Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations

Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application

Genetic and nongenetic variation of heifer fertility in Italian Holstein cattle

Excellent fertility performance is important to maximize farmers’ profit and to reduce the number of culled animals. Although female fertility of adult cows has been included in Italian Holstein breeding objectives since 2009, little has been done to quantify genetic variation of heifer fertility characteristics so far. The aim of the present study was to estimate genetic parameters of 4 fertility traits in nulliparous Italian Holstein heifers and to develop an aggregate selection index to improve heifer fertility. Data were retrieved from the national fertility database and included information on insemination, calving, and pregnancy diagnosis dates. The investigated phenotypes (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 following fixed effects: 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 (fitted to the pedigree-based relationship matrix) was considered as a 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 estimates from average covariance matrices ranged from 0.012 (CR) to 0.015 (IFL), with the exception of 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), and the relative emphasis placed on each selection criteria in the aggregate index was 10%, 47%, and 43% for AFI, IFL, and NRR56, respectively. The results of the present study suggest that heifer fertility should be considered as an additional trait in the breeding objectives of Italian Holstein

Misuriamo i vantaggi "reali" della genotipizzazione femminile

Fare progresso genetico implica scegliere soggetti miglioratori che, con la loro superiorit\ue0, vadano a costruire il futuro livello genetico dell\u2019azienda. Pi\uf9 alta \ue8 la media dei riproduttori selezionati sia maschi che femmine, pi\uf9 alto \ue8 il livello di miglioramento genetico atteso nella progenie. Delle 4 vie di selezione che contribuiscono al progresso genetico (la cui velocit\ue0 dipende da variabilit\ue0 genetico-additiva, intensit\ue0 di selezione, accuratezza e intervallo generazionale) due sono di pertinenza dei Centri di F.A.: Scelta Padri di Toro e Scelta Madri di Toro, mentre due sono quelle sulle quali pu\uf2 agire l\u2019allevatore direttamente in azienda e cio\ue8: Scelta dei Padri delle Vacche (i tori da usare in azienda), Scelta delle Madri delle Vacche (la scelta della rimonta). Sino ad oggi le strategie genetiche dell\u2019allevatore consistevano nell\u2019utilizzo di tutte le femmine in azienda per produrre la rimonta; oggi invece la tecnologia mette a disposizione nuovi scenari e si pu\uf2 abbinare l\u2019utilizzo del seme sessato abbinato alla genotipizzazione delle femmine

Così la genetica è spinta dai conti aziendali

Il miglioramento genetico rappresenta uno degli strumenti a disposizione degli allevatori utili a garantire la sostenibilità economica della propria attività. Migliorare geneticamente una popolazione bovina significa analizzare la situazione di mercato in cui il settore primario si trova ad agire nel presente e prevedere le sue evoluzioni negli anni a venire, in modo da individuare una serie di caratteri (fenotipi) importanti per la redditività aziendale e di conseguenza possibili oggetto di selezione. Questi fenotipi devono rispettare tre parametri: essere importanti, misurabili, ed ereditabili. Il miglioramento genetico è quindi una disciplina dinamica perchè si deve basare su previsioni dei cambiamenti futuri del mercato in cui gli allevatori si troveranno ad operare e deve fornire strumenti utili ad adeguarsi ad essi. Il tutto con notevole anticipo sui tempi, dato che i miglioramenti derivanti dalla selezione genetica sono visibili non nel breve ma nel lungo periodo in funzione dell’intervallo generazionale bovino. Questi miglioramenti sono trasmissibili di generazione in generazione e sono soprattutto cumulativi e permanenti nel tempo per cui impattano significativamente e permanentemente sulla redditività dell’allevamento: per questo, nella scelta dei caratteri da selezionare geneticamente è e sarà sempre più importante guardare non solo alle voci di guadagno derivanti dall’attività zootecnica, ma anche alle voci di spesa, con l’obiettivo di massimizzare i primi e minimizzare i secondi, riassumendo questo principio in un unico indice economico di selezione

Magnetic Properties of some Rhombohedral RE-Co Compounds

The magnetic properties and the magnetocrystalline anisotropy of the rhombohedral RECo3, RE2Co7 and RE5Co19 systems (RE = Y, Nd) have been studied. It has been evidenced that the magnetic phenomenology is qualitatively the same in the different phases. The variation in composition only has a quantitative influence

