Investigation of phenotypic, genetic and genomic background of Milk spectra in Sarda dairy sheep.

Aim of this study was to analyse the genetic background of milk Fourier transform infrared (FTIR) spectra in dairy sheep. Individual milk FTIR spectra, with 1060 wavenumbers each, were available for 793 adult Sarda breed ewes genotyped at 45,813 SNP. The absorbance values of each wavenumber was analysed using a linear mixed model that included dim class, parity and lambing month as fixed effects and flock-test date and animal as random effects. The model was applied to estimate variance components and heritability and to perform a genome-wide association study for each wavenumber. Average h2 of wavenumbers absorbance was 0.13 ± 0.08, with the largest values observed in the regions associated with the characteristic bonds of carbonylic and methylenic groups of milk fat (h2 = 0.57 at 1724-1728 cm-1; and h2 = 0.34 at 2811-2834 cm-1, respectively). The absorbance values of wavenumbers were moderately correlated with the estimated heritabilities. After the Bonferroni correction, a total of nine markers were found to be significantly associated with 32 different wavenumbers. Of particular interest was the SNP s63269.1, mapped on chromosome 2, that was found to be associated with 27 wavenumbers. Genes previously found to be related to traits of interest (e.g. disease resistance, milk yield and quality, cheese firmness) are located close to the significant SNP. As expected, the heritability estimated for the absorbance of each wavenumbers seems to be associated with the related milk components.

Effects of Age, Fulton's Condition Index (K) and Muscle Fat on Total Mercury Content in Raw, Pre-Canning and Canned Samples of Atlantic Bluefin Tuna (Thunnus thynnus).

A total of 30 samples of Atlantic bluefin tuna were analysed for total mercury concentration. Relationships between total mercury content and age, Fulton's condition index (K) and fat content were statistically evaluated. The effect of muscle status (raw, pre-canning, canned) on mercury content was also investigated. The average total mercury content was: 1.185 ± 0.662 mg/kg in raw, 1.481 ± 0.893 mg/kg in pre-canning and 1.393 ± 0.882 mg/kg in canned samples, respectively. Canning promotes a statistically significant increase in the concentration of mercury. The weight of fish, K and fat content are useful tools to estimate the mercury accumulation in Atlantic bluefin tuna. The results of the present study represent a contribution to the assessment of the EU mercury levels in Atlantic bluefin tuna.

A transgenerational study on the effect of great-granddam birth month on granddaughter EBV for production traits in Italian Simmental cattle.

Heat tolerance is a key feature of resilient animals. Offspring of animals that suffer environmental stress during pregnancy could show physiological, morphological, and metabolic modifications. This is due to a dynamic reprogramming of the epigenetics of the mammalian genome that occurs in the early life cycle. Thus, the aim of this study was to investigate the extent of the transgenerational effect of heat stress during the pregnancy of Italian Simmental cows. The effects of dam and granddam birth months (as indicator of pregnancy period) on their daughter and granddaughter estimated breeding values (EBV) for some dairy traits as well as of the temperature-humidity index (THI) during the pregnancy were tested. A total of 128,437 EBV (milk, fat, and protein yields, and somatic cell score) were provided by the Italian Association of Simmental Breeders. The best birth months (of both dam and granddam) for milk yield and protein yield were May and June, whereas the worst were January and March. Great-granddam pregnancies developed during the winter and spring seasons positively affected the EBV for milk and protein yields of their great-granddaughters; in contrast, pregnancies during summer and autumn had negative effects. These findings were confirmed by the effects of maximum and minimum THI in different parts of the great-granddam pregnancy on the performances of their great-granddaughters. Thus, a negative effect of high temperatures during the pregnancy of female ancestors was observed. Results of the present study suggest a transgenerational epigenetic inheritance in Italian Simmental cattle due to environmental stressors.

Analysis of runs of homozygosity of cattle living in different climate zones.

