Demographic characterization and genetic variability of the Girgentana goat breed by the analysis of genealogical data

The aim of this paper is to present an overview of the actual Sicilian Girgentana population structure by the analysis ofgenealogical data. Statistics show that in 1983 the population consisted of 30,000 Girgentana goats; ten years lateralmost 98% of the entire Girgentana population disappeared. The remaining population consists of 461 individuals (134males and 327 females), with 368 living animals. The effective population size is 380 individuals. The inbreeding rate pergeneration was equal to 0.13%. The average estimated inbreeding level within the living male population was equal to0.8% (0-15%); and the average inbreeding level within the living female population was equal to 0.7% (0-31%). Theaverage relationship between males and females estimated on 27,772 possible matings was equal to 0.5% (0-8.7%).The estimated inbreeding level was not high due to the lack of pedigree information. This is resulting in a ratio betweenthe number of founder equivalents (ƒe = 22,94) and the number of absolute founders (ƒa = 93) equal to 25%

Genetic aspects of heifer fertility in Italian Holstein population

Fertility is fundamental to enhance the production efficiency of the dairy herd and thus it is a contributor to annual farm profitability. Cow fertility has been included in Italian Holstein breeding objectives since 2009. Heifer fertility is another key trait that deserves attention as it has direct connection with overall efficiency. In general, the main goal is to improve conception and daughter pregnancy rates, favour shorter calving interval in lactating cows, and reduce failure of conceiving in heifers. The advantages of heifer over cow fertility traits are the early availability in life and, overall, the moderate to strong genetic correlations with fertility of lactating cows. The aims of the present study are to assess genetic parameters of Italian Holstein heifers and develop an aggregate selection index to improve heifer fertility. Data (ANAFIBJ, Cremona, Italy) included information on insemination, calving, and pregnancy diagnosis dates of Italian Holstein heifers. The investigated traits (mean ± standard deviation) were age at first insemination (AFI, mo; 17.25 ± 2.89), nonreturn rate at 56 d from the first insemination (NRR56, binary; 0.78 ± 0.41), conception rate at first insemination (CR, binary; 0.61 ± 0.49), and interval from first to last insemination (IFL, d; 26.09 ± 51.85). Genetic parameters were estimated using a 4-trait animal model that included the fixed effects of herd-year of birth and month of birth for AFI, and herd-year-season of birth and month-year of insemination for IFL, NRR56, and CR. The animal additive genetic effect was included as random term. An aggregate index was developed from the estimated additive genetic (co)variance matrix by considering CR as the breeding goal and AFI, NRR56, and IFL as selection criteria. Heritability ranged from 0.012 (CR) to 0.015 (IFL), except for AFI (0.071). Conception rate at first insemination was strongly correlated with both IFL (−0.730) and NRR56 (0.668), and weakly to AFI (−0.065). The relative emphasis placed on each selection criteria in the aggregate index was 10%, 47%, and 43% for AFI, IFL, and NRR56, respectively. Results of the present study suggest that heifer fertility should be considered as an additional trait in the breeding objectives of Italian Holstein

The effect of selection on casein genetic polymorphisms and haplotypes in Italian Holstein cattle

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Genetic Diversity in the Italian Holstein Dairy Cattle Based on Pedigree and SNP Data Prior and After Genomic Selection

