Differences in intestinal size, structure, and function contributing to feed efficiency in broiler chickens reared at geographically distant locations.

The contribution of the intestinal tract to differences in residual feed intake (RFI) has been inconclusively studied in chickens so far. It is also not clear if RFI-related differences in intestinal function are similar in chickens raised in different environments. The objective was to investigate differences in nutrient retention, visceral organ size, intestinal morphology, jejunal permeability and expression of genes related to barrier function, and innate immune response in chickens of diverging RFI raised at 2 locations (L1: Austria; L2: UK). The experimental protocol was similar, and the same dietary formulation was fed at the 2 locations. Individual BW and feed intake (FI) of chickens (Cobb 500FF) were recorded from d 7 of life. At 5 wk of life, chickens (L1, n = 157; L2 = 192) were ranked according to their RFI, and low, medium, and high RFI chickens were selected (n = 9/RFI group, sex, and location). RFI values were similar between locations within the same RFI group and increased by 446 and 464 g from low to high RFI in females and males, respectively. Location, but not RFI rank, affected growth, nutrient retention, size of the intestine, and jejunal disaccharidase activity. Chickens from L2 had lower total body weight gain and mucosal enzyme activity but higher nutrient retention and longer intestines than chickens at L1. Parameters determined only at L1 showed increased crypt depth in the duodenum and jejunum and enhanced paracellular permeability in low vs. high RFI females. Jejunal expression of IL1B was lower in low vs. high RFI females at L2, whereas that of TLR4 at L1 and MCT1 at both locations was higher in low vs. high RFI males. Correlation analysis between intestinal parameters and feed efficiency metrics indicated that feed conversion ratio was more correlated to intestinal size and function than was RFI. In conclusion, the rearing environment greatly affected intestinal size and function, thereby contributing to the variation in chicken RFI observed across locations.

Assessing serum metabolite profiles as predictors for feed efficiency in broiler chickens reared at geographically distant locations.

1. The objective of this study was to investigate differences in growth performance, serum intermediary metabolites, acute-phase proteins and white blood cells in low, medium and high-residual feed intake (RFI) chickens. It was also assessed if the environment affects the feed efficiency (FE) and FE-related performance and serum profiles of chickens. 2. Individual body weight (BW) and feed intake (FI) were recorded from d 7 of life. At 5 weeks of age, female and male broiler chickens (Cobb 500) were selected according to their RFI (L1: Austria; L2: UK; n = 9/RFI group, sex and locatity -45on) and blood samples were collected. 3. Chickens at L1 had similar FI but a 15% higher BW gain compared to chickens at L2. The RFI values of female chickens were -231, 8 and 215 g and those of male chickens -197, 0 and 267 g for low, medium and high RFI, respectively. 4. Location affected serum glucose, urea, cholesterol, non-esterified fatty acids (NEFA) and ovotransferrin in females, and serum glucose and triglycerides in male chickens. Serum uric acid and NEFA linearly increased from low to high RFI in females, whereas in males, cholesterol showed the same linear response from low to high RFI. Serum alpha-1-acid glycoprotein and blood heterophil-to-lymphocyte ratio linearly increased by 35% and 68%, respectively, from low to high RFI but only in male chickens at L1. 5. Regression analysis showed significant positive relationships between RFI and serum uric acid (R2 = 0.49) and cholesterol (R2 = 0.13). 6. It was concluded that RFI-related variation in serum metabolites of chickens was largely similar for the two environments and that serum metabolite patterns could be used to predict RFI in chickens.

Data compression can discriminate broilers by selection line, detect haplotypes, and estimate genetic potential for complex phenotypes.

Accurately establishing the relationships among individuals lays the foundation for genetic analyses such as genome-wide association studies and identification of selection signatures. Of particular interest to the poultry industry are estimates of genetic merit based on molecular data. These estimates can be commercially exploited in marker-assisted breeding programs to accelerate genetic improvement. Here, we test the utility of a new method we have recently developed to estimate animal relatedness and applied it to genetic parameter estimation in commercial broilers. Our approach is based on the concept of data compression from information theory. Using the real-world compressor gzip to estimate normalized compression distance (NCD) we have built compression-based relationship matrices (CRM) for 988 chickens from 4 commercial broiler lines-2 male and 2 female lines. For all pairs of individuals, we found a strong negative relationship between the commonly used genomic relationship matrix (GRM) and NCD. This reflects the fact that "similarity" is the inverse of "distance." The CRM explained more genetic variation than the corresponding GRM in 2 of 3 phenotypes, with corresponding improvements in accuracy of genomic-enabled predictions of breeding value. A sliding-window version of the analysis highlighted haplotype regions of the genome apparently under selection in a line-specific manner. In the male lines, we retrieved high population-specific scores for IGF-1 and a cognate receptor, INSR. For the female lines, we detected an extreme score for a region containing a reproductive hormone receptor (GNRHR). We conclude that our compression-based method is a valid approach to established relationships and identify regions under selective pressure in commercial lines of broiler chickens.

