Characterization of runs of homozygosity islands in American mink using whole-genome sequencing data.

The genome-wide analysis of runs of homozygosity (ROH) islands can be an effective strategy for identifying shared variants within a population and uncovering important genomic regions related to complex traits. The current study performed ROH analysis to characterize the genome-wide patterns of homozygosity, identify ROH islands and annotated genes within these candidate regions using whole-genome sequencing data from 100 American mink (Neogale vison). After sequence processing, variants were called using GATK and Samtools pipelines. Subsequent to quality control, 8,373,854 bi-allelic variants identified by both pipelines remained for further analysis. A total of 34,652 ROH segments were identified in all individuals, among which shorter segments (0.3-1 Mb) were abundant throughout the genome, approximately accounting for 84.39% of all ROH. Within these segments, we identified 63 ROH islands housing 156 annotated genes. The genes located in ROH islands were associated with fur quality (EDNRA, FGF2, FOXA2 and SLC24A4), body size/weight (MYLK4, PRIM2, FABP2, EYS and PHF3), immune capacity (IL2, IL21, PTP4A1, SEMA4C, JAK2, CCNA2 and TNIP3) and reproduction (ADAD1, KHDRBS2, INSL6, PGRMC2 and HSPA4L). Furthermore, Gene Ontology and KEGG pathway enrichment analyses revealed 56 and 9 significant terms (FDR-corrected p-value < 0.05), respectively, among which cGMP-PKG signalling pathway, regulation of actin cytoskeleton, and calcium signalling pathway were highlighted due to their functional roles in growth and fur characteristics. This is the first study to present ROH islands in American mink. The candidate genes from ROH islands and functional enrichment analysis suggest possible signatures of selection in response to the mink breeding targets, such as increased body length, reproductive performance and fur quality. These findings contribute to our understanding of genetic characteristics, and provide complementary information to assist with implementation of breeding strategies for genetic improvement in American mink.

Coat color inheritance in American mink.

BACKGROUND: Understanding the genetic mechanisms underlying coat color inheritance has always been intriguing irrespective of the animal species including American mink (Neogale vison). The study of color inheritance in American mink is imperative since fur color is a deterministic factor for the success of mink industry. However, there have been no studies during the past few decades using in-depth pedigree for analyzing the inheritance pattern of colors in American mink. METHODS: In this study, we analyzed the pedigree of 23,282 mink extending up to 16 generations. All animals that were raised at the Canadian Center for Fur Animal Research (CCFAR) from 2003 to 2021 were used in this study. We utilized the Mendelian ratio and Chi-square test to investigate the inheritance of Dark (9,100), Pastel (5,161), Demi (4,312), and Mahogany (3,358) colors in American mink. RESULTS: The Mendelian inheritance ratios of 1:1 and 3:1 indicated heterozygous allelic pairs responsible for all studied colors. Mating sire and dam of the same color resulted in the production of offspring with the same color most of the time. CONCLUSION: Overall, the results suggested that color inheritance was complex and subjected to a high degree of diversity in American mink as the genes responsible for all four colors were found to be heterozygous.

Genome-wide detection of copy number variation in American mink using whole-genome sequencing.

BACKGROUND: Copy number variations (CNVs) represent a major source of genetic diversity and contribute to the phenotypic variation of economically important traits in livestock species. In this study, we report the first genome-wide CNV analysis of American mink using whole-genome sequence data from 100 individuals. The analyses were performed by three complementary software programs including CNVpytor, DELLY and Manta. RESULTS: A total of 164,733 CNVs (144,517 deletions and 20,216 duplications) were identified representing 5378 CNV regions (CNVR) after merging overlapping CNVs, covering 47.3 Mb (1.9%) of the mink autosomal genome. Gene Ontology and KEGG pathway enrichment analyses of 1391 genes that overlapped CNVR revealed potential role of CNVs in a wide range of biological, molecular and cellular functions, e.g., pathways related to growth (regulation of actin cytoskeleton, and cAMP signaling pathways), behavior (axon guidance, circadian entrainment, and glutamatergic synapse), lipid metabolism (phospholipid binding, sphingolipid metabolism and regulation of lipolysis in adipocytes), and immune response (Wnt signaling, Fc receptor signaling, and GTPase regulator activity pathways). Furthermore, several CNVR-harbored genes associated with fur characteristics and development (MYO5A, RAB27B, FGF12, SLC7A11, EXOC2), and immune system processes (SWAP70, FYN, ORAI1, TRPM2, and FOXO3). CONCLUSIONS: This study presents the first genome-wide CNV map of American mink. We identified 5378 CNVR in the mink genome and investigated genes that overlapped with CNVR. The results suggest potential links with mink behaviour as well as their possible impact on fur quality and immune response. Overall, the results provide new resources for mink genome analysis, serving as a guideline for future investigations in which genomic structural variations are present.

Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data.

BACKGROUND: Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle. RESULTS: Based on the significant-association threshold (p < 5 × 10- 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10- 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10- 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs. CONCLUSIONS: Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types.

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

A comparison of different algorithms for phasing haplotypes using Holstein cattle genotypes and pedigree data.

Phasing genotypes to haplotypes is becoming increasingly important due to its applications in the study of diseases, population and evolutionary genetics, imputation, and so on. Several studies have focused on the development of computational methods that infer haplotype phase from population genotype data. The aim of this study was to compare phasing algorithms implemented in Beagle, Findhap, FImpute, Impute2, and ShapeIt2 software using 50k and 777k (HD) genotyping data. Six scenarios were considered: no-parents, sire-progeny pairs, sire-dam-progeny trios, each with and without pedigree information in Holstein cattle. Algorithms were compared with respect to their phasing accuracy and computational efficiency. In the studied population, Beagle and FImpute were more accurate than other phasing algorithms. Across scenarios, phasing accuracies for Beagle and FImpute were 99.49-99.90% and 99.44-99.99% for 50k, respectively, and 99.90-99.99% and 99.87-99.99% for HD, respectively. Generally, FImpute resulted in higher accuracy when genotypic information of at least one parent was available. In the absence of parental genotypes and pedigree information, Beagle and Impute2 (with double the default number of states) were slightly more accurate than FImpute. Findhap gave high phasing accuracy when parents' genotypes and pedigree information were available. In terms of computing time, Findhap was the fastest algorithm followed by FImpute. FImpute was 30 to 131, 87 to 786, and 353 to 1,400 times faster across scenarios than Beagle, ShapeIt2, and Impute2, respectively. In summary, FImpute and Beagle were the most accurate phasing algorithms. Moreover, the low computational requirement of FImpute makes it an attractive algorithm for phasing genotypes of large livestock populations.

Genome-wide association studies (GWAS) identify a QTL close to PRKAG3 affecting meat pH and colour in crossbred commercial pigs.

BACKGROUND: Improving meat quality is a high priority for the pork industry to satisfy consumers' preferences. GWAS have become a state-of-the-art approach to genetically improve economically important traits. However, GWAS focused on pork quality are still relatively rare. RESULTS: Six genomic regions were shown to affect loin pH and Minolta colour a* and b* on both loin and ham through GWAS in 1943 crossbred commercial pigs. Five of them, located on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, SSC16 and SSCX, were associated with meat colour. However, the most promising region was detected on SSC15 spanning 133-134 Mb which explained 3.51% - 17.06% of genetic variance for five measurements of pH and colour. Three SNPs (ASGA0070625, MARC0083357 and MARC0039273) in very strong LD were considered most likely to account for the effects in this region. ASGA0070625 is located in intron 2 of ZNF142, and the other two markers are close to PRKAG3, STK36, TTLL7 and CDK5R2. After fitting MARC0083357 (the closest SNP to PRKAG3) as a fixed factor, six SNPs still remained significant for at least one trait. Four of them are intragenic with ARPC2, TMBIM1, NRAMP1 and VIL1, while the remaining two are close to RUFY4 and CDK5R2. The gene network constructed demonstrated strong connections of these genes with two major hubs of PRKAG3 and UBC in the super-pathways of cell-to-cell signaling and interaction, cellular function and maintenance. All these pathways play important roles in maintaining the integral architecture and functionality of muscle cells facing the dramatic changes that occur after exsanguination, which is in agreement with the GWAS results found in this study. CONCLUSIONS: There may be other markers and/or genes in this region besides PRKAG3 that have an important effect on pH and colour. The potential markers and their interactions with PRKAG3 require further investigation.