Aim of this study was to analyze the distribution and characteristics of runs of homozygosity in Bos taurus taurus and Bos taurus indicus breeds, as well as their crosses, farmed all around the world. With this aim in view, we used single-nucleotide polymorphisms (SNP) genotypes for 3,263 cattle belonging to 204 different breeds. After quality control, 23,311 SNPs were retained for the analysis. Animals were divided into seven different groups: 1) continental taurus, 2) temperate taurus, 3) temperate indicus, 4) temperate composite, 5) tropical taurus, 6) tropical indicus, and 7) tropical composite. The climatic zones were created according to the latitude of the breeds' country of origin: i) continental, latitude ≥ 45°; ii) temperate, 45°< Latitude >23.26°; iii) tropics, latitude ≤ 23.26°. Runs of homozygosity were computed as 15 SNPs spanning in at least 2 Mb; number of ROH per animal (nROH), average ROH length (meanMb), and ROH-based inbreeding coefficients (FROH) were also computed. Temperate indicus showed the largest nROH, whereas Temperate taurus the lowest value. Moreover, the largest meanMb was observed for Temperate taurus, whereas the lowest value for Tropics indicus. Temperate indicus breeds showed the largest FROH values. Genes mapped in the identified ROH were reported to be associated with the environmental adaptation, disease resistance, coat color determinism, and production traits. Results of the present study confirmed that runs of homozygosity could be used to identify genomic signatures due to both artificial and natural selection.

Domestication and evolution of cattle originated different modern breeds in different places worldwide. The interaction between natural and artificial selection and the adaptation to environment shaped the genome, and the three different types of cattle here considered (taurus, indicus, and composite) may harbor different selection signatures. To study the difference among types and region of origin (tropics, temperate, and continental zones), Regions of Homozygosity (ROH) were used. ROH are continuous homozygous chromosomal segments identical by descendent, which characteristics can give information about inbreeding occurrence and natural and artificial selection. Moreover, it had been investigated which genes were mapped in these regions, and if interesting differences pertaining to environmental adaptation or fitness in general, could be observed.

Dry Matter Intake Prediction from Milk Spectra in Sarda Dairy Sheep.

Individual dry matter intake (DMI) is a relevant factor for evaluating feed efficiency in livestock. However, the measurement of this trait on a large scale is difficult and expensive. DMI, as well as other phenotypes, can be predicted from milk spectra. The aim of this work was to predict DMI from the milk spectra of 24 lactating Sarda dairy sheep ewes. Three models (Principal Component Regression, Partial Least Squares Regression, and Stepwise Regression) were iteratively applied to three validation schemes: records, ewes, and days. DMI was moderately correlated with the wavenumbers of the milk spectra: the largest correlations (around ±0.30) were observed at ~1100-1330 cm-1 and ~2800-3000 cm-1. The average correlations between real and predicted DMI were 0.33 (validation on records), 0.32 (validation on ewes), and 0.23 (validation on days). The results of this preliminary study, even if based on a small number of animals, demonstrate that DMI can be routinely estimated from the milk spectra.

Relationship between inbreeding and milk production traits in two Italian dairy sheep breeds.

The effects of inbreeding in livestock species breeds have been well documented and they have a negative impact on profitability. The objective of this study was to evaluate the levels of inbreeding in Sarda (SAR, n = 785) and Valle del Belice (VdB, n = 473) dairy sheep breeds and their impact on milk production traits. Two inbreeding coefficients (F) were estimated: using pedigree (FPED ), or runs of homozygosity (ROH; FROH ) at different minimum ROH lengths and different ROH classes. After the quality control, 38,779 single nucleotide polymorphisms remained for further analyses. A mixed-linear model was used to evaluate the impact of inbreeding coefficients on production traits within each breed. VdB showed higher inbreeding coefficients compared to SAR, with both breeds showing lower estimates as the minimum ROH length increased. Significant inbreeding depression was found only for milk yield, with a loss of around 7 g/day (for SAR) and 9 g/day (VdB) for a 1% increase of FROH . The present study confirms how the use of genomic information can be used to manage intra-breed diversity and to calculate the effects of inbreeding on phenotypic traits.

