Prediction of detailed blood metabolic profile using milk infrared spectra and machine learning methods in dairy cattle.

The adoption of preventive management decisions is crucial to dealing with metabolic impairments in dairy cattle. Various serum metabolites are known to be useful indicators of the health status of cows. In this study, we used milk Fourier-transform mid-infrared (FTIR) spectra and various machine learning (ML) algorithms to develop prediction equations for a panel of 29 blood metabolites, including those related to energy metabolism, liver function/hepatic damage, oxidative stress, inflammation/innate immunity, and minerals. For most traits, the data set comprised observations from 1,204 Holstein-Friesian dairy cows belonging to 5 herds. An exception was represented by ß-hydroxybutyrate prediction, which contained observations from 2,701 multibreed cows pertaining to 33 herds. The best predictive model was developed using an automatic ML algorithm that tested various methods, including elastic net, distributed random forest, gradient boosting machine, artificial neural network, and stacking ensemble. These ML predictions were compared with partial least squares regression, the most commonly used method for FTIR prediction of blood traits. Performance of each model was evaluated using 2 cross-validation (CV) scenarios: 5-fold random (CVr) and herd-out (CVh). We also tested the best model's ability to classify values precisely in the 2 extreme tails, namely, the 25th (Q25) and 75th (Q75) percentiles (true-positive prediction scenario). Compared with partial least squares regression, ML algorithms achieved more accurate performance. Specifically, elastic net increased the R2 value from 5% to 75% for CVr and 2% to 139% for CVh, whereas the stacking ensemble increased the R2 value from 4% to 70% for CVr and 4% to 150% for CVh. Considering the best model, with the CVr scenario, good prediction accuracies were obtained for glucose (R2 = 0.81), urea (R2 = 0.73), albumin (R2 = 0.75), total reactive oxygen metabolites (R2 = 0.79), total thiol groups (R2 = 0.76), ceruloplasmin (R2 = 0.74), total proteins (R2 = 0.81), globulins (R2 = 0.87), and Na (R2 = 0.72). Good prediction accuracy in classifying extreme values was achieved for glucose (Q25 = 70.8%, Q75 = 69.9%), albumin (Q25 = 72.3%), total reactive oxygen metabolites (Q25 = 75.1%, Q75 = 74%), thiol groups (Q75 = 70.4%), total proteins (Q25 = 72.4%, Q75 = 77.2.%), globulins (Q25 = 74.8%, Q75 = 81.5%), and haptoglobin (Q75 = 74.4%). In conclusion, our study shows that FTIR spectra can be used to predict blood metabolites with relatively good accuracy, depending on trait, and are a promising tool for large-scale monitoring.

Integrative analysis of methylomic and transcriptomic data in fetal sheep muscle tissues in response to maternal diet during pregnancy.

BACKGROUND: Numerous studies have established a link between maternal diet and the physiological and metabolic phenotypes of their offspring. In previous studies in sheep, we demonstrated that different maternal diets altered the transcriptome of fetal tissues. However, the mechanisms underlying transcriptomic changes are poorly understood. DNA methylation is an epigenetic mark regulating transcription and is largely influenced by dietary components of the one-carbon cycle that generate the methyl group donor, SAM. Therefore, in the present study, we tested whether different maternal diets during pregnancy would alter the DNA methylation and gene expression patterns in fetal tissues. RESULTS: Pregnant ewes were randomly divided into two groups which received either hay or corn diet from mid-gestation (day 67 ± 5) until day 131 ± 1 when fetuses were collected by necropsy. A total of 1516 fetal longissimus dorsi (LD) tissues were used for DNA methylation analysis and gene expression profiling. Whole genome DNA methylation using methyl-binding domain enrichment analysis revealed 60 differentially methylated regions (DMRs) between hay and corn fetuses with 39 DMRs more highly methylated in the hay fetuses vs. 21 DMRs more highly methylated in the corn fetuses. Three DMRs (LPAR3, PLIN5-PLIN4, and the differential methylation of a novel lincRNA) were validated using bisulfite sequencing. These DMRs were associated with differential gene expression. Additionally, significant DNA methylation differences were found at the single CpG level. Integrative methylome and transcriptome analysis revealed an association between gene expression and inter-/intragenic methylated regions. Furthermore, intragenic DMRs were found to be associated with expression of neighboring genes. CONCLUSIONS: The findings of this study imply that maternal diet from mid- to late-gestation can shape the epigenome and the transcriptome of fetal tissues, and putatively affect phenotypes of the lambs.

Distribution of ncRNAs expression across hypothalamic-pituitary-gonadal axis in Capra hircus.