Genome-wide association studies for economically important traits in mink using copy number variation.

Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.

Red osier dogwood and its use in animal nutrition: A review.

As the human population increases globally, the food animal industry has not been spared from the monumental demand for edible animal products, particularly meat. This has necessitated the simultaneous expansion of the productivity of the animal sector to meet the ever-growing human needs. Although antibiotics have been used in food animal production with commendable positive impacts on their growth performance, their sole contributive factor to the increasing incidence of antimicrobial resistance has ushered the strict restrictions placed on their use in the animal sector. This has handed a setback to both animals and farmers; thus, the intense push for a more sustainable antibiotic alternative for use in animal production. The use of plants with concentrated phytogenic compounds has gained much interest due to their beneficial bioactivities, including antioxidant and selective antimicrobial. While the reported beneficial activities of phytogenic additives on animals vary due to their varying total polyphenol concentrations (TPC), red osier dogwood (ROD) plant materials boast of high TPC with excellent antioxidant prowess and growth improvement capacities compared to some plant extracts commonly used in research. However, its adoption in research and commercial scale is still low. Thus, the present review aims to provide concise information on the dietary potential of ROD plant materials in animal feeding.

Corrigendum: Population genomics of American mink using genotype data.

[This corrects the article DOI: 10.3389/fgene.2023.1175408.].

Population genomics of American mink using genotype data.

Understanding the genetic structure of the target population is critically important to develop an efficient genomic selection program in domestic animals. In this study, 2,973 American mink of six color types from two farms (Canadian Centre for Fur Animal Research (CCFAR), Truro, NS and Millbank Fur Farm (MFF), Rockwood, ON) were genotyped with the Affymetrix Mink 70K panel to compute their linkage disequilibrium (LD) patterns, effective population size (Ne), genetic diversity, genetic distances, and population differentiation and structure. The LD pattern represented by average r 2, decreased to <0.2 when the inter-marker interval reached larger than 350 kb and 650 kb for CCFAR and MFF, respectively, and suggested at least 7,700 and 4,200 single nucleotide polymorphisms (SNPs) be used to obtain adequate accuracy for genomic selection programs in CCFAR and MFF respectively. The Ne for five generations ago was estimated to be 76 and 91 respectively. Our results from genetic distance and diversity analyses showed that American mink of the various color types had a close genetic relationship and low genetic diversity, with most of the genetic variation occurring within rather than between color types. Three ancestral genetic groups was considered the most appropriate number to delineate the genetic structure of these populations. Black (in both CCFAR and MFF) and pastel color types had their own ancestral clusters, while demi, mahogany, and stardust color types were admixed with the three ancestral genetic groups. This study provided essential information to utilize the first medium-density SNP panel for American mink in their genomic studies.

Investigation of the SARS-CoV-2 post-vaccination antibody response in Canadian farmed mink.

