First genome-wide CNV mapping in FELIS CATUS using next generation sequencing data.

BACKGROUND: Copy Number Variations (CNVs) have becoming very significant variants, representing a major source of genomic variation. CNVs involvement in phenotypic expression and different diseases has been widely demonstrated in humans as well as in many domestic animals. However, genome wide investigation on these structural variations is still missing in Felis catus. The present work is the first CNV mapping from a large data set of Next Generation Sequencing (NGS) data in the domestic cat, performed within the 99 Lives Consortium. RESULTS: Reads have been mapped on the reference assembly_6.2 by Maverix Biomics. CNV detection with cn.MOPS and CNVnator detected 592 CNVs. These CNVs were used to obtain 154 CNV Regions (CNVRs) with BedTools, including 62 singletons. CNVRs covered 0.26% of the total cat genome with 129 losses, 19 gains and 6 complexes. Cluster Analysis and Principal Component Analysis of the detected CNVRs showed that breeds tend to cluster together as well as cats sharing the same geographical origins. The 46 genes identified within the CNVRs were annotated. CONCLUSION: This study has improved the genomic characterization of 14 cat breeds and has provided CNVs information that can be used for studies of traits in cats. It can be considered a sound starting point for genomic CNVs identification in this species.

Few mitochondrial DNA sequences are inserted into the turkey (Meleagris gallopavo) nuclear genome: evolutionary analyses and informativity in the domestic lineage.

Mitochondrial DNA (mtDNA) insertions have been detected in the nuclear genome of many eukaryotes. These sequences are pseudogenes originated by horizontal transfer of mtDNA fragments into the nuclear genome, producing nuclear DNA sequences of mitochondrial origin (numt). In this study we determined the frequency and distribution of mtDNA-originated pseudogenes in the turkey (Meleagris gallopavo) nuclear genome. The turkey reference genome (Turkey_2.01) was aligned with the reference linearized mtDNA sequence using last. A total of 32 numt sequences (corresponding to 18 numt regions derived by unique insertional events) were identified in the turkey nuclear genome (size ranging from 66 to 1415 bp; identity against the modern turkey mtDNA corresponding region ranging from 62% to 100%). Numts were distributed in nine chromosomes and in one scaffold. They derived from parts of 10 mtDNA protein-coding genes, ribosomal genes, the control region and 10 tRNA genes. Seven numt regions reported in the turkey genome were identified in orthologues positions in the Gallus gallus genome and therefore were present in the ancestral genome that in the Cretaceous originated the lineages of the modern crown Galliformes. Five recently integrated turkey numts were validated by PCR in 168 turkeys of six different domestic populations. None of the analysed numts were polymorphic (i.e. absence of the inserted sequence, as reported in numts of recent integration in other species), suggesting that the reticulate speciation model is not useful for explaining the origin of the domesticated turkey lineage.

Genomic variability in Mexican chicken population using copy number variants.

BACKGROUND: Copy number variations are genome polymorphism that influence phenotypic variation and are an important source of genetic variation in populations. The aim of this study was to investigate genetic variability in the Mexican Creole chicken population using CNVs. RESULTS: The Hidden Markov Model of the PennCNV software detected a total of 1924 CNVs in the genome of the 256 samples processed with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix). The mapped CNVs comprised 1538 gains and 386 losses, resulting at population level in 1216 CNV regions (CNVRs), of which 959 gains, 226 losses and 31 complex (i.e. containing both losses and gains). The CNVRs covered a total of 47 Mb of the whole genome sequence length, corresponding to 5.12% of the chicken galGal4 autosome assembly. CONCLUSIONS: This study allowed a deep insight into the structural variation in the genome of unselected Mexican chicken population, which up to now has not been genetically characterized. The genomic study disclosed that the population, even if presenting extreme morphological variation, cannot be organized in differentiated genetic subpopulations. Finally this study provides a chicken CNV map based on the 600 K SNP chip array jointly with a genome-wide gene copy number estimates in a native unselected for more than 500 years chicken population.

Genome-wide association study for milk somatic cell score in holstein cattle using copy number variation as markers.

