Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink.

The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for mink.

Innovative construction of the first reliable catalogue of bovine circular RNAs.

The aim of this study was to compare the circular transcriptome of divergent tissues in order to understand: i) the presence of circular RNAs (circRNAs) that are not exonic circRNAs, i.e. originated from backsplicing involving known exons and, ii) the origin of artificial circRNA (artif_circRNA), i.e. circRNA not generated in-vivo. CircRNA identification is mostly an in-silico process, and the analysis of data from the BovReg project (https://www.bovreg.eu/) provided an opportunity to explore new ways to identify reliable circRNAs. By considering 117 tissue samples, we characterized 23,926 exonic circRNAs, 337 circRNAs from 273 introns (191 ciRNAs, 146 intron circles), 108 circRNAs from small non-coding genes and nearly 36.6K circRNAs classified as other_circRNAs. Furthermore, for 63 of those samples we analysed in parallel data from total-RNAseq (ribosomal RNAs depleted prior to library preparation) with paired mRNAseq (library prepared with poly(A)-selected RNAs). The high number of circRNAs detected in mRNAseq, and the significant number of novel circRNAs, mainly other_circRNAs, led us to consider all circRNAs detected in mRNAseq as artificial. This study provided evidence of 189 false entries in the list of exonic circRNAs: 103 artif_circRNAs identified by total RNAseq/mRNAseq comparison using two circRNA tools, 26 probable artif_circRNAs, and 65 identified by deep annotation analysis. Extensive benchmarking was performed (including analyses with CIRI2 and CIRCexplorer-2) and confirmed 94% of the 23,737 reliable exonic circRNAs. Moreover, this study demonstrates the effectiveness of a panel of highly expressed exonic circRNAs (5-8%) in analysing the tissue specificity of the bovine circular transcriptome.

Placental Transcriptome Analysis in Connection with Low Litter Birth Weight Phenotype (LBWP) Sows.

It is possible to identify sub-populations of sows in every pig herd that consistently give birth to low birth weight (BW) piglets, irrespective of the litter size. A previous study from our group demonstrated that placental development is a main factor affecting the litter birth weight phenotype (LBWP) in sows, thereby impacting the BW of entire litters, but the biological and molecular pathways behind this phenomenon are largely unknown. The aim of this study was to investigate the differential gene expression in placental tissues at day 30 of gestation between low LBWP (LLBWP) vs. high LBWP (HLBWP) sows from a purebred Large White maternal line. Using mRNA sequencing, we found 45 differentially expressed genes (DEGs) in placental tissues of LLBWP and HLBWP sows. Furthermore, (GO) enrichment of upregulated DEGs predicted that there were two biological processes significantly related to cornification and regulation of cell population proliferation. To better understand the molecular interaction between cell proliferation and cornification, we conducted transcriptional factor binding site (TFBS) prediction analysis. The results indicated that a highly significant TFBS was located at the 5' upstream of all four upregulated genes (CDSN, DSG3, KLK14, KRT17), recognized by transcription factors EGR4 and FOSL1. Our findings provide novel insight into how transcriptional regulation of two different biological processes interact in placental tissues of LLBWP sows.

A DIO2 missense mutation and its impact on fetal response to PRRSV infection.

