Design and characterization of a high-resolution multiple-SNP capture array by target sequencing for sheep.

The efficiency of molecular breeding largely depends on inexpensive genotyping arrays. In this study, we aimed to develop an ovine high-resolution multiple-single-nucleotide polymorphism (SNP) capture array, based on genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology. All the markers were from 40K captured regions, including genes located within selective sweep regions, breed-specific regions, quantitative trait loci (QTL), and the potential functional SNPs on the sheep genome. The results showed that a total of 210K high-quality SNPs were identified in the 40K regions, indicating a high average capture ratio (99.7%) for the target genomic regions. Using genotyped data (n = 317) from liquid chip technology, we further performed genome-wide association studies (GWAS) to detect the genetic loci affecting sheep hair types and teat number. A single significant association signal for hair types was identified on 6.7-7.1 Mb of chromosome 25. The IRF2BP2 gene (chr25: 7,067,974-7,071,785), which is located within this genomic region, has been previously known to be involved in hair/wool traits in sheep. The results further showed a new candidate region around 26.4 Mb of chromosome 13, between the ARHGAP21 and KIAA1217 genes, that was significantly related to teat number in sheep. The haplotype patterns of this region also showed differences in animals with 2, 3, or 4 teats. Advances in using the high-accuracy and low-cost liquid chip are expected to accelerate sheep genomic and breeding studies in the coming years.

Large-scale genotyping platforms are valuable tools for animal selection and breeding programs. The bead chip has been widely used in both research and commercial applications for a long time. A highly efficient and economical genotyping platform has been developed recently. In the present study, by combining the advantages of resequencing and bead chips, we developed a high-resolution capture array based on target sequencing with capture-in-solution technology (liquid chip), including updated functional probes according to the latest research. We further evaluated this approach by using 317 individuals and found that 210K single-nucleotide polymorphisms can be accurately genotyped, confirming the ratio of the captured regions compared with the designed rations is around 99.7%. Genome-wide association studies conducted using this chip suggested IRF2BP2 gene may be involved in hair types and ARHGAP21-KIAA1217 locus may be related to teats number. The liquid chip with high accuracy and low cost can be widely used in genome-wide association studies and genome selection, supporting efforts in molecular breeding and genetic improvement of sheep.

New insights into the novel sequences of the chicken pan-genome by liquid chip.

Increasing evidence indicates that the missing sequences and genes in the chicken reference genome are involved in many crucial biological pathways, including metabolism and immunity. The low detection rate of novel sequences by resequencing hindered the acquisition of these sequences and the exploration of the relationship between new genes and economic traits. To improve the capture ratio of novel sequences, a 48K liquid chip including 25K from the reference sequence and 23K from the novel sequence was designed. The assay was tested on a panel of 218 animals from 5 chicken breeds. The average capture ratio of the reference sequence was 99.55%, and the average sequencing depth of the target sites was approximately 187X, indicating a good performance and successful application of liquid chips in farm animals. For the target region in the novel sequence, the average capture ratio was 33.15% and the average sequencing depth of target sites was approximately 60X, both of which were higher than that of resequencing. However, the different capture ratios and capture regions among varieties and individuals proved the difficulty of capturing these regions with complex structures. After genotyping, GWAS showed variations in novel sequences potentially relevant to immune-related traits. For example, a SNP close to the differentiation of lymphocyte-related gene IGHV3-23-like was associated with the H/L ratio. These results suggest that targeted capture sequencing is a preferred method to capture these sequences with complex structures and genes potentially associated with immune-related traits.

A total of 48K target sites were selected to be placed on the liquid chip, including 23K from the novel sequence of the chicken pan-genome. The high average capture ratio (99.55%) of the reference sequence in five populations indicated the good performance of the liquid chip. For the target region in the novel sequence, the average capture ratio was approximately 33.15% and the average sequencing depth of target sites was approximately 60X, both of which were higher than that of resequencing. However, the capture ratio was different among varieties, ranging from 29.2% (White Leghorn) to 33.4% (B line). GWAS (Genome-wide association study) showed variations in novel sequences potentially related to immune-related traits. For example, an SNP (single nucleotide polymorphism) close to the differentiation of the lymphocyte-related gene IGHV3-23-like was associated with the H/L (heterophil/lymphocyte ratio) ratio. Overall, this study not only improved the capture ratio of regions with complex structures in novel sequences but also preliminarily explored the association of variations in these regions with chicken economic traits.

