Ruminal Transcriptomic Analysis of Grass-Fed and Grain-Fed Angus Beef Cattle

Beef represents a major diet component and one of the major sources of protein in human. The beef industry in the United States is currently undergoing changes and is facing increased demands especially for natural grass-fed beef. The grass-fed beef obtained their nutrients directly from pastures, which contained limited assimilable energy but abundant amount of fiber. On the contrary, the grain-fed steers received a grain-based regime that served as an efficient source of high-digestible energy. Lately, ruminant animals have been accused to be a substantial contributor for the green house effect. Therefore, the concerns from environmentalism, animal welfare and public health have driven consumers to choose grass-fed beef. Rumen is one of the key workshops to digest forage constituting a critical step to supply enough nutrients for animals’ growth and production. We hypothesize that rumen may function differently in grass- and grain-fed regimes. The objective of this study was to find the differentially expressed genes in the ruminal wall of grass-fed and grain-fed steers, and then explore the potential biopathways. In this study, the RNA Sequencing (RNA-Seq) method was used to measure the gene expression level in the ruminal wall. The total number of reads per sample ranged from 24,697,373 to 36,714,704. The analysis detected 342 differentially expressed genes between ruminal wall samples of animals raised under different regimens. The Fisher’s exact test performed in the Ingenuity Pathway Analysis (IPA) software found 16 significant molecular networks. Additionally, 13 significantly enriched pathways were identified, most of which were related to cell development and biosynthesis. Our analysis demonstrated that most of the pathways enriched with the differentially expressed genes were related to cell development and biosynthesis. Our results provided valuable insights into the molecular mechanisms resulting in the phenotype difference between grass-fed and grain-fed cattle.     

Growth curve,blood parameters and carcass traits of grass-fed Angus steers

The increasing demand for natural products is currently transforming the meat industry, making grass-fed and finished beef a valuable option for improving profits. However, the transformation of conventional operations to grass-fed systems comprises many modifications, such as logistical, technological, and financial that could be very complex and expensive, involving economic risk. Therefore, in this study, we analyzed the growth curve, critical economic traits, and carcass quality and finished characteristics over several consecutive years in closely related grass-fed and finished Angus steers, to reduce the genetic effect on the results. We found that grass-fed steers require around 188 additional days to reach the market weight (approx. 470 kg) and had approximately 70% less average daily gain compared to the grain-fed and finished steers. Regression analysis demonstrated an interaction between feed and age (P < 0.01); thus, individual regressions were fitted for each regimen style, obtaining almost perfect linear curves for both treatments, which could be straightforwardly used in practical situations due to its simplicity. Six of eight carcass traits were different between grain-fed and grass-fed and finished steers. Hot-carcass weight, dressing, back fat, and quality grade were superior in grain-fed individuals, contrarily to yield grade and ribeye area/carcass ratio, which were better in grass-fed and finished steers (P < 0.05).Interestingly, the meat tenderness was certainly low and similar in both treatments (P = 0.25), indicating the feasibility of producing tender meat with animals under a grass-fed diet. Nevertheless, according to the quality grade analysis, grain-fed carcasses were greater ranked compared to grass-fed bodies (P < 0.01), regardless of their same tenderness. The results will provide valuable information for better understanding beef cattle in grass-feeding finishing systems, especially from weaning to harvest. Additionally, the study will expand the knowledge about the quality of meat obtained from animals that received grass exclusively, becoming relevant information for economic evaluation and management decisions for grass-based cattle operations.     

Molecular Phenotyping of Immune Cells from Young NOD Mice Reveals Abnormal Metabolic Pathways in the Early Induction Phase of Autoimmune Diabetes

Islet leukocytic infiltration (insulitis) is first obvious at around 4 weeks of age in the NOD mouse – a model for human type 1 diabetes (T1D). The molecular events that lead to insulitis and initiate autoimmune diabetes are poorly understood. Since TID is caused by numerous genes, we hypothesized that multiple molecular pathways are altered and interact to initiate this disease. We evaluated the molecular phenotype (mRNA and protein expression) and molecular networks of ex vivo unfractionated spleen leukocytes from 2 and 4 week-old NOD mice in comparison to two control strains. Analysis of the global gene expression profiles and hierarchical clustering revealed that the majority (∼90%) of the differentially expressed genes in NOD mice were repressed. Furthermore, analysis using a modern suite of multiple bioinformatics approaches identified abnormal molecular pathways that can be divided broadly into 2 categories: metabolic pathways, which were predominant at 2 weeks, and immune response pathways, which were predominant at 4 weeks. Network analysis by Ingenuity pathway analysis identified key genes/molecules that may play a role in regulating these pathways. These included five that were common to both ages (TNF, HNF4A, IL15, Progesterone, and YWHAZ), and others that were unique to 2 weeks (e.g. MYC/MYCN, TGFB1, and IL2) and to 4 weeks (e.g. IFNG, beta-estradiol, p53, NFKB, AKT, PRKCA, IL12, and HLA-C). Based on the literature, genes that may play a role in regulating metabolic pathways at 2 weeks include Myc and HNF4A, and at 4 weeks, beta-estradiol, p53, Akt, HNF4A and AR. Our data suggest that abnormalities in regulation of metabolic pathways in the immune cells of young NOD mice lead to abnormalities in the immune response pathways and as such may play a role in the initiation of autoimmune diabetes. Thus, targeting metabolism may provide novel approaches to preventing and/or treating autoimmune diabetes.     