BACKGROUND: Porcine reproductive and respiratory syndrome virus 2 (PRRSV-2) infection during late gestation substantially lowers fetal viability and survival. In a previous genome-wide association study, a single nucleotide polymorphism on chromosome 7 was significantly associated with probability of fetuses being viable in response to maternal PRRSV-2 infection at 21 days post maternal inoculation. The iodothyronine deiodinase 2 (DIO2) gene, located ~ 14 Kilobase downstream of this SNP, was selected as a priority candidate related to fetal susceptibility following maternal PRRSV-2 infection. Our objectives were to identify mutation(s) within the porcine DIO2 gene and to determine if they were associated with fetal outcomes after PRRSV-2 challenge. Sequencing of the DIO2, genotyping identified variants, and association of DIO2 genotypes with fetal phenotypes including DIO2 mRNA levels, viability, survival, viral loads, cortisol and thyroid hormone levels, and growth measurements were conducted. RESULTS: A missense variant (p.Asn91Ser) was identified in the parental populations from two independent PRRSV-2 challenge trials. This variant was further genotyped to determine association with fetal PRRS outcomes. DIO2 mRNA levels in fetal heart and kidney differed by the genotypes of Asn91Ser substitution with significantly greater DIO2 mRNA expression in heterozygotes compared with wild-type homozygotes (P < 0.001 for heart, P = 0.002 for kidney). While Asn91Ser did not significantly alter fetal viability and growth measurements, interaction effects of the variant with fetal sex or trial were identified for fetal viability or crown rump length, respectively. However, this mutation was not related to dysregulation of the hypothalamic-pituitary-adrenal and thyroid axis, indicated by no differences in circulating cortisol, T4, and T3 levels in fetuses of the opposing genotypes following PRRSV-2 infection. CONCLUSIONS: The present study suggests that a complex relationship among DIO2 genotype, DIO2 expression, fetal sex, and fetal viability may exist during the course of fetal PRRSV infection. Our study also proposes the increase in cortisol levels, indicative of fetal stress response, may lead to fetal complications, such as fetal compromise, fetal death, or premature farrowing, during PRRSV infection.

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.

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.

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions.

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Genetic analysis of the blood transcriptome of young healthy pigs to improve disease resilience.

BACKGROUND: Disease resilience is the ability of an animal to maintain productive performance under disease conditions and is an important selection target. In pig breeding programs, disease resilience must be evaluated on selection candidates without exposing them to disease. To identify potential genetic indicators for disease resilience that can be measured on selection candidates, we focused on the blood transcriptome of 1594 young healthy pigs with subsequent records on disease resilience. Transcriptome data were obtained by 3'mRNA sequencing and genotype data were from a 650 K genotyping array. RESULTS: Heritabilities of the expression of 16,545 genes were estimated, of which 5665 genes showed significant estimates of heritability (p < 0.05), ranging from 0.05 to 0.90, with or without accounting for white blood cell composition. Genes with heritable expression levels were spread across chromosomes, but were enriched in the swine leukocyte antigen region (average estimate > 0.2). The correlation of heritability estimates with the corresponding estimates obtained for genes expressed in human blood was weak but a sizable number of genes with heritable expression levels overlapped. Genes with heritable expression levels were significantly enriched for biological processes such as cell activation, immune system process, stress response, and leukocyte activation, and were involved in various disease annotations such as RNA virus infection, including SARS-Cov2, as well as liver disease, and inflammation. To estimate genetic correlations with disease resilience, 3205 genotyped pigs, including the 1594 pigs with transcriptome data, were evaluated for disease resilience following their exposure to a natural polymicrobial disease challenge. Significant genetic correlations (p < 0.05) were observed with all resilience phenotypes, although few exceeded expected false discovery rates. Enrichment analysis of genes ranked by estimates of genetic correlations with resilience phenotypes revealed significance for biological processes such as regulation of cytokines, including interleukins and interferons, and chaperone mediated protein folding. CONCLUSIONS: These results suggest that expression levels in the blood of young healthy pigs for genes in biological pathways related to immunity and endoplasmic reticulum stress have potential to be used as genetic indicator traits to select for disease resilience.

Sequence-based GWAS meta-analyses for beef production traits.

