Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project Genomic Management Tools to Optimise Resilience and Efficiency, and the Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle.

Invited review: Advances and challenges in application of feedomics to improve dairy cow production and health.

Dairy cattle science has evolved greatly over the past century, contributing significantly to the improvement in milk production achieved today. However, a new approach is needed to meet the increasing demand for milk production and address the increased concerns about animal health and welfare. It is now easy to collect and access large and complex data sets consisting of molecular, physiological, and metabolic data as well as animal-level data (such as behavior). This provides new opportunities to better understand the mechanisms regulating cow performance. The recently proposed concept of feedomics could help achieve this goal by increasing our understanding of interactions between the different components or levels and their impact on animal production. Feedomics is an emerging field that integrates a range of omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, and metatranscriptomics) to provide these insights. In this way, we can identify the best strategies to improve overall animal productivity, product quality, welfare, and health. This approach can help research communities elucidate the complex interactions among nutrition, environment, management, animal genetics, metabolism, physiology, and the symbiotic microbiota. In this review, we summarize the outcomes of the most recent research on omics in dairy cows and highlight how an integrated feedomics approach could be applied in the future to improve dairy cow production and health. Specifically, we focus on 2 topics: (1) improving milk yield and milk quality, and (2) understanding metabolic physiology in transition dairy cows, which are 2 important challenges faced by the dairy industry worldwide.

Genome-wide association studies to identify quantitative trait loci affecting milk production traits in water buffalo.

Water buffalo is the second largest resource of milk supply around the world, and it is well known for its distinctive milk quality in terms of fat, protein, lactose, vitamin, and mineral contents. Understanding the genetic architecture of milk production traits is important for future improvement by the buffalo breeding industry. The advance of genome-wide association studies (GWAS) provides an opportunity to identify potential genetic variants affecting important economical traits. In the present study, GWAS was performed for 489 buffaloes with 1,424 lactation records using the 90K Affymetrix Buffalo SNP Array (Affymetrix/Thermo Fisher Scientific, Santa Clara, CA). Collectively, 4 candidate single nucleotide polymorphisms (SNP) in 2 genomic regions were found to associate with buffalo milk production traits. One region affecting milk fat and protein percentage was located on the equivalent of Bos taurus autosome (BTA)3, spanning 43.3 to 43.8 Mb, which harbored the most likely candidate genes MFSD14A, SLC35A3, and PALMD. The other region on the equivalent of BTA14 at 66.5 to 67.0 Mb contained candidate genes RGS22 and VPS13B and influenced buffalo total milk yield, fat yield, and protein yield. Interestingly, both of the regions were reported to have quantitative trait loci affecting milk performance in dairy cattle. Furthermore, we suggest that buffaloes with the C allele at AX-85148558 and AX-85073877 loci and the G allele at AX-85106096 locus can be selected to improve milk fat yield in this buffalo-breeding program. Meanwhile, the G allele at AX-85063131 locus can be used as the favorable allele for improving milk protein percentage. Genomic prediction showed that the reliability of genomic estimated breeding values (GEBV) of 6 milk production traits ranged from 0.06 to 0.22, and the correlation between estimated breeding values and GEBV ranged from 0.23 to 0.35. These findings provide useful information to understand the genetic basis of buffalo milk properties and may play a role in accelerating buffalo breeding programs using genomic approaches.

Coadministration of the Campylobacter jejuni N-Glycan-Based Vaccine with Probiotics Improves Vaccine Performance in Broiler Chickens.