Study of the Fatty Acid Profile of Milk in Different Sheep Breeds: Evaluation by Multivariate Factorial Analysis.

A multivariate analysis was used to investigate the fatty acid (FA) profile in three different Italian sheep breeds: Comisana, Massese, and Sarda. A sample of 852 animals was considered: 118 Massese, 303 Comisana, 431 Sarda. Sarda sheep were divided into two groups, based on their breeding origin (298 and 133 reared in Sardinia and Tuscany, respectively). Sarda sheep, bred both in Sardinia and in Tuscany, were considered in different groups, both because in these two regions most of the sheep of this breed are reared, and because they differ in geographical characteristics and in the farming system. The individual milk FA composition of dairy ewes was analyzed with multivariate factor analysis. The extracted factors were representative of the following eight groups of fatty acids or functions: factor 1 (odd branched fatty acids and long-chain fatty acids), factor 2 (sn3_position), factor 3 (alternative biohydrogenation), factor 4 (SCD_1), factor 5 (SCD_2), factor 6 (SCD_3), factor 7 (fat secretion) and factor 8 (omega-3). A factor analysis suggested the presence of different metabolic pathways for de novo short- and medium-chain fatty acids and Δ9-desaturase products. The ANOVA of factor scores highlighted the significant effects of the breed. The results of the present study showed that breed is an important factor in defining the fatty acid profile of milk, combined with the effect of the diet. Breeds reared in the same farming system (Comisana, Massese and Sarda reared in Tuscany) showed significant differences for all the factors extracted. At the same time, we found differences between the Sarda sheep reared in Sardinia and Tuscany, two different regions of Italy.

Unravelling the effect of environment on the genome of Sarda breed ewes using Runs of Homozygosity.

Natural adaptation and artificial selection have shaped the genome of modern livestock breeds. Among SNP-based metrics that are used to detect signatures of selection at genome-wide level, runs of homozygosity (ROH) are getting increasing popularity. In this paper, ROH distribution and features of a sample of 823 Sarda breed ewes farmed at different levels of altitude are analysed to investigate the effect of the environment on the patterns of homozygosity. A total of 46,829 (33,087 unique) ROH were detected. OAR2 exhibited the largest average number of ROH per animal. The most frequent ROH (OAR27, 38.9-44.2 Mb) was shared by 327. ROH length was statistically affected (p < 0.001) by both the altitude and temperature of the place where the flock was located. The highest probability of a SNP falling in a ROH was observed for hill ewes, whereas the smallest one for mountain. A total of 457 SNP exceeded the 99th percentile of the ROH count per SNP distribution and were considered significant. These markers mapped in eight chromosomes and they clustered into 17 ROH islands, where 80 candidate genes were mapped. Results of this study highlighted differences in the ROH distribution and features among sheep farmed in flocks located at different levels of altitude, confirming the role of environmental adaptability in shaping the genome of this breed.

The Nero Lucano Pig Breed: Recovery and Variability.

The Nero Lucano (NL) pig is a black coat colored breed characterized by a remarkable ability to adapt to the difficult territory and climatic conditions of Basilicata region in Southern Italy. In the second half of the twentieth century, technological innovation, agricultural evolution, new breeding methods and the demand for increasingly lean meat brought the breed almost to extinction. Only in 2001, thanks to local institutions such as: the Basilicata Region, the University of Basilicata, the Regional Breeders Association and the Medio Basento mountain community, the NL pig returned to populate the area with the consequent possibility to appreciate again its specific cured meat products. We analyzed the pedigrees recorded by the breeders and the Illumina Porcine SNP60 BeadChip genotypes in order to obtain the genetic structure of the NL pig. Results evidenced that this population is characterized by long mean generation intervals (up to 3.5 yr), low effective population size (down to 7.2) and high mean inbreeding coefficients (FMOL = 0.53, FROH = 0.39). This picture highlights the low level of genetic variability and the critical issues to be faced for the complete recovery of this population.

