Use of different marker pre-selection methods based on single SNP regression in the estimation of Genomic-EBVs

Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs) were compared using simulated data provided by the XII QTL-MAS workshop: i) Bonferroni correction of the significance threshold and ii) Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%). The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively). Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method

Analysis of BTA6 in Bruna Italiana and Pezzata Rossa cattle assayed with 2,535 SNPs

A high density SNP marker panel (54,000 SNPs) was used to investigate the genome of 775 Bruna Italiana and 493 Pezzata Rossa bulls. Observed and expected heterozygosities were calculated overall and per chromosome. In both breeds, values were not significantly different. Bos taurus Chromosome 6 (BTA6), carrying the casein loci, was analysed in higher detail. Overall, 2,535 markers were assayed on this chromosome. After discarding monomorphic markers, those having more than 10 missing values, and those having minor allele frequency below 2%, 1,814 and 2,061 SNPs were retained in Bruna Italiana and Pezzata Rossa, respectively. To detect signatures of ancient and recent selection, we calculated FIS inbreeding coefficient values of all BTA6 polymorphic markers, within sliding windows of groups of 5 adjacent SNPs and within 122 adjacent regions spanning 1 Mb intervals. These preliminary analyses indicated that genotyping of several thousand SNPs potentially allows the detection of the footprint of selection dodging the confounding effects of the population demographic history (i.e., effective population size, genetic structure, and mating pattern). A wider understanding of how and where selection shaped patterns of genetic variation along the genome may provide important insights into the dynamics of evolutionary change, facilitating both the identification of functionally significant genomic regions and genotype-phenotype correlations. Outlining such regions could allow focusing the fine mapping strategy to identify candidate genes and causative mutations affecting important economic or adaptive traits

Assessment of 29 candidate genes for milk traits in Italian dairy cattle

Several investigations have recently searched for significant association between gene polymorphisms and milk traits in livestock and model species. In several cases, it remains rather difficult to assess if the observed effects are caused by the mutation tested, by a nearby mutation in the same gene or by a mutation in a different gene or DNA region in linkage disequilibrium with the former. As a consequence, only in a few cases (e.g., κ-casein, SCD, DGAT1) the causative mutation seems to have been identified and, even when evidence is rather clear, genetic heterogeneity and genetic background may influence the size of allele substitution effects. Therefore, the significance of gene-trait associations and the estimate of their effect have to be verified in any new population in which this information is planned to be used, to estimate its actual utility in gene assisted breeding. In the SelMol project, we selected 29 candidate genes on the basis of known relationships between physiological or biochemical processes and evidence of significant association with milk traits in cattle, in related (e.g., sheep and goats) and model (e.g., mouse) species. A total of 106 SNPs were selected, using either information available in literature, or in silico, searching the NCBI dbSNP database. SNPs found significantly associated in other investigations were preferentially targeted. Otherwise non-synonymous SNPs and those in putative control regions (e.g., in promoter binding sites) were selected from dbSNP. If within a gene no SNP having one of these characteristics was available in dbSNP, synonymous SNPs, occurring in introns and untranslated non-control regions were chosen. DNA was extracted from semen of elite sires. SNPs polymorphism was confirmed by screening a panel of 32 individuals each of Pezzata Rossa (PR), Bruna Italiana (BI), and Frisona Italiana (FI) dairy cattle breeds. A total of 73 SNPs were confirmed as polymorphic in at least one breed: 63 in PR, 61 in BI, and 68 in FI. Polymorphic SNPs were genotyped on 400 individuals of PR and 600 of BI. Statistical tests were applied to detect selection sweeps, significant association to EBVs and phenotypic traits related to milk production and quality (milk yield, protein and fat yield and percentage), together with a number of functional traits (fertility, SCS as indicator of mastitis resistance, conformational traits, and milkability)

AdaptMap: exploring goat diversity and adaptation

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New trends in dairy cattle genetic evaluation

