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Physcomitrella patens is a bryophyte model plant that is often used to study plant evolution and development. Its resources are of great importance for comparative genomics and evo‐devo approaches. However, expression data from Physcomitrella patens were so far generated using different gene annotation versions and three different platforms: CombiMatrix and NimbleGen expression microarrays and RNA sequencing. The currently available P. patens expression data are distributed across three tools with different visualization methods to access the data. Here, we introduce an interactive expression atlas, Physcomitrella Expression Atlas Tool (PEATmoss), that unifies publicly available expression data for P. patens and provides multiple visualization methods to query the data in a single web‐based tool. Moreover, PEATmoss includes 35 expression experiments not previously available in any other expression atlas. To facilitate gene expression queries across different gene annotation versions, and to access P. patens annotations and related resources, a lookup database and web tool linked to PEATmoss was implemented. PEATmoss can be accessed at https://peatmoss.online.uni-marburg.de  相似文献   
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解淀粉芽孢杆菌生防菌BS-3全基因组测序及生物信息分析   总被引:1,自引:0,他引:1  
【背景】解淀粉芽孢杆菌BS-3是从健康橡胶树树根中分离获得的一株对真菌具有较强抗菌活性的内生细菌,有作为生物农药的潜力。【目的】解析菌株BS-3的基因组序列信息,以深入研究该菌株防病促生机制及挖掘次级代谢产物基因资源。【方法】采用第二代BGISEQ与第三代Pac Bio平台相结合的测序技术,对生防菌BS-3进行全基因组测序,并对测序数据进行基因组组装、基因预测与功能注释、共线性分析及次级代谢产物合成基因簇预测等。【结果】BS-3全基因组大小为3 870 130 bp,平均GC含量为46.88%,共编码4 161个基因;含有92个t RNA基因、28个r RNA、10个sRNA;含有122个串联重复序列、98个小卫星DNA、2个微卫星。在COG、GO、KEGG、NR和Swiss-Prot数据库分别注释到基因2 875、2 620、1 885、4 040和3 328个。同时,预测到BS-3中有10个次级代谢产物合成基因簇,编码表面活性素、丰原素、多烯类、儿茶酚型嗜铁素等抑菌物质。基因组测序数据提交至NCBI获得GenBank登录号为CP060384。【结论】为基因组层面上解析菌株BS-3具有良好防病效果的内在原因提供基础数据,为深入了解解淀粉芽孢杆菌次级代谢合成途径提供参考信息,对菌株BS-3后续相关研究具有重要意义。  相似文献   
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【背景】长孢葡萄穗霉菌(Stachybotrys longispora) FG216是一株稀有海洋真菌,其次生代谢产物FGFC1具有纤溶活性。进行S. longispora FG216的基因组序列分析,将充实和促进海洋微生物功能基因和次生代谢产物合成生物学的基础研究和应用研究。【目的】解析S. longispora FG216的基因组序列,分析基因组生物功能和同源相似性关系,分析次生代谢产物纤溶活性化合物FGFC1的相关基因。【方法】基于Illumina HiSeq高通量测序平台对S. longispora FG216菌株进行De Novo测序,使用SSPACE、Augustus等软件进行组装、编码基因预测、基因功能注释、物种共线性分析以及预测FGFC1次生代谢产物合成基因簇。【结果】S. longispora FG216的基因组测序总长度为45622830bp,共得到605个Scaffold,GC含量为51.31%,注释预测得到13329个编码基因和169个非编码RNA。基因组测序数据提交至国家微生物科学数据中心(编号为NMDC60016264),其中13 053、8 422、8 460、7 714和2 847个基因分别能够在NR、KEGG、KOG、GO和CAZy数据库匹配到注释信息。比较基因组学分析发现,Stachybotrys具有保守性,核心基因占基因家族总数目的71.44%,S. longispora FG216与S. chlorohalonata IBT 40285的相似性最高;同时,预测得到101个次生代谢产物合成基因簇,其中18个基因簇与已知的化合物相匹配。通过antiSMASH预测,Cluster57是编码合成FGFC1母核结构异吲哚啉酮的基因簇,与S.chlorohalonataIBT40285中的基因簇相似度为40%。【结论】海洋稀有真菌S.longisporaFG216的基因组信息已上传至国家微生物科学数据中心公开使用,为Stachybotrys种属的研究提供了重要的参考意义,同时发现了S. longispora FG216次生代谢产物纤溶活性化合物FGFC1母核部分编码基因是Cluster 57。  相似文献   
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All neurodegenerative diseases feature aggregates, which usually contain disease‐specific diagnostic proteins; non‐protein constituents, however, have rarely been explored. Aggregates from SY5Y‐APPSw neuroblastoma, a cell model of familial Alzheimer''s disease, were crosslinked and sequences of linked peptides identified. We constructed a normalized “contactome” comprising 11 subnetworks, centered on 24 high‐connectivity hubs. Remarkably, all 24 are nucleic acid‐binding proteins. This led us to isolate and sequence RNA and DNA from Alzheimer''s and control aggregates. RNA fragments were mapped to the human genome by RNA‐seq and DNA by ChIP‐seq. Nearly all aggregate RNA sequences mapped to specific genes, whereas DNA fragments were predominantly intergenic. These nucleic acid mappings are all significantly nonrandom, making an artifactual origin extremely unlikely. RNA (mostly cytoplasmic) exceeded DNA (chiefly nuclear) by twofold to fivefold. RNA fragments recovered from AD tissue were ~1.5‐to 2.5‐fold more abundant than those recovered from control tissue, similar to the increase in protein. Aggregate abundances of specific RNA sequences were strikingly differential between cultured SY5Y‐APPSw glioblastoma cells expressing APOE3 vs. APOE4, consistent with APOE4 competition for E‐box/CLEAR motifs. We identified many G‐quadruplex and viral sequences within RNA and DNA of aggregates, suggesting that sequestration of viral genomes may have driven the evolution of disordered nucleic acid‐binding proteins. After RNA‐interference knockdown of the translational‐procession factor EEF2 to suppress translation in SY5Y‐APPSw cells, the RNA content of aggregates declined by >90%, while reducing protein content by only 30% and altering DNA content by ≤10%. This implies that cotranslational misfolding of nascent proteins may ensnare polysomes into aggregates, accounting for most of their RNA content.  相似文献   
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This review describes how intimately proteogenomics and system biology are imbricated. Quantitative cell-wide monitoring of cellular processes and the analysis of this information is the basis for systems biology. Establishing the most comprehensive protein-parts list is an essential prerequisite prior to analysis of the cell-wide dynamics of proteins, their post-translational modifications, their complex network interactions and interpretation of these data as a whole. High-quality genome annotation is, thus, a crucial basis. Proteogenomics consists of high-throughput identification and characterization of proteins by extra-large shotgun MS/MS approaches and the integration of these data with genomic data. Discovery of the remaining unannotated genes, defining translational start sites, listing signal peptide processing events and post-translational modifications, are tasks that can currently be carried out at a full-genomic scale as soon as the genomic sequence is available. Proteomics is increasingly being used at the primary stage of genome annotation and such an approach may become standard in the near future for genome projects. Advantageously, the same experimental proteomic datasets may be used to characterize the specific metabolic traits of the organism under study. Undoubtedly, comparative genomics will experience a renaissance taking into account this new dimension. Synthetic biology aimed at re-engineering living systems will also benefit from these significant progresses.  相似文献   
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Background and Aims