Investigation of ß-hydroxybutyrate in early lactation of Simmental cows: Genetic parameters and genomic predictions.

Genomic information allows for a more accurate calculation of relationships among animals than the pedigree information, leading to an increase in accuracy of breeding values. Here, we used pedigree-based and single-step genomic approaches to estimate variance components and breeding values for ß-hydroxybutyrate milk content (BHB). Additionally, we performed a genome-wide association study (GWAS) to depict its genetic architecture. BHB concentrations within the first 90 days of lactation, estimated from milk medium infrared spectra, were available for 30,461 cows (70,984 records). Genotypes at 42,152 loci were available for 9,123 animals. Low heritabilities were found for BHB using pedigree-based (0.09 ± 0.01) and genomic (0.10 ± 0.01) approaches. Genetic correlation between BHB and milk traits ranged from -0.27 ± 0.06 (BHB and protein percentage) to 0.13 ± 0.07 (BHB and fat-to-protein ratio) using pedigree and from -0.26 ± 0.05 (BHB and protein percentage) to 0.13 ± 0.06 (BHB and fat-to-protein ratio) using genomics. Breeding values were validated for 344 genotyped cows using linear regression method. The genomic EBV (GEBV) had greater accuracy (0.51 vs. 0.45) and regression coefficient (0.98 vs. 0.95) compared to EBV. The correlation between two subsequent evaluations, without and with phenotypes for validation cows, was 0.85 for GEBV and 0.82 for EBV. Predictive ability (correlation between (G)EBV and adjusted phenotypes) was greater when genomic information was used (0.38) than in the pedigree-based approach (0.31). Validation statistics in the pairwise two-trait models (milk yield, fat and protein percentage, urea, fat/protein ratio, lactose and logarithmic transformation of somatic cells count) were very similar to the ones highlighted for the single-trait model. The GWAS allowed discovering four significant markers located on BTA20 (57.5-58.2 Mb), where the ANKH gene is mapped. This gene has been associated with lactose, alpha-lactalbumin and BHB. Results of this study confirmed the usefulness of genomic information to provide more accurate variance components and breeding values, and important insights about the genomic determination of BHB milk content.

The distribution of runs of homozygosity in the genome of river and swamp buffaloes reveals a history of adaptation, migration and crossbred events.

BACKGROUND: Water buffalo is one of the most important livestock species in the world. Two types of water buffalo exist: river buffalo (Bubalus bubalis bubalis) and swamp buffalo (Bubalus bubalis carabanensis). The buffalo genome has been recently sequenced, and thus a new 90 K single nucleotide polymorphism (SNP) bead chip has been developed. In this study, we investigated the genomic population structure and the level of inbreeding of 185 river and 153 swamp buffaloes using runs of homozygosity (ROH). Analyses were carried out jointly and separately for the two buffalo types. RESULTS: The SNP bead chip detected in swamp about one-third of the SNPs identified in the river type. In total, 18,116 ROH were detected in the combined data set (17,784 SNPs), and 16,251 of these were unique. ROH were present in both buffalo types mostly detected (~ 59%) in swamp buffalo. The number of ROH per animal was larger and genomic inbreeding was higher in swamp than river buffalo. In the separated datasets (46,891 and 17,690 SNPs for river and swamp type, respectively), 19,760 and 10,581 ROH were found in river and swamp, respectively. The genes that map to the ROH islands are associated with the adaptation to the environment, fitness traits and reproduction. CONCLUSIONS: Analysis of ROH features in the genome of the two water buffalo types allowed their genomic characterization and highlighted differences between buffalo types and between breeds. A large ROH island on chromosome 2 was shared between river and swamp buffaloes and contained genes that are involved in environmental adaptation and reproduction.