Source attribution studies report that the consumption of contaminated poultry is the primary source for acquiring human campylobacteriosis. Oral administration of an engineered Escherichia coli strain expressing the Campylobacter jejuni N-glycan reduces bacterial colonization in specific-pathogen-free leghorn chickens, but only a fraction of birds respond to vaccination. Optimization of the vaccine for commercial broiler chickens has great potential to prevent the entry of the pathogen into the food chain. Here, we tested the same vaccination approach in broiler chickens and observed similar efficacies in pathogen load reduction, stimulation of the host IgY response, the lack of C. jejuni resistance development, uniformity in microbial gut composition, and the bimodal response to treatment. Gut microbiota analysis of leghorn and broiler vaccine responders identified one member of Clostridiales cluster XIVa, Anaerosporobacter mobilis, that was significantly more abundant in responder birds. In broiler chickens, coadministration of the live vaccine with A. mobilis or Lactobacillus reuteri, a commonly used probiotic, resulted in increased vaccine efficacy, antibody responses, and weight gain. To investigate whether the responder-nonresponder effect was due to the selection of a C. jejuni "supercolonizer mutant" with altered phase-variable genes, we analyzed all poly(G)-containing loci of the input strain compared to nonresponder colony isolates and found no evidence of phase state selection. However, untargeted nuclear magnetic resonance (NMR)-based metabolomics identified a potential biomarker negatively correlated with C. jejuni colonization levels that is possibly linked to increased microbial diversity in this subgroup. The comprehensive methods used to examine the bimodality of the vaccine response provide several opportunities to improve the C. jejuni vaccine and the efficacy of any vaccination strategy.IMPORTANCECampylobacter jejuni is a common cause of human diarrheal disease worldwide and is listed by the World Health Organization as a high-priority pathogen. C. jejuni infection typically occurs through the ingestion of contaminated chicken meat, so many efforts are targeted at reducing C. jejuni levels at the source. We previously developed a vaccine that reduces C. jejuni levels in egg-laying chickens. In this study, we improved vaccine performance in meat birds by supplementing the vaccine with probiotics. In addition, we demonstrated that C. jejuni colonization levels in chickens are negatively correlated with the abundance of clostridia, another group of common gut microbes. We describe new methods for vaccine optimization that will assist in improving the C. jejuni vaccine and other vaccines under development.

Comparative transcriptomic analysis of porcine peripheral blood reveals differentially expressed genes from the cytokine-cytokine receptor interaction pathway related to health status.

While some research has looked into the host genetic response in pigs challenged with specific viruses or bacteria, few studies have explored the expression changes of transcripts in the peripheral blood of sick pigs that may be infected with multiple pathogens on farms. In this study, the architecture of the peripheral blood transcriptome of 64 Duroc sired commercial pigs, including 18 healthy animals at entry to a growing facility (set as a control) and 23 pairs of samples from healthy and sick pen mates, was generated using RNA-Seq technology. In total, 246 differentially expressed genes were identified to be specific to the sick animals. Functional enrichment analysis for those genes revealed that the over-represented gene ontology terms for the biological processes category were exclusively immune activity related. The cytokine-cytokine receptor interaction pathway was significantly enriched. Nine functional genes from this pathway encoding members (as well as their receptors) of the interleukins, chemokines, tumor necrosis factors, colony stimulating factors, activins, and interferons exhibited significant transcriptional alteration in sick animals. Our results suggest a subset of novel marker genes that may be useful candidate genes in the evaluation and prediction of health status in pigs under commercial production conditions.

Genomic investigation of piglet resilience following porcine epidemic diarrhea outbreaks.

Porcine epidemic diarrhea virus (PEDV) belongs to the Coronaviridae family and causes malabsorptive watery diarrhea, vomiting, dehydration and imbalanced blood electrolytes in pigs. Since the 1970s, PED outbreaks have become a source of problems in pig producing countries all over the world, causing large economic losses for pig producers. Although the infection in adults is not fatal, in naïve suckling piglets mortality is close to 100%. In this study, we investigated genome-wide differences between dead and recovered suckling piglets from commercial farms after PED outbreaks. Samples from 262 animals (156 dead and 106 recovered) belonging to several commercial lines were collected from five different farms in three different countries (USA, Canada and Germany) and genotyped with the porcine 80K SNP chip. Mean Fst value was calculated in 1-Mb non-overlapping windows between dead and recovered individuals, and the results were normalized to find differences within the comparison. Seven windows with high divergence between dead and recovered were detected-five on chromosome 2, one on chromosome 4 and one on chromosome 15-in total encompassing 152 genes. Several of these genes are either under- or overexpressed in many virus infections, including Coronaviridae (such as SARS-CoV). A total of 32 genes are included in one or more Gene Ontology terms that can be related to PED development, such as Golgi apparatus, as well as mechanisms generally linked to resilience or diarrhea development (cell proliferation, ion transport, ATPase activity). Taken together this information provides a first genomic picture of PEDV resilience in suckling piglets.

