http://www.csie.ntu.edu.tw/~b89x035/yeast/

There are two very different interpretations of the prehistory of Island Southeast Asia (ISEA), with genetic evidence invoked in support of both. The “out-of-Taiwan” model proposes a major Late Holocene expansion of Neolithic Austronesian speakers from Taiwan. An alternative, proposing that Late Glacial/postglacial sea-level rises triggered largely autochthonous dispersals, accounts for some otherwise enigmatic genetic patterns, but fails to explain the Austronesian language dispersal. Combining mitochondrial DNA (mtDNA), Y-chromosome and genome-wide data, we performed the most comprehensive analysis of the region to date, obtaining highly consistent results across all three systems and allowing us to reconcile the models. We infer a primarily common ancestry for Taiwan/ISEA populations established before the Neolithic, but also detected clear signals of two minor Late Holocene migrations, probably representing Neolithic input from both Mainland Southeast Asia and South China, via Taiwan. This latter may therefore have mediated the Austronesian language dispersal, implying small-scale migration and language shift rather than large-scale expansion.Electronic supplementary materialThe online version of this article (doi:10.1007/s00439-015-1620-z) contains supplementary material, which is available to authorized users.

Heroin use disorder (HUD) is a complex disease resulting from interactions among genetic and other factors (e.g., environmental factors). The mechanism of HUD development remains unknown. Newly developed network medicine tools provide a platform for exploring complex diseases at the system level. This study proposes that protein–protein interactions (PPIs), particularly those among proteins encoded by casual or susceptibility genes, are extremely crucial for HUD development. The giant component of our constructed PPI network comprised 111 nodes with 553 edges, including 16 proteins with large degree (k) or high betweenness centrality (BC), which were further identified as the backbone of the network. JUN with the largest degree was suggested to be central to the PPI network associated with HUD. Moreover, PCK1 with the highest BC and MAPK14 with the secondary largest degree and 9th highest BC might be involved in the development HUD and other substance diseases.

BackgroundInvestigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut-offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies.ResultsAmong the discarded data, we found that 23.7 ± 3.9% of singletons and 14.1 ± 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The Pearson correlation coefficient revealed a high degree of similarity (0.94 ± 0.03 at the phylum rank and 0.80 ± 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach.ConclusionsOur findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.