BACKGROUND: Molecular regulation of the hypothalamic-pituitary-gonadal (HPG) axis plays an essential role in the fine tuning of seasonal estrus in Capra hircus. Noncoding RNAs (ncRNAs) are emerging as key regulators in sexual development and mammalian reproduction. In order to identify ncRNAs and to assess their expression patterns, along the HPG axis, we sequenced ncRNA libraries from hypothalamus, pituitary and ovary of three goats. RESULTS: Among the medium length noncoding RNAs (mncRNAs) identified, small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs) were found to be more abundant in ovary and hypothalamus, respectively. The observed GC content was representative for different classes of ncRNAs, allowing the identification of a tRNA-derived RNA fragments (tRFs) subclass, which had a peak distribution around 32-38% GC content in the hypothalamus. Differences observed among organs confirmed the specificity of microRNA (miRNA) profiles for each organ system. CONCLUSIONS: Data on ncRNAs in organs constituting the HPG axis will contribute to understanding their role in the physiological regulation of reproduction in goats.

Synergies between assisted reproduction technologies and functional genomics.

This review, is a synopsis of advanced reproductive technologies in farm animals, including the discussion of their limiting factors as revealed by the study of offspring derived from embryos produced in vitro and through cloning. These studies show that the problems of epigenetic mis-programming, which were reported in the initial stages of assisted reproduction, still persist. The importance of whole-genome analyses, including the methylome and transcriptome, in improving embryo biotechnologies in farm animals, are discussed. Genome editing approaches for the improvement of economically-relevant traits in farm animals are also described. Efficient farm animal embryo biotechnologies, including cloning and the most recent technologies such as genome editing, will effectively complement the latest strategies to accelerate genetic improvement of farm animals.

Use of canonical discriminant analysis to study signatures of selection in cattle.

BACKGROUND: Cattle include a large number of breeds that are characterized by marked phenotypic differences and thus constitute a valuable model to study genome evolution in response to processes such as selection and domestication. Detection of "signatures of selection" is a useful approach to study the evolutionary pressures experienced throughout history. In the present study, signatures of selection were investigated in five cattle breeds farmed in Italy using a multivariate approach. METHODS: A total of 4094 bulls from five breeds with different production aptitudes (two dairy breeds: Italian Holstein and Italian Brown Swiss; two beef breeds: Piemontese and Marchigiana; and one dual purpose breed: Italian Simmental) were genotyped using the Illumina BovineSNP50 v.1 beadchip. Canonical discriminant analysis was carried out on the matrix of single nucleotide polymorphisms (SNP) genotyping data, separately for each chromosome. Scores for each canonical variable were calculated and then plotted in the canonical space to quantify the distance between breeds. SNPs for which the correlation with the canonical variable was in the 99th percentile for a specific chromosome were considered to be significantly associated with that variable. Results were compared with those obtained using an FST-based approach. RESULTS: Based on the results of the canonical discriminant analysis, a large number of signatures of selection were detected, among which several had strong signals in genomic regions that harbour genes known to have an impact on production and morphological bovine traits, including MSTN, LCT, GHR, SCD, NCAPG, KIT, and ASIP. Moreover, new putative candidate genes were identified, such as GCK, B3GALNT1, MGAT1, GALNTL1, PRNP, and PRND. Similar results were obtained with the FST-based approach. CONCLUSIONS: The use of canonical discriminant analysis on 50 K SNP genotypes allowed the extraction of new variables that maximize the separation between breeds. This approach is quite straightforward, it can compare more than two groups simultaneously, and relative distances between breeds can be visualized. The genes that were highlighted in the canonical discriminant analysis were in concordance with those obtained using the FST index.

Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel.

In this study we used a medium density panel of SNP markers to perform population genetic analysis in five Italian cattle breeds. The BovineSNP50 BeadChip was used to genotype a total of 2,935 bulls of Piedmontese, Marchigiana, Italian Holstein, Italian Brown and Italian Pezzata Rossa breeds. To determine a genome-wide pattern of positive selection we mapped the F st values against genome location. The highest F st peaks were obtained on BTA6 and BTA13 where some candidate genes are located. We identified selection signatures peculiar of each breed which suggest selection for genes involved in milk or meat traits. The genetic structure was investigated by using a multidimensional scaling of the genetic distance matrix and a Bayesian approach implemented in the STRUCTURE software. The genotyping data showed a clear partitioning of the cattle genetic diversity into distinct breeds if a number of clusters equal to the number of populations were given. Assuming a lower number of clusters beef breeds group together. Both methods showed all five breeds separated in well defined clusters and the Bayesian approach assigned individuals to the breed of origin. The work is of interest not only because it enriches the knowledge on the process of evolution but also because the results generated could have implications for selective breeding programs.

Genetic diversity in widespread species is not congruent with species richness in alpine plant communities.

The Convention on Biological Diversity (CBD) aims at the conservation of all three levels of biodiversity, that is, ecosystems, species and genes. Genetic diversity represents evolutionary potential and is important for ecosystem functioning. Unfortunately, genetic diversity in natural populations is hardly considered in conservation strategies because it is difficult to measure and has been hypothesised to co-vary with species richness. This means that species richness is taken as a surrogate of genetic diversity in conservation planning, though their relationship has not been properly evaluated. We tested whether the genetic and species levels of biodiversity co-vary, using a large-scale and multi-species approach. We chose the high-mountain flora of the Alps and the Carpathians as study systems and demonstrate that species richness and genetic diversity are not correlated. Species richness thus cannot act as a surrogate for genetic diversity. Our results have important consequences for implementing the CBD when designing conservation strategies.