Mastitis, the most common and expensive disease in dairy cows, implies significant losses in the dairy industry worldwide. Many efforts have been made to improve genetic mastitis resistance in dairy populations, but low heritability of this trait made this process not as effective as desired. The purpose of this study was to identify genomic regions explaining genetic variation of somatic cell count using copy number variations (CNVs) as markers in the Holstein population, genotyped with the Illumina BovineHD BeadChip. We found 24 and 47 copy number variation regions significantly associated with estimated breeding values for somatic cell score (SCS_EBVs) using SVS 8.3.1 and PennCNV-CNVRuler software, respectively. The association analysis performed with these two software allowed the identification of 18 candidate genes (TERT, NOTCH1, SLC6A3, CLPTM1L, PPARα, BCL-2, ABO, VAV2, CACNA1S, TRAF2, RELA, ELF3, DBH, CDK5, NF2, FASN, EWSR1 and MAP3K11) that result classified in the same functional cluster. These genes are also part of two gene networks, whose genes share the 'stress', 'cell death', 'inflammation' and 'immune response' GO terms. Combining CNV detection/association analysis based on two different algorithms helps towards a more complete identification of genes linked to phenotypic variation of the somatic cell count.

Quantitative trait loci mapping for conjugated linoleic acid, vaccenic acid and ∆(9) -desaturase in Italian Brown Swiss dairy cattle using selective DNA pooling.

A selective DNA pooling approach was applied to identify QTL for conjugated linoleic acid (CLA), vaccenic acid (VA) and Δ(9) -desaturase (D9D) milk content in Italian Brown Swiss dairy cattle. Milk samples from 60 animals with higher values (after correction for environmental factors) and 60 animals with lower values for each of these traits from each of five half-sib families were pooled separately. The pools were genotyped using the Illumina BovineSNP50 BeadChip. Sire allele frequencies were compared between high and low tails at the sire and marker level for SNPs for which the sires were heterozygous. An r procedure was implemented to perform data analysis in a selective DNA pooling design. A correction for multiple tests was applied using the proportion of false positives among all test results. BTA 19 showed the largest number of markers in association with CLA. Associations between SNPs and the VA and Δ(9) -desaturase traits were found on several chromosomes. A bioinformatics survey identified genes with an important role in pathways for milk fat and fatty acids metabolism within 1 Mb of SNP markers associated with fatty acids contents.

A Phase II, randomized, double-blind study of zibotentan (ZD4054) in combination with carboplatin/paclitaxel versus placebo in combination with carboplatin/paclitaxel in patients with advanced ovarian cancer sensitive to platinum-based chemotherapy (AGO-OVAR 2.14).

BACKGROUND: In platinum-sensitive relapsed ovarian cancer, paclitaxel plus carboplatin is a standard second-line treatment. Zibotentan (ZD4054) is an oral, specific ETA-receptor antagonist with demonstrated antitumour activity in xenograft models of human ovarian cancer. METHODS: In this Phase II, randomized, placebo-controlled study, patients with relapsed ovarian cancer sensitive to platinum-based chemotherapy received zibotentan 10mg or placebo once-daily, plus paclitaxel 175 mg/m(2) iv followed by carboplatin iv (AUC 5) on day 1 of every 3-week cycle for a maximum of eight cycles. The primary endpoint was progression-free survival (PFS), evaluated by Response Evaluation Criteria In Solid Tumours (RECIST). Secondary and exploratory endpoints included objective tumour response rate, tumour size, CA-125/RECIST progression, and safety and tolerability. RESULTS: A total of 120 patients were randomized (zibotentan: n=59; placebo: n=61). Addition of zibotentan 10mg/day to carboplatin and paclitaxel did not improve PFS compared with placebo (median PFS, 7.6 versus 10.0 months, respectively; HR=1.46, [80% CI: 1.10-1.94]; P=0.0870). No improvements in any of the secondary or exploratory efficacy endpoints were observed for patients receiving zibotentan compared with placebo. Median duration of total treatment exposure was 6.7 months. Total chemotherapy dose received was lower for zibotentan-treated versus placebo-treated patients (carboplatin: -16%; paclitaxel: -14%). The most common adverse events in the zibotentan arm were anaemia, nausea, alopecia, headache and neutropenia (43-48% of patients). CONCLUSIONS: Zibotentan 10mg/day plus carboplatin and paclitaxel did not result in an improvement in PFS compared with chemotherapy alone in patients with advanced ovarian cancer sensitive to platinum-based chemotherapy. No unexpected safety concerns were identified.

A whole genome scan for QTL affecting milk protein percentage in Italian Holstein cattle, applying selective milk DNA pooling and multiple marker mapping in a daughter design.