Currently, SARS-CoV-2 have been detected in farmed mink in 13 different countries. Due to the high susceptibility and transmissibility among mink, great concerns of mink serving as a reservoir to generate novel variants with unknown virulence and antigenic properties arose. These concerns have consequently resulted in entire mink productions being culled and banned. This study investigates the post-vaccination antibody response in the Canadian farmed mink vaccinated with a commercial Index spike protein-based vaccine, approved for use in cats, and compares the antibody response to that observed post infection in Danish farmed mink. Blood samples were obtained from 50 mink at the Canadian Centre for Fur Animal Research (CCFAR), Dalhousie University (Truro, Canada). The sera were initially analyzed for antibodies by enzyme-linked immunosorbent assay (ELISA), and selected sera was subsequently tested in a virus neutralization tests. The levels of neutralizing antibodies were evaluated for an ancestral D614G strain and a recent circulating SARS-CoV-2 variant of concern (Omicron BA.4). The results revealed that the vaccine induced a strong antibody response in mink by reaching antibody titer levels of up to 1:12800 in the ELISA. Moreover, high levels of neutralizing antibodies were obtained, and despite the great level of genetic differences between the ancestral and Omicron BA.4 strains, the vaccinated mink showed high levels of cross-reacting neutralizing antibodies. Interestingly, the antibody levels towards SARS-CoV-2 in the Canadian vaccinated mink were significantly higher than observed in recently SARS-CoV-2 infected Danish mink and equal to anamnestic responses following re-infection. In conclusion, the vaccine used in the Canadian farmed mink was able to induce a strong and broad-reacting antibody response in mink, which could limit the spread of SARS-CoV-2 in farmed mink and thereby reduce the risk of mink serving as a SARS-CoV-2 reservoir for human infections.

Emerging Roles of Non-Coding RNAs in the Feed Efficiency of Livestock Species.

A global population of already more than seven billion people has led to an increased demand for food and water, and especially the demand for meat. Moreover, the cost of feed used in animal production has also increased dramatically, which requires animal breeders to find alternatives to reduce feed consumption. Understanding the biology underlying feed efficiency (FE) allows for a better selection of feed-efficient animals. Non-coding RNAs (ncRNAs), especially micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), play important roles in the regulation of bio-logical processes and disease development. The functions of ncRNAs in the biology of FE have emerged as they participate in the regulation of many genes and pathways related to the major FE indicators, such as residual feed intake and feed conversion ratio. This review provides the state of the art studies related to the ncRNAs associated with FE in livestock species. The contribution of ncRNAs to FE in the liver, muscle, and adipose tissues were summarized. The research gap of the function of ncRNAs in key processes for improved FE, such as the nutrition, heat stress, and gut-brain axis, was examined. Finally, the potential uses of ncRNAs for the improvement of FE were discussed.

Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency.

Despite the significant improvement of feed efficiency (FE) in pigs over the past decades, feed costs remain a major challenge for producers profitability. Improving FE is a top priority for the global swine industry. A deeper understanding of the biology underlying FE is crucial for making progress in genetic improvement of FE traits. This review comprehensively discusses the topics related to the FE in pigs including: measurements, genetics, genomics, biological pathways and the advanced technologies and methods involved in FE improvement. We first provide an update of heritability for different FE indicators and then characterize the correlations of FE traits with other economically important traits. Moreover, we present the quantitative trait loci (QTL) and possible candidate genes associated with FE in pigs and outline the most important biological pathways related to the FE traits in pigs. Finally, we present possible ways to improve FE in swine including the implementation of genomic selection, new technologies for measuring the FE traits, and the potential use of genome editing and omics technologies.

Applying Machine Learning Algorithms for the Classification of Mink Infected with Aleutian Disease Using Different Data Sources.

American mink (Neogale vison) is one of the major sources of fur for the fur industries worldwide, whereas Aleutian disease (AD) is causing severe financial losses to the mink industry. A counterimmunoelectrophoresis (CIEP) method is commonly employed in a test-and-remove strategy and has been considered a gold standard for AD tests. Although machine learning is widely used in livestock species, little has been implemented in the mink industry. Therefore, predicting AD without using CIEP records will be important for controlling AD in mink farms. This research presented the assessments of the CIEP classification using machine learning algorithms. The Aleutian disease was tested on 1157 individuals using CIEP in an AD-positive mink farm (Nova Scotia, Canada). The comprehensive data collection of 33 different features was used for the classification of AD-infected mink. The specificity, sensitivity, accuracy, and F1 measure of nine machine learning algorithms were evaluated for the classification of AD-infected mink. The nine models were artificial neural networks, decision tree, extreme gradient boosting, gradient boosting method, K-nearest neighbors, linear discriminant analysis, support vector machines, naive bayes, and random forest. Among the 33 tested features, the Aleutian mink disease virus capsid protein-based enzyme-linked immunosorbent assay was found to be the most important feature for classifying AD-infected mink. Overall, random forest was the best-performing algorithm for the current dataset with a mean sensitivity of 0.938 ± 0.003, specificity of 0.986 ± 0.005, accuracy of 0.962 ± 0.002, and F1 value of 0.961 ± 0.088, and across tenfold of the cross-validation. Our work demonstrated that it is possible to use the random forest algorithm to classify AD-infected mink accurately. It is recommended that further model tests in other farms need to be performed and the genomic information needs to be used to optimize the model for implementing machine learning methods for AD detection.

