Development of ketosis in high-producing dairy cows contributes to several animal health issues and highlights the need for a better understanding of the genetic basis of metabolic diseases. To evaluate the pattern of differential gene expression in the liver of cows under negative energy balance (NEB), and under subclinical and clinical ketosis, a meta-analysis of gene expression and genome-wide association studies results was performed. An initial systematic review identified 118 articles based on the key words "cow," "liver," "negative energy balance," "ketosis," "expression," "qPCR," "microarray," "proteomic," "RNA-Seq," and "GWAS." After further screening for only peer-reviewed and pertinent articles for gene expression during NEB and clinical and subclinical ketosis (considering plasma levels of β-hydroxybutyrate), 20 articles were included in the analysis. From the systematic review, 430 significant SNPs identified by genome-wide association studies (GWAS) were assigned to genes reported in gene expression studies by considering chromosome and base pair positions in the ARS-UCD 1.2 bovine assembly. Venn diagrams were created to integrate the data obtained in the systematic review, and Gene Ontology enrichment analysis was carried out using official gene names. A QTL enrichment analysis was also performed to identify potential positional candidate loci. Twenty-four significant SNPs were located within the coordinates of differentially expressed genes located on chromosomes 2, 3, 6, 9, 11, 14, 27, and 29. Three significant metabolic pathways were associated with NEB and subclinical and clinical ketosis. In addition, 2 important genes, PPARA (peroxisome proliferator activated receptor alpha) and ACACA (acetyl-coenzyme A carboxylase α), were identified, which were differentially expressed in the 3 metabolic conditions. The PPARA gene is involved in the regulation of lipid metabolism and fatty liver disease and the ACACA gene encodes an enzyme that catalyzes the carboxylation of acetyl-coenzyme A to malonyl-coenzyme A, which is a rate-limiting step in fatty acid synthesis. Gene network analysis revealed co-expression interactions among 34 genes associated with functions involving fatty acid transport and fatty acid metabolism. For the annotated QTL, 9 QTL were identified for ketosis. The genes FN1 (fibronectin 1) and PTK2 (protein tyrosine kinase 2), which are mainly involved in cell adhesion and formation of extracellular matrix constituents, were enriched for QTL previously associated with the trait "ketosis" on chromosome 2 and for the trait "milk iron content" on chromosome 14, respectively. This integration of gene expression and GWAS data provides an additional understanding of the genetic background of NEB and subclinical and clinical ketosis in dairy cattle. Thus, it is a useful approach to identify biological mechanisms underlying these metabolic conditions in dairy cattle.

The aim of this study was to identify novel lncRNA differentially expressed (DE) between divergent animals for beef tenderness and marbling traits in Nellore cattle. Longissimus thoracis muscle samples from the 20 most extreme bulls (of 80 bulls set) for tenderness, tender (n = 10) and tough (n = 10) groups, and marbling trait, high (n = 10) and low (n = 10) groups were used to perform transcriptomic analysis using RNA‐Sequencing. For tenderness, 29 lncRNA were DE (p‐value ≤ 0.01) in tough beef animals in relation to tender beef animals. We observed that genic lncRNAs, for example, lncRNA_595.1, were overlapping exonic part of the PICK gene, while lncRNA_3097.2 and lncRNA_3129.5 overlapped intronic part of the genes GADL1 and PSMD6. The lncRNA associated with PICK1, GADL1, and PMD6 genes were enriched in the pathways associated with the ionotropic glutamate receptor, gamma‐aminobutyric acid synthesis, and the ubiquitin–proteasome pathway. For marbling, 50 lncRNA were DE (p‐value ≤ 0.01) in high marbling group compared with low marbling animals. The genic lncRNAs, such as lncRNA_3191.1, were overlapped exonic part of the ITGAL gene, and the lncRNA_512.1, lncRNA_3721.1, and lncRNA_41.4 overlapped intronic parts of the KRAS and MASP1 genes. The KRAS and ITGAL genes were enriched in pathways associated with integrin signaling, which is involved in intracellular signals in response to the extracellular matrix, including cell form, mobility, and mediates progression through the cell cycle. In addition, the lincRNAs identified to marbling trait were associated with several genes related to calcium binding, muscle hypertrophy, skeletal muscle, lipase, and oxidative stress response pathways that seem to play a role important in the physiological processes related to meat quality. These findings bring new insights to better understand the biology mechanisms involved in the gene regulation of these traits, which will be valuable for a further investigation of the interactions between lncRNA and mRNAs, and of how these interactions may affect meat quality traits.

Whole-genome alignment (WGA) is a critical process in comparative genomics, facilitating the detection of genetic variants and aiding our understanding of evolution. This paper offers a detailed overview and categorization of WGA techniques, encompassing suffix tree-based, hash-based, anchor-based, and graph-based methods. It elaborates on the algorithmic properties of these tools, focusing on performance and methodological aspects. This paper underscores the latest progress in WGA, emphasizing the increasing capacity to manage the growing intricacy and volume of genomic data. However, the field still grapples with computational and biological hurdles affecting the precision and speed of WGA. We explore these challenges and potential future solutions. This paper aims to provide a comprehensive resource for researchers, deepening our understanding of WGA tools and their applications, constraints, and prospects.

The aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content. A total of 30 transcriptomics datasets (RNA-Seq) obtained from longissimus thoracis muscle were selected based on the phenotypic value of divergent intramuscular fat content: 15 with the highest intramuscular fat content (HIF) and 15 with the lowest intramuscular fat content (LIF). The transcriptomics datasets were aligned with a reference genome and 65 differentially expressed genes (DEGs) were identified, including 21 upregulated and 44 downregulated genes in HIF animals. The normalized count data from DEGs was then used for co-expression network construction. From the co-expression network, four modules were identified. The topological properties of the network were analyzed; those genes engaging in the most interactions (maximal clique centrality method) with other DEGs were predicted to be hub genes (PDE4D, KLHL30 and IL1RAP), which consequently may play a role in cellular and/or systemic lipid biology in Nelore cattle. Top modules screened from the gene co-expression network were identify. The two candidate modules had clear associated biological pathways related to fat development, cell adhesion, and muscle differentiation, immune system, among others. The hub genes belonged in top modules and were downregulated in HIF animals. PDE4D and IL1RAP have known effects on lipid metabolism and the immune system through the regulation of cAMP signaling. Given that cAMP is known to play a role in lipid systems, PDE4D and IL1RAP downregulation may contribute to increased levels of intracellular cAMP and thus may have effects on IF content differences in Nelore cattle. KLHL30 may have effects on muscle metabolism. Klhl protein families play a role in protein degradation. However, the downregulation of this gene and its role in lipid metabolism has not yet been clarified. The results reported in this study indicate candidate genes and molecular mechanisms involved in IF content difference in Nelore cattle.