We report on a complete genome scan for quantitative trait loci (QTL) affecting milk protein percentage (PP) in the Italian Holstein-Friesian cattle population, applying a selective DNA pooling strategy in a daughter design. Ten Holstein-Friesian sires were chosen, and for each sire, about 200 daughters, each from the high and low tails of estimated breeding value for PP, were used to construct milk DNA pools. Sires and pools were genotyped for 181 dinucleotide microsatellites covering all cattle autosomes. Sire marker allele frequencies in the pools were obtained by shadow correction of peak height in the electropherograms. After quality control, pool data from eight sires were used for all subsequent analyses. The QTL heterozygosity estimate was lower than that of similar studies in other cattle populations. Multiple marker mapping identified 19 QTL located on 14 chromosomes (BTA1, 2, 3, 4, 5, 6, 8, 9, 12, 14, 17, 20, 23 and 27). The sires were also genotyped for seven polymorphic sites in six candidate genes (ABCG2, SPP1, casein kappa, DGAT1, GHR and PRLR) located within QTL regions of BTA6, 14 and 20 found in this study. The results confirmed or excluded the involvement of some of the analysed markers as the causative polymorphic sites of the identified QTL. The QTL identified, combined with genotype data of these candidate genes, will help to identify other quantitative trait genes and clarify the complex QTL patterns observed for a few chromosomes. Overall, the results are consistent with the Italian Holstein population having been under long-term selection for high PP.

Genetic evaluations for measures of the milk-flow curve in the Italian Brown Swiss population.

The objective of this study was to estimate heritabilities and genetic correlations between milk-release parameters, somatic cell score, milk yield, and udder functional traits in the Italian Brown Swiss population. Data were available from 37,511 cows over a span of 12 yr (1997-2008) from 1,592 herds. Milking flows were recorded for each individual once during lactation. Three different analyses were performed to estimate variance components for all the traits of interest. The first analysis included single control data milk yield, somatic cell score, maximum milk flow, average milk flow, time of plateau, decreasing time, and total milking time, whereas the second analysis included milk-release parameters as well as total udder score, udder depth, and 305-d milk yield and somatic cell score as dependent variables. The third analysis included total milking time, 305-d milk yield and somatic cell score, total udder score, udder depth, and ratios of maximum milk flow over total milking time (R1), time of plateau (R2), and decreasing time (R3) to estimate the relationship between the shape of the milk-release curves and important milking traits. Results from the first and second analysis found similar heritabilities for milkability traits ranging from 0.05 to 0.41 with genetic correlations between production traits and flow traits ranging from low to moderate values. Positive genetic correlations were found among production, somatic cell score, and milkability traits. The third analysis showed that R1 had the greatest heritability of the ratio traits (0.37) with large genetic correlations with R2 and R3, a low correlation with 305-d somatic cell score, and no correlation with 305-d milk yield. Estimated responses to selection over 5 generations were also calculated using different indexes, which included either flow or ratio traits. The results of this study show that it is possible to use information collected through portable flowmeters to improve milkability traits. Using a set of variables or traits to describe the overall release of milk can be an advantageous selection strategy to decrease management costs while maintaining milk production.

Bimodality and the genetics of milk flow traits in the Italian Holstein-Friesian breed.

The overall goal of this study was to investigate milk flow traits in Italian Holstein-Friesian cows and, in particular, the bimodality of milk flow, defined as delayed milk ejection at the start of milking. Using a milkometer, 2,886 records were collected from 133 herds in northern Italy from 2001 to 2007. All records included 5 time-period measurements for milk flow, somatic cell score (SCS), milk yield, 8 udder type traits, and the presence or absence of bimodality in milk flow. Genetic parameters were estimated using linear animal models for continuous traits such as milk flow, udder type, SCS, and milk production, whereas bimodality was analyzed as a categorical trait. With the exception of decreasing time (which had a very small heritability value of 0.06), heritability values for milk flow traits were moderate, ranging from 0.10 (ascending time) to 0.41 (maximum milk flow). In addition, moderate to high genetic correlations were estimated between total milking time and other time measures (from 0.78 to 0.87), and among time flow traits (from 0.62 to 0.91). The decreasing time was the trait most genetically correlated with udder type traits, with correlation values of 0.92 with rear udder height, 0.85 with rear udder width, and 0.73 with teat placement. Large udders with strong attachments were also associated with greater milk production. Heritability estimated for bimodality was 0.43, and its genetic correlation with milk flow traits and SCS indicated a sizable genetic component underlying this trait. Bimodality was negatively associated with milk production; shorter milking times and greater peak milk levels were genetically correlated with more frequent bimodal flows, indicating that faster milk release would result in an increase in bimodal patterns. The negative genetic correlation of bimodality with SCS (-0.30) and the genetic correlation between milk flow traits and SCS suggest that the relationship between milkability and SCS is probably nonlinear and that intermediate flow rates are optimal with respect to mastitis susceptibility. Quicker milk flow over a shorter period would increase the frequency of bimodal curves in milking, whereas the correlation between bimodality and both ascending and descending time was less clear.