Genetic and phenotypic parameters for feed efficiency and component traits in American mink.

Feed cost is the largest expense of mink production systems, and, therefore, improvement of feed efficiency (FE) through selection for high feed-efficient mink is a practical way to increase the mink industry's sustainability. In this study, we estimated the heritability, phenotypic, and genetic correlations for different FE measures and component traits, including harvest weight (HW), harvest length (HL), final body length (FBL), final body weight (FBW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR), using data from 2,288 American mink (for HW and HL), and 1,038 to 1,906 American mink (for other traits). Significance (P < 0.05) of fixed effects (farm, sex, and color type), a covariate (age of animal), and random effects (additive genetic, maternal, and common litter) were evaluated through univariate models implemented in ASReml-R version 4. Genetic parameters were estimated via fitting a set of bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.28 ± 0.06, 0.23 ± 0.06, 0.28 ± 0.10, 0.27 ± 0.11, 0.25 ± 0.09, 0.26 ± 0.09, 0.20 ± 0.09, 0.23 ± 0.09, 0.21 ± 0.10, 0.25 ± 0.10, and 0.26 ± 0.10 for HW, HL, FBL, FBW, ADG, DFI, FCR, RFI, RG, RIG, and KR, respectively. RIG had favorable genetic correlations with DFI (-0.62 ± 0.24) and ADG (0.58 ± 0.21), and nonsignificant (P > 0.05) genetic correlations with FBW (0.14 ± 0.31) and FBL (-0.15 ± 0.31). These results revealed that RIG might be a superior trait as it guarantees reduced feed intake with faster-growing mink yet with no negative impacts on body weight and length. In addition, the strong positive genetic correlations (±SE) between KR with component traits (0.88 ± 0.11 with FBW, 0.68 ± 0.17 with FBL, and 0.97 ± 0.02 with ADG) suggested KR as an applicable indirect measure of FE for improvement of component traits as it did not require the individual feed intake to be measured. Overall, our results confirmed the possibility of including FE traits in mink breeding programs to effectively select feed-efficient animals.

Improvement of feed efficiency (FE) in American mink is highly beneficial, as feed costs comprise the largest expense of mink production systems. The present study estimated the heritability, phenotypic and genetic correlations for different FE measures and component traits in mink. The residual intake and gain can be applied as FE measurement in selection programs as it will guarantee faster-growing mink with reduced feed intake, yet without negative impacts on growth traits. In addition, Kleiber ratio had strong positive genetic correlations with component traits, which made this trait an appealing indirect FE trait for mink breeding programs, knowing the fact that this trait was not dependent on feed intake records. Overall, our results suggested that including FE traits can assist mink breeding programs to develop an index for the selection of feed-efficient mink and, therefore, reduce the cost of mink production.

A chromosome-level genome assembly reveals genomic characteristics of the American mink (Neogale vison).

