BackgroundChinese indigenous pigs in Yunnan exhibit considerable phenotypic diversity, but their population structure and the biological interpretation of signatures of artificial selection require further investigati...
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BackgroundChinese indigenous pigs in Yunnan exhibit considerable phenotypic diversity, but their population structure and the biological interpretation of signatures of artificial selection require further investigation. To uncover population genetic diversity, migration events, and artificial selection signatures in Chinese domestic pigs, we sampled 111 Yunnan pigs from four breeds in Yunnan which is considered to be one of the centres of livestock domestication in China, and genotyped them using Illumina Porcine SNP60K BeadChip. We then leveraged multiple bioinformatics database tools to further investigate the signatures and associated complex *** structure and migration analyses showed that Diannanxiaoer pigs had different genetic backgrounds from other Yunnan pigs, and Gaoligongshan may undergone the migration events from Baoshan and Saba pigs. Intriguingly, we identified a possible common target of sharing artificial selection on a 265.09 kb region on chromosome 5 in Yunnan indigenous pigs, and the genes on this region were associated with cardiovascular and immune systems. We also detected several candidate genes correlated with dietary adaptation, body size (e.g., PASCIN1, GRM4, ITPR2), and reproductive performance. In addition, the breed-sharing gene MMP16 was identified to be a human-mediated gene. Multiple lines of evidence at the mammalian genome, transcriptome, and phenome levels further supported the evidence for the causality between MMP16 variants and the metabolic diseases, brain development, and cartilage tissues in Chinese pigs. Our results suggested that the suppression of MMP16 would directly lead to inactivity and insensitivity of neuronal activity and skeletal development in Chinese indigenous *** this study, the population genetic analyses and identification of artificial selection signatures of Yunnan indigenous pigs help to build an understanding of the effect of human-mediated selection mechanisms on phen
Background: Although the toxicological impacts of the xenoestrogen bisphenol-A (BPA) have been studied extensively, but the mechanism of action is poorly understood. Eventually, no standard method exists for evaluatin...
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Background: Although the toxicological impacts of the xenoestrogen bisphenol-A (BPA) have been studied extensively, but the mechanism of action is poorly understood. Eventually, no standard method exists for evaluating the possible health hazards of BPA exposure. Considering mice spermatozoa as a potential in vitro model, we investigated the effects of BPA exposure (0.0001, 0.01, 1, and 100 mu M for 6 h) on spermatozoa and the related mechanisms of action. The same doses were also employed to evaluate protein profiles of spermatozoa as a means to monitor their functional affiliation to diseases. Results: Our results demonstrated that high concentrations of BPA negatively affect sperm motility, viability, mitochondrial functions, and intracellular ATP levels by activating the mitogen-activated protein kinase, phosphatidylinositol 3-kinase, and protein kinase-A pathways. Moreover, short-term exposure of spermatozoa to high concentrations of BPA induced differential expressions of 24 proteins. These effects appeared to be caused by protein degradation and phosphorylation in spermatozoa. Proteins differentially expressed in spermatozoa from BPA treatment groups are putatively involved in the pathogenesis of several diseases, mainly cancer, carcinoma, neoplasm, and infertility. Conclusions: Based on these results, we propose that BPA adversely affects sperm function by the activation of several kinase pathways in spermatozoa. In addition, BPA-induced changes in the sperm proteome might be partly responsible for the observed effects in spermatozoa, subsequently involve in the pathogenesis of many diseases. Therefore, we anticipated that current strategy might broadly consider for the health hazards assessment of other toxicological agents.
Background: Several online databases provide a large amount of biomedical data of different biological entities. These resources are typically stored in systems implementing their own data model, user interface and qu...
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Background: Several online databases provide a large amount of biomedical data of different biological entities. These resources are typically stored in systems implementing their own data model, user interface and query language. On the other hand, in many bioinformatics scenarios there is often the need to use more than one resource. The availability of a single bioinformatics platform that integrates many biological resources and services is, for those reasons a fundamental issue. Description: Here, we present BioGraph, a web application that allows to query, visualize and analyze biological data belonging to several online available sources. BioGraph is built upon our previously developed graph database called BioGraphDB, that integrates and stores heterogeneous biological resources and make them available by means of a common structure and a unique query language. BioGraph implements state-of-the-art technologies and provides pre-compiled bioinformatics scenarios, as well as the possibility to perform custom queries and obtaining an interactive and dynamic visualization of results. Conclusion: We present a case study about functional analysis of microRNA in breast cancer in order to demonstrate the functionalities of the system. BioGraph is freely available at http://***. Source files are available on GitHub at https://***/IcarPA-TBlab/BioGraph
A compressed full-text self-index represents a text in a compressed form and still answers queries efficiently. This represents a significant advancement over the (full-)text indexing techniques of the previous decade...
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A compressed full-text self-index represents a text in a compressed form and still answers queries efficiently. This represents a significant advancement over the (full-)text indexing techniques of the previous decade, whose indexes required several times the size of the text. Although it is relatively new, this algorithmic technology has matured up to a point where theoretical research is giving way to practical developments. Nonetheless this requires significant programming skills, a deep engineering effort, and a strong algorithmic background to dig into the research results. To date only isolated implementations and focused comparisons of compressed indexes have been reported, and they missed a common API, which prevented their re-use or deployment within other applications. The goal of this article is to fill this gap. First, we present the existing implementations of compressed indexes from a practitioner's point of view. Second, we introduce the Pizza & Chili site, which offers tuned implementations and a standardized API for the most successful compressed full-text self-indexes, together with effective test-beds and scripts for their automatic validation and test. Third, we show the results of our extensive experiments on these codes with the aim of demonstrating the practical relevance of this novel algorithmic technology. Categories and Subject Descriptors: F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems-Pattern matching, computations on discrete structures, sorting and searching;H.2.1 [Database Management]: Physical Design-Access methods;H.3.2 [Information Storage and Retrieval]: Information Storage-File organization;H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval-Search process General Terms: Algorithms Additional Key Words and Phrases: Text indexing, text compression, data structures, data storage representation, coding and information theory, indexing methods, textual databases, bi
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