Animal genetics最新文献

Neuronal ceroid lipofuscinosis (NCL) is a group of neurodegenerative disorders that occur in humans, dogs, and several other species. NCL is characterised clinically by progressive deterioration of cognitive and motor function, epileptic seizures, and visual impairment. Most forms present early in life and eventually lead to premature death. Typical pathological changes include neuronal accumulation of autofluorescent, periodic acid-Schiff- and Sudan black B-positive lipopigments, as well as marked loss of neurons in the central nervous system. Here, we describe a 19-month-old Schapendoes dog, where clinical signs were indicative of lysosomal storage disease, which was corroborated by pathological findings consistent with NCL. Whole genome sequencing of the affected dog and both parents, followed by variant calling and visual inspection of known NCL genes, identified a missense variant in CLN6 (c.386T>C). The variant is located in a highly conserved region of the gene and predicted to be harmful, which supports a causal relationship. The identification of this novel CLN6 variant enables pre-breeding DNA-testing to prevent future cases of NCL6 in the Schapendoes breed, and presents a potential natural model for NCL6 in humans.

The primary purpose of genetic improvement in lean pig breeds is to enhance production performance. Owing to their similar breeding directions, Duroc and Pietrain pigs are ideal models for investigating the phenotypic convergence underlying artificial selection. However, most important economic traits are controlled by a polygenic basis, so traditional strategies for detecting selection signatures may not fully reveal the genetic basis of complex traits. The pathway-based gene network analysis method utilizes each pathway as a unit, overcoming the limitations of traditional strategies for detecting selection signatures by revealing the selection of complex biological processes. Here, we utilized 13 122 398 high-quality SNPs from whole-genome sequencing data of 48 Pietrain pigs, 156 Duroc pigs and 36 European wild boars to detect selective signatures. After calculating F_ST and iHS scores, we integrated the pathway information and utilized the r/bioconductor graphite and signet packages to construct gene networks, identify subnets and uncover candidate genes underlying selection. Using the traditional strategy, a total of 47 genomic regions exhibiting parallel selection were identified. The enriched genes, including INO80, FZR1, LEPR and FAF1, may be associated with reproduction, fat deposition and skeletal development. Using the pathway-based selection signatures detection method, we identified two significant biological pathways and eight potential candidate genes underlying parallel selection, such as VTN, FN1 and ITGAV. This study presents a novel strategy for investigating the genetic basis of complex traits and elucidating the phenotypic convergence underlying artificial selection, by integrating traditional selection signature methods with pathway-based gene network analysis.

Animal genetic resources are crucial for ensuring global food security. However, in recent years, a noticeable decline in the genetic diversity of livestock has occurred worldwide. This decline is pronounced in developing countries, where the management of these resources is insufficient. In the current study, we performed whole genome sequencing for 20 Wuxue (WX) and five Guizhou White (GW) goats. Additionally, we utilized the published genomes of 131 samples representing five different goat breeds from various regions in China. We investigated and compared the genetic diversity and selection signatures of WX goats. Whole genome sequencing analysis of the WX and GW populations yielded 120 425 063 SNPs, which resided primarily in intergenic and intron regions. Population genetic structure revealed that WX exhibited genetic resemblance to GW, Chengdu Brown, and Jintang Black and significant differentiation from the other goat breeds. In addition, three methods (nucleotide diversity, linkage disequilibrium decay, and runs of homozygosity) showed moderate genetic diversity in WX goats. We used nucleotide diversity and composite likelihood ratio methods to identify within-breed signatures of positive selection in WX goats. A total of 369 genes were identified using both detection methods, including genes related to reproduction (GRID2, ZNF276, TCF25, and SPIRE2), growth (HMGA2 and GJA3), and immunity (IRF3 and SRSF3). Overall, this study explored the adaptability of WX goats, shedding light on their genetic richness and potential to thrive in challenges posed by climatic changes and diseases. Further investigations are warranted to harness these insights to enhance more efficient and sustainable goat breeding initiatives.

Copy number variations (CNVs) are large-scale changes in the DNA sequence that can affect the genetic structure and phenotype of an organism. The purpose of this study was to investigate the existing CNVs and their associations with the shank diameter (ShD) and shank length (ShL) traits using data from an F₂ crossbred chicken population. To carry out the study, 312 chickens were genotyped using the Illumina 60k SNP Beadchip. The shank traits of the birds were measured from day 1 to 12 weeks of age. penncnv and cnvruler tools were used to find copy numbers and regions with copy number changes (CNVR), respectively. The CNVRanger package was used to perform a genome-wide association study between shank traits and CNVs. Gene ontology research in CNVRs was carried out using the david database. In this investigation, 966 CNVs and 606 regions with copy number changes were discovered. The copy number states and variations were randomly distributed along the length of the autosomal chromosomes. Weeks 1–4, 9 and 12 of growth revealed a significant association of copy number variations with shank traits, false discovery rate (FDR-corrected p-value < 0.01), and the majority of CNVs that were statistically significant were found on chromosomes 1–3. These CNV segments are nearby genes such as KCNJ12, FGF6 and MYF5, which are fundamental to growth and development. In addition, gene set analyses revealed terms related to muscle physiology, regulation of cellular processes and potassium channels.