Associations between single nucleotide polymorphisms in 33 candidate genes and meat quality traits in commercial pigs.

This study aimed to evaluate the effects of single nucleotide polymorphisms (SNPs) in candidate genes for meat quality using a custom 96-SNP panel (Illumina Vera Code GoldenGate Assay) on 15 traits collected from 400 commercial pigs. Meat quality measurements included muscle pH, color (L*, a* and b*), drip loss, cooking loss, peak shear force and six sensory traits including appearance (outside and inside), tenderness, juiciness, flavor and overall liking as well as carcass weight and probe yield. Thirty-five SNPs with minor allele frequencies > 0.10 remained for the multimarker association using the GLM procedure of sas 9.2. Results showed that 20 SNPs were significantly associated with at least one of the traits with either additive or dominance or both effects (P < 0.05). Among these significant SNPs, five of them in ADIPOQ, FTO, TNF, LEPR and AMPD1 had an effect on more than three traits simultaneously; those in MC4R, CAST, DGAT1 and MYF6 had an effect on two traits, while the others were associated with one trait. The results suggest that these markers could be incorporated into commercial pigs for marker-assisted selection and breeding programs for carcass and meat quality trait improvement.

GWAS and genetic and phenotypic correlations of plasma metabolites with complete blood count traits in healthy young pigs reveal implications for pig immune response.

Introduction: In this study estimated genetic and phenotypic correlations between fifteen complete blood count (CBC) traits and thirty-three heritable plasma metabolites in young healthy nursery pigs. In addition, it provided an opportunity to identify candidate genes associated with variation in metabolite concentration and their potential association with immune response, disease resilience, and production traits. Methods: The blood samples were collected from healthy young pigs and Nuclear Magnetic Resonance (NMR) was used to quantify plasma metabolites. CBC was determined using the ADVIA® 2120i Hematology System. Genetic correlations of metabolite with CBC traits and single step genome-wide association study (ssGWAS) were estimated using the BLUPF90 programs. Results: Results showed low phenotypic correlation estimates between plasma metabolites and CBC traits. The highest phenotypic correlation was observed between lactic acid and plasma basophil concentration (0.36 ± 0.04; p < 0.05). Several significant genetic correlations were found between metabolites and CBC traits. The plasma concentration of proline was genetically positively correlated with hemoglobin concentration (0.94 ± 0.03; p < 0.05) and L-tyrosine was negatively correlated with mean corpuscular hemoglobin (MCH; -0.92 ± 0.74; p < 0.05). The genomic regions identified in this study only explained a small percentage of the genetic variance of metabolites levels that were genetically correlated with CBC, resilience, and production traits. Discussion: The results of this systems approach suggest that several plasma metabolite phenotypes are phenotypically and genetically correlated with CBC traits, suggesting that they may be potential genetic indicators of immune response following disease challenge. Genomic analysis revealed genes and pathways that might interact to modulate CBC, resilience, and production traits.

Structural analysis of MHC alleles in an RSV tumour regression chicken using a BAC library.

The chicken major histocompatibility complex (MHC-B locus) has a strong association with resistance and susceptibility to numerous diseases. We have found a B haplotype designated WLA that associated with the regression of tumours caused by Rous sarcoma virus J strain (RSV-J). Haplotype WLA was identical to the regressive B6 haplotype when partial genotyping was performed (Poultry Science, 89, 2010, 651). We then constructed a bacterial artificial chromosome (BAC) library from a WLA homozygote chicken to evaluate the structure of this regression haplotype and compared it to those of the B6 haplotype. Comparison between WLA and B6 above 59 kb within the 167 kb, including 14 genes from BG1 to BF2, revealed 75 SNPs and 14 indels. However, several genes were identical between WLA and B6, including the BF1 and BF2 genes, which encode a class I molecule previously suggested to be related to the regression phenotype. The BLB2 gene encoding the MHC class II beta chain showed the greatest diversity, with 19 non-synonymous SNPs. A comparison of WLA and B6 haplotpyes that are associated with tumour regression and RIRa and B24 haplotypes associated with tumour progression suggests that DMA1, DMA2, BRD2, TAPBP and BLB2 genes are not involved in the intensity of RSV J tumour regression.