BACKGROUND: Combining the results of within-population genome-wide association studies (GWAS) based on whole-genome sequences into a single meta-analysis (MA) is an accurate and powerful method for identifying variants associated with complex traits. As part of the H2020 BovReg project, we performed sequence-level MA for beef production traits. Five partners from France, Switzerland, Germany, and Canada contributed summary statistics from sequence-based GWAS conducted with 54,782 animals from 15 purebred or crossbred populations. We combined the summary statistics for four growth, nine morphology, and 15 carcass traits into 16 MA, using both fixed effects and z-score methods. RESULTS: The fixed-effects method was generally more informative to provide indication on potentially causal variants, although we combined substantially different traits in each MA. In comparison with within-population GWAS, this approach highlighted (i) a larger number of quantitative trait loci (QTL), (ii) QTL more frequently located in genomic regions known for their effects on growth and meat/carcass traits, (iii) a smaller number of genomic variants within the QTL, and (iv) candidate variants that were more frequently located in genes. MA pinpointed variants in genes, including MSTN, LCORL, and PLAG1 that have been previously associated with morphology and carcass traits. We also identified dozens of other variants located in genes associated with growth and carcass traits, or with a function that may be related to meat production (e.g., HS6ST1, HERC2, WDR75, COL3A1, SLIT2, MED28, and ANKAR). Some of these variants overlapped with expression or splicing QTL reported in the cattle Genotype-Tissue Expression atlas (CattleGTEx) and could therefore regulate gene expression. CONCLUSIONS: By identifying candidate genes and potential causal variants associated with beef production traits in cattle, MA demonstrates great potential for investigating the biological mechanisms underlying these traits. As a complement to within-population GWAS, this approach can provide deeper insights into the genetic architecture of complex traits in beef cattle.

The WUR0000125 PRRS resilience SNP had no apparent effect on pigs' infectivity and susceptibility in a novel transmission trial.

BACKGROUND: Porcine reproductive and respiratory syndrome (PRRS) remains one of the most important infectious diseases for the pig industry. A novel small-scale transmission experiment was designed to assess whether the WUR0000125 (WUR for Wageningen University and Research) PRRS resilience single nucleotide polymorphism (SNP) confers lower susceptibility and infectivity to pigs under natural porcine reproductive and respiratory syndrome virus (PRRSV-2) transmission. METHODS: Commercial full- and half-sib piglets (n = 164) were assigned as either Inoculation, Shedder, or Contact pigs. Pigs were grouped according to their relatedness structure and WUR genotype, with R- and R+ referring to pigs with zero and one copy of the dominant WUR resilience allele, respectively. Barcoding of the PRRSV-2 strain (SD09-200) was applied to track pig genotype-specific transmission. Blood and nasal swab samples were collected and concentrations of PRRSV-2 were determined by quantitative (q)-PCR and cell culture and expressed in units of median tissue culture infectious dose (TCID50). The Log10TCID50 at each sampling event, derived infection status, and area under the curve (AUC) were response variables in linear and generalized linear mixed models to infer WUR genotype differences in Contact pig susceptibility and Shedder pig infectivity. RESULTS: All Shedder and Contact pigs, except one, became infected through natural transmission. There was no significant (p > 0.05) effect of Contact pig genotype on any virus measures that would indicate WUR genotype differences in susceptibility. Contact pigs tended to have higher serum AUC (p = 0.017) and log10TCID50 (p = 0.034) when infected by an R+ shedder, potentially due to more infectious R+ shedders at the early stages of the transmission trial. However, no significant Shedder genotype effect was found in serum (p = 0.274) or nasal secretion (p = 0.951) that would indicate genotype differences in infectivity. CONCLUSIONS: The novel design demonstrated that it is possible to estimate genotype effects on Shedder pig infectivity and Contact pig susceptibility that are not confounded by family effects. The study, however, provided no supportive evidence that genetic selection on WUR genotype would affect PRRSV-2 transmission. The results of this study need to be independently validated in a larger trial using different PRRSV strains before dismissing the effects of the WUR marker or the previously detected GBP5 gene on PRRSV transmission.

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.

Improving the annotation of the cattle genome by annotating transcription start sites in a diverse set of tissues and populations using Cap Analysis Gene Expression sequencing.