Evaluation of non-additive genetic variation in feed-related traits of broiler chickens.

Genome-wide association mapping and genomic predictions of phenotype of individuals in livestock are predominately based on the detection and estimation of additive genetic effects. Non-additive genetic effects are largely ignored. Studies in animals, plants, and humans to assess the impact of non-additive genetic effects in genetic analyses have led to differing conclusions. In this paper, we examined the consequences of including non-additive genetic effects in genome-wide association mapping and genomic prediction of total genetic values in a commercial population of 5,658 broiler chickens genotyped for 45,176 single nucleotide polymorphism (SNP) markers. We employed mixed-model equations and restricted maximum likelihood to analyze 7 feed related traits (TRT1 - TRT7). Dominance variance accounted for a significant proportion of the total genetic variance in all 7 traits, ranging from 29.5% for TRT1 to 58.4% for TRT7. Using a 5-fold cross-validation schema, we found that in spite of the large dominance component, including the estimated dominance effects in the prediction of total genetic values did not improve the accuracy of the predictions for any of the phenotypes. We offer some possible explanations for this counter-intuitive result including the possible confounding of dominance deviations with common environmental effects such as hatch, different directional effects of SNP additive and dominance variations, and the gene-gene interactions' failure to contribute to the level of variance.

Comparison of growth performance and excreta composition in broiler chickens when ranked according to various feed efficiency metrics.

Several feed efficiency (FE) metrics are currently used in livestock production to select for improved FE. Whether or not different FE metrics similarly estimate physiological characteristics in chickens of diverging FE has not been reported so far. This study aimed to assess potential differences in feed intake (FI), performance, and nutrient excretion in broiler chickens of diverging FE when ranked according to their residual FI (RFI), residual BW gain (RBG), RFI and BW gain (RIG), and G:F between d 7 and 35 of life. The FI was determined daily and BW was recorded once a week. The ranking of chickens into good, medium, and poor FE groups was completed separately for each FE metric. Freshly dropped excreta were collected for pH and DM measurements on d 30 to 32 of life and total excreta for determination of nutrient excretion was collected on d 34 to 36 of life. Relationships among FE metrics were evaluated using regression analysis showing that RFI, RIG, and G:F were more related to each other than to RBG. The FE values greatly varied among chickens for all FE metrics and chickens did not always cluster within the same FE group when using RFI, RIG, RBG, and G:F as the FE metrics because of the calculation approaches. Due to sex-related differences in performance, data of male and female chickens were analyzed separately. The RFI and RIG metrics showed a linear increase ( < 0.01) in total FI from good to poor FE in male and female chickens, whereas G:F showed this effect ( ≤ 0.011) only when BW gain was standardized to 1,500 g. The RBG did not clearly select chickens of enhanced total BW gain and only tended ( < 0.1) to select for greater BW gain from good to poor FE in female chickens. Excreta pH linearly decreased by 0.7 log units and DM content increased in males from good to poor FE when using RFI and RIG, respectively ( < 0.01). In both sexes, RFI ( < 0.05) and RIG metrics ( ≤ 0.06) showed a linear increase in daily nitrogen excretion from good to poor FE. In conclusion, results demonstrate that selection of the metric used to determine the FE of chickens modified the results obtained for comparison of production parameters and nutrient excretion among FE groups. Thereby, the RFI, RIG, and G:F metrics were beneficial in selecting the most feed efficient chickens to reduce feed costs, whereas the use of RFI and RIG may be better to select chickens with improved nitrogen retention and thus reduced excretion of an environmental pollutant.

Large-scale investigation of the parameters in response to Eimeria maxima challenge in broilers.