The influence of litter birth weight phenotype on embryonic and placental development at day 30 of gestation in multiparous purebred Large White sows.

The aim of this study was to understand the intrauterine biological processes associated with the low litter birth weight phenotype in pigs. Analyses were conducted on reproductive data from a purebred Large White maternal line to identify sows (>2 parities) with repeatable high or low litter birth weight phenotype (HLBWP or LLBWP). A total of 40 sows were selected (n = 20 HLBWP and n = 20 LLBWP) and bred with semen from purebred Large White boars of proven fertility. Sows were euthanized on day 28-30 of gestation (day 29.5 ± 0.6) and samples of placenta and embryos collected. Total number of embryos (TNE), embryonic weight (EW), embryonic viability, and crown-rump (CRL) measurements were recorded, along with the ovulation rate (OR) and allantochorionic fluid volume (AFV). No significant difference was detected (P > 0.05) in OR, TNE, and number of viable embryos on day 30 of gestation between the two groups. There was no significant difference in EW (LLBWP: 0.80 ± 0.05 g; HLBWP: 0.88 ± 0.04 g, P = 0.18) or CRL (LLBWP: 21.5 ± 0.7 mm; HLBWP: 21.9 ± 0.68 mm, P = 0.46). Placental development represented by the average AFV was significantly lower in the LLBWP compared to HLBWP (LLBWP: 131 ± 9.82 mL; HLBWP: 149 ± 9.39 mL, P = 0.03). In conclusion, placental development may be the main factor causing lower BW of entire litters in LLBWP sows.

Predicting enteric methane emission in lactating Holsteins based on reference methane data collected by the GreenFeed system.

Methane emission is not included in the current breeding goals for dairy cattle mainly due to the expense and difficulty in obtaining sufficient data to generate accurate estimates of the relevant traits. While several models have been developed to predict methane emission from milk spectra using reference methane data obtained by the respiration chamber, SF6 and sniffer methods, the prediction of methane emission from milk mid-infrared (MIR) spectra using reference methane data collected by the GreenFeed system has not yet been explored. Methane emission was monitored for 151 cows using the GreenFeed system. Prediction models were developed for daily and average (for the trial period of 12 or 14 days) methane production (g/d), yield (g/kg DM intake (DMI)) and intensity (g/kg of fat- and protein-corrected milk) using partial least squares regression. The predictions were evaluated in 100 repeated validation cycles, where animals were randomly partitioned into training (80%) and testing (20%) populations for each cycle. The best performing model was observed for average methane intensity using MIR, parity and DMI with validation coefficient of determination (R2val) and RMSE of prediction of 0.66 and 4.7 g/kg of fat- and protein-corrected milk, respectively. The accuracy of the best models for average methane production and average methane yield were poor (R2val = 0.28 and 0.12, respectively). A lower accuracy of prediction was observed for methane intensity and production (R2val = 0.42 and 0.17) when daily records were used while prediction for methane yield was comparable to that for average methane yield (R2val = 0.16). Our results suggest the potential to predict methane intensity with moderate accuracy. In this case, prediction models for average methane values were generally better than for daily measures when using the GreenFeed system to obtain reference methane emission measurements.

Mapping QTL in the porcine MHC region affecting fatness and growth traits in a Meishan/Large White composite population.