Genome-wide association studies for egg quality traits in White Leghorn layers using low-pass sequencing and SNP chip data.

Low-pass sequencing data have been proposed as an alternative to single nucleotide polymorphism (SNP) chips in genome-wide association studies (GWAS) of several species. However, it has not been used in layer chickens yet. This study aims at comparing the GWAS results of White Leghorn chickens using low-pass sequencing data (1×) and 54 k SNP chip data. Ten commercially relevant egg quality traits including albumen height, shell strength, shell colour, egg weight and yolk weight collected from up to 1,420 White Leghorn chickens were analysed. The results showed that the genomic heritability estimates based on low-pass sequencing data were higher than those based on SNP chip data. Although two GWAS analyses showed similar overall landscape for most traits, low-pass sequencing captured some significant SNPs that were not on the SNP chip. In GWAS analysis using 54 k SNP chip data, after including more individuals (up to 5,700), additional significant SNPs not detected by low-pass sequencing data were found. In conclusion, GWAS using low-pass sequencing data showed similar results to those with SNP chip data and may require much larger sample sizes to show measurable advantages.

Microarray analysis and PCR validation of genes associated with facultative parthenogenesis in Meleagris gallopavo (Turkey).

A cDNA microarray containing 43,661 differentially expressed genes was carried out on the blastoderm of fertilized and facultative parthenogenic turkey embryos at different hours of development. The total number of up-regulated (UR) and down-regulated (DR) genes at 0, 12, and 24 h of development were 725 and 1436, 942 and 599, and 589 and 1044, respectively. Common genes between 0 and 12 h, 12 and 24 h, and 0 and 24 h were 55, 67, and 110, respectively. The proportion of genes showing above 50-fold UR and DR at 0, 12, and 24 h of development were 2.0% and 1.5%, 0.5% and 1.2%, and 0.2% and 1.1%, respectively. Eight UR genes were validated (APOA1, THRAP3, ARL14EP, PSAP, MOG, MYBPC2, MTIF3 and EDG4) and relative expression of six of them was significantly higher (P ≤ 0.05) in parthenogenic embryos, while two genes showed non-significant (P ≥ 0.05) variation. The expression of BCL11A, PRP4B, TCP1, and TPI1 genes was significantly (P ≤ 0.05) DR in parthenotes in the micro-array study, while the TCP1 gene was up-regulated, and there was no variation in TPI1 gene expression in the PCR validation study. In conclusion, our findings demonstrate differential expression of a large number of genes in parthenotes at different stages of embryo development compared to fertilized embryos. Up-regulation of APOA1, MYBPC2, TCP1, and THRAP3 genes, suggest their crucial role in spontaneous facultative parthenogenic development in turkey birds.

Comparison of three statistical approaches for feature selection for fine-scale genetic population assignment in four pig breeds.

BACKGROUND: Assigning animals to their corresponding breeds through breed informative single-nucleotide polymorphisms (SNPs) is required in many fields. For instance, it is used in the traceability and the authentication of meat and other livestock products. SNPs' information for several pork breeds are now accessible thanks to the availability of dense SNP chips. These SNP chips cover a large number of molecular markers distributed across the entire genome. To identify the pork breed from a sample of industrial meat, one must analyze a large panel of genetic markers depending on the SNP chip used. The analysis of such large datasets requires intensive work. This leads to the idea of creating less dense chips of breed informative markers based on a reduced number of SNPs. Therefore, the analysis of the data emanating from the genotyping of these reduced chips will require less time and effort. AIM: The objective of this study is to find the most informative SNPs for the discrimination between four pig breeds, namely Duroc, Landrace, Large White, and Pietrain. METHOD: The Illumina Porcine 60 k SNP chip was used to genotype SNPs distributed all over the individuals' genomes. Firstly, we used three different statistical approaches for feature selection: (i) principal component analysis (PCA), (ii) least absolute shrinkage and selection operator (LASSO), and (iii) random forest (RF). These three approaches identified three sets of SNPs; each set corresponds to one approach. Then, we combined the results of the three methods by setting up a final panel containing the SNPs which appear on the three sets altogether. RESULTS: Separately, each method resulted in a panel with the corresponding most discriminating SNPs. The PCA, the LASSO, and the random forest with Boruta algorithm highlighted 28,816, 50, and 286 SNPs, respectively. The number of SNPs selected by PCA is high compared to Boruta and LASSO because PCA chooses the variables while preserving as much information about the data as possible. The only downside of LASSO regression is that among a group of correlated variables, LASSO tends to select only one variable and ignore the others regardless of their importance. Contrarily to LASSO, the Boruta algorithm considers the interdependence between SNPs and selects informative variables even if they are correlated and have the same effect. The three panels shared 23 SNPs; the distribution of the individuals according to these SNPs showed a grouping of individuals of each breed in well-defined clusters without any overlapping. CONCLUSIONS: The biological pathways represented by 23 breed informative SNPs resulted by the combination of PCA, LASSO, and Boruta should be explored in further analysis. The results provided by our study are promising for further applications of this method in other livestock animals.