Coccidiosis, a parasitic disease of the intestinal tract caused by members of the genera Eimeria and Isospora, is one of the most common and costly diseases in chicken. The aims of this study were to assess the effect of the challenge and level of variability of measured parameters in chickens during the challenge with Eimeria maxima. Furthermore, this study aimed to investigate which parameters are the most relevant indicators of the health status. Finally, the study also aimed to estimate accuracy of prediction for traits that cannot be measured on large scale (such as intestinal lesion score and fecal oocyst count) using parameters that can easily be measured on all animals. The study was performed in 2 parts: a pilot challenge on 240 animals followed by a large-scale challenge on 2,024 animals. In both experiments, animals were challenged with 50,000 Eimeria maxima oocysts at 16 d of age. In the pilot challenge, all animals were measured for BW gain, plasma coloration, hematocrit, and rectal temperature and, in addition, a subset of 48 animals was measured for oocyst count and the intestinal lesion score. All animals from the second challenge were measured for BW gain, plasma coloration, and hematocrit whereas a subset of 184 animals was measured for intestinal lesion score, fecal oocyst count, blood parameters, and plasma protein content and composition. Most of the parameters measured were significantly affected by the challenge. Lesion scores for duodenum and jejunum (P < 0.001), oocyst count (P < 0.05), plasma coloration for the optical density values between 450 and 490 nm (P < 0.001), albumin (P < 0.001), α1-globulin (P < 0.01), α2-globulin (P < 0.001), α3-globulin (P < 0.01), and ß2-globulin (P < 0.001) were the most strongly affected parameters and expressed the greatest levels of variation. Plasma protein profiles proved to be a new, reliable parameter for measuring response to Eimeria maxima. Prediction of intestinal lesion score and fecal oocyst count using the other parameters measured was not very precise (R2 < 0.7). The study was successfully performed in real raising conditions on a large scale. Finally, we observed a high variability in response to the challenge, suggesting that broilers' response to Eimeria maxima has a strong genetic determinism, which may be improved by genetic selection.

Numerical analysis of intensity signals resulting from genotyping pooled DNA samples in beef cattle and broiler chicken.

Pooled genomic DNA has been proposed as a cost-effective approach in genomewide association studies (GWAS). However, algorithms for genotype calling of biallelic SNP are not adequate with pooled DNA samples because they assume the presence of 2 fluorescent signals, 1 for each allele, and operate under the expectation that at most 2 copies of the variant allele can be found for any given SNP and DNA sample. We adapt analytical methodology from 2-channel gene expression microarray technology to SNP genotyping of pooled DNA samples. Using 5 datasets from beef cattle and broiler chicken of varying degrees of complexity in terms of design and phenotype, continuous and dichotomous, we show that both differential hybridization (M = green minus red intensity signal) and abundance (A = average of red and green intensities) provide useful information in the prediction of SNP allele frequencies. This is predominantly true when making inference about extreme SNP that are either nearly fixed or highly polymorphic. We propose the use of model-based clustering via mixtures of bivariate normal distributions as an optimal framework to capture the relationship between hybridization intensity and allele frequency from pooled DNA samples. The range of M and A values observed here are in agreement with those reported within the context of gene expression microarray and also with those from SNP array data within the context of analytical methodology for the identification of copy number variants. In particular, we confirm that highly polymorphic SNP yield a strong signal from both channels (red and green) while lowly or nonpolymorphic SNP yield a strong signal from 1 channel only. We further confirm that when the SNP allele frequencies are known, either because the individuals in the pools or from a closely related population are themselves genotyped, a multiple regression model with linear and quadratic components can be developed with high prediction accuracy. We conclude that when these approaches are applied to the estimation of allele frequencies, the resulting estimates allow for the development of cost-effective and reliable GWAS.

Evidence for pleiotropism and recent selection in the PLAG1 region in Australian Beef cattle.