A number of studies have mapped QTL regulating porcine fatness and growth traits to the region of the major histocompatibility complex (MHC) on porcine chromosome 7 using various experimental crosses. The QTL results from crosses using the Chinese Meishan (MS) (slow growing and fat) are particularly interesting because the MS alleles have been found to be associated with increased growth rate and reduced backfat depth. We investigated these QTL further in a composite population derived previously over eight generations by intercrossing Meishan and the European Large White breeds. Genotype information from 32 markers in a 15cM target region was used in linkage and association analyses. A two-step variance component analysis identified QTL for three growth-related traits, explaining 19 ∼ 24% of the phenotypic variance with a confidence interval of 4 cM in the target region. SNP association analyses found that ss181128966 and ss181128924 within the QTL interval were strongly associated with the growth traits. Only weak signals for an effect on backfat depth were found in the association and linkage analyses, possibly because of past directional selection in the composite population.

Identification of candidate markers on bovine chromosome 14 (BTA14) under milk production trait quantitative trait loci in Holstein.

The objective of this study was to identify single-nucleotide polymorphisms using a bovine chromosome 14 high-density SNP panel after accounting for the effect of DGAT1. Linkage disequilibrium information and sire heterozygosity were used to select markers for linkage analysis on bovine chromosome 14 for milk production traits in 321 Holstein animals. Results show putative milk peaks at 42 and 61 cM, both at p<0.10, a fat yield peak at 42 and 63 cM, both at p<0.05; a protein yield peak at 42 (p<0.01) and 84 cM (p<0.05); fat per cent peaks at 3 (p<0.01) and 29 cM (p<0.05), and a protein per cent peak at 4 cM (p<0.05). Once quantitative trait loci positions were established, allele substitution effects for all markers were evaluated using the same statistical model. Overlaying information between quantitative trait loci (QTL) and allele effect analysis enabled the identification (p<0.01) of 20 SNPs under the milk yield QTL, 2 under both of the fat yield peaks, 8 and 9 under the protein yield peaks, 2 and 6 for the fat per cent peaks and 5 for the protein per cent peak. One SNP in particular, ss61514555:A>C, showed association with 3 of the 5 traits: milk (p=1.59E-04), fat (p=6.88E-05) and protein yields (p=5.76E-05). Overall, combining information from linkage disequilibrium, sire heterozygosity and genetic knowledge of traits enabled the characterization of additional markers with significant associations with milk production traits.

Economic comparison of an ear tag automated activity monitor for estrus detection with timed-AI in Holstein heifers.

The objective of this study was to compare the economic performance of an ear tag automated activity monitor system (AAM) versus a timed-AI (TAI) protocol in Holstein heifers. In total, 340 heifers were enrolled onto the study at 13.5 mo of age and randomly assigned to receive either an AAM (n = 170) or TAI (n = 170) protocol before breeding eligibility (D 0). Heifers in the AAM group were fitted with an ear tag AAM and bred based on high activity alert from the system. Heifers in the TAI group received a progesterone releasing intravaginal device on D -8, followed by device removal and prostaglandin on D -3 and gonadotropin-releasing hormone with TAI on D 0. In both treatments, the majority of heifers received sex-sorted semen for the first AI and conventional semen for subsequent AIs, with three opportunities to become pregnant. All heifers were diagnosed for pregnancy approximately 25 d post AI using transrectal ultrasonography, with confirmation at 30 and 45 d. Non-pregnant heifers in the TAI group, were resynchronized using the same TAI protocol. A partial budget was used to compare the costs and benefits of switching from a TAI to an AAM protocol in heifers, including protocol, labour, and rearing costs for each treatment, as well as estimated calf and milk value. Sensitivity analyses were also conducted to determine the effect of pregnancy per AI (P/AI), outsourcing AI, AAM tag cost and herd size on the net outcome. There was no difference in overall P/AI or days to pregnancy between treatments. However, number of AI was greater in the TAI than the AAM group. For the first AI, the P/AI was less in the TAI compared to the AAM group; however, the interval to first AI was less in TAI. There was minimal difference in performance for the second and third AI. There was a net gain of $11.97 per heifer when switching from a TAI to AAM protocol, due to the increased P/AI to the first AI and reduced cost of hormones. Several variables in the sensitivity analyses affected the net outcome. Considering only the first AI, switching to an AAM collar and a larger herd size all increased the net gain. Considering a greater P/AI to the first AI in the TAI group, outsourcing AI, using more AAM ear tags, and smaller herd sizes resulted in a net loss when switching from TAI to AAM. The AAM system resulted in exceptional P/AI and may be an economically viable alternative to improve heifer reproductive efficiency in herds with suboptimal P/AI to TAI.