MicroRNA-based signatures impacting clinical course and biology of ovarian cancer: a miRNOmics study.

BACKGROUND: In Western countries, ovarian cancer (OC) still represents the leading cause of gynecological cancer-related deaths, despite the remarkable gains in therapeutical options. Novel biomarkers of early diagnosis, prognosis definition and prediction of treatment outcomes are of pivotal importance. Prior studies have shown the potentials of micro-ribonucleic acids (miRNAs) as biomarkers for OC and other cancers. METHODS: We focused on the prognostic and/or predictive potential of miRNAs in OC by conducting a comprehensive array profiling of miRNA expression levels in ovarian tissue samples from 17 non-neoplastic controls, and 60 tumor samples from OC patients treated at the Regina Elena National Cancer Institute (IRE). A set of 54 miRNAs with differential expression in tumor versus normal samples (T/N-deregulated) was identified in the IRE cohort and validated against data from the Cancer Genoma Atlas (TCGA) related to 563 OC patients and 8 non-neoplastic controls. The prognostic/predictive role of the selected 54 biomarkers was tested in reference to survival endpoints and platinum resistance (P-res). RESULTS: In the IRE cohort, downregulation of the 2 miRNA-signature including miR-99a-5p and miR-320a held a negative prognostic relevance, while upregulation of miR-224-5p was predictive of less favorable event free survival (EFS) and P-res. Data from the TCGA showed that downregulation of 5 miRNAs, i.e., miR-150, miR-30d, miR-342, miR-424, and miR-502, was associated with more favorable EFS and overall survival outcomes, while miR-200a upregulation was predictive of P-res. The 9 miRNAs globally identified were all included into a single biologic signature, which was tested in enrichment analysis using predicted/validated miRNA target genes, followed by network representation of the miRNA-mRNA interactions. CONCLUSIONS: Specific dysregulated microRNA sets in tumor tissue showed predictive/prognostic value in OC, and resulted in a promising biological signature for this disease.

Extensive long-range and nonsyntenic linkage disequilibrium in livestock populations: deconstruction of a conundrum.

Great interest was aroused by reports, based on microsatellite markers, of high levels of statistically significant long-range and nonsyntenic linkage disequilibrium (LD) in livestock. Simulation studies showed that this could result from population family structure. In contrast, recent SNP-based studies of livestock populations report much lower levels of LD. In this study we show, on the basis of microsatellite data from four cattle populations, that high levels of long-range LD are indeed obtained when using the multi-allelic D' measure of LD. Long-range and nonsyntenic LD are exceedingly low, however, when evaluated by the standardized chi-square measure of LD, which stands in relation to the predictive ability of LD. Furthermore, specially constructed study populations provided no evidence for appreciable LD resulting from family structure at the grandparent level. We propose that the high statistical significance and family structure effects observed in the earlier studies are due to the use of large sample sizes, which accord high statistical significance to even slight deviations from asymptotic expectations under the null hypothesis. Nevertheless, even after taking sample size into account, our results indicate that microsatellites testify to the presence of usable LD at considerably wider separation distances than SNPs, suggesting that use of SNP haplotypes may considerably increase the usefulness of a given fixed SNP array.

A genome scan for quantitative trait loci affecting milk somatic cell score in Israeli and Italian Holstein cows by means of selective DNA pooling with single- and multiple-marker mapping.