Genome-wide analysis of homozygosity regions in european simmental bulls.

The study of Runs of Homozygosity (ROH) is a useful approach for the characterization of the genome of livestock populations. Due to their high relationship with autozygosity, ROH allow to make inference about population genetic history, to estimate the level of inbreeding, to assess within breed heterogeneity and to detect the footprints of selection on livestock genomes. Aim of this study was to investigate the distribution of runs of homozygosity in bulls belonging to five European Simmental populations and to assess the relationship between three production traits (milk yield, fat and protein contents) and autozygosity. ROH count, distribution and ROH-based coefficient of inbreeding (FROH ) were calculated for 3,845 Simmental bulls of five different European countries: Austria (AT), Switzerland (CH), Czech Republic (CZ), Germany (DE) and Italy (IT). Average values of ROH number per animal, and total genome length covered by ROH were 77.8 ± 20.7 and 205 ± 74.4 Mb, respectively. Bulls from AT, DE and IT exhibited similar ROH characteristics. Swiss animals showed the highest (12.6%), while CZ the lowest (4.6%) FROH coefficient. The relationship between ROH occurrence and milk production traits was investigated through a genome-wide ROH-traits association analysis (GWRA). A total of 34 regions previously associated with milk traits (yield and/or composition) were identified by GWRA. Results of the present research highlight a mixed genetic background in the 5 European Simmental populations, with the possible presence of three subgroups. Moreover, a strong relationship between autozygosity and production traits has been detected.

Genomic prediction for latent variables related to milk fatty acid composition in Holstein, Simmental and Brown Swiss dairy cattle breeds.

Genomic selection (GS) reports on milk fatty acid (FA) profiles have been published quite recently and are still few despite this trait represents the most important aspect of milk nutritional and sensory quality. Reasons for this can be found in the high costs of phenotype recording but also in issues related to its nature of complex trait constituted by multiple genetically correlated variables with low heritabilities. One possible strategy to deal with such constraint is represented by the use of dimension reduction methods. We analysed 40 individual FAs from Italian Brown Swiss, Holstein and Simmental milk through multivariate factor analysis (MFA) to study the genetics of milk FA-related latent variables (factors) and assess their potential use in breeding. A total of nine factors were obtained, and their genetic parameters were inferred under a Bayesian framework using two statistical approaches: the classical pedigree best linear unbiased prediction (ABLUP) and the single-step genomic BLUP (ssGBLUP). The resulting factorial solutions were able to represent groups of FAs with common origin and function and can be considered concise pathway-level phenotypes. The heritability (h2 ) values showed relevant variations across different factors in each breed (0.03 ≤ h2  ≤ 0.38). The accuracies of breeding values predicted were low to high, ranging from 0.13 to 0.72 and from 0.18 to 0.74 considering the pedigree and the genomic model, respectively. The gain in accuracy in genetic prediction due to the addition of genomic information was ~30% and ~5% in validation and training groups respectively, confirming the contribution of genomic information in yielding more accurate predictions compared to the traditional ABLUP methodology. Our results suggest that MFA in combination with GS can be a valuable tool in dairy cattle breeding and deserves to be further investigated for use in future breeding programs to improve cow's milk FA-related traits.

Genetics of Arthrogryposis and Macroglossia in Piemontese Cattle Breed.