Heritability and genetic correlations of plasma metabolites of pigs with production, resilience and carcass traits under natural polymicrobial disease challenge.

Metabolites in plasma of healthy nursery pigs were quantified using nuclear magnetic resonance. Heritabilities of metabolite concentration were estimated along with their phenotypic and genetic correlations with performance, resilience, and carcass traits in growing pigs exposed to a natural polymicrobial disease challenge. Variance components were estimated by GBLUP. Heritability estimates were low to moderate (0.11 ± 0.08 to 0.19 ± 0.08) for 14 metabolites, moderate to high (0.22 ± 0.09 to 0.39 ± 0.08) for 17 metabolites, and highest for L-glutamic acid (0.41 ± 0.09) and hypoxanthine (0.42 ± 0.08). Phenotypic correlation estimates of plasma metabolites with performance and carcass traits were generally very low. Significant genetic correlation estimates with performance and carcass traits were found for several measures of growth and feed intake. Interestingly the plasma concentration of oxoglutarate was genetically negatively correlated with treatments received across the challenge nursery and finisher (- 0.49 ± 0.28; P < 0.05) and creatinine was positively correlated with mortality in the challenge nursery (0.85 ± 0.76; P < 0.05). These results suggest that some plasma metabolite phenotypes collected from healthy nursery pigs are moderately heritable and genetic correlations with measures of performance and resilience after disease challenge suggest they may be potential genetic indicators of disease resilience.

A major SNP resource for dissection of phenotypic and genetic variation in Pacific white shrimp (Litopenaeus vannamei).

Bioinformatics and re-sequencing approaches were used for the discovery of sequence polymorphisms in Litopenaeus vannamei. A total of 1221 putative single nucleotide polymorphisms (SNPs) were identified in a pool of individuals from various commercial populations. A set of 211 SNPs were selected for further molecular validation and 88% showed variation in 637 samples representing three commercial breeding lines. An association analysis was performed between these markers and several traits of economic importance for shrimp producers including resistance to three major viral diseases. A small number of SNPs showed associations with test weekly gain, grow-out survival and resistance to Taura Syndrome Virus. Very low levels of linkage disequilibrium were revealed between most SNP pairs, with only 11% of SNPs showing an r(2)-value above 0.10 with at least one other SNP. Comparison of allele frequencies showed small changes over three generations of the breeding programme in one of the commercial breeding populations. This unique SNP resource has the potential to catalyse future studies of genetic dissection of complex traits, tracing relationships in breeding programmes, and monitoring genetic diversity in commercial and wild populations of L. vannamei.

Genotypes of chicken major histocompatibility complex B locus associated with regression of Rous sarcoma virus J-strain tumors.

The chicken MHC-B locus affects the response to several strains of Rous sarcoma virus (RSV). We evaluated the association between haplotypes of the MHC-B locus and responses to the J strain of RSV by using an F(2) experimental resource family constructed with tumor-regressive (White Leghorn) and tumor-progressive (Rhode Island Red) chickens. The MHC-B haplotypes were determined by genotyping of the microsatellite marker LEI0258 and MHC-B locus class I alpha chain 2 (BF2). Two haplotypes in the resource family, one associated with tumor regression and one with progression, were defined by these 2 markers. To discriminate more precisely the regressive haplotype in this family, we further developed 35 SNP markers at the MHC-B locus. Information on the haplotypes revealed here should be useful for identifying chickens with regression and progression phenotypes of J-strain RSV-induced tumors.

Performance and optimization of an ear tag automated activity monitor for estrus prediction in dairy heifers.

