Effect of calving age on genetic evaluation of milk yield in Holstein cattle.

The aim of this study was to evaluate the effect of including calving age (CA) on genetic evaluation models for Holstein cattle. The evaluated models included the permanent environment, the sire-herd interactions, and the animals and residual effects as random. The fixed effects included the average production of milk, fat, and protein and the herd-year-season effect. The analyzed data included 603,521 records of milk production (in kg) corresponding to 438,098 animals from 527 herds. Additionally, there were 179,122 records of fat and protein components, corresponding to 148,930 animals from 137 herds. The records were classified by first lactation only (FL) and all available lactations (AL) for validation test (VT). The FL records corresponded to 275,487 milk production records with a mean of 10,874.1 ± 2773.9 kg at a mean CA of 25.6 ± 4.2 months. For FL, the milk components consisted of 78,955 records with a mean fat production of 392.86 ± 89.9 kg, a mean protein production of 362.8 ± 74.9 kg and a mean CA of 25.2 ± 4.1 months. For AL, the number of records was 603,521 for milk production with a mean of 10,802.8 ± 2905.9 kg and a mean CA of 35.6 ± 11.5 months. For the milk components, there were 179,122 records with a mean of 36.1 ± 9.5 months for CA and 388.3 ± 98.4 kg and 356.7 ± 82.6 kg for fat and protein, respectively. Three models were compared: the base model (M0) described above, and two alternative models that included CA in a linear and quadratic form (M1 and M2, respectively). Estimations of the variance components (VC) and breeding value (BV) were obtained using a repeatability animal model, with the same phenotypic and pedigree information used for all models. To select the best fit model for the data, a likelihood ratio test (LRtest) was used. A validation test (VT) was also applied to each model to evaluate the consistency of the genetic trends for females with information on AL and FL. The inclusion of CA in its linear form (M1) was the model that achieved the best results in the LRtest and an acceptable value for the VT. These results show that CA improves the model fit for BV prediction and reliability.

Genome-Wide Association Studies for Methane Production in Dairy Cattle.

Genomic selection has been proposed for the mitigation of methane (CH4) emissions by cattle because there is considerable variability in CH4 emissions between individuals fed on the same diet. The genome-wide association study (GWAS) represents an important tool for the detection of candidate genes, haplotypes or single nucleotide polymorphisms (SNP) markers related to characteristics of economic interest. The present study included information for 280 cows in three dairy production systems in Mexico: 1) Dual Purpose (n = 100), 2) Specialized Tropical Dairy (n = 76), 3) Familiar Production System (n = 104). Concentrations of CH4 in a breath of individual cows at the time of milking (MEIm) were estimated through a system of infrared sensors. After quality control analyses, 21,958 SNPs were included. Associations of markers were made using a linear regression model, corrected with principal component analyses. In total, 46 SNPs were identified as significant for CH4 production. Several SNPs associated with CH4 production were found at regions previously described for quantitative trait loci of composition characteristics of meat, milk fatty acids and characteristics related to feed intake. It was concluded that the SNPs identified could be used in genomic selection programs in developing countries and combined with other datasets for global selection.

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.

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.

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.

Genomic and genetic variability of six chicken populations using single nucleotide polymorphism and copy number variants as markers.

Genomic and genetic variation among six Italian chicken native breeds (Livornese, Mericanel della Brianza, Milanino, Bionda Piemontese, Bianca di Saluzzo and Siciliana) were studied using single nucleotide polymorphism (SNP) and copy number variants (CNV) as markers. A total of 94 DNA samples genotyped with Axiom® Genome-Wide Chicken Genotyping Array (Affymetrix) were used in the analyses. The results showed the genetic and genomic variability occurring among the six Italian chicken breeds. The genetic relationship among animals was established with a principal component analysis. The genetic diversity within breeds was calculated using heterozygosity values (expected and observed) and with Wright's F-statistics. The individual-based CNV calling, based on log R ratio and B-allele frequency values, was done by the Hidden-Markov Model (HMM) of PennCNV software on autosomes. A hierarchical agglomerative clustering was applied in each population according to the absence or presence of definite CNV regions (CNV were grouped by overlapping of at least 1 bp). The CNV map was built on a total of 1003 CNV found in individual samples, after grouping by overlaps, resulting in 564 unique CNV regions (344 gains, 213 losses and 7 complex), for a total of 9.43 Mb of sequence and 1.03% of the chicken assembly autosome. All the approaches using SNP data showed that the Siciliana breed clearly differentiate from other populations, the Livornese breed separates into two distinct groups according to the feather colour (i.e. white and black) and the Bionda Piemontese and Bianca di Saluzzo breeds are closely related. The genetic variability found using SNP is comparable with that found by other authors in the same breeds using microsatellite markers. The CNV markers analysis clearly confirmed the SNP results.

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.

Evaluation of mathematical models to describe testicular growth in Blackbelly ram lambs.

The primary objective was to compare various mathematical models to describe scrotal circumference (SC) and paired testis volume development in Blackbelly ram lambs. The study was conducted in the state of Querétaro, México (20° 43' N, 100° 15' W). Spring-born Blackbelly ram lambs (n = 41) were housed outdoors and fed alfalfa hay and concentrate. Body weight, SC, and testis length, diameter, and volume were recorded every 2 wk from 24 to 172 d of age (June 18 to November 3). The following mathematical functions were used to model SC-age and testis volume-age relationship: Von Bertalanffy, Brody, Gompertz, Logistic, and Richards. The suitability of the models was evaluated based on parameter values and standard errors, residual mean square, the coefficient of determination (R(2)), and the average prediction error (APE). All models, except for Brody's, had good fit to SC (R(2) > 0.98) and testis volume (R(2) > 0.95), and produced similar growth curves in the range of ages studied. The logistic model predicted SC at maturity quite well, 33.6 ± 0.6 cm as compared with 33.9 ± 0.5 cm observed in adult animals; all models had APE's smaller than ± 7% between 56 and 168 d of age. The Bertalanffy model predicted testis volume at maturity quite well, 513 ± 22 cm(3) as compared with 488 ± 20 cm(3) calculated for adult animals. The logistic model had a good fit to testis volume during the period of study, but underestimated the volume at maturity by 28%. All models, except for Brody's, had APE's smaller than ± 14% between 98 and 168 d of age. The logistic and Bertalanffy models predicted the inflection point for SC at 83 and 59 d of age, and testis volume at 116 and 109 d of age, respectively. In conclusion, all models, except for Brody's, had good fit to actual SC and testis volume data in the range of age evaluated, whereas the logistic and Bertalanffy's models made the best predictions for adult SC and testis volume, respectively.