Permanent genetic resources added to Molecular Ecology Resources Database 1 December 2010-31 January 2011

This article documents the addition of 238 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Alytes dickhilleni, Arapaima gigas, Austropotamobius italicus, Blumeria graminis f. sp. tritici, Cobitis lutheri, Dendroctonus ponderosae, Glossina morsitans morsitans, Haplophilus subterraneus, Kirengeshoma palmata, Lysimachia japonica, Macrolophus pygmaeus, Microtus cabrerae, Mytilus galloprovincialis, Pallisentis (Neosentis) celatus, Pulmonaria officinalis, Salminus franciscanus, Thais chocolata and Zootoca vivipara. These loci were cross-tested on the following species: Acanthina monodon, Alytes cisternasii, Alytes maurus, Alytes muletensis, Alytes obstetricans almogavarii, Alytes obstetricans boscai, Alytes obstetricans obstetricans, Alytes obstetricans pertinax, Cambarellus montezumae, Cambarellus zempoalensis, Chorus giganteus, Cobitis tetralineata, Glossina fuscipes fuscipes, Glossina pallidipes, Lysimachia japonica var. japonica, Lysimachia japonica var. minutissima, Orconectes virilis, Pacifastacus leniusculus, Procambarus clarkii, Salminus brasiliensis and Salminus hilarii.     

Human migration through bottlenecks from Southeast Asia into East Asia during Last Glacial Maximum revealed by Y chromosomes

Molecular anthropological studies of the populations in and around East Asia have resulted in the discovery that most of the Y-chromosome lineages of East Asians came from Southeast Asia. However, very few Southeast Asian populations had been investigated, and therefore, little was known about the purported migrations from Southeast Asia into East Asia and their roles in shaping the genetic structure of East Asian populations. Here, we present the Y-chromosome data from 1,652 individuals belonging to 47 Mon-Khmer (MK) and Hmong-Mien (HM) speaking populations that are distributed primarily across Southeast Asia and extend into East Asia. Haplogroup O3a3b-M7, which appears mainly in MK and HM, indicates a strong tie between the two groups. The short tandem repeat network of O3a3b-M7 displayed a hierarchical expansion structure (annual ring shape), with MK haplotypes being located at the original point, and the HM and the Tibeto-Burman haplotypes distributed further away from core of the network. Moreover, the East Asian dominant haplogroup O3a3c1-M117 shows a network structure similar to that of O3a3b-M7. These patterns indicate an early unidirectional diffusion from Southeast Asia into East Asia, which might have resulted from the genetic drift of East Asian ancestors carrying these two haplogroups through many small bottle-necks formed by the complicated landscape between Southeast Asia and East Asia. The ages of O3a3b-M7 and O3a3c1-M117 were estimated to be approximately 19 thousand years, followed by the emergence of the ancestors of HM lineages out of MK and the unidirectional northward migrations into East Asia.     

Plasma biomarkers of brain atrophy in Alzheimer's disease

Peripheral biomarkers of Alzheimer''s disease (AD) reflecting early neuropathological change are critical to the development of treatments for this condition. The most widely used indicator of AD pathology in life at present is neuroimaging evidence of brain atrophy. We therefore performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD. Using gel based proteomics we previously identified seven plasma proteins that were significantly associated with hippocampal volume in a combined cohort of subjects with AD (N = 27) and MCI (N = 17). In the current report, we validated this finding in a large independent cohort of AD (N = 79), MCI (N = 88) and control (N = 95) subjects using alternative complementary methods—quantitative immunoassays for protein concentrations and estimation of pathology by whole brain volume. We confirmed that plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients. These proteins are complement components C3 and C3a, complement factor-I, γ-fibrinogen and alpha-1-microglobulin. Our findings suggest that these plasma proteins are strong predictors of in vivo AD pathology. Moreover, these proteins are involved in complement activation and coagulation, providing further evidence for an intrinsic role of these pathways in AD pathogenesis.     

