHC2, and PHLPP1 genes. Although additional studies will be needed to validate the importance of these regions in horses and the relevance of these regions in other species, the knowledge gained from the current study has the potential to be a step forward in unraveling the complex nature of hypersensitive reactions

Quantitative trait loci (QTL) mapping for growth traits on bovine chromosome 14

Quantitative trait loci (QTL) mapping in livestock allows the identification of genes that determine the genetic variation affecting traits of economic interest. We analyzed the birth weight and weight at 60 days QTL segregating on bovine chromosome BTA14 in a F2 resource population using genotypes produced from seven microsatellite markers. Phenotypes were derived from 346 F2 progeny produced from crossing Bos indicus Gyr x Holstein Bos taurus F1 parents. Interval analysis to detect QTL for birth weight revealed the presence of a QTL (p < 0.05) at 1 centimorgan (cM) from the centromere with an additive effect of 1.210 ± 0.438 kg. Interval analysis for weight at 60 days revealed the presence of a QTL (p < 0.05) at 0 cM from the centromere with an additive effect of 2.122 ± 0.735 kg. The region to which the QTL were assigned is described in the literature as responsible for some growth traits, milk yield, milk composition, fat deposition and has also been related to reproductive traits such as daughter pregnancy rate and ovulation rate. The effects of the QTL described on other traits were not investigated