Comprehensive Analysis of CircRNA Expression Profiles in Multiple Tissues of Pigs.

Circular RNAs (circRNAs) are a class of non-coding RNAs with diverse functions, and previous studies have reported that circRNAs are involved in the growth and development of pigs. However, studies about porcine circRNAs over the past few years have focused on a limited number of tissues. Based on 215 publicly available RNA sequencing (RNA-seq) samples, we conducted a comprehensive analysis of circRNAs in nine pig tissues, namely, the gallbladder, heart, liver, longissimus dorsi, lung, ovary, pituitary, skeletal muscle, and spleen. Here, we identified a total of 82,528 circRNAs and discovered 3818 novel circRNAs that were not reported in the CircAtlas database. Moreover, we obtained 492 housekeeping circRNAs and 3489 tissue-specific circRNAs. The housekeeping circRNAs were enriched in signaling pathways regulating basic biological tissue activities, such as chromatin remodeling, nuclear-transcribed mRNA catabolic process, and protein methylation. The tissue-specific circRNAs were enriched in signaling pathways related to tissue-specific functions, such as muscle system process in skeletal muscle, cilium organization in pituitary, and cortical cytoskeleton in ovary. Through weighted gene co-expression network analysis, we identified 14 modules comprising 1377 hub circRNAs. Additionally, we explored circRNA-miRNA-mRNA networks to elucidate the interaction relationships between tissue-specific circRNAs and tissue-specific genes. Furthermore, our conservation analysis revealed that 19.29% of circRNAs in pigs shared homologous positions with their counterparts in humans. In summary, this extensive profiling of housekeeping, tissue-specific, and co-expressed circRNAs provides valuable insights into understanding the molecular mechanisms of pig transcriptional expression, ultimately deepening our understanding of genetic and biological processes.

Study on detection of CNVs using human whole genome bisulfite sequencing data.

It has been reported that the aberrant DNA methylation may result in copy number variations (CNVs), and the CNVs may alter the levels of DNA methylation. Whole genome bisulfite sequencing (WGBS) is able to generate the sequencing data of DNAs, and shows the potential ability to detect CNVs. However, the evaluations and performances on the detections of CNVs using WGBS data is still unclear. In this study, five software with different strategies for CNV detections, e.g., BreakDancer, cn.mops, CNVnator, DELLY and Pindel, were selected to explore and benchmark the performances of CNV detections with WGBS data. Based on the real (2.62 billion reads) and simulated (12.35 billion reads) WGBS data of humans, we calculated the number, precision, recall, relative ability, memory usage, and running time of CNV detections by 150 times, and tried to figure out the optimal strategy for CNV detections with WGBS data. Based on the real WGBS data, Pindel detected the most deletions and duplications, CNVnator detected the deletions with the highest precision, cn.mops detected the duplications with the highest precision, Pindel detected the deletions with the highest recall, and cn.mops detected the duplications with the highest recall. Based on the simulated WGBS data, BreakDancer detected the most deletions, and cn.mops detected the most duplications. The CNVnator showed the highest precision and recall for both deletions and duplications. In real and simulated WGBS data, the ability of CNVnator to detect CNVs was likely to overtake that in the whole genome sequencing data. Additionally, DELLY and BreakDancer displayed the lowest peak of memory usage and the lest CPU runtime, while CNVnator expressed the highest peak of memory usage and the most CPU runtime. Taken together, CNVnator and cn.mops showed the excellent performances of CNV detections with WGBS data. These results suggested that it was feasible to detect CNVs using WGBS data, and provided the useful information to further investigate both CNVs and DNA methylation using WGBS data alone.

Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs.

Enhancers and the enhancer RNAs (eRNAs) have been strongly implicated in regulations of transcriptions. Based the multi-omics data (ATAC-seq, ChIP-seq and RNA-seq) from public databases, Pig-eRNAdb is a dataset that comprehensively integrates enhancers and eRNAs for pigs using the machine learning strategy, which incorporates 82,399 enhancers and 37,803 eRNAs from 607 samples across 15 tissues of pigs. This user-friendly dataset covers a comprehensive depth of enhancers and eRNAs annotation for pigs. The coordinates of enhancers and the expression patterns of eRNAs are downloadable. Besides, thousands of regulators on eRNAs, the target genes of eRNAs, the tissue-specific eRNAs, and the housekeeping eRNAs are also accessible as well as the sequence similarity of eRNAs with humans. Moreover, the tissue-specific eRNA-trait associations encompass 652 traits are also provided. It will crucially facilitate investigations on enhancers and eRNAs with Pig-eRNAdb as a reference dataset in pigs.

