Domestic animals are excellent models for genetic studies of phenotypic evolution. They have evolved genetic adaptations to a new environment, the farm, and have been subjected to strong human-driven selection leading to remarkable phenotypic changes in morphology, physiology and behaviour. Identifying the genetic changes underlying these developments provides new insight into general mechanisms by which genetic variation shapes phenotypic diversity. Here we describe the use of massively parallel sequencing to identify selective sweeps of favourable alleles and candidate mutations that have had a prominent role in the domestication of chickens (Gallus gallus domesticus) and their subsequent specialization into broiler (meat-producing) and layer (egg-producing) chickens. We have generated 44.5-fold coverage of the chicken genome using pools of genomic DNA representing eight different populations of domestic chickens as well as red jungle fowl (Gallus gallus), the major wild ancestor. We report more than 7,000,000 single nucleotide polymorphisms, almost 1,300 deletions and a number of putative selective sweeps. One of the most striking selective sweeps found in all domestic chickens occurred at the locus for thyroid stimulating hormone receptor (TSHR), which has a pivotal role in metabolic regulation and photoperiod control of reproduction in vertebrates. Several of the selective sweeps detected in broilers overlapped genes associated with growth, appetite and metabolic regulation. We found little evidence that selection for loss-of-function mutations had a prominent role in chicken domestication, but we detected two deletions in coding sequences that we suggest are functionally important. This study has direct application to animal breeding and enhances the importance of the domestic chicken as a model organism for biomedical research.

Firmicutes and Bacteroidetes, 2 major phyla of gut microbiota, are involved in lipid and bile acid metabolism to maintain systemic energy homeostasis in host. Recently, accumulating evidence has suggested that dietary changes promptly induce the alteration of abundance of both Firmicutes and Bacteroidetes in obesity and its related metabolic diseases. Nevertheless, the metabolic roles of Firmicutes and Bacteroidetes on such disease states remain unclear. The aim of this study was to determine the effects of antibiotic-induced depletion of Firmicutes and Bacteroidetes on dysregulation of energy homeostasis in obesity. Treatment of C57BL/6J mice with the antibiotics (vancomycin [V] and bacitracin [B]), in the drinking water, before diet-induced obesity (DIO) greatly decreased both Firmicutes and Bacteroidetes in the gut as revealed by pyrosequencing of the microbial 16S rRNA gene. Concomitantly, systemic glucose intolerance, hyperinsulinemia, and insulin resistance in DIO were ameliorated via augmentation of GLP-1 secretion (active form; 2.03-fold, total form; 5.09-fold) independently of obesity as compared with untreated DIO controls. Furthermore, there were increases in metabolically beneficial metabolites derived from the gut. Together, our data suggest that Firmicutes and Bacteroidetes potentially mediate insulin resistance throughmodulationofGLP-1secretion in

In obesity, adipose tissue macrophages (ATMs) play a key role in mediating proinflammatory responses in the adipose tissue, which are associated with obesity-related metabolic complications. Recently, adipose tissue hypoxia has been implicated in the regulation of ATMs in obesity. However, the role of hypoxia-inducible factor (HIF)-2α, one of the major transcription factors induced by hypoxia, has not been fully elucidated in ATMs. In this study, we demonstrate that elevation of macrophage HIF-2α would attenuate adipose tissue inflammation and improve insulin resistance in obesity. In macrophages, overexpression of HIF-2α decreased nitric oxide production and suppressed expression of proinflammatory cytokines through induction of arginase 1. HIF-2α–overexpressing macrophages alleviated proinflammatory responses and improved insulin resistance in adipocytes. In contrast, knockdown of macrophage HIF-2α augmented palmitate-induced proinflammatory gene expression in adipocytes. Furthermore, compared with wild-type mice, Hif-2α heterozygous-null mice aggravated insulin resistance and adipose tissue inflammation with more M1-like ATMs upon high-fat diet (HFD). Moreover, glucose intolerance in HFD-fed Hif-2α heterozygous-null mice was relieved by macrophage depletion with clodronate treatment, implying that increase of proinflammatory ATMs is responsible for insulin resistance by haplodeficiency of Hif-2α upon HFD. Taken together, these data suggest that macrophage HIF-2α would counteract the proinflammatory responses to relieve obesity-induced insulin resistance in adipose tissue.

Adipocyte differentiation, termed adipogenesis, is a complicated process in which pluripotent mesenchymal stem cells differentiate into mature adipocytes. The process of adipocyte differentiation is tightly regulated by a number of transcription factors, hormones and signaling pathway molecules. Recent studies have demonstrated that microRNAs, which belong to small noncoding RNA species, are also involved in adipocyte differentiation. In vivo and in vitro studies have revealed that various microRNAs affect adipogenesis by targeting several adipogenic transcription factors and key signaling molecules. In this review, we will summarize the roles of microRNAs in adipogenesis and their target genes associated with each stage of adipocyte differentiation.

BackgroundSeveral recent studies showed that next-generation sequencing (NGS)-based human leukocyte antigen (HLA) typing is a feasible and promising technique for variant calling of highly polymorphic regions. To date, however, no method with sufficient read depth has completely solved the allele phasing issue. In this study, we developed a new method (HLAscan) for HLA genotyping using NGS data.ResultsHLAscan performs alignment of reads to HLA sequences from the international ImMunoGeneTics project/human leukocyte antigen (IMGT/HLA) database. The distribution of aligned reads was used to calculate a score function to determine correctly phased alleles by progressively removing false-positive alleles. Comparative HLA typing tests using public datasets from the 1000 Genomes Project and the International HapMap Project demonstrated that HLAscan could perform HLA typing more accurately than previously reported NGS-based methods such as HLAreporter and PHLAT. In addition, the results of HLA-A, −B, and -DRB1 typing by HLAscan using data generated by NextGen were identical to those obtained using a Sanger sequencing–based method. We also applied HLAscan to a family dataset with various coverage depths generated on the Illumina HiSeq X-TEN platform. HLAscan identified allele types of HLA-A, −B, −C, −DQB1, and -DRB1 with 100% accuracy for sequences at ≥ 90× depth, and the overall accuracy was 96.9%.ConclusionsHLAscan, an alignment-based program that takes read distribution into account to determine true allele types, outperformed previously developed HLA typing tools. Therefore, HLAscan can be reliably applied for determination of HLA type across the whole-genome, exome, and target sequences.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1671-3) contains supplementary material, which is available to authorized users.