Genetic diversity has become an urgent matter not only in small local breeds but also in more specialized ones. While the use of genomic data in livestock breeding programs increased genetic gain, there is increasing evidence that this benefit may be counterbalanced by the potential loss of genetic variability. Thus, in this study, we aimed to investigate the genetic diversity in the Italian Holstein dairy cattle using pedigree and genomic data from cows born between 2002 and 2020. We estimated variation in inbreeding, effective population size, and generation interval and compared those aspects prior to and after the introduction of genomic selection in the breed. The dataset contained 84,443 single-nucleotide polymorphisms (SNPs), and 74,485 cows were analyzed. Pedigree depth based on complete generation equivalent was equal to 10.67. A run of homozygosity (ROH) analysis was adopted to estimate SNP-based inbreeding (FROH). The average pedigree inbreeding was 0.07, while the average FROH was more than double, being equal to 0.17. The pattern of the effective population size based on pedigree and SNP data was similar although different in scale, with a constant decrease within the last five generations. The overall inbreeding rate (ΔF) per year was equal to +0.27% and +0.44% for Fped and FROH throughout the studied period, which corresponded to about +1.35% and +2.2% per generation, respectively. A significant increase in the ΔF was found since the introduction of genomic selection in the breed. This study in the Italian Holstein dairy cattle showed the importance of controlling the loss of genetic diversity to ensure the long-term sustainability of this breed, as well as to guarantee future market demands

Predicted Feed Efficiency index applied to Italian Holstein Friesian cattle population

Submitted 2020-08-02 | Accepted 2020-09-21 | Available 2020-12-01https://doi.org/10.15414/afz.2020.23.mi-fpap.326-330Feed efficiency has a major influence on farm profitability and environmental stewardship in the dairy industry. The aim of this study was to describe a new selection index adopted by the Italian Holstein and Jersey Association (ANAFIJ, Cremona, Italy) to improve feed efficiency using data recorded by the official dairy recording system. Predicted dry matter intake (pDMI) was derived from milk yield, fat content, and estimated cow body weight. Fat-protein corrected milk (FPCM) was derived from milk yield corrected for fat, protein, and a fixed coefficient for lactose content (4.80%). Therefore, the predicted feed efficiency (pFE) was estimated as ratio between FPCM and pDMI. Average pFE was 1.27±0.18 (kg.d-1) with heritability of 0.32. Predicted Feed Efficiency index (pFEi), traditional and genomic, has been implemented in the Italian Holstein Friesian evaluation system. Results suggest that pFEi may be a new breeding objective for Italian Friesians. The official selection index (PFT), in use since 2002, is positively correlated with pFEi. However, the introduction of pFEi will improve the positive feed efficiency trend. This approach will permit the Italian Holstein Friesian breeders to improve feed efficiency, without increasing costs of recording system. However, to avoid the risk of selecting animals with an excessive negative energy balance after calving, it would be useful to include in the pFE a correction for body condition score and reproductive performances. Meanwhile, in order to increase the accuracy of the predicted phenotype, an Italian consortium is creating a consistent phenotypic critical mass of individual data for dry matter intake in cows, heifers and young bulls.Keywords: feed efficiency, cattle breeding, dry matter intake, breeding value estimationReferencesCassandro, M. (2020). Animal breeding and climate change, mitigation and adaptation. Journal of Animal Breeding and Genetics, 137(2), 121-122. https://doi.org/10.1111/jbg.12469Cassandro, M. et al. (2010). Genetic parameters of predicted methane production in Holstein Friesian cows. Proceedings of the 9th World Congress on Genetics Applied to Livestock Production, Leipzig, Germany.Cassandro, M., Mele, M. and Stefanon, B. (2013). Genetic aspects of enteric methane emission in livestock ruminants. Italian Journal of Animal Science, 12(3), 450-458.De Haas, Y. et al. (2012). Improved accuracy of genomic prediction for dry matter intake of dairy cattle from combined European and Australian data sets. Journal of Dairy Science, 95(10), 6103-6112.De Vries, M. and Veerkamp, R. (2000). Energy balance of dairy cattle in relation to milk production variables and fertility. Journal of Dairy Science, 83(1), 62-69.Finocchiaro, R. et al. (2017). Body weight prediction in Italian Holstein cows. ICAR Technical Series, 22, 95-98.Hegarty, R. et al. (2007). Cattle selected for lower residual feed intake have reduced daily methane production. Journal of Animal Science, 85(6), 1479-1486.Hurley, A. M. et al. (2018). Characteristics of feed efficiency within and across lactation in dairy cows and the effect of genetic selection. Journal of Dairy Science, 101(2), 1267-1280. https://doi.org/https://doi.org/10.3168/jds.2017-12841Meuwissen, T. H., Hayes, B. J. and Goddard, M. E. (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157(4), 1819-1829.National Research Council. (2001). Nutrient Requirements of Dairy Cattle: Seventh Revised Edition, 2001. The National Academies Press. http://www.nap.edu/catalog.php?record_id=9825Pryce, J. et al. (2014). Genomic selection for feed efficiency in dairy cattle. Animal, 8(1), 1-10.Sjaunja, L. et al. (1990). A Nordic proposal for an energy corrected milk formula. Proceedings of the 2nd Session of Committee for Recording and Productivity of Milk Animal, Paris, p. 156.Veerkamp, R. et al. (2000). Genetic correlation between days until start of luteal activity and milk yield, energy balance, and live weights. Journal of Dairy Science, 83(3), 577-583.Verbyla, K. et al. (2010). Predicting energy balance for dairy cows using high-density single nucleotide polymorphism information. Journal of Dairy Science, 93(6), 2757-2764.Wall, E., Coffey, M. and Brotherstone, S. (2007). The relationship between body energy traits and production and fitness traits in first-lactation dairy cows. Journal of Dairy Science, 90(3), 1527-1537.Wallace, R. J. et al. (2019). A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions. Science Advances, 5(7), eaav8391

