Physiological genomics: tools and concepts

Nutrient supply affects the mRNA expression profile of the porcine skeletal muscle

Background

The genetic basis of muscle fat deposition in pigs is not well known. So far, we have only identified a limited number of genes involved in the absorption, transport, storage and catabolism of lipids. Such information is crucial to interpret, from a biological perspective, the results of genome-wide association analyses for intramuscular fat content and composition traits. Herewith, we have investigated how the ingestion of food changes gene expression in the gluteus medius muscle of Duroc pigs.

Results

By comparing the muscle mRNA expression of fasted pigs (T0) with that of pigs sampled 5 h (T1) and 7 h (T2) after food intake, we have detected differential expression (DE) for 148 (T0-T1), 520 (T0-T2) and 135 (T1-T2) genes (q-value <0.05 and a |FC| > of 1.5). Many of these DE genes were transcription factors, suggesting that we have detected the coordinated response of the skeletal muscle to nutrient supply. We also found DE genes with a dual role in oxidative stress and angiogenesis (THBS1, THBS2 and TXNIP), two biological processes that are probably activated in the post-prandial state. Finally, we have identified several loci playing a key role in the modulation of circadian rhythms (ARNTL, PER1, PER2, BHLHE40, NR1D1, SIK1, CIART and CRY2), a result that indicates that the porcine muscle circadian clock is modulated by nutrition.

Conclusion

We have shown that hundreds of genes change their expression in the porcine skeletal muscle in response to nutrient intake. Many of these loci do not have a known metabolic role, a result that suggests that our knowledge about the genetic basis of muscle energy homeostasis is still incomplete.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3986-x) contains supplementary material, which is available to authorized users.

Insights from physiology into myometrial function and dysfunction

NEW FINDINGS

What is the topic of this review? I focus on clinical aspects of uterine physiology, specifically, myometrial contractility. I bring together and contrast findings using physiological approaches and those using newer techniques, 'omics'. What advances does it highlight? Physiological studies have recently shed light on the myometrium in twin pregnancies, but there have been no 'omic' approaches. In contrast, studies of preterm delivery using newer approaches are generating new research avenues, whereas traditional approaches have not flourished. Finally, I describe significant advances in understanding of 'slow-to-progress' labours, achieved using physiological and clinical approaches. Advances in molecular, genetic and 'omic' technologies are fuelling the thirst for better understanding of the uterus and application of this information to problems in pregnancy and labour. Progress has, however, been limited while we still have an incomplete understanding of some of the basic physiology of uterine smooth muscle (myometrium). In this review and opinion piece, I explore some of the fascinating findings from selected recent studies and see how these may provide new avenues for physiological and clinical research. It is also the case, however, that there is still limited mechanistic understanding about physiological and pathophysiological processes in the myometrium. This lack of understanding limits the usefulness of some findings from genomic and allied studies. By focusing on some key recent findings and relating these to two important clinical problems in childbirth that involve myometrial activity, namely preterm delivery and difficult labours, the interplay between our physiological knowledge and the information provided by newer technologies is explored. My opinion is that physiology has provided much more new mechanistic insight into difficult births and that the newer technologies may lead to breakthroughs in preterm birth research, but that this has not yet happened.

Tissue engineering: a new frontier in physiological genomics

Considerable progress has been made in the last decade in the engineering and construction of a number of artificial tissue types. These constructs are typically viewed from the perspective of possible sources for implant and transplant materials in the clinical arena. However, incorporation of engineered tissues, often referred to as three-dimensional (3D) cell culture, also offers the possibility for significant advancements in research for physiological genomics. These 3D systems more readily mimic the in vivo setting than traditional 2D cell culture, and offer distinct advantages over the in vivo setting for some organ systems. As an example, cardiac cells in 3D culture 1) are more accessible for siRNA studies, 2) can be engineered with specific cell types, and 3) offer the potential for high-throughput screening of gene function. Here the state-of-the-art is reviewed and the applications for engineered tissue in genomics research are proposed. The ability to use engineered tissue in combination with genomics creates a bridge between traditional cellular and in vivo studies that is critical to enabling the transition of genetic information into mechanistic understanding of disease processes.

Tools and strategies for physiological genomics: the Rat Genome Database

The broad goal of physiological genomics research is to link genes to their functions using appropriate experimental and computational techniques. Modern genomics experiments enable the generation of vast quantities of data, and interpretation of this data requires the integration of information derived from many diverse sources. Computational biology and bioinformatics offer the ability to manage and channel this information torrent. The Rat Genome Database (RGD; http://rgd.mcw.edu) has developed computational tools and strategies specifically supporting the goal of linking genes to their functional roles in rat and, using comparative genomics, to human and mouse. We present an overview of the database with a focus on these unique computational tools and describe strategies for the use of these resources in the area of physiological genomics.