Understanding the genomic control of tissue-specific gene expression and regulation can help to inform the application of genomic technologies in farm animal breeding programs. The fine mapping of promoters [transcription start sites (TSS)] and enhancers (divergent amplifying segments of the genome local to TSS) in different populations of cattle across a wide diversity of tissues provides information to locate and understand the genomic drivers of breed- and tissue-specific characteristics. To this aim, we used Cap Analysis Gene Expression (CAGE) sequencing, of 24 different tissues from 3 populations of cattle, to define TSS and their coexpressed short-range enhancers (<1 kb) in the ARS-UCD1.2_Btau5.0.1Y reference genome (1000bulls run9) and analyzed tissue and population specificity of expressed promoters. We identified 51,295 TSS and 2,328 TSS-Enhancer regions shared across the 3 populations (dairy, beef-dairy cross, and Canadian Kinsella composite cattle from 2 individuals, 1 of each sex, per population). Cross-species comparative analysis of CAGE data from 7 other species, including sheep, revealed a set of TSS and TSS-Enhancers that were specific to cattle. The CAGE data set will be combined with other transcriptomic information for the same tissues to create a new high-resolution map of transcript diversity across tissues and populations in cattle for the BovReg project. Here we provide the CAGE data set and annotation tracks for TSS and TSS-Enhancers in the cattle genome. This new annotation information will improve our understanding of the drivers of gene expression and regulation in cattle and help to inform the application of genomic technologies in breeding programs.

Milk metabolomics analyses of lactating dairy cows with divergent residual feed intake reveals physiological underpinnings and novel biomarkers.

The opportunity to select for feed efficient cows has been limited by inability to cost-effectively record individual feed efficiency on an appropriate scale. This study investigated the differences in milk metabolite profiles between high- and low residual feed intake (RFI) categories and identified biomarkers of residual feed intake and models that can be used to predict residual feed intake in lactating Holsteins. Milk metabolomics analyses were undertaken at early, mid and late lactation stages and residual feed intake was calculated in 72 lactating dairy cows. Cows were ranked and grouped into high residual feed intake (RFI >0.5 SD above the mean, n = 20) and low residual feed intake (RFI <0.5 SD below the mean, n = 20). Milk metabolite profiles were compared between high residual feed intake (least efficient) and low residual feed intake (most efficient) groups. Results indicated that early lactation was predominantly characterized by significantly elevated levels of medium chain acyl carnitines and glycerophospholipids in high residual feed intake cows. Citrate cycle and glycerophospholipid metabolism were the associated pathways enriched with the significantly different metabolites in early lactation. At mid lactation short and medium chain acyl carnitines, glycerophospholipids and amino acids were the main metabolite groups differing according to residual feed intake category. Late lactation was mainly characterized by increased levels of amino acids in high residual feed intake cows. Amino acid metabolism and biosynthesis pathways were enriched for metabolites that differed between residual feed intake groups at the mid and late lactation stages. Receiver operating characteristic curve analysis identified candidate biomarkers: decanoylcarnitine (area under the curve: AUC = 0.81), dodecenoylcarnitine (AUC = 0.81) and phenylalanine (AUC = 0.85) at early, mid and late stages of lactation, respectively. Furthermore, panels of metabolites predicted residual feed intake with validation coefficient of determination (R 2) of 0.65, 0.37 and 0.60 at early, mid and late lactation stages, respectively. The study sheds light on lactation stage specific metabolic differences between high-residual feed intake and low-residual feed intake lactating dairy cows. Candidate biomarkers that distinguished divergent residual feed intake groups and panels of metabolites that predict individual residual feed intake phenotypes were identified. This result supports the potential of milk metabolites to select for more efficient cows given that traditional residual feed intake phenotyping is costly and difficult to conduct in commercial farms.

Genetic Analysis of Methane Emission Traits in Holstein Dairy Cattle.