Mastitis is an important and common dairy cattle disease affecting milk yield, quality, and consumer safety as well as cheese yields and quality. Animal welfare and residues of the antibiotics used to treat mastitis cause public concern. Considerable genetic variation may allow selection for increased resistance to mastitis. Because of high genetic correlation to milk somatic cell score (SCS), SCS can serve as a surrogate trait for mastitis resistance. The present study intended to identify quantitative trait loci (QTL) affecting SCS in Israeli and Italian Holstein dairy cattle (IsH and ItH, respectively), using selective DNA pooling with single and multiple marker mapping. Milk samples of 4,788 daughters of 6 IsH and 7 ItH sires were used to construct sire-family high- and low-tail pools, which were genotyped at 123 (IsH) and 133 (ItH) microsatellite markers. Shadow correction was used to obtain pool allele frequency estimates. Frequency difference between the tails and empirical standard error of D, SE(D), were used to obtain P-values. All markers significant by single marker mapping were also significant by multiple marker mapping, but not vice versa. Combining both populations, 22 QTL on 21 chromosomes were identified; all corresponded to previous reports in the literature. Confidence intervals were set by chi-squared drop method. Heterozygosity of QTL was estimated at 44.2%. Allele substitution effects ranged from 1,782 to 4,930 cells/mL in estimated breeding value somatic cell count units. Most (80%) of the observed variation in estimated breeding value somatic cell score could be explained by the QTL identified under the stringent criteria. The results found here can be used as a basis for further genome-wide association studies for the same trait.

Whole-genome scan for quantitative trait loci associated with birth weight, gestation length and passive immune transfer in a Holstein x Jersey crossbred population.

We herein report results from a daughter design genome-scan study aiming to identify quantitative trait loci (QTL) associated with birth weight, direct gestation length and passive immune transfer in a backcross (Holstein x Jersey) x Holstein population. Two-hundred and seventy-six calves, offspring of seven crossbred sires, were genotyped for 161 microsatellite markers distributed along the 29 bovine autosomes. The genome scan was performed through interval mapping using an animal model in order to identify QTL accounting for phenotypic differences between individual animals. Based on significant chi-squared values, we identified putative QTL on BTA7 and BTA14 for gestation length, on BTA2, BTA6 and BTA14 for birth weight and on BTA20 for passive immune transfer. In total, these QTL accounted for 12%, 18% and 1% of the phenotypic variance in gestation length, birth weight and passive immune transfer respectively. We also report results from a supplementary and independent influential grand-daughter Holstein family. In this family, findings on BTA7 and BTA14 for direct gestation length were in agreement with results in the crossbred population. Two other regions on BTA6 and BTA21 putatively underlying QTL for direct gestation length variability were discovered with this analysis.

Expected effects on protein yield of marker-assisted selection at quantitative trait loci affecting milk yield and milk protein percentage.

Protein yield (PY) is currently the major economic product of the dairy herd. Genome-wide scans for quantitative trait loci (QTL) affecting milk yield (MY) and milk protein percentage (PP) suggest that of the loci affecting the 2 traits, about 1/4 exclusively affect MY, 1/4 exclusively affect PP, and half affect both traits. Because PY is the product of MY and PP, it is of interest to evaluate the expected effects on PY of marker-assisted selection (MAS) applied to these 3 classes of QTL. It is clear that selection for the appropriate allele at QTL exclusively affecting MY or PP will have a positive effect on PY. The question arises as to the effect of MAS directed at QTL affecting both MY and PP. Because the observed genetic correlation of about -0.5 between MY and PP must be generated by these loci, and because they comprise about half the total number of loci affecting the 2 traits, it can be inferred that the genetic correlation between MY and PP at loci affecting both traits is close to -1.0. This seems to imply that generally such loci would be neutral in their effects on PY. In the present study, biometrical expressions originally developed to describe the relationships of MY, fat percentage, and fat yield were adapted to describe the relationships of MY, PP, and PY. The resultant expressions were validated by showing that they correctly predicted the observed phenotypic standard deviation and heritability of PY, and the vastly different genetic correlations of PY with MY (very high positive) and of PY with PP (very low positive). Contrary to initial impressions, further biometrical analysis of the projected effects on PY of MAS at the loci affecting both traits, showed that even under the assumption that the genetic correlation between MY and PP at these loci is -1.0, selection for the allele favoring MY will have a strong positive effect on PY, whereas selection for the allele favoring PP will have an equal but opposite negative effect on PY. These diametrically opposed effects are due to the lower genetic coefficient variation of PP compared with MY. It is speculated that the reduced coefficient of variation of PP may be because of more stringent homeostatic buffering of milk composition compared with milk yield.