Il PFT si aggiorna: obiettivo una Frisona più sostenibile e redditizia

Il miglioramento genetico rappresenta uno degli strumenti a disposizione degli allevatori utili a garantire la sostenibilità economica della propria attività. Migliorare geneticamente una popolazione significa analizzare la situazione sociale e di mercato in cui il settore primario si trova ad agire nel presente e prevedere le sue evoluzioni negli anni a venire, in modo da individuare una serie di caratteri (fenotipi) importanti per i nostri obiettivi di miglioramento e, di conseguenza, possibili oggetto di selezione. Questi fenotipi devono rispettare 3 parametri: essere importanti, misurabili ed ereditabili. Il miglioramento genetico è quindi una disciplina dinamica proprio per la sua natura “di previsione” dei cambiamenti futuri del mercato e della società in cui gli allevatori si troveranno ad operare. I miglioramenti derivanti dalla selezione genetica sono visibili non nel breve ma nel lungo periodo, in funzione dell’intervallo generazionale bovino. Tuttavia, questi miglioramenti sono trasmissibili di generazione in generazione e sono soprattutto cumulativi e permanenti nel tempo. Abbiamo parlato, non a caso, di evoluzione della società: oggi più che mai le nuove normative e le Associazioni dei consumatori chiedono che l’allevamento da latte sia sempre più sostenibile, attento al benessere animale e con minore impatto ambientale. Si tratta quindi di “ricercare” un interesse comune tra produttore e consumatore: selezionare per una Frisona che sia più efficiente (più reddito per l’allevatore), con minore impatto ambientale e minore uso di farmaci

Phenomenological analysis of the magnetocrystalline anisotropy of the Co sublattice in some rhombohedral and hexagonal intermetallic structures derived from the CaCu5 unit cell

A comparative study of the saturation magnetization, Curie temperature, and magnetocrystalline anisotropy in several rhombohedral and hexagonal Y‐Co compounds was done. The considered phases YCo3, Y2Co7, Y5Co19 (rhombohedrals), YCo5+z, and Y2Co17 (hexagonals) are all derived from the hexagonal CaCu5 unit. The variation of the magnetic properties in the different compounds was found to be strongly correlated to the cobalt content. In particular the Co sublattice anisotropy varies linearly with the Co content in the phases, while it seems to be not affected by structural changes (rhombohedral‐hexagonal). The highest anisotropy of Co was found in YCo5, every modification of the CaCu5 cell resulting in a weakening of the overall axial anisotropy. An evaluation of the strength of the Co anisotropy in the 2c, 3g, and dumbbell sites was done using a phenomenological model

Revision of the aggregate fertility index for Italian Holstein-Friesian dairy cattle

The aggregate fertility index was added to the national Holstein breeding objective in 2009, and is a linear combination of five selection criteria: angularity, milk yield (MY), interval calving-first service (DTFS), 56 days non-return rate (NR56), and calving interval. The objective of the present study was to include new traits, measured in both productive cows and heifers, to such aggregate index, by exploiting information from linear scoring and fertility-related events. Six subsets of ~15,000 animals calving since 1994 were extracted from the national database. Traits identified were: age at first insemination in heifers (AFI), interval first-last insemination (IFL), NR56, and conception rate (CR) in heifers and cows, and DTFS, MY, and body condition score (BCS) in cows. A multiple-trait animal model was employed to estimate (co)variances of these phenotypes, separately for cows and heifers. Fixed effects per trait were: herd-year of birth (AFI), month of birth (AFI), herd-year-season of birth (IFL, NR56, CR in heifers), month-year of insemination (IFL, NR56, CR in heif-ers), herd-year-season of calving (MY, DTFS, IFL, NR56, CR in cows), month of calving (DTFS, IFL, CR in cows) or insemination (NR56 in cows), age-year of calving (DTFS, IFL, NR56, CR in cows), herd-year-season of classification (BCS), age-stage of lactation at linear scoring (BCS), and year of calving (BCS). Animal additive genetic and residual were treated as random terms. The pedigree was traced back 5 generations. Estimates of G and R matrixes of all the six subsets were averaged to apply selection index methodology for deriving appropriate index weights, by fixing CR in cows and heifers as the only breeding goals. Heritability of cow fertility traits ranged from 0.013 (NR56) to 0.076 (DTFS), whereby estimates of heifer traits were between 0.012 (CR) and 0.071 (AFI). Relative emphasis placed in the selection criteria of the aggregate index for cows were: 0.55 (IFL), 0.16 (DTFS), 0.13 (NR56), 0.09 (MY), and 0.07 (BCS). Index weights for heifer traits were 0.47 (IFL), 0.43 (NR56), and 0.10 (AFI). Both indexes were scaled to have mean 100 and standard deviation 5. The aggregate fertility index published in the official genetic evaluation release is a combined index which includes both indexes by placing 90% emphasis on cow aggregate index and 10% emphasis on heifer aggregate index