A putative functional mutation (rs109231213) near PLAG1 (BTA14) associated with stature was studied in beef cattle. Data from 8199 Bos taurus, Bos indicus and Tropical Composite cattle were used to test the associations between rs109231213 and various phenotypes. Further, 23 496 SNPs located on BTA14 were tested for association with these phenotypes, both independently and fitted together with rs109231213. The C allele of rs109231213 significantly increased hip height, weight, net food intake, age at puberty in males and females and decreased IGF-I concentration in blood and fat depth. When rs109231213 was fitted as a fixed effect in the model, there was an overall reduction in associations between other SNPs and these traits but some SNPs remained associated (P < 10(-4) ). Frequency of the mutant C allele of rs109231213 differed among B. indicus (0.52), B. taurus (0.96) and Tropical Composite (0.68). Most chromosomes carrying the C allele had the same surrounding 10 SNP haplotype, probably because the C allele was introgressed into Brahman from B. taurus cattle. A region of reduced heterozygosity surrounds the C allele; this is small in B. taurus but 20 Mb long in Brahmans, indicating recent and strong selection for the mutant allele. Thus, the C allele appears to mark a mutation that has been selected almost to fixation in the B. taurus breeds studied here and introduced into Brahman cattle during grading up and selected to a frequency of 0.52 despite its negative effects on fertility.

Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors.

Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.

Genetic variants affecting meat and milk production traits appear to have effects on reproduction traits in cattle.

Polymorphisms located in the genes ABCG2, DGAT1, LEP, PRLR, RORC, CAPN1 and CAST previously have been associated with milk or meat production traits. In this study, these polymorphisms were examined for significant effects on reproductive traits [age at puberty (AGECL), post-partum anoestrus interval (PPAI) and the ability ovulate prior to weaning (PW)] and on a panel of correlated traits such as weight, growth and serum concentration of insulin-like growth factor I. The effects of the polymorphisms were examined in two samples of tropically adapted beef cattle: Brahman (N = 932) and Tropical Composites (N = 1097). A polymorphism in the gene DGAT1 was associated with age at puberty in the combined sample (P = 0.042), and two polymorphisms in CAPN1 were associated with PPAI (P = 0.033) and with the ability ovulate PW (P = 0.017). The favourable allele for reproductive traits was not always the favourable allele associated with production traits. The effects of these polymorphisms on reproductive traits were small compared to their effects on the traits for which they were originally discovered.

Genome-wide association studies of female reproduction in tropically adapted beef cattle.

The genetics of reproduction is poorly understood because the heritabilities of traits currently recorded are low. To elucidate the genetics underlying reproduction in beef cattle, we performed a genome-wide association study using the bovine SNP50 chip in 2 tropically adapted beef cattle breeds, Brahman and Tropical Composite. Here we present the results for 3 female reproduction traits: 1) age at puberty, defined as age in days at first observed corpus luteum (CL) after frequent ovarian ultrasound scans (AGECL); 2) the postpartum anestrous interval, measured as the number of days from calving to first ovulation postpartum (first rebreeding interval, PPAI); and 3) the occurrence of the first postpartum ovulation before weaning in the first rebreeding period (PW), defined from PPAI. In addition, correlated traits such as BW, height, serum IGF1 concentration, condition score, and fatness were also examined. In the Brahman and Tropical Composite cattle, 169 [false positive rate (FPR) = 0.262] and 84 (FPR = 0.581) SNP, respectively, were significant (P < 0.001) for AGECL. In Brahman, 41% of these significant markers mapped to a single chromosomal region on BTA14. In Tropical Composites, 16% of these significant markers were located on BTA5. For PPAI, 66 (FPR = 0.67) and 113 (FPR = 0.432) SNP were significant (P < 0.001) in Brahman and Tropical Composite, respectively, whereas for PW, 68 (FPR = 0.64) and 113 (FPR = 0.432) SNP were significant (P < 0.01). In Tropical Composites, the largest concentration of PPAI markers were located on BTA5 [19% (PPAI) and 23% (PW)], and BTA16 [17% (PPAI) and 18% (PW)]. In Brahman cattle, the largest concentration of markers for postpartum anestrus was located on BTA3 (14% for PPAI and PW) and BTA14 (17% PPAI). Very few of the significant markers for female reproduction traits for the Brahman and Tropical Composite breeds were located in the same chromosomal regions. However, fatness and BW traits as well as serum IGF1 concentration were found to be associated with similar genome regions within and between breeds. Clusters of SNP associated with multiple traits were located on BTA14 in Brahman and BTA5 in Tropical Composites.

A single nucleotide polymorphism-derived regulatory gene network underlying puberty in 2 tropical breeds of beef cattle.