Although monocotyledonous plants comprise one of the two major groups of angiosperms and include >65 000 species, comprehensive genome analysis has been focused mainly on the Poaceae (grass) family. Due to this bias, most of the conclusions that have been drawn for monocot genome evolution are based on grasses. It is not known whether these conclusions apply to many other monocots.

Methods

To extend our understanding of genome evolution in the monocots, Asparagales genomic sequence data were acquired and the structural properties of asparagus and onion genomes were analysed. Specifically, several available onion and asparagus bacterial artificial chromosomes (BACs) with contig sizes >35 kb were annotated and analysed, with a particular focus on the characterization of long terminal repeat (LTR) retrotransposons.

Key Results

The results reveal that LTR retrotransposons are the major components of the onion and garden asparagus genomes. These elements are mostly intact (i.e. with two LTRs), have mainly inserted within the past 6 million years and are piled up into nested structures. Analysis of shotgun genomic sequence data and the observation of two copies for some transposable elements (TEs) in annotated BACs indicates that some families have become particularly abundant, as high as 4–5 % (asparagus) or 3–4 % (onion) of the genome for the most abundant families, as also seen in large grass genomes such as wheat and maize.

Conclusions

Although previous annotations of contiguous genomic sequences have suggested that LTR retrotransposons were highly fragmented in these two Asparagales genomes, the results presented here show that this was largely due to the methodology used. In contrast, this current work indicates an ensemble of genomic features similar to those observed in the Poaceae.  相似文献   
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RNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent–gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent–gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.  相似文献   
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