Genetic selection can be a feasible method to help mitigate enteric methane emissions from dairy cattle, as methane emission-related traits are heritable and genetic gains are persistent and cumulative over time. The objective of this study was to estimate heritability of methane emission phenotypes and the genetic and phenotypic correlations between them in Holstein cattle. We used 1765 individual records of methane emission obtained from 330 Holstein cattle from two Canadian herds. Methane emissions were measured using the GreenFeed system, and three methane traits were analyzed: the amount of daily methane produced (g/d), methane yield (g methane/kg dry matter intake), and methane intensity (g methane/kg milk). Genetic parameters were estimated using univariate and bivariate repeatability animal models. Heritability estimates (±SE) of 0.16 (±0.10), 0.27 (±0.12), and 0.21 (±0.14) were obtained for daily methane production, methane yield, and methane intensity, respectively. A high genetic correlation (rg = 0.94 ± 0.23) between daily methane production and methane intensity indicates that selecting for daily methane production would result in lower methane per unit of milk produced. This study provides preliminary estimates of genetic parameters for methane emission traits, suggesting that there is potential to mitigate methane emission in Holstein cattle through genetic selection.

Genome-wide association studies for additive and dominance effects for body composition traits in commercial crossbred Piétrain pigs.

Fat depth (FD) and muscle depth (MD) are economically important traits and used to estimate carcass lean content (LMP), which is one of the main breeding objectives in pig breeding programmes. We assessed the genetic architectures of body composition traits for additive and dominance effects in commercial crossbred Piétrain pigs using both 50 K array and sequence genotypes. We first performed a genome-wide association study (GWAS) using single-marker association analysis with a false discovery rate of 0.1. Then, we estimated the additive and dominance effects of the most significant variant in the quantitative trait loci (QTL) regions. It was investigated whether the use of whole-genome sequence (WGS) will improve the QTL detection (both additive and dominance) with a higher power compared with lower density SNP arrays. Our results showed that more QTL regions were detected by WGS compared with 50 K array (n = 54 vs. n = 17). Of the novel associated regions associated with FD and LMP and detected by WGS, the most pronounced peak was on SSC13, situated at ~116-118, 121-127 and 129-134 Mbp. Additionally, we found that only additive effects contributed to the genetic architecture of the analysed traits and no significant dominance effects were found for the tested SNPs at QTL regions, regardless of panel density. The associated SNPs are located in or near several relevant candidate genes. Of these genes, GABRR2, GALR1, RNGTT, CDH20 and MC4R have been previously reported as being associated with fat deposition traits. However, the genes on SSC1 (ZNF292, ORC3, CNR1, SRSF12, MDN1, TSHZ1, RELCH and RNF152) and SSC18 (TTC26 and KIAA1549) have not been reported previously to our best knowledge. Our current findings provide insights into the genomic regions influencing composition traits in Piétrain pigs.

Plasma protein levels of young healthy pigs as indicators of disease resilience.

Selection for disease resilience, which refers to the ability of an animal to maintain performance when exposed to disease, can reduce the impact of infectious diseases. However, direct selection for disease resilience is challenging because nucleus herds must maintain a high health status. A possible solution is indirect selection of indicators of disease resilience. To search for such indicators, we conducted phenotypic and genetic quantitative analyses of the abundances of 377 proteins in plasma samples from 912 young and visually healthy pigs and their relationships with performance and subsequent disease resilience after natural exposure to a polymicrobial disease challenge. Abundances of 100 proteins were significantly heritable (false discovery rate (FDR) <0.10). The abundance of some proteins was or tended to be genetically correlated (rg) with disease resilience, including complement system proteins (rg = -0.24, FDR = 0.001) and IgG heavy chain proteins (rg = -0.68, FDR = 0.22). Gene set enrichment analyses (FDR < 0.2) based on phenotypic and genetic associations of protein abundances with subsequent disease resilience revealed many pathways related to the immune system that were unfavorably associated with subsequent disease resilience, especially the innate immune system. It was not possible to determine whether the observed levels of these proteins reflected baseline levels in these young and visually healthy pigs or were the result of a response to environmental disturbances that the pigs were exposed to before sample collection. Nevertheless, results show that, under these conditions, the abundance of proteins in some immune-related pathways can be used as phenotypic and genetic predictors of disease resilience and have the potential for use in pig breeding and management.