Genome-wide association study and inbreeding depression on body size traits in Qira black sheep (Ovis aries).

Qira black sheep is a famous indigenous sheep breed in China. The objectives of this study are to identify candidate genes related to body size, and to estimate the level of inbreeding depression on body size based on runs of homozygosity in Qira black sheep. Here, 188 adult Qira black sheep were genotyped with a high density (630 K) SNP chip and genome-wide association study for body weight and body size traits (including withers height, body slanting length, tail length, chest girth, chest width, and chest depth) were performed using an additive linear model. In consequence, 12 genome- and chromosome-wide significant SNPs and, accordingly, six candidate genes involved in muscle differentiation, metabolism and cell processes were identified. Of them, ZNF704 (zinc finger protein 704) was identified for body weight; AK2 (adenylate kinase 2) and PARK2 (parkin RBR E3 ubiquitin protein ligase) for tail length; MOCOS (molybdenum cofactor sulfurase) and ELP2 (elongator acetyltransferase complex subunit 2) for chest width; and MFAP1 (microfibril associated protein 1) for chest girth. Additionally, inbreeding depressions on body size were observed in the current herd. These results will provide insightful understandings into the genetic mechanisms of adult body size, and into the conservation and utilization of Qira black sheep.

Assessing the accuracy of imputation in the Gyr breed using different SNP panels.

The aim of this study was to evaluate the accuracy of imputation in a Gyr population using two medium-density panels (Bos taurus - Bos indicus) and to test whether the inclusion of the Nellore breed increases the imputation accuracy in the Gyr population. The database consisted of 289 Gyr females from Brazil genotyped with the GGP Bovine LDv4 chip containing 30 000 SNPs and 158 Gyr females from Colombia genotyped with the GGP indicus chip containing 35 000 SNPs. A customized chip was created that contained the information of 9109 SNPs (9K) to test the imputation accuracy in Gyr populations; 604 Nellore animals with information of LD SNPs tested in the scenarios were included in the reference population. Four scenarios were tested: LD9K_30KGIR, LD9K_35INDGIR, LD9K_30KGIR_NEL, and LD9K_35INDGIR_NEL. Principal component analysis (PCA) was computed for the genomic matrix and sample-specific imputation accuracies were calculated using Pearson's correlation (CS) and the concordance rate (CR) for imputed genotypes. The results of PCA of the Colombian and Brazilian Gyr populations demonstrated the genomic relationship between the two populations. The CS and CR ranged from 0.88 to 0.94 and from 0.93 to 0.96, respectively. Among the scenarios tested, the highest CS (0.94) was observed for the LD9K_30KGIR scenario. The present results highlight the importance of the choice of chip for imputation in the Gyr breed. However, the variation in SNPs may reduce the imputation accuracy even when the chip of the Bos indicus subspecies is used.

Using sequence variants of a QTL region improves the accuracy of genomic evaluation in French Saanen goats.