Arthrogryposis and macroglossia are congenital pathologies known in several cattle breeds, including Piemontese. As variations in single genes were identified as responsible for arthrogryposis in some breeds, we decided: (i) to test the hypothesis of a similar genetic determinism for arthrogryposis in the Piemontese breed by genotyping affected and healthy animals with a high-density chip and applying genome-wide association study (GWAS), FST and canonical discriminant analysis (CDA) procedures, and (ii) to investigate with the same approach the genetic background of macroglossia, for which no genetic studies exist so far. The study included 125 animals (63 healthy, 30 with arthrogryposis, and 32 with macroglossia). Differently from what reported for other breeds, the analysis did not evidence a single strong association with the two pathologies. Rather, 23 significant markers on different chromosomes were found (7 associated to arthrogryposis, 11 to macroglossia, and 5 to both pathologies), suggesting a multifactorial genetic mechanism underlying both diseases in the Piemontese breed. In the 100-kb interval surrounding the significant SNPs, 20 and 26 genes were identified for arthrogryposis and macroglossia, respectively, with 12 genes in common to both diseases. For some genes (NTN3, KCNH1, KCNH2, and KANK3), a possible role in the pathologies can be hypothesized, being involved in processes related to muscular or nervous tissue development. The real involvement of these genes needs to be further investigated and validated.

Use of the Multivariate Discriminant Analysis for Genome-Wide Association Studies in Cattle.

Genome-wide association studies (GWAS) are traditionally carried out by using the single marker regression model that, if a small number of individuals is involved, often lead to very few associations. The Bayesian methods, such as BayesR, have obtained encouraging results when they are applied to the GWAS. However, these approaches, require that an a priori posterior inclusion probability threshold be fixed, thus arbitrarily affecting the obtained associations. To partially overcome these problems, a multivariate statistical algorithm was proposed. The basic idea was that animals with different phenotypic values of a specific trait share different allelic combinations for genes involved in its determinism. Three multivariate techniques were used to highlight the differences between the individuals assembled in high and low phenotype groups: the canonical discriminant analysis, the discriminant analysis and the stepwise discriminant analysis. The multivariate method was tested both on simulated and on real data. The results from the simulation study highlighted that the multivariate GWAS detected a greater number of true associated single nucleotide polymorphisms (SNPs) and Quantitative trait loci (QTLs) than the single marker model and the Bayesian approach. For example, with 3000 animals, the traditional GWAS highlighted only 29 significantly associated markers and 13 QTLs, whereas the multivariate method found 127 associated SNPs and 65 QTLs. The gap between the two approaches slowly decreased as the number of animals increased. The Bayesian method gave worse results than the other two. On average, with the real data, the multivariate GWAS found 108 associated markers for each trait under study and among them, around 63% SNPs were also found in the single marker approach. Among the top 118 associated markers, 76 SNPs harbored putative candidate genes.

Use of multivariate factor analysis of detailed milk fatty acid profile to perform a genome-wide association study in Italian Simmental and Italian Holstein.

Milk fatty acid (FA) profile is a clear example of complex and multiple correlated traits whose genetic basis is difficult to assess. Although genome-wide association (GWA) studies have been successful in the identification of significant genetic variants for complex traits, when correlated phenotypes are analysed separately, the outcomes are difficult to compare and interpret in a metabolic context. Here, we performed a multivariate factor analysis (MFA) on Italian Simmental and Italian Holstein milk fat profiles to extract latent unobserved factors able to explain correlation structure and common metabolic function among different FAs. Individual factor scores obtained by MFA were used to perform a single-SNP based GWA. In both breeds, MFA was able to extract ten latent factors with specific biological meaning, notably: de novo synthesis, desaturation activity and biohydrogenation. The GWA result confirmed the increased power of joint association analysis on multiple correlated traits and allowed us to identify major candidate genes with well-documented function consistent with the metabolic classification of factors obtained, such as DGAT1, FASN and SCD.

Variance components using genomic information for 2 functional traits in Italian Simmental cattle: Calving interval and lactation persistency.