A challenge of selection for disease resilience is that it is difficult to directly select pigs that have greater resilience to multiple diseases in the healthy nucleus herd environment which is essential for breeding programs. A possible alternative is to select an indicator trait or marker that can be measured in a healthy setting, is heritable, and is associated with the genetics of disease resilience. In this study, we investigated plasma protein levels measured on young healthy pigs as indicator traits to select for disease resilience. For this purpose, we used plasma proteome data collected prior to the natural exposure of nursery pigs to multiple diseases, performed phenotypic and genetic quantitative analyses, and investigated their relationships with disease resilience. Our results suggest that plasma protein levels of young healthy pigs have the potential as biomarkers to select for disease resistance.

Exploration of plasma metabolite levels in healthy nursery pigs in response to environmental enrichment and disease resilience.

The purpose of this study was to explore plasma metabolite levels in young healthy pigs and their potential association with disease resilience and estimate genetic and phenotypic correlation with the change in lymphocyte concentration following disease challenge. Plasma samples were collected from 968 healthy nursery pigs over 15 batches at an average of 28 ± 3.23 d of age. Forty-four metabolites were identified and quantified by nuclear magnetic resonance. Pigs were then introduced into a natural disease challenge barn, and were classified into four groups based on the growth rate of each animal in the grow-to-finish phase (GFGR) and treatment rate (TR): resilient (RES), average (MID), susceptible (SUS), and dead (pigs that died before harvest). Blood samples were collected from all pigs before and 2 wk after disease challenge and complete blood count was determined. Environmental enrichment (inedible point source objects) was provided for half of the pigs in seven batches (N = 205) to evaluate its impact on resilience and metabolite concentrations. Concentration of all metabolites was affected by batch, while entry age affected the concentration of 16 metabolites. The concentration of creatinine was significantly lower for pigs classified as "dead" and "susceptible" when compared to "average" (P < 0.05). Pigs that received enrichment had significantly lower concentrations of six metabolites compared with pigs that did not receive enrichment (P ≤ 0.05). Both, group classification and enrichment affected metabolites that are involved in the same pathways of valine, leucine, and isoleucine biosynthesis and degradation. Resilient pigs had higher increase in lymphocyte concentration after disease challenge. The concentration of plasma l-α-aminobutyric acid was significantly negatively genetically correlated with the change in lymphocyte concentration following challenge. In conclusion, creatinine concentration in healthy nursery pigs was lower in pigs classified as susceptible or dead after disease challenge, whilst l-α-aminobutyric may be a genetic biomarker of lymphocyte response after pathogen exposure, and both deserve further investigation. Batch, entry age, and environmental enrichment were important factors affecting the concentration of metabolites and should be taken into consideration in future studies.

The focus of this study was to explore plasma metabolite levels in young healthy pigs and their potential association with health outcome classification following the exposure to a polymicrobial disease challenge. In addition, we explored the effect of the environmental enrichment on metabolite concentrations. Finally, we estimated genetic and phenotypic correlations between metabolites and the magnitude of change in lymphocytes levels following exposure to a polymicrobial disease challenge. We found that concentration of creatinine was lower in pigs that died before marketing, classified as "dead" and susceptible when compared to average group. This indicates that creatinine can be used as an early indicator of death and/or susceptibility of disease in pigs. Providing environmental enrichment affected the concentration of six metabolites and branched chain amino acids index. Such results would be very useful to design environmental enrichment strategies when pigs are challenged by disease in commercial farms. The magnitude of change in lymphocytes level was negatively genetically correlated with l-α-aminobutyric acid. This result indicates that l-αs-aminobutyric acid can be an early indicator of the magnitude of change in lymphocytes level. Such indicator can be collected from nucleus breeding herds in healthy animals and could provide an early biomarker of resilience.

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.