The enhanced availability of sequence data in livestock provides an opportunity for more accurate predictions in routine genomic evaluations. Such evaluations would therefore no longer rely only on the linkage disequilibrium between a chip marker and the causal mutation. The objective of this study was to assess the usefulness of sequence data in Saanen goats (n = 33) to better capture a quantitative trait locus (QTL) on chromosome 19 (CHI19) and improve the accuracy of predictions for 3 milk production traits, 5 type traits, and somatic cell scores. All 1,207 50K genotypes were imputed to the sequence level. Four scenarios, each using a subset of CHI19 imputed variants, were then tested. Sequence-derived information included all CHI19 variants (529,576), all variants in the QTL region (22,269), 178 variants selected in the QTL region and added to an updated chip, or 178 randomly selected variants on CHI19. Two genomic evaluation models were applied: single-step genomic BLUP and weighted single-step genomic BLUP. All scenarios were compared with single-step genomic BLUP using 50K genotypes. Best overall results were obtained using single-step genomic BLUP on 50K genotypes completed with all variants in the QTL region of chromosome 19 (6.2% average increase in accuracy for 9 traits) with the highest accuracy gain for fat yield (17.9%), significant increases for milk (13.7%) and protein yields (12.5%), and type traits associated with CHI19. Despite its association with the QTL region of chromosome 19, the somatic cell score showed decreased accuracy in every alternative scenario. Using all CHI19 variants led to an overall decrease of 4.8% in prediction accuracy. The updated chip was efficient and improved genomic evaluations by 3.1 to 6.4% on average, depending on the scenario. Indeed, information from only a few carefully selected variants increased accuracies for traits of interest when used in a single-step genomic BLUP model. In conclusion, using QTL region variants imputed from sequence data in single-step genomic evaluations represents a promising perspective for such evaluations in dairy goats. Furthermore, using only a limited number of selected variants in QTL regions, as available on SNP chip updates, significantly increases the accuracy for QTL-associated traits without deteriorating the evaluation accuracy for other traits. The latter approach is interesting, as it avoids time-consuming imputation and data formatting processes and provides reliable genotypes.

Tissue and species identification in minced meat and meat products from Italian commercial markets by DNA microarray and histological approach.

Adequate testing and adulterant detection of food products are required to assure its safety and avoid fraudulent activities. Adulteration/substitution of costlier meat with a cheaper or inferior meat is one of the most common fraudulence in meat industry. Aim of this study was to check the correct labelling of meat and ready to cook bovine meat products, combining the DNA microarray approach to identify the animal species with the histological examination, to check the composition and safety of meat. One hundred and one samples of bovine minced meat (Group 1) and ready to cook meat products (Group 2) were collected from supermarkets in Turin, Italy. DNA microarray revealed that 25.7% of samples were positive for species not declared on the label, swine being the most common. Histology showed the presence of cartilage, bone and glandular tissue. A higher presence of bacteria and inflammatory cells was detected in Group 1. Bacterial cells associated to inflammatory cells were detected with a higher score in Group 2. Sarcocystis spp. were present in 83.3% samples of Group 1 and 49.1% of Group 2. This study confirmed that the mislabelling of meat products is not uncommon. The combination of DNA microarrays and histology can increase the monitoring capacity in bovine meat industry.

Microarray-based detection of resistance genes in coagulase-negative staphylococci isolated from cattle and buffalo with mastitis in Egypt.