Genome-wide scan reveals genetic divergence in Italian Holstein cows bred within PDO cheese production chains

Abstract Dairy cattle breeds have been exposed to intense artificial selection for milk production traits over the last fifty years. In Italy, where over 80% of milk is processed into cheese, selection has also focused on cheese-making traits. Due to a deep-rooted tradition in cheese-making, currently fifty Italian cheeses are marked with the Protected Designation of Origin (PDO) label as they proved traditional land of origin and procedures for milk transformation. This study aimed to explore from a genetic point of view if the presence of such diverse productive contexts in Italy have shaped in a different manner the genome of animals originally belonging to a same breed. We analyzed high density genotype data from 1000 Italian Holstein cows born between 2014 and 2018. Those animals were either farmed in one of four Italian PDO consortia or used for drinkable milk production only. Runs of Homozygosity, Bayesian Information Criterion and Discriminant Analysis of Principal Components were used to evaluate potential signs of genetic divergence within the breed. We showed that the analyzed Italian Holstein cows have genomic inbreeding level above 5% in all subgroups, reflecting the presence of ongoing artificial selection in the breed. Our study provided a comprehensive representation of the genetic structure of the Italian Holstein breed, highlighting the presence of potential genetic subgroups due to divergent dairy farming systems. This study can be used to further investigate genetic variants underlying adaptation traits in these subgroups, which in turn might be used to design more specialized breeding programs

Sviluppo di un indice per la resistenza alla mastite

none7noDurante l’ultimo convegno della Federazione Mondiale della razza Frisona (WHFF), svoltosi in Argentina dal 31 marzo al 3 aprile 2016, l’ANAFI ha presentato il suo lavoro in corso per la messa a punto di un nuovo indice per la resistenza alla mastite. Per la costituzione di questo indice viene utilizzata la conta delle cellule somatiche (CCS, cellule/mL di latte), carattere rilevato routinariamente nel corso dei controlli funzionali e, quindi, già disponibile nel sistema di raccolta dati nazionale. L’obiettivo è quello di sfruttare le informazioni già presenti ma gestirle in maniera diversa. L’attuale indice per le cellule somatiche non verrà sostituito perché importante per la qualità del latte e fondamentale in quanto fa parte dell’indice composto per la trasformazione casearia (ITC), ufficiale dal dicembre 2013.openRaffaella Finocchiaro; Mauro Penasa; Alice Varotto; Giulio Visentin; Jan-Thijs van Kaam; Maurizio Marusi; Martino CassandroRaffaella Finocchiaro; Mauro Penasa; Alice Varotto; Giulio Visentin; Jan-Thijs van Kaam; Maurizio Marusi; Martino Cassandr

Signatures of selection in the genome of Italian Holstein cattle for cheese production.