Effects of clustering herds with small-sized contemporary groups in dairy cattle genetic evaluations.

Most test-day models used in genetic evaluations of dairy cattle define contemporary groups (CG) as the herd-test-date effect. Fitting this effect as fixed may minimize prediction bias, but requires a minimum number of observations per CG to simultaneously maximize the effective number of observations and minimize the residual error and prediction error variance. Nearly 4 million test-day records from the Portuguese Holstein database of 238,271 cows calving in 1,330 herds from 1994 through 2006 were used to evaluate the effect of clustering CG from small herds based on the similarity of their production environments. Principal component analysis was used to summarize 14 descriptive variables in 5 eigenvectors that explained 88% of the total variation. Based on the distance matrix, 2 different approaches were applied to group the herds. For each approach, 4 data sets were built having at least 3, 5, 10, or 15 observations per CG, respectively. For the data sets of group A, all herds, with or without the required number of observations per CG, were used in the clustering process. For the data sets of group B, only herds without the minimum number of observations were candidates to form clusters. All data sets were analyzed by an autoregressive test-day animal model fitting a fixed herd test date in a multiple-lactation setting, and results were compared with the current clustering procedure used in the Portuguese genetic evaluations. The data set from group B, with a minimum of 3 records per CG, was the one that provided the highest accuracy of prediction and the smaller within-CG variance, revealing a better fit for the data. This procedure also preserved the original herd structure of the database, better maximizing the number of herd groups. Correlations among EBV, rank, prediction error variance, and accuracies of prediction for this data set were high (0.97, 0.97, 0.85, and 0.82, respectively), suggesting that no major reranking is to be expected.

Genetic correlation patterns between somatic cell score and protein yield in the Italian Holstein-Friesian population.

Genetic parameters for somatic cell score (SCS) in the Italian Holstein-Friesian population were estimated addressing the pattern of genetic correlation with protein yield in different parities (first, second, and third) and on different days in milk within each parity. Three approaches for parameter estimation were applied using random samples of herds from the national database of the Italian Holstein Association. Genetic correlations for lactation measures (305-d protein yield and lactation SCS) were positive in the first parity (0.31) and close to zero in the second (0.01) and third (0.09) parities. These results indicated that larger values of SCS were genetically associated with increased production. The second and third sets of estimates were based on random regression test-day models, modeling the shape of lactation curve with the Wilmink function and fourth-order Legendre polynomials, respectively. Genetic correlations from both random regression models showed a specific pattern associated with days in milk within and across parities. Estimates varied from positive to negative in the first and second parity, and from null to negative in the third parity. Patterns were similar for both random regression models. The average overall correlation between SCS and protein yield was zero or slightly positive in the first lactation and ranged from zero to negative in later lactations. Correlation estimates differed by parity and stage of lactation. They also demonstrated the dubiousness of applying a single genetic correlation measure between SCS and protein in setting selection strategies. Differences in magnitude and the sign of genetic correlations between SCS and yields across and within parities should be accounted for in selection schemes.

Quantitative trait loci affecting milk yield and protein percentage in a three-country Brown Swiss population.