The present study aimed to provide a detailed characterization of coagulase-negative staphylococci (CoNS) isolated from cows and buffaloes with mastitis. The study included seventy-five CoNS isolates (60 came from cattle and 15 from buffaloes) originating from 68 individual quarters of 67 dairy cows (53 cattle and 14 buffaloes). The animals belonged to five different small holding dairy herds (n = 140 cows) that show clinical or subclinical mastitis. CoNS isolates were phenotypically characterized using MALDI-TOF-MS and were further genotypically characterized by microarray-based assays. Furthermore, the antimicrobial susceptibility of CoNS strains which carried the mecA gene was examined by broth microdilution. The occurrence of CoNS in the respective five herds was 10.5%, 14.7%, 14.8%, 12.8%, and 9.9%, with an average of 12.4%. Six different CoNS species were identified: S. sciuri (n = 37; 30 from cattle and 7 from buffaloes), S. chromogenes (n = 14; 8 from cattle and 6 from buffaloes), S. haemolyticus (n = 10; nine from cattle and one buffalo), S. xylosus (n = 10; nine from cattle and one buffalo), S. hyicus (n = 2), S. warneri (n = 1), and unidentified CoNS (n = 1). Twenty percent (20%) of CoNS isolates (17.3% of cattle origin) carried at least one antimicrobial resistance gene, while 4% of the isolate including two isolates of S. haemolyticus and one S. warneri of cattle origin carried the mecA gene and were phenotypically identified as methicillin-resistant strains. The genes detected were blaZ (16%), followed by tet(K) (8%), aacA-aphD (4%), aphA3 (2.6%), msr(A) (2.6%), [far1 (2.6%), and fusC (2.6%)], sat (2.6%), and cat (1.3%) conferring resistance to penicillin, tetracycline, gentamicin, neomycin/kanamycin, erythromycin, fusidic acid, streptothricin, and chloramphenicol, respectively. The majority of investigated CoNS strains displayed considerably low prevalence of resistance genes, while resistance to more than three antibiotics was found in S. haemolyticus and S. warneri. Implementing effective preventive measures is, therefore, important for limiting the transmission of CoNS, rather than using antibiotics to control mastitis in bovines.

Fine mapping genetic variants associated with age at puberty and sow fertility using SowPro90 genotyping array.

Sow fertility traits, such as litter size and the number of lifetime parities produced (reproductive longevity), are economically important. Selection for these traits is difficult because they are lowly heritable and expressed late in life. Age at puberty (AP) is an early indicator of reproductive longevity. Here, we utilized a custom Affymetrix single-nucleotide polymorphisms (SNPs) array (SowPro90) enriched with positional candidate genetic variants for AP and a haplotype-based genome-wide association study to fine map the genetic sources associated with AP and other fertility traits in research (University of Nebraska-Lincoln [UNL]) and commercial sow populations. Five major quantitative trait loci (QTL) located on four Sus scrofa chromosomes (SSC2, SSC7, SSC14, and SSC18) were discovered for AP in the UNL population. Negative correlations (r = -0.96 to -0.10; P < 0.0001) were observed at each QTL between genomic estimated breeding values for AP and reproductive longevity measured as lifetime number of parities (LTNP). Some of the SNPs discovered in the major QTL regions for AP were located in candidate genes with fertility-associated gene ontologies (e.g., P2RX3, NR2F2, OAS1, and PTPN11). These SNPs showed significant (P < 0.05) or suggestive (P < 0.15) associations with AP, reproductive longevity, and litter size traits in the UNL population and litter size traits in the commercial sows. For example, in the UNL population, when the number of favorable alleles of an SNP located in the 3' untranslated region of PTPN11 (SSC14) increased, AP decreased (P < 0.0001), while LTNP increased (P < 0.10). Additionally, a suggestive difference in the observed NR2F2 isoforms usage was hypothesized to be the source of the QTL for puberty onset mapped on SSC7. It will be beneficial to further characterize these candidate SNPs and genes to understand their impact on protein sequence and function, gene expression, splicing process, and how these changes affect the phenotypic variation of fertility traits.

DNA microarray-based characterization and antimicrobial resistance phenotypes of clinical MRSA strains from animal hosts.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of severe infections in humans and animals worldwide. Studies elucidating the population structure, staphylococcal cassette chromosome mec types, resistance phenotypes, and virulence gene profiles of animal-associated MRSA are needed to understand spread and transmission. OBJECTIVES: The objective of this study was to determine 1) clonal complexes and spa types, 2) resistance phenotypes, and 3) virulence/resistance gene profiles of MRSA isolated from animals in Switzerland. METHODS: We analyzed 31 presumptive MRSA isolates collected from clinical infections in horses, dogs, cattle, sheep, and pigs, which had tested positive in the Staphaurex Latex Agglutination Test. The isolates were characterized by spa typing and DNA microarray profiling. In addition, we performed antimicrobial susceptibility testing using the VITEK 2 Compact system. RESULTS: Characterization of the 31 presumptive MRSA isolates revealed 3 methicillin-resistant Staphylococcus pseudintermedius isolates, which were able to grow on MRSA2 Brilliance agar. Of the 28 MRSA isolates, the majority was assigned to CC398 (86%), but CC8 (11%) and CC1 (4%) were also detected. The predominant spa type was t011 (n = 23), followed by t009 (n = 2), t034 (n = 1), t008 (n = 1), and t127 (n = 1). CONCLUSIONS: The results of this study extend the current body of knowledge on the population structure, resistance phenotypes, and virulence and resistance gene profiles of MRSA from livestock and companion animals.

