Animal genetics最新文献

We recently discovered that the Manech Tête Rousse (MTR) deficient homozygous haplotype 2 (MTRDHH2) probably carries a recessive lethal mutation in sheep. In this study, we fine-mapped this region through whole-genome sequencing of five MTRDHH2 heterozygous carriers and 95 non-carriers from various ovine breeds. We identified a single base pair duplication within the SLC33A1 gene, leading to a frameshift mutation and a premature stop codon (p.Arg246Alafs*3). SLC33A1 encodes a transmembrane transporter of acetyl-coenzyme A that is crucial for cellular metabolism. To investigate the lethality of this mutation in homozygous MTR sheep, we performed at-risk matings using artificial insemination (AI) between heterozygous SLC33A1 variant carriers (SLC33A1_dupG). Pregnancy was confirmed 15 days post-AI using a blood test measuring interferon Tau-stimulated MX1 gene expression. Ultrasonography between 45 and 60 days post-AI revealed a 12% reduction in AI success compared with safe matings, indicating embryonic/fetal loss. This was supported by the MX1 differential expression test suggesting fetal losses between 15 and 60 days of gestation. We also observed a 34.7% pre-weaning mortality rate in 49 lambs born from at-risk matings. Homozygous SLC33A1_dupG lambs accounted for 47% of this mortality, with deaths occurring mostly within the first 5 days without visible clinical signs. Therefore, appropriate management of SLC33A1_dupG with an allele frequency of 0.04 in the MTR selection scheme would help increase overall fertility and lamb survival.

Unfavorable genetic correlations between milk production, fertility, and urea traits have been reported. However, knowledge of the genomic regions associated with these unfavorable correlations is limited. Here, we used the correlation scan method to identify and investigate the regions driving or antagonizing the genetic correlations between production vs. fertility, urea vs. fertility, and urea vs. production traits. Driving regions produce an estimate of correlation that is in the same direction as the global correlation. Antagonizing regions produce an estimate in the opposite direction of the global estimates. Our dataset comprised 6567, 4700, and 12,658 Holstein cattle with records of production traits (milk yield, fat yield, and protein yield), fertility (calving interval) and urea traits (milk urea nitrogen and blood urea nitrogen predicted using milk-mid-infrared spectroscopy), respectively. Several regions across the genome drive the correlations between production, fertility, and urea traits. Antagonizing regions were confined to certain parts of the genome and the genes within these regions were mostly involved in preventing metabolic dysregulation, liver reprogramming, metabolism remodeling, and lipid homeostasis. The driving regions were enriched for QTL related to puberty, milk, and health-related traits. Antagonizing regions were mostly related to muscle development, metabolic body weight, and milk traits. In conclusion, we have identified genomic regions of potential importance for dairy cattle breeding. Future studies could investigate the antagonizing regions as potential genomic regions to break the unfavorable correlations and improve milk production as well as fertility and urea traits.

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.

Congenital myasthenic syndromes (CMSs) are inherited disorders of neuromuscular transmission. In the 1980s, spontaneously occurring CMS following autosomal recessive inheritance patterns were described in English Springer Spaniels (ESSs) (Oda et al., 1984) and Smooth Fox Terriers (SFTs) (Miller et al., 1983; OMIA:000685–9615). Affected puppies exhibited muscle weakness and fatigability that was exacerbated by exercise. Skeletal muscle biopsies revealed notably fewer acetylcholine receptors (AChRs) than healthy controls, and no autoantibodies against AChR were detected. Ohno et al. (2023) describe 35 genes classified into 14 groups according to the pathomechanical, clinical, and therapeutic features of human CMS patients. Forms of CMS with AChR deficiency most often result from mutation of CHRNE, encoding the epsilon subunit of the AChR (Finsterer, 2019). Homozygous mutations in other subunits are typically embryonic lethal (Engel et al., 2015). To identify the genetic cause for CMS in these breeds, we sequenced the coding regions and splice sites of CHRNE.

We obtained archival thymus tissue from two affected ESS half-siblings, peripheral blood leukocytes from their unaffected dam (an obligate carrier), and cultured muscle cells from an affected SFT. Buccal swabs were collected from 17 unaffected, unrelated ESSs with informed owner consent under protocols approved by the Clemson University Institutional Review Board (IBC2015-24). DNA was extracted following Puregene Kit protocols (Qiagen). PCR amplification and sequencing of CHRNE exons 3–13 were conducted for the affected individuals and obligate carrier as described in Rinz et al., 2015. Based on updated gene annotation (XM_014113502.3), we designed new primers to capture exons 1 and 2: exon 1 forward 5′-GAATCATCGGTGGAATCTGT-3′ and reverse 5′-GGAGTAGAAATGAGAGGGACC-3′, exon 2 forward 5′-CAATGATGAGTTTTCTGGGTG-3′ and reverse 5′-CCAATCACACCAGCAGAGTC-3′. Resultant sequences were compared to the canFam4 reference genome.

In both breeds, we discovered unique point mutations at position chr5:31915101 in exon 13. A C>A transversion in the ESS predicts the substitution of an arginine for a serine (S503R) (XP_013968977.2). A rapid genotyping protocol was developed through restriction enzyme digestion using Hinf1 (Fisher BioReagents), following manufacturer's instructions. PCR products from exons 12 and 13 incubated with Hinf1 resulted in distinct banding patterns corresponding to genotype when resolved on an agarose gel (Figure S1). All 17 healthy ESSs produced a single 612-bp band. The two affected ESSs produced bands at 398 and 214 bp, and the obligate carrier had all three fragment sizes.

In the affected SFT, we identified a 1-bp insertion (c.1508_1509insG) that predicts a frameshift mutation, p.Ser503Argfs*14. The ESS and SFT variants were absent from 1987 dog genomes available thr

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.