Harsh tropical environments impose serious challenges on poorly adapted species. In beef cattle, tropical adaptation in the form of temperature and disease resistance, coupled with acclimatization to seasonal and limited forage, comes at a cost to production efficiency. Prominent among these costs is delayed onset of puberty, a challenging phenotype to manipulate through traditional breeding mechanisms. Recently, system biology approaches, including gene networks, have been applied to the genetic dissection of complex phenotypes. We aimed at developing and studying gene networks underlying cattle puberty. Our starting material comprises the association results of ~50,000 SNP on 22 traits, including age at puberty, and 2 cattle breed populations: Brahman (n = 843) and Tropical Composite (n = 866). We defined age at puberty as the age at first corpus luteum (AGECL). By capturing the genes harboring mutations minimally associated (P < 0.05) to AGECL or to a set of traits related with AGECL, we derived a gene network for each breed separately and a third network for the combined data set. At the intersection of the 3 networks, we identified candidate genes and pathways that were common to both breeds. Resulting from these analyses, we identified an enrichment of genes involved in axon guidance, cell adhesion, ErbB signaling, and glutamate activity, pathways that are known to affect pulsatile release of GnRH, which is necessary for the onset of puberty. Furthermore, we employed network connectivity and centrality parameters along with a regulatory impact factor metric to identify the key transcription factors (TF) responsible for the molecular regulation of puberty. As a novel finding, we report 5 TF (HIVEP3, TOX, EYA1, NCOA2, and ZFHX4) located in the network intersecting both breeds and interacting with other TF, forming a regulatory network that harmonizes with the recent literature of puberty. Finally, we support our network predictions with evidence derived from gene expression in hypothalamic tissue of adult cows.

Detection of chromosome segments of zebu and taurine origin and their effect on beef production and growth.

Cattle in breeds formed by recent crossing of Bos taurus (Bt) and Bos indicus (Bi) subspecies should contain chromosomes that are a composite of Bt and Bt segments. Using data from a 50K SNP chip, we were able to identify whether a chromosome segment of 11 SNP in a composite animal descended from a Bt or a Bi ancestor. When the method was tested in purebred Bt or Brahman cattle, about 94% of segments were assigned correctly. About 10% of the genome in Australian Brahman cattle appears to be of Bt origin, as might be expected from their history. We then examined the effect of the origin of each chromosome segment on BW in a population of 515 Bt × Bi composite cattle and found 67 chromosome segments with a significant (P<0.01) effect. We confirmed these effects by examining these 67 segments in a population of Brahman cattle and in a population of mixed breeds including composite breeds such as Santa Gertrudis and Brahman cattle. About 66% of the 67 segments had an effect in the same direction in the confirmation analyses as in the discovery population. However, the effect on BW and other traits of chromosome segment origin is small, indicating that we had low power to detect these effects with the number of animals available. Consequently, when chromosome segment origin was used in genomic selection to predict BW, the accuracy was low (0.08). Chromosome segments that had a positive effect on BW tend to be at greater frequency in composite breeds than chromosome segments with a negative effect on BW.

Genome-wide association studies for feedlot and growth traits in cattle.

A genome wide-association study for production traits in cattle was carried out using genotype data from the 10K Affymetrix (Santa Clara, CA) and the 50K Illumina (San Diego, CA) SNP chips. The results for residual feed intake (RFI), BW, and hip height in 3 beef breed types (Bos indicus, Bos taurus, and B. indicus × B. taurus), and for stature in dairy cattle, are presented. The aims were to discover SNP associated with all traits studied, but especially RFI, and further to test the consistency of SNP effects across different cattle populations and breed types. The data were analyzed within data sets and within breed types by using a mixed model and fitting 1 SNP at a time. In each case, the number of significant SNP was more than expected by chance alone. A total of 75 SNP from the reference population with 50K chip data were significant (P < 0.001) for RFI, with a false discovery rate of 68%. These 75 SNP were mapped on 24 different BTA. Of the 75 SNP, the 9 most significant SNP were detected on BTA 3, 5, 7, and 8, with P ≤ 6.0 × 10(-5). In a population of Angus cattle divergently selected for high and low RFI and 10K chip data, 111 SNP were significantly (P < 0.001) associated with RFI, with a false discovery rate of 7%. Approximately 103 of these SNP were therefore likely to represent true positives. Because of the small number of SNP common to both the 10K and 50K SNP chips, only 27 SNP were significantly (P < 0.05) associated with RFI in the 2 populations. However, other chromosome regions were found that contained SNP significantly associated with RFI in both data sets, although no SNP within the region showed a consistent effect on RFI. The SNP effects were consistent between data sets only when estimated within the same breed type.