Application of multivariate single-step SNP best linear unbiased predictor model and revised SNP list for genomic evaluation of dairy cattle in Australia.

The objectives of this study were (1) to evaluate the computational feasibility of the multitrait test-day single-step SNP-BLUP (ssSNP-BLUP) model using phenotypic records of genotyped and nongenotyped animals, and (2) to compare accuracies (coefficient of determination; R2) and bias of genomic estimated breeding values (GEBV) and de-regressed proofs as response variables in 3 Australian dairy cattle breeds (i.e., Holstein, Jersey, and Red breeds). Additive genomic random regression coefficients for milk, fat, protein yield and somatic cell score were predicted in the first, second, and third lactation. The predicted coefficients were used to derive 305-d GEBV and were compared with the traditional parent averages obtained from a BLUP model without genomic information. Cow fertility traits were evaluated from the 5-trait repeatability model (i.e., calving interval, days from calving to first service, pregnancy diagnosis, first service nonreturn rate, and lactation length). The de-regressed proofs were only for calving interval. Our results showed that ssSNP-BLUP using multitrait test-day model increased reliability and reduced bias of breeding values of young animals when compared with parent average from traditional BLUP in Australian Holsten, Jersey, and Red breeds. The use of a custom selection of approximately 46,000 SNP (custom XT SNP list) increased the reliability of GEBV compared with the results obtained using the commercial Illumina 50K chip (Illumina, San Diego, CA). The use of the second preconditioner substantially improved the convergence rate of the preconditioned conjugate gradient method, but further work is needed to improve the efficiency of the computation of the Kronecker matrix product by vector. Application of ssSNP-BLUP to multitrait random regression models is computationally feasible.

Genome-wide association study of shank length and diameter at different developmental stages in chicken F2 resource population.

In order to find SNPs and genes affecting shank traits, we performed a GWAS in a chicken F2 population of eight half-sib families from five hatches derived from reciprocal crosses between an Arian fast-growing line and an Urmia indigenous slow-growing chicken. A total of 308 birds were genotyped using a 60K chicken SNP chip. Shank traits including shank length and diameter were measured weekly from birth to 12 weeks of age. A generalized linear model and a compressed mixed linear model (CMLM) were applied to achieve the significant regions. The value of the average genomic inflation factor (λ statistic) of the CMLM model (0.99) indicated that the CMLM was more effective than the generalized linear model in controlling the population structure. The genes surrounding significant SNPs and their biological functions were identified from NCBI, Ensembl and UniProt databases. The results indicated that 12 SNPs at 12 different ages passed the LD-adjusted 5% Bonferroni significant threshold. Two SNPs were significant for shank length and nine SNPs were significant for shank diameter. The significant SNPs were located near to or inside 11 candidate genes. The results showed that a number of significant SNPs in the middle ages were higher than the rest. The MXRA8 gene was related to the significant SNP at week 1 that promotes proliferation of growth plate chondrocytes. A unique SNP of Gga_rs16689511 located on chicken Z chromosome within the LOC101747628 gene was related to shank length at three different ages of birds (weeks 8, 9 and 11). The significant SNPs for shank diameter were found at weeks 4 and 7 (four and five SNPs respectively). The identifications of SNPs and genes here could contribute to a better understanding of the genetic control of shank traits in chicken.

Interest of using imputation for genomic evaluation in layer chicken.

With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values (GEBV) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits.

Evidence of distinct gene functional patterns in GC-poor and GC-rich isochores in Bos taurus.

