Combinatorial Discriminant Analysis Applied to RNAseq Data Reveals a Set of 10 Transcripts as Signatures of Exposure of Cattle to Mycobacterium avium subsp. paratuberculosis

Whole-genome resequencing deciphers patterns of genetic diversity, phylogeny, and evolutionary dynamics in Kashmir cattle

Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattle breed remain elusive. This study utilized whole genome sequences of Kashmir cattle (n = 20; newly sequenced) alongside published whole genomes of 32 distinct breeds and seven core cattle populations (n = 135). The analysis identified ~25.87 million biallelic single nucleotide polymorphisms in Kashmir cattle, predominantly in intergenic and intron regions. Population structure analyses revealed distinct clustering patterns of Kashmir cattle with proximity to the South Asian, African and Chinese indicine cattle populations. Genetic diversity analysis of Kashmir cattle demonstrated lower inbreeding and greater nucleotide diversity than analyzed global breeds. Homozygosity runs indicated less consanguineous mating in Kashmir cattle compared with European taurine breeds. Furthermore, six selection sweep detection methods were used within Kashmir cattle and other cattle populations to identify genes associated with vital traits, including immunity (BOLA-DQA5, BOLA-DQB, TNFAIP8L, FCRL4, AOAH, HIF1AN, FBXL3, MPEG1, CDC40, etc.), reproduction (GOLGA4, BRWD1, OSBP2, LEO1 ADCY5, etc.), growth (ADPRHL1, NRG2, TCF12, TMOD4, GBP4, IGF2, RSPO3, SCD, etc.), milk composition (MRPS30 and CSF1) and high-altitude adaptation (EDNRA, ITPR2, AGBL4 and SCG3). These findings provide essential genetic insights into the characteristics and establish the foundation for the scientific conservation and utilization of Kashmir cattle breed.

Comparative Characterization of Immune Response in Sheep with Caseous Lymphadenitis through Analysis of the Whole Blood Transcriptome

Caseous lymphadenitis (CL) is a chronic contagious disease that affects small ruminants and is characterized by the formation of pyogranulomas in lymph nodes and other organs. However, the pathogenesis of this disease and the response of the host genome to infection are not yet fully understood. This study aimed to investigate the whole blood transcriptome and evaluate differential gene expression during the later stages of CL in naturally infected ewes. The study included diseased, serologically positive (EP), exposed, serologically negative (EN) ewes from the same infected flock and healthy ewes (CN) from a different flock. RNA sequencing was performed using the Illumina NextSeq system, and differential gene expression was estimated using DESeq2 and Edge R approaches. The analysis identified 191 annotated differentially expressed genes (DEGs) in the EP group (102 upregulated and 89 downregulated) and 256 DEGs in the EN group (106 upregulated and 150 downregulated) compared to the CN group. Numerous immunoregulatory interactions between lymphoid and nonlymphoid cells were influenced in both EP and EN ewes. Immune DEGs were preferentially assigned to antigen presentation through the MHC complex, T lymphocyte-mediated immunity, and extracellular matrix interactions. Furthermore, the EP group showed altered regulation of cytokine and chemokine signaling and activation and recombination of B-cell receptors. Conversely, NF-kappa B signaling, apoptosis, and stress response were the main processes influenced in the EN group. In addition, statistically significant enrichment of the essential immune pathways of binding and uptake of ligands by scavenger receptors in EP and p53 signaling in the EN group was found. In conclusion, this study provides new insights into the disease course and host-pathogen interaction in naturally CL-infected sheep by investigating the blood transcriptome.

Genome-wide association study for antibody response to Mycobacterium avium ssp. paratubeculosis in goats

Mycobacterium avium ssp. paratuberculosis (MAP), causes Johne's disease (JD), or paratuberculosis, a chronic enteritis of ruminants, which in goats is characterized by ileal lesions. The work described here is a case-control association study using the Illumina Caprine SNP50 BeadChip to unravel the genes involved in susceptibility of goats to JD. Goats in herds with a high occurrence of Johne's disease were classified as healthy or infected based on the level of serum antibodies against MAP, and 331 animals were selected for the association study. Goats belonged to the Jonica (157) and Siriana breeds (174). Whole-genome association analysis identified one region suggestive of significance associated with an antibody response to MAP on chromosome 7 (p-value = 1.23 × 10^-5 ). These results provide evidence for genetic loci involved in the antibody response to MAP in goats.

A network approach for low dimensional signatures from high throughput data

One of the main objectives of high-throughput genomics studies is to obtain a low-dimensional set of observables-a signature-for sample classification purposes (diagnosis, prognosis, stratification). Biological data, such as gene or protein expression, are commonly characterized by an up/down regulation behavior, for which discriminant-based methods could perform with high accuracy and easy interpretability. To obtain the most out of these methods features selection is even more critical, but it is known to be a NP-hard problem, and thus most feature selection approaches focuses on one feature at the time (k-best, Sequential Feature Selection, recursive feature elimination). We propose DNetPRO, Discriminant Analysis with Network PROcessing, a supervised network-based signature identification method. This method implements a network-based heuristic to generate one or more signatures out of the best performing feature pairs. The algorithm is easily scalable, allowing efficient computing for high number of observables ([Formula: see text]-[Formula: see text]). We show applications on real high-throughput genomic datasets in which our method outperforms existing results, or is compatible with them but with a smaller number of selected features. Moreover, the geometrical simplicity of the resulting class-separation surfaces allows a clearer interpretation of the obtained signatures in comparison to nonlinear classification models.

Using Omics Approaches in the Discovery of Biomarkers for Early Diagnosis of Johne's Disease in Sheep and Goats

Simple Summary

Johne’s disease (JD) is caused by Mycobacterium avium subsp. paratuberculosis (MAP) and is an important and emerging problem in livestock. Most JD research has been carried out on cattle, but interest in the pathogenesis and diagnosis of this disease in sheep and goats is greatest in developing countries. Sheep and goats are also a relevant part of livestock production in Europe and Australia, and these species provide an excellent resource to study and better understand the mechanism of survival of MAP and gain insights into possible approaches to control this disease. This review gives an overview of the literature on paratuberculosis in sheep and goats, highlighting the immunological aspects and the potential for “omics” approaches to identify effective biomarkers for the early detection of infection.

Abstract

Johne’s disease (JD) is caused by Mycobacterium avium subsp. paratuberculosis (MAP) and is an important and emerging problem in livestock; therefore, its control and prevention is a priority to reduce economic losses and health risks. Most JD research has been carried out on cattle, but interest in the pathogenesis and diagnosis of this disease in sheep and goats is greatest in developing countries. Sheep and goats are also a relevant part of livestock production in Europe and Australia, and these species provide an excellent resource to study and better understand the mechanism of survival of MAP and gain insights into possible approaches to control this disease. This review gives an overview of the literature on paratuberculosis in sheep and goats, highlighting the immunological aspects and the potential for “omics” approaches to identify effective biomarkers for the early detection of infection. As JD has a long incubation period before the disease becomes evident, early diagnosis is important to control the spread of the disease.