Bovine Muc1 is a highly polymorphic gene encoding an extensively glycosylated mucin that binds bacteria.

The bovine Muc1 protein is synthesized by mammary epithelial cells and shed into milk as an integral component of the milk fat globule membrane; however, the structure and functions of this mucin, particularly in relation to lactation, are poorly defined. The objectives of this investigation were to investigate the Muc1 gene and protein structures in the context of lactation and to test the hypothesis that Muc1 has a role in innate immune defense. Polymerase chain reaction analysis of genomic DNA from 630 cattle revealed extensive polymorphism in the variable number of tandem repeats (VNTR) in the bovine Muc1 gene. Nine allelic variants spanning 7 to 23 VNTR units, each encoding 20 AA, were identified. Three alleles, containing 11, 14, and 16 VNTR units, respectively, were predominant. In addition, a polymorphism in one of the VNTR units has the potential to introduce a unique site for N-linked glycosylation. Statistical analysis indicated weak associations between the VNTR alleles and milk protein and fat percentages in a progeny-tested population of Holstein-Friesian dairy cattle. No association with somatic cell count could be demonstrated. Bovine Muc1 was purified from milk fat globule membranes and characterized. The protein was highly glycosylated, primarily with O-linked sialylated T-antigen [Neu5Ac(alpha2-3)-Gal(beta1-3)-GalNAcalpha1] and, to a lesser extent, with N-linked oligosaccharides, which together accounted for approximately 60% of the apparent mass of Muc1. Purified bovine Muc1 directly bound fluorescently labeled Escherichia coli BioParticles (Invitrogen, Mount Waverley, Australia) and inhibited their binding to bovine mammary epithelial cells grown in vitro. It was also demonstrated that the expression of Muc1 mRNA in bovine mammary epithelial cells was markedly upregulated by lipopolysaccharide. Muc1 may be a pattern recognition protein that has the capacity to sequester bacteria and prevent their attachment to epithelial surfaces by immobilizing and subsequently shedding Muc1-bound bacteria from the cell surface. It was concluded that bovine Muc1 is probably an inducible innate immune effector and an important component of the first line of defense against bacterial invasion of epithelial surfaces, particularly mammary epithelial surfaces and the neonatal gut.

The combined effect of SNP-marker and phenotype attributes in genome-wide association studies.

The last decade has seen rapid improvements in high-throughput single nucleotide polymorphism (SNP) genotyping technologies that have consequently made genome-wide association studies (GWAS) possible. With tens to hundreds of thousands of SNP markers being tested simultaneously in GWAS, it is imperative to appropriately pre-process, or filter out, those SNPs that may lead to false associations. This paper explores the relationships between various SNP genotype and phenotype attributes and their effects on false associations. We show that (i) uniformly distributed ordinal data as well as binary data are more easily influenced, though not necessarily negatively, by differences in various SNP attributes compared with normally distributed data; (ii) filtering SNPs on minor allele frequency (MAF) and extent of Hardy-Weinberg equilibrium (HWE) deviation has little effect on the overall false positive rate; (iii) in some cases, filtering on MAF only serves to exclude SNPs from the analysis without reduction of the overall proportion of false associations; and (iv) HWE, MAF and heterozygosity are all dependent on minor genotype frequency, a newly proposed measure for genotype integrity.

Predicting genetic merit for mastitis and fertility in dairy cattle using genome wide selection and high density SNP screens.

Two novel methods for genome wide selection (GWS) were examined for predicting the genetic merit of animals using SNP information alone. A panel of 1,546 dairy bulls with reliable EBVs was genotyped for 15,380 SNPs that spanned the whole bovine genome. Two complexity reduction methods were used, partial least squares (PLS) and regression using a genetic algorithm (GAR), to find optimal solutions of EBVs against SNP information. Extensive internal cross-validation was used tofind the best predictive models followed by external validation (without direct use of the pedigree or SNP location). Both PLS and GAR provided both accurate fit to the training data set for somatic cell count (SCC) (max r = 0.83) and fertility (max r = 0.88) and showed an accuracy of prediction of r = 0.47 for SCC, and r = 0.72 for fertility. This is the first empirical demonstration that genome wide selection can account for a very high proportion of additive genetic variation in fitness traits whilst exploiting only a small percentage of available SNP information, without use of pedigree or QTL mapping. PLS was computationally more efficient than GAR.