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.

Landscape genomics and biased FST approaches reveal single nucleotide polymorphisms under selection in goat breeds of North-East Mediterranean.

BACKGROUND: In this study we compare outlier loci detected using a FST based method with those identified by a recently described method based on spatial analysis (SAM). We tested a panel of single nucleotide polymorphisms (SNPs) previously genotyped in individuals of goat breeds of southern areas of the Mediterranean basin (Italy, Greece and Albania). We evaluate how the SAM method performs with SNPs, which are increasingly employed due to their high number, low cost and easy of scoring. RESULTS: The combined use of the two outlier detection approaches, never tested before using SNP polymorphisms, resulted in the identification of the same three loci involved in milk and meat quality data by using the two methods, while the FST based method identified 3 more loci as under selection sweep in the breeds examined. CONCLUSION: Data appear congruent by using the two methods for FST values exceeding the 99% confidence limits. The methods of FST and SAM can independently detect signatures of selection and therefore can reduce the probability of finding false positives if employed together. The outlier loci identified in this study could indicate adaptive variation in the analysed species, characterized by a large range of climatic conditions in the rearing areas and by a history of intense trade, that implies plasticity in adapting to new environments.

Mitochondrial DNA of seven Italian sheep breeds shows faint signatures of domestication and suggests recent breed formation.

Italy represented a crucial zone for migration and formation of sheep breeds. However, few data on Italian breeds have been published so far. We analysed seven Italian sheep breeds using mitochondrial DNA (mtDNA) sequencing to gain information on their genetic diversity and history. A 721 bp mtDNA control region fragment was amplified and sequenced in a total of 138 samples belonging to seven breeds and to Italian mohuflon (Ovis orientalis musimon) to investigate genetic diversity and phylogenetic evolution. We retrieved 68 variable sites and 79 haplotypes. The sheep breeds in our study are quite diverse, and phylogenetic analyses resulted in 3.6% of the samples belonging to A, 2.2% to D and 94.2% to B mtDNA haplogroups. Principal Component Analysis (PCA) showed a separation of breeds on both dimensions. The results of this study provide data on Italian breeds, presently scarcely investigated, and contribute to the knowledge of Italian sheep breeds and will be useful to the understanding of population genetics and breed evolution.

The nutrigenomic investigation of C57BL/6N mice fed a short-term high-fat diet highlights early changes in clock genes expression.

Mice fed long-term high-fat diets (HFD) are an established model for human metabolic disorders, such as obesity and diabetes. However, also the effects of short-term HFD feeding should be investigated to understand which are the first events that trigger the onset of a pre-disease condition, the so-called metabolic syndrome, that increases the risk of developing clinical diseases. In this study, C57BL/6N mice were fed a control diet (CTR) or a HFD for 1 (T1) or 2 weeks (T2). Metabolic and histological effects were examined. Cecum transcriptomes of HFD and CTR mice were compared at T2 by microarray analysis. Differentially expressed genes were validated by real-time PCR in the cecum and in the liver. After 2 weeks of diet administration, HFD mice showed an altered expression pattern in only seven genes, four of which are involved in the circadian clock regulatory pathway. Real-time PCR confirmed microarray results of the cecum and revealed the same trend of clock gene expression changes in the liver. These findings suggest that clock genes may play an important role in early controlling gut output systems in response to HFD in mice and that their expression change may also represent an early signaling of the development of an intestinal pro-inflammatory status.

Double muscling in Marchigiana beef breed is caused by a stop codon in the third exon of myostatin gene.

Double muscling is a partially recessive trait present in some beef breeds. It shows a high frequency in some breeds, while in others the frequency is low, and double-muscled individuals are rare. The double muscling is caused by an allelic series of mutations that cause a loss of function of the myostatin gene ( GDF8). We describe here a new mutation in the myostatin gene in Marchigiana breed, a typical beef breed of Central Italy, in which rare double-muscling individuals have been described. A PCR product of the third exon was sequenced in subjects phenotypically showing double muscling, and a G > T transversion was discovered that introduces a premature stop codon. The variant found adds to the large series of mutations present in cattle, and particularly to the only two causative of double muscling in the third exon. A PCR-RFLP test is described for the rapid and effective identification of both heterozygous and homozygous subjects. It was applied to a larger survey carried on the same and also in two other beef breeds, Chianina and Romagnola. Further individuals carrying the new variant were found in Marchigiana, but none in the other breeds. The results may be important for a better comprehension of the role of myostatin in muscular development, for commercial use and for the inference of phylogeny of this gene.