Functional traits, such as fertility and lactation persistency, are becoming relevant breeding goals for dairy cattle. Fertility is a key element for herd profitability and animal welfare; in particular, calving interval (CIN) is an indicator of female fertility that can be easily recorded. Lactation persistency (LPE; i.e., the ability of a cow to maintain a high milk yield after the lactation peak) is economically important and is related to several other traits, such as feed efficiency, health, and reproduction. The selection of these functional traits is constrained by their low heritability. In this study, variance components for CIN and LPE in the Italian Simmental cattle breed were estimated using genomic and pedigree information under the single-step genomic framework. A data set of 594,257 CIN records (from 275,399 cows) and 285,213 LPE records (from 1563,389 cows) was considered. Phenotypes were limited up to the third parity. The pedigree contained about 2 million animals, and 7,246 genotypes were available. Lactation persistency was estimated using principal component analysis on test day records, with higher values of the second extracted principal component (PC2) values associated with lower LPE, and lower PC2 values associated with higher LPE. Heritability of CIN and LPE were estimated using single-trait repeatability models. A multiple-trait analysis using CIN and production traits (milk, fat, and protein yields) was performed to estimate genetic correlations among these traits. Heritability for CIN in the single-trait model was low (0.06 ± 0.002). Unfavorable genetic correlations were found between CIN and production traits. A measure of LPE was derived using principal component analysis on test day records. The heritability and repeatability of LPE were 0.11 ± 0.004 and 0.20 ± 0.02, respectively. Genetic correlation between CIN and LPE was weak but had a favorable direction. Despite the low heritability estimates, results of the present work suggest the possibility of including these traits in the Italian Simmental breeding program. The use of a single-step approach may provide better results for young genotyped animals without their own phenotypes.

Genetic Parameters for Tolerance to Heat Stress in Crossbred Swine Carcass Traits.

Data for loin and backfat depth, as well as carcass growth of 126,051 three-way crossbred pigs raised between 2015 and 2019, were combined with climate records of air temperature, relative humidity, and temperature-humidity index. Environmental covariates with the largest impact on the studied traits were incorporated in a random regression model that also included genomic information. Genetic control of tolerance to heat stress and the presence of genotype by environment interaction were detected. Its magnitude was more substantial for loin depth and carcass growth, but all the traits studied showed a different impact of heat stress and different magnitude of genotype by environment interaction. For backfat depth, heritability was larger under comfortable conditions (no heat stress), as compared to heat stress conditions. Genetic correlations between extreme values of environmental conditions were lower (∼0.5 to negative) for growth and loin depth. Based on the solutions obtained from the model, sires were ranked on their breeding value for general performance and tolerance to heat stress. Antagonism between overall performance and tolerance to heat stress was moderate. Still, the models tested can provide valuable information to identify genetic material that is resilient and can perform equally when environmental conditions change. Overall, the results obtained from this study suggest the existence of genotype by environment interaction for carcass traits, as a possible genetic contributor to heat tolerance in swine.

Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression.

The objectives of this study were (i) the prediction of sheep milk coagulation properties (MCP) and individual laboratory cheese yield (ILCY) from mid-infrared (MIR) spectra by using partial least squares (PLS) regression, and (ii) the comparison of different data pre-treatments on prediction accuracy. Individual milk samples of 970 Sarda breed ewes were analyzed for rennet coagulation time (RCT), curd-firming time (k20), and curd firmness (a30) using the Formagraph instrument; ILCY was measured by micro-manufacturing assays. An Furier-transform Infrared (FTIR) milk-analyzer was used for the estimation of the milk gross composition and the recording of MIR spectrum. The dataset (n = 859, after the exclusion of 111 noncoagulating samples) was divided into two sub-datasets: the data of 700 ewes were used to estimate prediction model parameters, and the data of 159 ewes were used to validate the model. Four prediction scenarios were compared in the validation, differing for the use of whole or reduced MIR spectrum and the use of raw or corrected data (locally weighted scatterplot smoothing). PLS prediction statistics were moderate. The use of the reduced MIR spectrum yielded the best results for the considered traits, whereas the data correction improved the prediction ability only when the whole MIR spectrum was used. In conclusion, PLS achieves good accuracy of prediction, in particular for ILCY and RCT, and it may enable increasing the number of traits to be included in breeding programs for dairy sheep without additional costs and logistics.