Quantitative trait loci (QTL) mapping projects have been implemented mainly in the Holstein dairy cattle breed for several traits. The aim of this study is to map QTL for milk yield (MY) and milk protein percent (PP) in the Brown Swiss cattle populations of Austria, Germany, and Italy, considered in this study as a single population. A selective DNA pooling approach using milk samples was applied to map QTL in 10 paternal half-sib daughter families with offspring spanning from 1,000 to 3,600 individuals per family. Three families were sampled in Germany, 3 in Italy, 1 in Austria and 3 jointly in Austria and Italy. The pools comprised the 200 highest and 200 lowest performing daughters, ranked by dam-corrected estimated breeding value for each sire-trait combination. For each tail, 2 independent pools, each of 100 randomly chosen daughters, were constructed. Sire marker allele frequencies were obtained by densitometry and shadow correction analyses of 172 genome-wide allocated autosomal markers. Particular emphasis was placed on Bos taurus chromosomes 3, 6, 14, and 20. Marker association for MY and PP with a 10% false discovery rate resulted in nominal P-values of 0.071 and 0.073 for MY and PP, respectively. Sire marker association tested at a 20% false discovery rate (within significant markers) yielded nominal P-values of 0.031 and 0.036 for MY and PP, respectively. There were a total of 36 significant markers for MY, 33 for PP, and 24 for both traits; 75 markers were not significant for any of the traits. Of the 43 QTL regions found in the present study, 10 affected PP only, 8 affected MY only, and 25 affected MY and PP. Remarkably, all 8 QTL regions that affected only MY in the Brown Swiss, also affected MY in research reported in 3 Web-based QTL maps used for comparison with the findings of this study (http://www.vetsci.usyd.edu.au/reprogen/QTL_Map/; http://www.animalgenome.org/QTLdb/cattle.html; http://bovineqtl.tamu.edu/). Similarly, all 10 QTL regions in the Brown Swiss that affected PP only, affected only PP in the databases. Thus, many QTL appear to be common to Brown Swiss and other breeds in the databases (mainly Holstein), and an appreciable fraction of QTL appears to affect MY or PP primarily or exclusively, with little or no effect on the other trait. Although QTL information available today in the Brown Swiss population can be utilized only in a within family marker-assisted selection approach, knowledge of QTL segregating in the whole population should boost gene identification and ultimately the implementation and efficiency of an individual genomic program.

Looking at genetic structure and selection signatures of the Mexican chicken population using single nucleotide polymorphism markers.

Genetic variation enables both adaptive evolutionary changes and artificial selection. Genetic makeup of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems. The aim of this study was to characterize the genetic variability of México's chicken population to reveal any underlying population structure. A total of 213 chickens were sampled in different rural production units located in 25 states of México. Genotypes were obtained using the Affymetrix Axiom® 600 K Chicken Genotyping Array. The Identity by Descent (IBD) and the principal components analysis (PCA) were performed by SVS software on pruned single nucleotide polymorphisms (SNPs).ADMIXTURE analyses identified 3 ancestors and the proportion of the genetic contribution of each of them has been determined in each individual. The results of the Neighbor-Joining (NJ) analysis resulted consistent with those obtained by the PCA. All methods utilized in this study did not allow a classification of Mexican chicken in distinct clusters or groups. A total of 3,059 run of homozygosity (ROH) were identified and, being mainly short in length (<4 Mb), these regions are indicative of a low inbreeding level in the population. Finally, findings from the ROH analysis indicated the presence of natural selective pressure in the population of Mexican chicken.The study indicates that the Mexican chicken clearly appear to be a unique creole chicken population that was not subjected to a specific artificial selection. Results provide a genetic knowledge that can be used as a basis for the genetic management of a unique and very large creole population, especially in the view of using it in production of hybrids to increase the productivity and economic revenue of family farming agriculture, which is widely present in México.

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds.

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.

Comparing local and commercial breeds on functional traits and profitability: the case of Reggiana dairy cattle.

The objective of this study was to compare fertility, longevity, milkability, and profitability of cows from the Reggiana and Holstein breeds in northern Italy. Profitability was gauged for each breed, with consideration of economic incentive programs and alternative milk pricing scenarios. Calving to first service interval, days open, and calving interval were significantly shorter in Reggiana than in Holstein cows. Reggiana cows conceived approximately one estrus cycle before Holstein and had a calving interval 33 d shorter. Holstein cows released a significantly higher quantity of milk per unit of time (1.81 vs. 1.28 kg/min). Reggiana cows had longer expected total and productive lives than Holstein cows, by 5.8 and 10.0 mo, respectively. Replacement rate was 26% higher in the Holstein. Standard 305-d milk production was 5,360 and 7,870 kg in Reggiana and Holstein, respectively. Comparing breeds on annual milk and meat production, instead of standard 305-d milk yield, changed marginally the difference in annual profitability between the Reggiana and Holstein, from -696 euros to -679 euros per cow per year. Including feeding, milking, replacement, and insemination costs reduced the gap between breeds by 32%, from -679 euros, measured on annual milk and meat production, to -460 euros. These differences in profitability assumed a pricing scenario referring to milk sold to the dairy industry where protein and fat contents are valued but not the breed origin of milk. Incentive payments to farmers of endangered cattle compensated partially (22%) the lower income from Reggiana cows. When Reggiana milk production was sold as branded Parmigiano Reggiano cheese, Reggiana cows were more profitable than Holstein cows by 1,953 euros per cow per year.