Vertebrate genomes are mosaics of megabase-size DNA segments with a fairly homogeneous base composition, called isochores. They are divided into five families characterized by different guanine-cytosine (GC) levels and linked to several functional and structural properties. The increased availability of fully sequenced genomes allows the investigation of isochores in several species, assessing their level of conservation across vertebrate genomes. In this work, we characterized the isochores in Bos taurus using the ARS-UCD1.2 genome version. The comparison of our results with the well-studied human isochores and those of other mammals revealed a large conservation in isochore families, in number, average GC levels and gene density. Exceptions to the established increase in gene density with the increase in isochores (GC%) were observed for the following gene biotypes: tRNA, small nuclear RNA, small nucleolar RNA and pseudogenes that have their maximum number in H2 and H1 isochores. Subsequently, we assessed the ontology of all gene biotypes looking for functional classes that are statistically over- or under-represented in each isochore. Receptor activity and sensory perception pathways were significantly over-represented in L1 and L2 (GC-poor) isochores. This was also validated for the horse genome. Our analysis of housekeeping genes confirmed a preferential localization in GC-rich isochores, as reported in other species. Finally, we assessed the SNP distribution of a bovine high-density SNP chip across the isochores, finding a higher density in the GC-rich families, reflecting a potential bias in the chip, widely used for genetic selection and biodiversity studies.

A unified local objective function for optimally selecting SNPs on arrays for agricultural genomics applications.

Over the years, ad-hoc procedures were used for designing SNP arrays, but the procedures and strategies varied considerably case by case. Recently, a multiple-objective, local optimization (MOLO) algorithm was proposed to select SNPs for SNP arrays, which maximizes the adjusted SNP information (E score) under multiple constraints, e.g. on MAF, uniformness of SNP locations (U score), the inclusion of obligatory SNPs and the number and size of gaps. In the MOLO, each chromosome is split into equally spaced segments and local optima are selected as the SNPs having the highest adjusted E score within each segment, conditional on the presence of obligatory SNPs. The computation of the adjusted E score, however, is empirical, and it does not scale well between the uniformness of SNP locations and SNP informativeness. In addition, the MOLO objective function does not accommodate the selection of uniformly distributed SNPs. In the present study, we proposed a unified local function for optimally selecting SNPs, as an amendment to the MOLO algorithm. This new local function takes scalable weights between the uniformness and informativeness of SNPs, which allows the selection of SNPs under varied scenarios. The results showed that the weighting between the U and the E scores led to a higher imputation concordance rate than the U score or E score alone. The results from the evaluation of six commercial bovine SNP chips further confirmed this conclusion.

Transcriptome analyses of liver in newly-hatched chicks during the metabolic perturbation of fasting and re-feeding reveals THRSPA as the key lipogenic transcription factor.

BACKGROUND: The fasting-refeeding perturbation has been used extensively to reveal specific genes and metabolic pathways that control energy metabolism in the chicken. Most global transcriptional scans of the fasting-refeeding response in liver have focused on juvenile chickens that were 1, 2 or 4 weeks old. The present study was aimed at the immediate post-hatch period, in which newly-hatched chicks were subjected to fasting for 4, 24 or 48 h, then refed for 4, 24 or 48 h, and compared with a fully-fed control group at each age (D1-D4). RESULTS: Visual analysis of hepatic gene expression profiles using hierarchical and K-means clustering showed two distinct patterns, genes with higher expression during fasting and depressed expression upon refeeding and those with an opposing pattern of expression, which exhibit very low expression during fasting and more abundant expression with refeeding. Differentially-expressed genes (DEGs), identified from five prominent pair-wise contrasts of fed, fasted and refed conditions, were subjected to Ingenuity Pathway Analysis. This enabled mapping of analysis-ready (AR)-DEGs to canonical and metabolic pathways controlled by distinct gene interaction networks. The largest number of hepatic DEGs was identified by two contrasts: D2FED48h/D2FAST48h (968 genes) and D2FAST48h/D3REFED24h (1198 genes). The major genes acutely depressed by fasting and elevated upon refeeding included ANGTPL, ATPCL, DIO2, FASN, ME1, SCD, PPARG, SREBP2 and THRSPA-a primary lipogenic transcription factor. In contrast, major lipolytic genes were up-regulated by fasting or down-regulated after refeeding, including ALDOB, IL-15, LDHB, LPIN2, NFE2L2, NR3C1, NR0B1, PANK1, PPARA, SERTAD2 and UPP2. CONCLUSIONS: Transcriptional profiling of liver during fasting/re-feeding of newly-hatched chicks revealed several highly-expressed upstream regulators, which enable the metabolic switch from fasted (lipolytic/gluconeogenic) to fed or refed (lipogenic/thermogenic) states. This rapid homeorhetic shift of whole-body metabolism from a catabolic-fasting state to an anabolic-fed state appears precisely orchestrated by a small number of ligand-activated transcription factors that provide either a fasting-lipolytic state (PPARA, NR3C1, NFE2L2, SERTAD2, FOX01, NR0B1, RXR) or a fully-fed and refed lipogenic/thermogenic state (THRSPA, SREBF2, PPARG, PPARD, JUN, ATF3, CTNNB1). THRSPA has emerged as the key transcriptional regulator that drives lipogenesis and thermogenesis in hatchling chicks, as shown here in fed and re-fed states.