Pathway-based analysis of a melanoma genome-wide association study: analysis of genes related to tumour-immunosuppression

Systemic immunosuppression is a risk factor for melanoma, and sunburn-induced immunosuppression is thought to be causal. Genes in immunosuppression pathways are therefore candidate melanoma-susceptibility genes. If variants within these genes individually have a small effect on disease risk, the association may be undetected in genome-wide association (GWA) studies due to low power to reach a high significance level. Pathway-based approaches have been suggested as a method of incorporating a priori knowledge into the analysis of GWA studies. In this study, the association of 1113 single nucleotide polymorphisms (SNPs) in 43 genes (39 genomic regions) related to immunosuppression have been analysed using a gene-set approach in 1539 melanoma cases and 3917 controls from the GenoMEL consortium GWA study. The association between melanoma susceptibility and the whole set of tumour-immunosuppression genes, and also predefined functional subgroups of genes, was considered. The analysis was based on a measure formed by summing the evidence from the most significant SNP in each gene, and significance was evaluated empirically by case-control label permutation. An association was found between melanoma and the complete set of genes (p(emp)=0.002), as well as the subgroups related to the generation of tolerogenic dendritic cells (p(emp)=0.006) and secretion of suppressive factors (p(emp)=0.0004), thus providing preliminary evidence of involvement of tumour-immunosuppression gene polymorphisms in melanoma susceptibility. The analysis was repeated on a second phase of the GenoMEL study, which showed no evidence of an association. As one of the first attempts to replicate a pathway-level association, our results suggest that low power and heterogeneity may present challenges.     

Permanent Genetic Resources added to Molecular Ecology Resources Database 1 April 2011-31 May 2011

This article documents the addition of 92 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Anopheles minimus, An. sinensis, An. dirus, Calephelis mutica, Lutjanus kasmira, Murella muralis and Orchestia montagui. These loci were cross-tested on the following species: Calephelis arizonensi, Calephelis borealis, Calephelis nemesis, Calephelis virginiensis and Lutjanus bengalensis.     

Permanent genetic resources added to Molecular Ecology Resources Database 1 February 2011-31 March 2011

This article documents the addition of 111 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acipenser oxyrinchus desotoi, Anopheles nuneztovari sensu lato, Asellus aquaticus, Calopteryx splendens, Calopteryx virgo, Centaurea aspera, Centaurea seridis, Chilina dombeyana, Proctoeces cf. lintoni and Pyrenophora teres f. teres.     

Identification of close relatives in the HUGO Pan-Asian SNP database

The HUGO Pan-Asian SNP Consortium has recently released a genome-wide dataset, which consists of 1,719 DNA samples collected from 71 Asian populations. For studies of human population genetics such as genetic structure and migration history, this provided the most comprehensive large-scale survey of genetic variation to date in East and Southeast Asia. However, although considered in the analysis, close relatives were not clearly reported in the original paper. Here we performed a systematic analysis of genetic relationships among individuals from the Pan-Asian SNP (PASNP) database and identified 3 pairs of monozygotic twins or duplicate samples, 100 pairs of first-degree and 161 second-degree of relationships. Three standardized subsets with different levels of unrelated individuals were suggested here for future applications of the samples in most types of population-genetics studies (denoted by PASNP1716, PASNP1640 and PASNP1583 respectively) based on the relationships inferred in this study. In addition, we provided gender information for PASNP samples, which were not included in the original dataset, based on analysis of X chromosome data.     

The Nuclear Receptor Signaling Atlas: development of a functional atlas of nuclear receptors

The Nuclear Receptor Signaling Atlas (NURSA) was developed by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), the National Institute on Aging (NIA), and the National Cancer Institute (NCI) of the National Institutes of Health (NIH); the aim of NURSA is to utilize classical approaches to validate existing hypotheses and exploit new and emerging technologies to formulate and test new hypotheses that might elucidate the program of nuclear receptor (NR) structure, function, and role in disease. The means for carrying out this ambitious program required development of interactions among investigators and the combined application of new high-throughput technologies and existing approaches to allow for both mechanistic studies and accrual of large datasets in a discovery-based research effort, all leading to advances with implications for the missions of the NIDDK, NIA, and NCI. A team-based multidisciplinary approach has allowed for both objectives to proceed simultaneously, tied together via a central bioinformatics resource and one web-accessible venue (www.nursa.org). The ultimate goals for the NURSA consortium are to: 1) establish the mechanistic principles of NR function, 2) characterize NR-coregulator complex formation and regulation, 3) map protein-protein interactions for coregulators, 4) identify candidate downstream target genes of NR action, 5) identify target tissue expression of NRs, 6) understand the regulation of NR expression and, 7) integrate existing and emerging information through NURSA bioinformatics tools.