Analysis on Differential Gene Expression Data for Prediction of New Biological Features in Permanent Atrial Fibrillation

Permanent Atrial fibrillation (pmAF) has largely remained incurable since the existing information for explaining precise mechanisms underlying pmAF is not sufficient. Microarray analysis offers a broader and unbiased approach to identify and predict new biological features of pmAF. By considering the unbalanced sample numbers in most microarray data of case - control, we designed an asymmetric principal component analysis algorithm and applied it to re - analyze differential gene expression data of pmAF patients and control samples for predicting new biological features. Finally, we identified 51 differentially expressed genes using the proposed method, in which 42 differentially expressed genes are new findings compared with two related works on the same data and the existing studies. The enrichment analysis illustrated the reliability of identified differentially expressed genes. Moreover, we predicted three new pmAF – related signaling pathways using the identified differentially expressed genes via the KO-Based Annotation System. Our analysis and the existing studies supported that the predicted signaling pathways may promote the pmAF progression. The results above are worthy to do further experimental studies. This work provides some new insights into molecular features of pmAF. It has also the potentially important implications for improved understanding of the molecular mechanisms of pmAF.     

Development of a prognostic model based on an immunogenomic landscape analysis of medulloblastoma

Medulloblastoma (MB) is one of the most common central nervous system tumors in children. At present, the vital role of immune abnormalities has been proved in tumorigenesis and progression. However, the immune mechanism in MB is still poorly understood. In the present study, 51 differentially expressed immune-related genes (DE-IRGs) and 226 survival associated immune-related genes (Sur-IRGs) were screened by an integrated analysis of multi-array. Moreover, the potential pathways were enriched by functional analysis, such as ‘cytokine–cytokine receptor interaction’, ‘Ras signaling pathway’, ‘PI3K-Akt signaling pathway’ and ‘pathways in cancer’. Furthermore, 10 core IRGs were identified from DE-IRGs and Sur-IRGs. And the potential regulatory mechanisms of core IRGs were also explored. Additionally, a new prognostic model, including 7 genes (HDGF, CSK, PNOC, S100A13, RORB, FPR1, and ICAM2) based on IRGs, was established by multivariable COX analysis. In summary, our study revealed the underlying immune mechanism of MB. Moreover, we developed a prognostic model associated with clinical characteristics and could reflect the infiltration of immune cells.     

Identification of key biomarkers for thyroid cancer by integrative gene expression profiles

Thyroid cancer is a frequently diagnosed malignancy and the incidence has been increased rapidly in recent years. Despite the favorable prognosis of most thyroid cancer patients, advanced patients with metastasis and recurrence still have poor prognosis. Therefore, the molecular mechanisms of progression and targeted biomarkers were investigated for developing effective targets for treating thyroid cancer. Eight chip datasets from the gene expression omnibus database were selected and the inSilicoDb and inSilicoMerging R/Bioconductor packages were used to integrate and normalize them across platforms. After merging the eight gene expression omnibus datasets, we obtained one dataset that contained the expression profiles of 319 samples (188 tumor samples plus 131 normal thyroid tissue samples). After screening, we identified 594 significantly differentially expressed genes (277 up-regulated genes plus 317 down-regulated genes) between the tumor and normal tissue samples. The differentially expressed genes exhibited enrichment in multiple signaling pathways, such as p53 signaling. By building a protein–protein interaction network and module analysis, we confirmed seven hub genes, and they were all differentially expressed at all the clinical stages of thyroid cancer. A diagnostic seven-gene signature was established using a logistic regression model with the area under the receiver operating characteristic curve (AUC) of 0.967. Seven robust candidate biomarkers predictive of thyroid cancer were identified, and the obtained seven-gene signature may serve as a useful marker for thyroid cancer diagnosis and prognosis.     

miRNAs may play a major role in the control of gene expression in key pathobiological processes in Chagas disease cardiomyopathy

Chronic Chagas disease cardiomyopathy (CCC), an especially aggressive inflammatory dilated cardiomyopathy caused by lifelong infection with the protozoan Trypanosoma cruzi, is a major cause of cardiomyopathy in Latin America. Although chronic myocarditis may play a major pathogenetic role, little is known about the molecular mechanisms responsible for its severity. The aim of this study is to study the genes and microRNAs expression in tissues and their connections in regards to the pathobiological processes. To do so, we integrated for the first time global microRNA and mRNA expression profiling from myocardial tissue of CCC patients employing pathways and network analyses. We observed an enrichment in biological processes and pathways associated with the immune response and metabolism. IFNγ, TNF and NFkB were the top upstream regulators. The intersections between differentially expressed microRNAs and differentially expressed target mRNAs showed an enrichment in biological processes such as Inflammation, inflammation, Th1/IFN-γ-inducible genes, fibrosis, hypertrophy, and mitochondrial/oxidative stress/antioxidant response. MicroRNAs also played a role in the regulation of gene expression involved in the key cardiomyopathy-related processes fibrosis, hypertrophy, myocarditis and arrhythmia. Significantly, a discrete number of differentially expressed microRNAs targeted a high number of differentially expressed mRNAs (>20) in multiple processes. Our results suggest that miRNAs orchestrate expression of multiple genes in the major pathophysiological processes in CCC heart tissue. This may have a bearing on pathogenesis, biomarkers and therapy.