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Wu J 《BMC genomics》2008,9(Z2):S13
Background
Computational gene prediction tools routinely generate large volumes of predicted coding exons (putative exons). One common limitation of these tools is the relatively low specificity due to the large amount of non-coding regions.Methods
A statistical approach is developed that largely improves the gene prediction specificity. The key idea is to utilize the evolutionary conservation principle relative to the coding exons. By first exploiting the homology between genomes of two related species, a probability model for the evolutionary conservation pattern of codons across different genomes is developed. A probability model for the dependency between adjacent codons/triplets is added to differentiate coding exons and random sequences. Finally, the log odds ratio is developed to classify putative exons into the group of coding exons and the group of non-coding regions.Results
The method was tested on pre-aligned human-mouse sequences where the putative exons are predicted by GENSCAN and TWINSCAN. The proposed method is able to improve the exon specificity by 73% and 32% respectively, while the loss of the sensitivity ≤ 1%. The method also keeps 98% of RefSeq gene structures that are correctly predicted by TWINSCAN when removing 26% of predicted genes that are in non-coding regions. The estimated number of true exons in TWINSCAN's predictions is 157,070. The results and the executable codes can be downloaded from http://www.stat.purdue.edu/~jingwu/codon/Conclusion
The proposed method demonstrates an application of the evolutionary conservation principle to coding exons. It is a complementary method which can be used as an additional criteria to refine many existing gene predictions.2.
Background
Intrinsically disordered proteins (IDPs) and regions (IDRs) perform a variety of crucial biological functions despite lacking stable tertiary structure under physiological conditions in vitro. State-of-the-art sequence-based predictors of intrinsic disorder are achieving per-residue accuracies over 80%. In a genome-wide study of intrinsic disorder in human genome we observed a big difference in predicted disorder content between confirmed and putative human proteins. We investigated a hypothesis that this discrepancy is not correct, and that it is due to incorrectly annotated parts of the putative protein sequences that exhibit some similarities to confirmed IDRs, which lead to high predicted disorder content.Methods
To test this hypothesis we trained a predictor to discriminate sequences of real proteins from synthetic sequences that mimic errors of gene finding algorithms. We developed a procedure to create synthetic peptide sequences by translation of non-coding regions of genomic sequences and translation of coding regions with incorrect codon alignment.Results
Application of the developed predictor to putative human protein sequences showed that they contain a substantial fraction of incorrectly assigned regions. These regions are predicted to have higher levels of disorder content than correctly assigned regions. This partially, albeit not completely, explains the observed discrepancy in predicted disorder content between confirmed and putative human proteins.Conclusions
Our findings provide the first evidence that current practice of predicting disorder content in putative sequences should be reconsidered, as such estimates may be biased.3.
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Background
Many protein regions and some entire proteins have no definite tertiary structure, presenting instead as dynamic, disorder ensembles under different physiochemical circumstances. These proteins and regions are known as Intrinsically Unstructured Proteins (IUP). IUP have been associated with a wide range of protein functions, along with roles in diseases characterized by protein misfolding and aggregation.Results
Identifying IUP is important task in structural and functional genomics. We exact useful features from sequences and develop machine learning algorithms for the above task. We compare our IUP predictor with PONDRs (mainly neural-network-based predictors), disEMBL (also based on neural networks) and Globplot (based on disorder propensity).Conclusion
We find that augmenting features derived from physiochemical properties of amino acids (such as hydrophobicity, complexity etc.) and using ensemble method proved beneficial. The IUP predictor is a viable alternative software tool for identifying IUP protein regions and proteins.6.
Lili Fu Binhui Jiang Jinliang Liu Xin Zhao Qian Liu Xiaomin Hu 《Biotechnology letters》2016,38(3):447-453
Objective
To explore the metabolic process of Paenibacillus shenyangensis that is an efficient bioflocculant-producing bacterium. The biosynthesis mechanism of bioflocculation was used to enrich the genome of Paenibacillus shenyangensis and provide a basis for molecular genetics and functional genomics analyses.Results
According to the analysis of de novo assembly, a total of 5,501,467 bp clean reads were generated, and were assembled into 92 contigs. 4800 unigenes were predicted of which 4393 were annotated showing a specific gene function in the NCBI-Nr database. 3423 genes were found in the database of cluster of orthologous groups. Among the 168 Kyoto Encyclopedia of Genes and Genomes database, cell growth and metabolism were the main biological processes, and a potential metabolic pathway was predicted from glucose to exopolysaccharide within the starch and sucrose metabolism pathway.Conclusion
By using the high-throughput sequencing technology, we provide a genome analysis of Paenibacillus shenyangensis that predicts the main metabolic processes and a potential pathway of exopolysaccharide biosynthesis.7.