Availability of a contiguous chromosome-level genome assembly is the foundational step to develop genome-based studies in American mink (Neogale vison). The main objective of this study was to provide a high quality chromosome-level genome assembly for American mink. An initial draft of the genome assembly was generated using 2,884,047 PacBio long reads. Integration of Hi-C data into the initial draft led to an assembly with 183 scaffolds and scaffold N50 of 220 Mb. This gap-free genome assembly of American mink (ASM_NN_V1) had a length of 2.68 Gb in which about 98.6% of the whole genome was covered by 15 chromosomes. In total, 25,377 genes were predicted across the American mink genome using the NCBI Eukaryotic Genome Annotation Pipeline. In addition, gene orthology, demographic history, synteny blocks, and phylogenetic relationships were studied in connection with the genomes of other related Carnivora. Furthermore, population-based statistics of 100 sequenced mink were presented using the newly assembled genome. Remarkable improvements were observed in genome contiguity, the number of scaffolds, and annotation compared to the first draft of mink genome assembly (NNQGG.v01). This high-quality genome assembly will support the development of efficient breeding strategies as well as conservation programs for American mink.

Genetic and phenotypic correlations between Aleutian disease tests with body weight, growth, and feed efficiency traits in mink.

The ineffectiveness of vaccination, medicine, and culling strategy leads mink farmers to control Aleutian disease (AD) by selecting AD-resilient mink based on AD tests. However, the genetic background of AD tests and their correlations with economically important or AD-resilient traits are limited. This study estimated the genetic and phenotypic correlations between four AD tests and seven body weight (BW) traits, six growth parameters from the Richards growth model, and eight feed-related traits. Univariate models were used to test the significance (P < 0.05) of fixed effects (sex, color type, AD test year, birth year, and row-by-year), random effects (additive genetic, maternal genetic, and permanent environmental), and a covariate of age using ASReml 4.1. Likewise, pairwise bivariate analyses were conducted to estimate the phenotypic and genetic correlations among the studied traits. Both antigen- and virus capsid protein-based enzyme-linked immunosorbent assay tests (ELISA-G and ELISA-P) showed significant (P < 0.05) moderate positive genetic correlations (±SE) with maturation rate (from 0.36 ± 0.18 to 0.38 ± 0.19). ELISA-G showed a significant negative genetic correlation (±SE) with average daily gain (ADG, -0.37 ± 0.16). ELISA-P showed a significant positive moderate genetic correlation (±SE) with off-feed days (DOF, 0.42 ± 0.17). These findings indicated that selection for low ELISA scores would reduce the maturation rate, increase ADG (by ELISA-G), and minimize DOF (by ELISA-P). The iodine agglutination test (IAT) showed significant genetic correlations with DOF (0.73 ± 0.16), BW at 16 weeks of age (BW16, 0.45 ± 0.23), and BW at harvest (HW, -0.47 ± 0.20), indicating that selection for lower IAT scores would lead to lower DOF and BW16, and higher HW. These estimated genetic correlations suggested that the selection of AD tests would not cause adverse effects on the growth, feed efficiency, and feed intake of mink. The estimates from this study might strengthen the previous finding that ELISA-G could be applied as a reliable and practical indicator trait in the genetic selection of AD-resilient mink in AD-positive farms.

The selection of Aleutian disease-resistant individuals based on Aleutian disease (AD) tests is seen as a potential method to control AD effectively. However, the knowledge regarding the genetic background of AD tests is limited. This study estimated the genetic and phenotypic correlations between Aleutian disease tests and body weight, growth, and feed-related traits in mink. The estimates in this study indicated that the growth, feed efficiency, and feed intake of mink would not be adversely influenced by the selection of AD tests. In the meantime, the estimates further illustrate that the antigen-based enzyme-linked immunosorbent assay test could be applied as the most reliable and practical indicator trait to select AD-resilient mink in AD-positive farms.

Genetic and Phenotypic Parameters for Pelt Quality and Body Length and Weight Traits in American Mink.

