Porcine reproductive and respiratory syndrome virus (PRRSV) infection is the most important viral disease causing severe economic losses in the swine industry. However, mechanisms underlying gene expression control in immunity-responsible tissues at different time points during PRRSV infection are poorly understood. We constructed an integrated gene co-expression network and identified tissue- and time-dependent biological mechanisms of PRRSV infection through bioinformatics analysis using three tissues (lungs, bronchial lymph nodes [BLNs], and tonsils) via RNA-Seq. Three groups with specific expression patterns (i.e., the 3-dpi, lung, and BLN groups) were discovered. The 3 dpi-specific group showed antiviral and innate-immune signalling similar to the case for influenza A infection. Moreover, we observed adaptive immune responses in the lung-specific group based on various cytokines, while the BLN-specific group showed down-regulated AMPK signalling related to viral replication. Our study may provide comprehensive insights into PRRSV infection, as well as useful information for vaccine development.

Genome-wide studies provide considerable insights into the genetic background of animals; however, the inheritance of several heritable factors cannot be elucidated. Epigenetics explains these heritabilities, including those of genes influenced by environmental factors. Knowledge of the mechanisms underlying epigenetics enables understanding the processes of gene regulation through interactions with the environment. Recently developed next-generation sequencing (NGS) technologies help understand the interactional changes in epigenetic mechanisms. There are large sets of NGS data available; however, the integrative data analysis approaches still have limitations with regard to reliably interpreting the epigenetic changes. This review focuses on the epigenetic mechanisms and profiling methods and multi-omics integration methods that can provide comprehensive biological insights in animal genetic studies.

Bisphenol A (BPA) is a very important chemical from the commercial perspective. Many useful products are made from it, so its production is increasing day by day. It is widely known that Bisphenol A (BPA) and its analogs are present in the environment and that they enter our body through various routes on a daily basis as we use things made of this chemical in our daily lives. BPA has already been reported to be an endocrine disruptor. Studies have shown that BPA binds strongly to the human estrogen-related receptor gamma (ERRγ) and is an important target of it. This study seeks to understand how it interacts with ERRγ. Molecular docking of BPA and its analogs with ERRγ was performed, and estradiol was taken as a reference. Then, physico-chemical and toxicological analysis of BPA compounds was performed. Subsequently, the dynamic behavior of ERRγ and ERRγ-BPA compound complexes was studied by molecular dynamics simulations over 500 ns, and using this simulated data, their binding energies were again calculated using the MM-PBSA method. We observed that the binding affinity of BPA and its analogs was much higher than that of estradiol, and apart from being toxic, they can be easily absorbed in our body as their physicochemical properties are similar to those of oral medicines. Therefore, this study facilitates the understanding of the structure-activity relationship of ERRγ and BPA compounds and provides information about the key amino acid residues of ERRγ that interact with BPA compounds, which can be helpful to design competitive inhibitors so that we can interrupt the interaction of BPA with ERRγ. In addition, it provides information on BPA and its analogs and will also be helpful in developing new therapeutics.

Female fertility is a highly regulated process involving the synchronized activities of multiple tissues. The underlying genomic regulation of the tissue synchronization is poorly understood. To understand this better we investigated the transcriptomes of the porcine ovary, endometrium, and oviduct at days 0, 3, 6, 9, 12, 15, or 18 of the oestrous cycle. We analysed the transcriptome profiles of the individual tissues and focus on the bridging genes shared by two or more tissues. The three tissue-networks were connected forming a triangular shape. We identified 65 bridging genes with a high level of connectivity to all other genes in the network. The expression levels showed negative correlations between the ovary and the other two tissues, and low correlations between endometrium and oviduct. The main functional annotations involved biosynthesis of steroid hormones, cell-to-cell adhesion, and cell apoptosis, suggesting that regulation of steroid hormone synthesis and tissue viability are major regulatory mechanisms.