Putative Regulatory Factors Associated with Intramuscular Fat Content

Intramuscular fat (IMF) content is related to insulin resistance, which is an important prediction factor for disorders, such as cardiovascular disease, obesity and type 2 diabetes in human. At the same time, it is an economically important trait, which influences the sensorial and nutritional value of meat. The deposition of IMF is influenced by many factors such as sex, age, nutrition, and genetics. In this study Nellore steers (Bos taurus indicus subspecies) were used to better understand the molecular mechanisms involved in IMF content. This was accomplished by identifying differentially expressed genes (DEG), biological pathways and putative regulatory factors. Animals included in this study had extreme genomic estimated breeding value (GEBV) for IMF. RNA-seq analysis, gene set enrichment analysis (GSEA) and co-expression network methods, such as partial correlation coefficient with information theory (PCIT), regulatory impact factor (RIF) and phenotypic impact factor (PIF) were utilized to better understand intramuscular adipogenesis. A total of 16,101 genes were analyzed in both groups (high (H) and low (L) GEBV) and 77 DEG (FDR 10%) were identified between the two groups. Pathway Studio software identified 13 significantly over-represented pathways, functional classes and small molecule signaling pathways within the DEG list. PCIT analyses identified genes with a difference in the number of gene-gene correlations between H and L group and detected putative regulatory factors involved in IMF content. Candidate genes identified by PCIT include: ANKRD26, HOXC5 and PPAPDC2. RIF and PIF analyses identified several candidate genes: GLI2 and IGF2 (RIF1), MPC1 and UBL5 (RIF2) and a host of small RNAs, including miR-1281 (PIF). These findings contribute to a better understanding of the molecular mechanisms that underlie fat content and energy balance in muscle and provide important information for the production of healthier beef for human consumption.     

Genomic Analysis of Stress Response against Arsenic in Caenorhabditis elegans

Arsenic, a known human carcinogen, is widely distributed around the world and found in particularly high concentrations in certain regions including Southwestern US, Eastern Europe, India, China, Taiwan and Mexico. Chronic arsenic poisoning affects millions of people worldwide and is associated with increased risk of many diseases including arthrosclerosis, diabetes and cancer. In this study, we explored genome level global responses to high and low levels of arsenic exposure in Caenorhabditis elegans using Affymetrix expression microarrays. This experimental design allows us to do microarray analysis of dose-response relationships of global gene expression patterns. High dose (0.03%) exposure caused stronger global gene expression changes in comparison with low dose (0.003%) exposure, suggesting a positive dose-response correlation. Biological processes such as oxidative stress, and iron metabolism, which were previously reported to be involved in arsenic toxicity studies using cultured cells, experimental animals, and humans, were found to be affected in C. elegans. We performed genome-wide gene expression comparisons between our microarray data and publicly available C. elegans microarray datasets of cadmium, and sediment exposure samples of German rivers Rhine and Elbe. Bioinformatics analysis of arsenic-responsive regulatory networks were done using FastMEDUSA program. FastMEDUSA analysis identified cancer-related genes, particularly genes associated with leukemia, such as dnj-11, which encodes a protein orthologous to the mammalian ZRF1/MIDA1/MPP11/DNAJC2 family of ribosome-associated molecular chaperones. We analyzed the protective functions of several of the identified genes using RNAi. Our study indicates that C. elegans could be a substitute model to study the mechanism of metal toxicity using high-throughput expression data and bioinformatics tools such as FastMEDUSA.     

Expression profiling analysis for genes related to meat quality and carcass traits during postnatal development of backfat in two pig breeds

The competitive equilibrium of fatty acid biosynthesis and oxidation in vivo determines porcine sub-cutaneous fat thickness(SFT) and intramuscular fat(IMF) content.Obese and lean-type pig breeds show obvious differences in adipose deposition;however, the molecular mechanism underlying this phenotypic variation remains unclear.We used pathway-focused oligo microarray studies to examine the expression changes of 140 genes associated with meat quality and carcass traits in backfat at five growth stages(1―5 months) of Landrace(a leaner, Western breed) and Taihu pigs(a fatty, indigenous, Chinese breed).Variance analysis(ANOVA) revealed that differences in the expression of 25 genes in Landrace pigs were significant(FDR adjusted permutation, P<0.05) among 5 growth stages.Gene class test(GCT) indicated that a gene-group was very significant between 2 pig breeds across 5 growth stages(PErmineJ<0.01), which consisted of 23 genes encoding enzymes and regulatory proteins associ-ated with lipid and steroid metabolism.These findings suggest that the distinct differences in fat deposition ability between Landrace and Taihu pigs may closely correlate with the expression changes of these genes.Clustering analysis revealed a very high level of significance(FDR adjusted, P<0.01) for 2 gene expression patterns in Landrace pigs and a high level of significance(FDR adjusted, P<0.05) for 2 gene expression patterns in Taihu pigs.Also, expression patterns of genes were more diversified in Taihu pigs than those in Landrace pigs, which suggests that the regulatory mechanism of micro-effect polygenes in adipocytes may be more complex in Taihu pigs than in Landrace pigs.Based on a dy-namic Bayesian network(DBN) model, gene regulatory networks(GRNs) were reconstructed from time-series data for each pig breed.These two GRNs initially revealed the distinct differences in physiological and biochemical aspects of adipose metabolism between the two pig breeds;from these results, some potential key genes could be identified.Quantitative, real-time RT-PCR(QRT-PCR) was used to verify the microarray data for five modulated genes, and a good correlation between the two measures of expression was observed for both 2 pig breeds at different growth stages(R=0.874±0.071).These results highlight some possible candidate genes for porcine fat characteristics and provide some data on which to base further study of the molecular basis of adipose metabolism.     

Monitoring expression profiles of Arabidopsis genes during cold acclimation and deacclimation using DNA microarrays

A comparative analysis of gene expression profiles during cold acclimation and deacclimation is necessary to elucidate the molecular mechanisms of cold stress responses in higher plants. We analyzed gene expression profiles in the process of cold acclimation and deacclimation (recovery from cold stress) using two microarray systems, the 7K RAFL cDNA microarray and the Agilent 22K oligonucleotide array. By both microarray analyses, we identified 292 genes up-regulated and 320 genes down-regulated during deacclimation, and 445 cold up-regulated genes and 341 cold down-regulated genes during cold acclimation. Many genes up-regulated during deacclimation were found to be down-regulated during cold acclimation, and vice versa. The genes up-regulated during deacclimation were classified into (1) regulatory proteins involved in further regulation of signal transduction and gene expression and (2) functional proteins involved in the recovery process from cold-stress-induced damages and plant growth. We also applied expression profiling studies to identify the key genes involved in the biosynthesis of carbohydrates and amino acids that are known to play important roles in cold acclimation. We compared genes that are regulated during deacclimation with those regulated during rehydration after dehydration to discuss the similarity and difference of each recovery process.Electronic Supplementary Material Supplementary materials are available for this article at