Epidermal stem cells (ESCs) accelerate diabetic wound healing via the Notch signalling pathway

Synopsis Chronic, non-healing wounds are a major complication of diabetes. Recently, various cell therapies have been reported for promotion of diabetic wound healing. Epidermal stem cells (ESCs) are considered a powerful tool for tissue therapy. However, the effect and the mechanism of the therapeutic properties of ESCs in the diabetic wound healing are unclear. Herein, to determine the ability of ESCs to diabetic wound healing, a dorsal skin defect in a streptozotocin (STZ)-induced diabetes mellitus (DM) mouse model was used. ESCs were isolated from mouse skin. We found that both the mRNA and protein levels of a Notch ligand Jagged1 (Jag1), Notch1 and Notch target gene Hairy Enhancer of Split-1 (Hes1) were significantly increased at the wound margins. In addition, we observed that Jag1 was high expressed in ESCs. Overexpression of Jag1 promotes ESCs migration, whereas knockdown Jag1 resulted in a significant reduction in ESCs migration in vitro. Importantly, Jag1 overexpression improves diabetic wound healing in vivo. These results provide evidence that ESCs accelerate diabetic wound healing via the Notch signalling pathway, and provide a promising potential for activation of the Notch pathway for the treatment of diabetic wound

ChickVD: a sequence variation database for the chicken genome

Working in parallel with the efforts to sequence the chicken (Gallus gallus) genome, the Beijing Genomics Institute led an international team of scientists from China, USA, UK, Sweden, The Netherlands and Germany to map extensive DNA sequence variation throughout the chicken genome by sampling DNA from domestic breeds. Using the Red Jungle Fowl genome sequence as a reference, we identified 3.1 million non-redundant DNA sequence variants. To facilitate the application of our data to avian genetics and to provide a foundation for functional and evolutionary studies, we created the ‘Chicken Variation Database’ (ChickVD). A graphical MapView shows variants mapped onto the chicken genome in the context of gene annotations and other features, including genetic markers, trait loci, cDNAs, chicken orthologs of human disease genes and raw sequence traces. ChickVD also stores information on quantitative trait loci using data from collaborating institutions and public resources. Our data can be queried by search engine and homology-based BLAST searches. ChickVD is publicly accessible at http://chicken.genomics.org.cn

A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms

We describe a genetic variation map for the chicken genome containing 2.8 million single-nucleotide polymorphisms ( SNPs). This map is based on a comparison of the sequences of three domestic chicken breeds ( a broiler, a layer and a Chinese silkie) with that of their wild ancestor, red jungle fowl. Subsequent experiments indicate that at least 90% of the variant sites are true SNPs, and at least 70% are common SNPs that segregate in many domestic breeds. Mean nucleotide diversity is about five SNPs per kilobase for almost every possible comparison between red jungle fowl and domestic lines, between two different domestic lines, and within domestic lines - in contrast to the notion that domestic animals are highly inbred relative to their wild ancestors. In fact, most of the SNPs originated before domestication, and there is little evidence of selective sweeps for adaptive alleles on length scales greater than 100 kilobases

The diploid genome sequence of an Asian individual

Here we present the first diploid genome sequence of an Asian individual. The genome was sequenced to 36-fold average coverage using massively parallel sequencing technology. We aligned the short reads onto the NCBI human reference genome to 99.97% coverage, and guided by the reference genome, we used uniquely mapped reads to assemble a high-quality consensus sequence for 92% of the Asian individual's genome. We identified approximately 3 million single-nucleotide polymorphisms (SNPs) inside this region, of which 13.6% were not in the dbSNP database. Genotyping analysis showed that SNP identification had high accuracy and consistency, indicating the high sequence quality of this assembly. We also carried out heterozygote phasing and haplotype prediction against HapMap CHB and JPT haplotypes (Chinese and Japanese, respectively), sequence comparison with the two available individual genomes (J. D. Watson and J. C. Venter), and structural variation identification. These variations were considered for their potential biological impact. Our sequence data and analyses demonstrate the potential usefulness of next-generation sequencing technologies for personal genomics