I sistemi di valutazione genetica nel mondo sono in rapido sviluppo. Attualmente, i programmi di selezione “tradizionale” basati su fenotipi e rapporti di parentela tra gli animali vengono integrati, e nel futuro potrebbero essere sostituiti, dalle informazioni molecolari. In questo periodo di transizione, questa tesi riguarda ricerche su entrambi i tipi di valutazioni: dall’accertamento sull’accuratezza degli indici genetici internazionali (tradizionali), allo studio di metodi statistici utilizzati per integrare informazioni genomiche nella selezione (selezione genomica). Tre capitoli valutano gli approcci per stimare i valori genetici dai dati genomici riducendo il numero di variabili indipendenti. In modo particolare, la correzione di Bonferroni e il test di permutazioni con regressione a marcatori singoli (Capitolo III), analisi delle componenti principali con BLUP (Capitolo IV) e indice Fst tra razze con BayesA (Capitolo VI). Inoltre, il Capitolo V analizza l’accuratezza dei valori genomici con BLUP, BayesA e Bayesian LASSO includendo tutte le variabili disponibili. I risultati di questa tesi indicano che il progresso genetico atteso dall’analisi dei dati simulati può effettivamente essere ottenuto, anche se ulteriori ricerche sono necessarie per ottimizzare l’utilizzo delle informazioni molecolari in modo da ottimizzare i risultati per tutti i caratteri sotto selezione.Genetic evaluation systems are in rapid development worldwide. In most countries, “traditional” breeding programs based on phenotypes and relationships between animals are currently being integrated and in the future might be replaced by the introduction of molecular information. This thesis stands in this transition period, therefore it covers research on both types of genetic evaluations: from the assessment of the accuracy of (traditional) international genetic evaluations to the study of statistical methods used to integrate genomic information into breeding (genomic selection). Three chapters investigate and evaluate approaches for the estimation of genetic values from genomic data reducing the number of independent variables. In particular, Bonferroni correction and Permutation test combined with single marker regression (Chapter III), principal component analysis combined with BLUP (Chapter IV) and Fst across breeds combined with BayesA (Chapter VI). In addition, Chapter V analyzes the accuracy of direct genomic values with BLUP, BayesA and Bayesian LASSO including all available variables. The results of this thesis indicate that the genetic gains expected from the analysis of simulated data can be obtained on real data. Still, further research is needed to optimize the use of genome-wide information and obtain the best possible estimates for all traits under selection

SNPConvert: SNP Array Standardization and Integration in Livestock Species

One of the main advantages of single nucleotide polymorphism (SNP) array technology is providing genotype calls for a specific number of SNP markers at a relatively low cost. Since its first application in animal genetics, the number of available SNP arrays for each species has been constantly increasing. However, conversely to that observed in whole genome sequence data analysis, SNP array data does not have a common set of file formats or coding conventions for allele calling. Therefore, the standardization and integration of SNP array data from multiple sources have become an obstacle, especially for users with basic or no programming skills. Here, we describe the difficulties related to handling SNP array data, focusing on file formats, SNP allele coding, and mapping. We also present SNPConvert suite, a multi-platform, open-source, and user-friendly set of tools to overcome these issues. This tool, which can be integrated with open-source and open-access tools already available, is a first step towards an integrated system to standardize and integrate any type of raw SNP array data. The tool is available at: https://github. com/nicolazzie/SNPConvert.git

REVISITING DEMOGRAPHIC PROCESSES IN CATTLE WITH GENOME-WIDE POPULATION GENETIC ANALYSIS

The domestication of the aurochs took place approximately 10,000 years ago giving rise to the two main types of domestic cattle known today, taurine (Bos taurus) domesticated somewhere on or near the Fertile Crescent, and indicine (B. indicus) domesticated in the Indus Valley. However, although cattle have historically played a prominent role in human society the exact origin of many extant breeds is not well known. Here we used a combination of medium and high-density Illumina Bovine SNP arrays (i.e. ~54,000 and ~770,000 SNPs respectively), genotyped for over 1,300 animals representing 56 cattle breeds, to describe the relationships among major European cattle breeds and detect patterns of admixture among them. Our results suggest modern cross-breeding and ancient hybridisation events have both played an important role, including with animals of indicine origin. We use these data to identify signatures of selection reflecting both domestication (hypothesised to produce a common signature across breeds) and local adaptation (predicted to exhibit a signature of selection unique to a single breed or group of related breeds with a common history) to uncover additional demographic complexity of modern European cattle

Analysis of lactation shapes in extended lactations

In order to describe the temporal evolution of milk yield (MY) and composition in extended lactations, 21 658 lactations of Italian Holstein cows were analyzed. Six empirical mathematical models currently used to fit 305 standard lactations (Wood, Wilmink, Legendre, Ali and Schaeffer, quadratic and cubic splines) and one function developed specifically for extended lactations (a modification of the Dijkstra model) were tested to identify a suitable function for describing patterns until 1000 days in milk (DIM). Comparison was performed on individual patterns and on average curves grouped according to parity (primiparous and multiparous) and lactation length (standard ≤305 days, and extended from 600 to 1000 days). For average patterns, polynomial models showed better fitting performances when compared with the three or four parameters models. However, LEG and spline regression, showed poor prediction ability at the extremes of the lactation trajectory. The Ali and Schaeffer polynomial and Dijkstra function were effective in modelling average curves for MY and protein percentage, whereas a reduced fitting ability was observed for fat percentage and somatic cell score. When individual patterns were fitted, polynomial models outperformed nonlinear functions. No detectable differences were observed between standard and extended patterns in the initial phase of lactation, with similar values of peak production and time at peak. A considerable difference in persistency was observed between 200 and 305 DIM. Such a difference resulted in an estimated difference between standard and extended cycle of about 7 and 9 kg/day for daily yield at 305 DIM and of 463 and 677 kg of cumulated milk production at 305 DIM for the first- and second-parity groups, respectively. For first and later lactation animals, peak yield estimates were nearly 31 and 38 kg, respectively, and occurred at around 65 and 40 days. The asymptotic level of production was around 9 kg for multiparous cows, whereas the estimate was negative for first parity