Dairy cattle breeds have been exposed to intense artificial selection for milk production traits over the last fifty years. In Italy, where over 75% of milk is processed into cheese, selection has also focussed on cheese-making traits. The most widely spread PDO Italian cheeses in the world are the Parmigiano Reggiano and the Grana Padano, which cover 16% and 24% of the total Italian milk production. Intensive selection programmes that aim at increasing production yield can cause loss of genetic variability and increased genomic homozygosity. To this end, recent advances in genome mapping have the potential both to improve our understanding of selection and to be used in the breeding programme. The present study aims to detect potential selection signatures in the genome of Italian Holstein dairy cows bred for PDO cheese productions. High-density genotype information from SNP-chip was available for 400 cattle, reared in certified farms for Parmigiano Reggiano (PR =200) and Grana Padano (GP =200). The quality control (QC) of the data was performed by excluding both animals and SNPs with a call rate <90% and by removing both unassigned and on-sex-chromosome SNP. We then performed a genomic scan for runs of homozygosity (ROH) which were detected in PLINK 1.9 by using a sliding window approach. ROH were defined based on at least 1 Mb-long homozygous segments, and by allowing for a maximum of one missing and one heterozygous SNP. All animals passed the QC and 311,501 SNP were used to estimate ROH. In total, 142,211 ROH were detected (355.5 segments per animal), with an average length of 1.59 Mb. The mean number of homozygous segments in the PR and GP cattle was similar (354 and 356, respectively). For 115 PR and 122 GP cows, at least one ROH longer than 16 Mb was found, probably indicating recent inbreeding. Six genomic regions with ROH shared among more than 70% of the 400 cattle were located on the following chromosomes: BTA 11, 14, 16, 18, 21 and 29. As a small amount of regions showed a different rate of homozygosity when comparing PR and GP cattle, further studies will investigate any potentially-different signs of selection among PDO dairy chains. Further research is ongoing to demonstrate the role of those homozygous segments on cheese-making traits

Implementation of Ketosis breeding value in Italian Holstein

An increase of circulating ketone bodies is associated, particularly at the onset of the lactation, with (sub)clinical ketosis, which may reduce cows\u2019 health, production and increase culling rate. The aim of the current research was to develop a genetic evaluation for subclinical ketosis for Holstein dairy cattle using data routinely available from the national milk recording system and linear type classification. For this breeding value three traits were considered: 1) \u3b2-hydroxybutyrate (BHB), 2) fat-to-protein ratio (FPR), both measured during routine milk recording, and 3) linear body condition score (BCS) measured by a classifier. Both FPR and BCS were used as indicator traits for sub-clinical ketosis. Currently milk BHB and FPR were available on more than 2.2 million test-days records belonging to Holstein cows in the first 90 days-in-milk from first, second and third lactation. These records were subsequently matched to the closest linear classification date when body condition score (BCS) was scored. The pedigree of phenotyped cows was traced back up to 4 generations. (Co)variance components were estimated using trivariate linear mixed models; in particular, for BHB and FPR the fixed effects of herd-test-day, the two-way interaction between week of lactation and parity, and the three-way interaction between classes of age at calving, parity and year of calving were considered. The additive genetic effect and, only for BHB and FPR, the permanent environment were the random effects. Heritability estimates were 0.093, 0.090 and 0.157 for BHB, FPR and BCS, respectively, while repeatability estimates were 0.179 (BHB) and 0.209 (FPR). Phenotypically, milk BHB was positively correlated with FPR (0.279) and weakly with BCS (-0.038), similarly to the correlation estimated between FPR and BCS (-0.049). Milk BHB was genetically correlated with FPR (0.159) and BCS (-0.161), while the genetic correlation between FPR and BCS was -0.14. The results from the present study demonstrated the presence of exploitable genetic variation for breeding purposes resulting in EBVs