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Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by two metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced datasets were investigated using four machine-learning algorithms and a multivariate regression method. The Orthogonal Partial Least Square algorithm outperformed other ML algorithms for the FCR prediction in the scenarios using the complete milk metabolite signature (r2=0.62±0.06) and the 26 selected features (0.62±0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the Multilayer feedforward artificial neural network (r2=0.18±0.14) and extreme gradient boosting (r2=0.17±0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared to the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

One of the most promising strategies of Pine Pitch Canker (PPC) management is the use of reproductive plant material resistant to the disease. Understanding the complexity of plant transcriptome that underlies the defence to the causal agent Fusarium circinatum, would greatly facilitate the development of an accurate breeding program. Long non-coding RNAs (lncRNAs) are emerging as important transcriptional regulators under biotic stresses in plants. However, to date, characterization of lncRNAs in conifer trees has not been reported. In this study, transcriptomic identification of lncRNAs was carried out using strand-specific paired-end RNA sequencing, from Pinus radiata samples inoculated with F. circinatum at an early stage of infection.

As higher feed efficiency in dairy ruminants means a higher capability to transform feed nutrients into milk and milk components, dierences in feed efficiency are expected to be partly linked to changes in the physiology of the mammary glands. Therefore, this study aimed to determine the biological functions and key regulatory genes associated with feed efficiency in dairy sheep using the milk somatic cell transcriptom

Optimization of an RNA-Sequencing (RNA-Seq) pipeline is critical to maximize power and accuracy to identify genetic variants, including SNPs, which may serve as genetic markers to select for feed efficiency, leading to economic benefits for beef production. This study used RNA-Seq data (GEO Accession ID: PRJEB7696 and PRJEB15314) from muscle and liver tissue, respectively, from 12 Nellore beef steers selected from 585 steers with residual feed intake measures (RFI; n = 6 low-RFI, n = 6 high-RFI). Three RNA-Seq pipelines were compared including multi-sample calling from i) non-merged samples; ii) merged samples by RFI group, iii) merged samples by RFI and tissue group. The RNA-Seq reads were aligned against the UMD3.1 bovine reference genome (release 94) assembly using STAR aligner. Variants were called using BCFtools and variant effect prediction (VeP) and functional annotation (ToppGene) analyses were performed.

In dairy sheep flocks from Mediterranean countries, replacement and adult ewes are the animals most affected by gastrointestinal nematode (GIN) infections. In this study, we have exploited the information derived from an RNA-Seq experiment with the aim of identifying potential causal mutations related to GIN resistance in sheep. Considering the RNA-Seq samples from 12 ewes previously classified as six resistant and six susceptible animals to experimental infection by Teladorsagia circumcincta, we performed a variant calling analysis pipeline using two different types of software, gatk version 3.7 and Samtools version 1.4. The variants commonly identified by the two packages (high-quality variants) within two types of target regions – (i) QTL regions previously reported in sheep for parasite resistance based on SNP-chip or sequencing technology studies and (ii) functional candidate genes selected from gene expression studies related to GIN resistance in sheep – were further characterised to identify mutations with a potential functional impact. Among the genes harbouring these potential functional variants (930 and 553 respectively for the two types of regions), we identified 111 immune-related genes in the QTL regions and 132 immune-related genes from the initially selected candidate genes. For these immune-related genes harbouring potential functional variants, the enrichment analyses performed highlighted significant GO terms related to apoptosis, adhesion and inflammatory response, in relation to the QTL related variants, and significant disease-related terms such as inflammation, adhesion and necrosis, in relation to the initial candidate gene list. Overall, the study provides a valuable list of potential causal mutations that could be considered as candidate causal mutations in relation to GIN resistance in sheep. Future studies should assess the role of these suggested mutations with the aim of identifying genetic markers that could be directly implemented in

El objetivo general de esta Tesis Doctoral ha sido utilizar las herramientas genómicas disponibles en el estudio de caracteres de importancia económica en el ganado ovino lechero. En concreto, utilizar el OvineSNP50 BeadChip en el mapeo de regiones portadoras de mutaciones causales de enfermedades de herencia mendeliana y utilizar las herramientas de secuenciación masiva paralela en la caracterización de la mutación causal de enfermedades monogénicas y del transcriptoma de la glándula mamaria de la oveja en lactación. Este trabajo ofrece una visión global del transcriptoma mamario de la oveja en lactación, proporcionando información para el desarrollo de futuros análisis detallados de los genes implicados en las rutas significativas detectadas, relacionadas a priori con caracteres productivos, así como el análisis funcional de transcritos no anotados en el genoma de referencia o la identificación de variantes relacionadas con caracteres productivos de interés

Este proyecto trata de estudiar el transcriptoma de los tejidos de mayor importancia durante la respuesta inmune de ovejas adultas ante la infección por nematodos gastrointestinales, la mucosa abomasal y los ganglios abomasales. El transcriptoma es el conjunto completo de todos los transcritos (regiones del DNA que pasan a RNA mensajero, o mRNA) de una célula, y su cuantificación en un momento fisiológico específico. La identificación de genes diferencialmente expresados en los tejidos afectados por la infección entre ovejas susceptibles y resistentes es un primer paso para la identificación de genes y rutas génicas involucradas en la resistencia/susceptibilidad a este tipo de infecciones. Esta comunicación es el resultado de la investigación dentro del Proyecto: “Análisis del transcriptoma de la mucosa y los ganglios abomasales para la identificación de genes involucrados en la resistencia a los nematodos gastrointestinales en ovejas adultas”. Financiado por la Junta de Castilla y León (Conserjería de Educación) y Fondo Social Europeo (Ref. LE248U14). Ejecución: Universidad de León. Dpto. Producción Animal. Investigador Principal: Dr. Beatriz Gutierrez Gil

Milk fat depression (MFD) is characterized by a reduction in the content of milk fat, presumably caused by the anti-lipogenic effects of rumen biohydrogenation intermediates, such as trans-10 cis-12 conjugated linoleic acid (CLA). In this study, RNA-Seq technology was used to help elucidate the mammary responses involved in CLA-induced MFD in lactating ewes. To this end, we compared the milk somatic cell transcriptome of ewes suffering from CLA-induced MFD with control ewes (i.e., those without MFD), as well as with ewes fed a diet supplemented with fish oil (FO-MFD) that we previously reported affects the mammary transcriptome. In the differential expression analysis between CLA-MFD and controls, we identified 1,524 differentially expressed genes (DEGs), whereas 653 were detected between CLA- and FO-MFD groups. Although this article focuses on lipid metabolism, CLA affected the expression of many genes related to other biological processes, especially immunity. Among the 55 genes shared by both MFD conditions, some genes linked to fatty acid synthesis, such as ACACA, AACS, ACSS2, or ACSS3, were downregulated. In addition, this study provides a list of candidate genes that are not usually considered in the nutrigenomics of MFD but that may act as key regulators of this syndrome in dairy ewes.