Lean meat percentage is a critical production trait in pig breeding systems with direct implications for the sustainability of the industry. In this study, we conducted a genome-wide association study for lean meat percentage using a cohort of 850 Duroc × (Landrace × Yorkshire) crossbred pigs and we identified QTL on SSC3 and SSC18. Based on the predicted effect of imputed variants and using the PigGTEx database of molecular QTL, we prioritized candidate genes and SNPs located within the QTL regions, which may be involved in the regulation of porcine leanness. Our results indicate that a nonsense mutation in ZC3HAV1L on SSC18 has a direct effect on lean meat percentage.

Variants in RPGRIP1 and MAP9, termed RPGRIP1ins44 and MAP9del respectively, are both associated with a form of canine progressive retinal atrophy referred to as RPGRIP1-CRD and have both been demonstrated to modify the development and progression of this disease. In the current study both variants were genotyped in at least 50 dogs of 132 diverse breeds and the data reveal that both segregate in multiple breeds. Individually, each variant is common within largely non-overlapping subsets of breed, and there is a negative correlation between their frequencies within breeds that segregate both variants. The frequency of both variants exceeds 0.05 in a single breed only, the Miniature Longhaired Dachshund. These data indicate that both variants are likely to be ancient and predate the development and genetic isolation of modern dog breeds. That both variants are present individually at high frequency in multiple breeds is consistent with the hypothesis that homozygosity of either variant alone is not associated with a clinically relevant phenotype, whereas the negative correlation between the two variants is consistent with the application of selective pressure, from dog breeders, against homozygosity at both loci, probably due to the more severe phenotype associated with homozygosity at both loci.

Genetic improvement of complex traits in animal and plant breeding depends on the efficient and accurate estimation of breeding values. Deep learning methods have been shown to be not superior over traditional genomic selection (GS) methods, partially due to the degradation problem (i.e. with the increase of the model depth, the performance of the deeper model deteriorates). Since the deep learning method residual network (ResNet) is designed to solve gradient degradation, we examined its performance and factors related to its prediction accuracy in GS. Here we compared the prediction accuracy of conventional genomic best linear unbiased prediction, Bayesian methods (BayesA, BayesB, BayesC, and Bayesian Lasso), and two deep learning methods, convolutional neural network and ResNet, on three datasets (wheat, simulated and real pig data). ResNet outperformed other methods in both Pearson's correlation coefficient (PCC) and mean squared error (MSE) on the wheat and simulated data. For the pig backfat depth trait, ResNet still had the lowest MSE, whereas Bayesian Lasso had the highest PCC. We further clustered the pig data into four groups and, on one separated group, ResNet had the highest prediction accuracy (both PCC and MSE). Transfer learning was adopted and capable of enhancing the performance of both convolutional neural network and ResNet. Taken together, our findings indicate that ResNet could improve GS prediction accuracy, affected potentially by factors such as the genetic architecture of complex traits, data volume, and heterogeneity.

Split paw pad disease is a scarcely defined phenotype characterized by skin lesions on the paw pads of dogs. We studied a family of German Shepherd dogs, in which four dogs developed intermittent paw pad lesions and lameness. The paw pads of two of the affected dogs were biopsied and demonstrated cleft formation in the stratum spinosum and stratum corneum, the outermost layers of the epidermis. Whole genome sequencing data from an affected dog revealed a private heterozygous 18 bp in frame deletion in the KRT5 gene. The deletion NM_001346035.1:c.988_1005del or NP_001332964.1:p.(Asn330_Asp335del) is predicted to lead to a loss of six amino acids in the L12 linker domain of the encoded keratin 5. KRT5 variants in human patients lead to various subtypes of epidermolysis bullosa simplex (EBS). Localized EBS is the mildest of the KRT5-related human diseases and may be caused by variants affecting the L12 linker domain of keratin 5. We therefore think that the detected KRT5 deletion in dogs represents a candidate causal variant for the observed skin lesions in dogs. However, while the clinical phenotype of KRT5-mutant dogs of this study closely resembles human patients with localized EBS, there are differences in the histopathology. EBS is defined by cleft formation within the basal layer of the epidermis while the cleft formation in the dogs described herein occurred in the outermost layers, a hallmark of split paw pad disease. Our study provides a basis for further studies into the exact relation of split paw pad disease and EBS.