Understanding the genetics of fur characteristics and skin size is important for developing effective breeding programs in the mink industry. Therefore, the objectives of this study were to estimate the genetic and phenotypic parameters for pelt quality traits including live grading overall quality (LQU), live grading nap size (LNAP), dried pelt size (DPS), dried pelt nap size (DNAP) and overall quality of dried pelt (DQU), and body length and weight traits, including November body weight (Nov_BW), November body length (Nov_BL), harvest weight (HW) and harvest length (HL) in American mink. Dried pelt quality traits on 1195 mink and pelt quality traits on live animals on 1680 were collected from mink raised at two farms, in Nova Scotia and Ontario. A series of univariate analyses were implemented in ASReml 4.1 software to identify the significance (p < 0.05) of random effects (maternal genetic effects, and common litter effects) and fixed effects (farm, sex, color type, year, and age) for each trait. Subsequently, bivariate models were used to estimate the genetic and phenotypic parameters using ASReml 4.1. Heritability (±SE) estimates were 0.41 ± 0.06 for DPS, 0.23 ± 0.10 for DNAP, 0.12 ± 0.04 for DQU, 0.28 ± 0.06 for LQU, 0.44 ± 0.07 for LNAP, 0.29 ± 0.10 for Nov_BW, 0.28 ± 0.09 for Nov_BL, 0.41 ± 0.07 for HW and 0.31 ± 0.06 for HL. DPS had high positive genetic correlations (±SE) with Nov_BW (0.89 ± 0.10), Nov_BL (0.81 ± 0.07), HW (0.85 ± 0.05) and HL (0.85 ± 0.06). These results suggested that body weight and length measured on live animals in November of the first year were reliable indicators of dried pelt size. DQU had favorable genetic correlations with Nov_BL (0.55 ± 0.24) and HL (0.46 ± 0.20), and nonsignificant genetic correlations with DNAP (0.13 ± 0.25), Nov_BW (0.25 ± 0.25) and HW (0.06 ± 0.20), which made body length traits an appealing trait for selection for increased pelt size. High positive genetic correlation (±SE) was observed between LNAP and DNAP (0.82 ± 0.22), which revealed that nap size measurement on live animals is a reliable indicator trait for dried pelt nap size. However, nonsignificant (p > 0.05) low genetic correlation (±SE) was obtained between LQU and DQU (0.08 ± 0.45), showing that indirect selection based on live grading might not lead to the satisfactory improvement of dried pelt overall quality. The estimated genetic parameters for live grading, dried pelt quality, and body weight and body length traits may be incorporated into breeding programs to improve fur characteristics in Canadian mink populations.

Genome-Wide Detection of Selection Signatures for Pelt Quality Traits and Coat Color Using Whole-Genome Sequencing Data in American Mink.

Domestication and selection are the major driving forces responsible for creating genetic variability in farmed species. American mink has been under selection for more than 100 years for improved body size and pelt quality. This study aimed to identify the genomic regions subjected to selection for pelt quality traits, and coat color using the whole genome sequences of 100 mink raised in the Canadian Centre for Fur Animal Research (CCFAR) at Dalhousie Agriculture Campus (Truro, NS, Canada), and Millbank fur farm (Rockwood, ON, Canada). Measurements of three dried pelt characteristics (including pelt size (n = 35), overall quality of fur (n = 27), and nap size (n = 29)), and three coat color of Black, Stardust, and Pastel (Stardust_ Black (n = 38), and Pastel_Black (n = 41)) were used to assign animals to pairwise groups. Signatures of selection were detected using integrated measurement of fixation index (Fst), extended haplotype homozygosity (XP-EHH), and nucleotide diversity (θπ) tests. In total, overlapping top 1% of Fst and XP-EHH harbored 376 genes for pelt quality traits (110 for nap size, 163 for overall quality of fur, and 98 pelt size), and 194 genes for coat color (123 for Pastel_Black and 71 for Stardust_Black) were detected in different groups. Integrating results of Fst, and XP-EHH with the θπ test supported 19 strongly selected regions on chromosomes 3, 4, 5, 6, 7, 8, 9, and 10 that contained 33 candidate genes related to fur quality, hair follicle function, and pelt size traits. Gene ontology revealed numerous genes related to the hair cycle process and molting cycle process, epidermis development, Wnt signaling pathway and muscle development. This study provided the first map of putative selection signals related to pelt quality and coat color in American mink, which could be used as a reference for future studies attempting to identify genes associated with economically important traits in mink.