Expression Profile of Housekeeping Genes and Tissue-Specific Genes in Multiple Tissues of Pigs.

Pigs have become an ideal model system for human disease research and development and an important farm animal that provides a valuable source of nutrition. To profile the all-sided gene expression and their biological functions across multiple tissues, we conducted a comprehensive analysis of gene expression on a large scale around the side of housekeeping genes (HKGs), tissue specific genes (TSGs), and the co-expressed genes in 14 various tissues. In this study, we identified 2351 HKGs and 3018 TSGs across tissues, among which 4 HKGs (COX1, UBB, OAZ1/NPFF) exhibited low variation and high expression levels, and 31 particular TSGs (e.g., PDC, FKBP6, STAT2, and COL1A1) were exclusively expressed in several tissues, including endocrine brain, ovaries, livers, backfat, jejunum, kidneys, lungs, and longissimus dorsi muscles. We also obtained 17 modules with 230 hub genes (HUBGs) by weighted gene co-expression network analysis. On the other hand, HKGs functions were enriched in the signaling pathways of the ribosome, spliceosome, thermogenesis, oxidative phosphorylation, and nucleocytoplasmic transport, which have been highly suggested to involve in the basic biological tissue activities. While TSGs were highly enriched in the signaling pathways that were involved in specific physiological processes, such as the ovarian steroidogenesis pathway in ovaries and the renin-angiotensin system pathway in kidneys. Collectively, these stable, specifical, and co-expressed genes provided useful information for the investigation of the molecular mechanism for an understanding of the genetic and biological processes of complex traits in pigs.

Determination and Difference Analysis of Phenolic Compounds in Smokers' Saliva and Mainstream Smoke.

To study the differences in phenolic compounds between tobacco smokers' saliva and mainstream smoke, a method was developed for the analysis of 12 phenolic compounds in saliva and mainstream smoke based on ultrahigh-performance liquid chromatography with fluorescence detection (UPLC-FLD). The contents and distributions of phenolic compounds in tobacco smokers' saliva and mainstream smoke were compared. The results were as follows: (1) Phenolic compounds were quantitatively analyzed by the internal standard method using 4-fluorophenol as an internal standard. For smokers' saliva samples, the limits of quantification (LOQs) ranged from 2.2 to 19.1 µg/L, and the recoveries were from 80.2% to 119.2% at the three spiked levels. For mainstream smoke samples, the LOQs ranged from 0.03 to 0.26 µg/cig, and the recoveries ranged from 84.9% to 107.0% at the three spiked levels. (2) The contents of phenolic compounds from 14 cigarettes in mainstream smoke and smokers' saliva were determined. In mainstream smoking, the main phenolic compounds were hydroquinone, catechol, phenol, meta- and para-Cresol, and o-methylhydroquinone. In smokers' saliva, the main phenolic compounds were phenol and meta- and para-Cresol and the contents of phenolic compounds in smokers' saliva from different cigarettes were significantly different. (3) The content distribution patterns of phenolic compounds in smokers' saliva differed from those in mainstream smoke. The predominant phenolic compound in mainstream smoke was dihydroxybenzene, while monophenols predominated in smokers' saliva. (4) The contents of phenolic compounds from five kinds of cigarettes were analyzed in the saliva of different smokers using principal component analysis, which indicated that cigarettes with different sensory effects were clearly distinguished by differences in the contents of phenolic compounds in saliva.

Organic Selenium Alleviated the Formation of Ethylene Glycol-Induced Calcium Oxalate Renal Calculi by Improving Osteopontin Expression and Antioxidant Capability in Dogs.

Twenty one-year-old local male dogs were randomly assigned into four groups (five dogs per group). The control and the ethylene glycol (EG) groups were fed basal diets without and with EG, and the EG+sodium selenite (EG+SS) and EG+selenium yeast (EG+SY) groups were fed basal diets with EG containing SS and SY, respectively. Blood, urine, and renal samples were taken after 18 weeks of feeding. The results showed that compared with the control group, the serum calcium levels and antioxidase activities significantly decreased in the EG group. Serum creatinine, urea nitrogen, and malondialdehyde (MDA) levels and urine calcium and oxalate levels significantly increased. Calcium oxalate crystal deposition and osteopontin (OPN) messenger RNA and protein expression in the renal tissues significantly increased. These changes above in the EG group were reversed within limits by adding selenium in the diets (both EG+SS and EG+SY groups). Further, compared with the EG+SS group, the EG+SY group showed better effects in decreasing the formation of EG-induced calcium oxalate renal calculi and OPN expression and improving antioxidant capability in dogs. It indicates that organic selenium has the potential value to alleviate the formation of EG-induced calcium oxalate renal calculi.