The objectives of this study were to evaluate the performance of the SCR eSense ear tag automated activity monitor (AAM) to detect estrus behavior in Holstein heifers and to determine the optimal time from estrus alert to artificial insemination (AI) using sex-sorted or conventional semen. In total, 281 heifers were fitted with the AAM once eligible for breeding (>13.5 m of age). For the first AI, estrus was synchronized using 500 µg of cloprostenol (PGF), given 14 d apart, and heifers were given estrus detection patches (Estrotect™) after the second PGF. Heifers were inseminated at randomly attributed times after high activity alert from the AAM system or if the estrus patch had ≥ 50% colour change. Most heifers received sex-sorted semen for the first AI and conventional semen for subsequent inseminations. Pregnancy diagnosis was performed at 30 d post AI and heifers had four opportunities to become pregnant. In a subset of heifers (n = 149), ovaries were scanned every 12 h from the time of AI until ovulation (OV). The system recorded a heat index (measure of estrus strength), maximum activity change, maximum rumination change and duration of high activity. The sensitivity was 91.0%, with a false positive and false negative rate of 8.0%, and the positive predictive value to detect true estrus events was 83.5%. Pregnancy per AI to first AI was 67.6% and 97.9% of heifers become pregnant after four inseminations. Most false positive estrus events had a heat index < 45 and a rumination change < -20, while false negative events had a rumination change ≥ -20. Odds of pregnancy was not associated with any estrus characteristics measured by the system. However, pre-ovulatory follicle diameter had a weak correlation (r < 0.25) with all estrus characteristics. The average (range) interval of onset of high activity, peak activity and end of high activity to OV was 28 h (16-46 h), 22 h (10-40 h) and 16 h (0-36 h), respectively. For conventional semen, each hour increase in interval from activity onset or peak activity to AI reduced the predicted probability of pregnancy by 3.8 and 4.2%, respectively. For sex-sorted semen, the relationship between activity onset or peak activity to AI and predicted probability of pregnancy was quadratic, but not significant. Overall, the SCR eSense ear tag AAM performed well and strategies to identify false positive and false negative estrus events, along with optimization of timing of AI, should further improve performance in Holstein heifers.

Detailed characterization of the porcine MC4R gene in relation to fatness and growth.

In contrast to the human MC4R gene, where multiple variants have been described, several of which are associated with appetite and obesity, few MC4R variants have been reported in the pig. The most interesting polymorphism reported to date in the pig is p.Asp298Asn, which is significantly associated with variation in growth and fatness traits in most breeds and crosses. However, some reports have seemingly failed to confirm this association. The discrepancy of p.Asp298Asn associations in some pig populations suggested that further discovery of SNPs in MC4R would be useful. Utilizing the recently released pig genome sequence information, we obtained the whole MC4R genome sequence and detected five additional SNPs, a variable (CA)(n) repeat and a C indel in the ISU Berkshire x Yorkshire pig resource family. Linkage disequilibrium (LD) analysis revealed that the additional five SNPs were not in strong LD with p.Asp298Asn, but single marker association analysis indicated that they were significantly (P < 0.05) associated with fatness measures and very highly significantly (P < 0.0001) associated with average daily gain on test (ADGTEST). Three major haplotypes were identified and the subsequent association analyses suggested that the two non-synonymous SNPs had different effects, e.g. p.Arg236His influenced back fat and growth on test while p.Asp298Asn was primarily associated with variation in growth rate in this population. An interaction effect between these two SNPs was found for ADGTEST, which may partly explain some of the previous discrepancies reported for MC4R in different pig populations. Examination of the p.Arg236His polymorphism in populations where the effect of p.Asp298Asn is limited is warranted.

Genes located on a SSC17 meat quality QTL region are associated with growth in outbred pig populations.

The objective of this study was to evaluate the effect of markers developed in eight genes, located in a previously detected meat quality QTL region on SSC17, on growth, fat and meat quality traits collected in commercial pig populations of different genetic backgrounds. The genes had been previously mapped to SSC17 as part of a fine-mapping effort. Association analyses were conducted between each marker and the available phenotypic traits. Results showed that three genes (CTSZ, CSTF1 and C20orf43) were significantly associated with the growth traits. In addition, CTSZ also impacted on meat colour, with the less favourable genotype for growth being associated with darker meat. The differences observed between genotypes were substantial and may be of economic importance to pig producers. These markers may be useful for selecting for faster growth or improved meat quality.