Rapid detection of deformed wing virus in honeybee using ultra-rapid qPCR and a DNA-chip.

Fast and accurate detection of viral RNA pathogens is important in apiculture. A polymerase chain reaction (PCR)-based detection method has been developed, which is simple, specific, and sensitive. In this study, we rapidly (in 1 min) synthesized cDNA from the RNA of deformed wing virus (DWV)-infected bees (Apis mellifera), and then, within 10 min, amplified the target cDNA by ultra-rapid qPCR. The PCR products were hybridized to a DNA-chip for confirmation of target gene specificity. The results of this study suggest that our method might be a useful tool for detecting DWV, as well as for the diagnosis of RNA virus-mediated diseases on-site.

Value of sharing cow reference population between countries on reliability of genomic prediction for milk yield traits.

Increasing the reliability of genomic prediction (GP) of economic traits in the pasture-based dairy production systems of New Zealand (NZ) and Australia (AU) is important to both countries. This study assessed if sharing cow phenotype and genotype data of NZ and AU improves the reliability of GP for NZ bulls. Data from approximately 32,000 NZ genotyped cows and their contemporaries were included in the May 2018 routine genetic evaluation of the Australian Dairy cattle in an attempt to provide consistent phenotypes for both countries. After the genetic evaluation, deregressed proofs of cows were calculated for milk yield traits. The April 2018 multiple across-country evaluation of Interbull was also used to calculate deregressed proofs for bulls on the NZ scale. Approximately 1,178 Jersey (Jer) and 6,422 Holstein (Hol) bulls had genotype and phenotype data. In addition to NZ cows, phenotype data of close to 60,000 genotyped Australian (AU) cows from the same genetic evaluation run as NZ cows were used. All AU and NZ females were genotyped using low-density SNP chips (<10K SNP) and were imputed first to 50K and then to ∼600K (referred to as high density; HD). We used up to 98,000 animals in the reference populations, both by expanding the NZ reference set (cow, bull, single breed to multi-breed set) and by adding AU cows. Reliabilities of GP were calculated for 508 Jer and 1,251 Hol bulls whose sires are not included in the reference set (RS) to ensure that real differences are not masked by close relationships. The GP was tested using 50K or high-density SNP chip using genomic BLUP in bivariate (considering country as a trait) or single trait models. The RS that gave the highest reliability for each breed were also tested using a hybrid GP method that combines expectation maximization with Bayes R. The addition of the AU cows to an NZ RS that included either NZ cows only, or cows and bulls, improved the reliability of GP for both NZ Hol and Jer validation bulls for all traits. Using single breed reference populations also increased reliability when NZ crossbred cows were added to reference populations that included only purebred NZ bulls and cows and AU cows. The full multi-breed RS (all NZ cows and bulls and AU cows) provided similar reliabilities in NZ Hol bulls, when compared with the single breed reference with crossbred NZ cows. For Jer validation bulls, the RS that included Jer cows and bulls and crossbred cows from NZ and Jer cows from AU was marginally better than the all-breed, all-country RS. In terms of reliability, the advantage of the HD SNP chip was small but captured more of the genomic variance than the 50K, particularly for Hol. The expectation maximization Bayes R GP method was slightly (up to 3 percentage points) better than genomic BLUP. We conclude that GP of milk production traits in NZ bulls improves by up to 7 percentage points in reliability by expanding the NZ reference population to include AU cows.