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Background
The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.Results
The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.Conclusion
The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.11.
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Background
In crop species, QTL analysis is commonly used for identification of factors contributing to variation of agronomically important traits. As an important pasture species, a large number of QTLs have been reported for perennial ryegrass based on analysis of biparental mapping populations. Further characterisation of those QTLs is, however, essential for utilisation in varietal improvement programs.Results
A bibliographic survey of perennial ryegrass trait-dissection studies identified a total of 560 QTLs from previously published papers, of which 189, 270 and 101 were classified as morphology-, physiology- and resistance/tolerance-related loci, respectively. The collected dataset permitted a subsequent meta-QTL study and implementation of a cross-species candidate gene identification approach. A meta-QTL analysis based on use of the BioMercator software was performed to identify two consensus regions for pathogen resistance traits. Genes that are candidates for causal polymorphism underpinning perennial ryegrass QTLs were identified through in silico comparative mapping using rice databases, and 7 genes were assigned to the p150/112 reference map. Markers linked to the Lp DGL1, Lp Ph1 and Lp PIPK1 genes were located close to plant size, leaf extension time and heading date-related QTLs, respectively, suggesting that these genes may be functionally associated with important agronomic traits in perennial ryegrass.Conclusions
Functional markers are valuable for QTL meta-analysis and comparative genomics. Enrichment of such genetic markers may permit further detailed characterisation of QTLs. The outcomes of QTL meta-analysis and comparative genomics studies may be useful for accelerated development of novel perennial ryegrass cultivars with desirable traits.13.
Yeong C Kim Yong-Chul Jung Jun Chen Ali H Alhasan Parawee Kaewsaard Yanming Zhang Shuo Ma Steve Rosen San Ming Wang 《BMC research notes》2010,3(1):341
Background
Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the western population. Although genetic factors are considered to contribute to CLL etiology, at present genomic aberrations identified in CLL are limited compared with those identified in other types of leukemia, which raises the question of the degree of genetic influence on CLL. We performed a high-resolution genome scanning study to address this issue.Findings
Using the restriction paired-end-based Ditag Genome Scanning technique, we analyzed three primary CLL samples at a kilobase resolution, and further validated the results in eight primary CLL samples including the two used for ditag collection. From 51,632 paired-end tags commonly detected in the three CLL samples representing 5% of the HindIII restriction fragments in the genomes, we identified 230 paired-end tags that were present in all three CLL genomes but not in multiple normal human genome reference sequences. Mapping the full-length sequences of the fragments detected by these unmapped tags in seven additional CLL samples confirmed that these are the genomic aberrations caused by small insertions and deletions, and base changes spreading across coding and non-coding regions.Conclusions
Our study identified hundreds of loci with insertion, deletion, base change, and restriction site polymorphism present in both coding and non-coding regions in CLL genomes, indicating the wide presence of small genomic aberrations in chronic lymphocytic leukemia. Our study supports the use of a whole genome sequencing approach for comprehensively decoding the CLL genome for better understanding of the genetic defects in CLL.14.
Background
With the maturity of next generation sequencing technology, a huge amount of epigenomic data have been generated by several large consortia in the last decade. These plenty resources leave us the opportunity about sufficiently utilizing those data to explore biological problems.Results
Here we developed an integrative and comparative method, CsreHMM, which is based on a hidden Markov model, to systematically reveal cell type-specific regulatory elements (CSREs) along the whole genome, and simultaneously recognize the histone codes (mark combinations) charactering them. This method also reveals the subclasses of CSREs and explicitly label those shared by a few cell types. We applied this method to a data set of 9 cell types and 9 chromatin marks to demonstrate its effectiveness and found that the revealed CSREs relates to different kinds of functional regulatory regions significantly. Their proximal genes have consistent expression and are likely to participate in cell type-specific biological functions.Conclusions
These results suggest CsreHMM has the potential to help understand cell identity and the diverse mechanisms of gene regulation.15.
Natsumi Takei Takuma Nakamura Shohei Kawamura Yuki Takada Yui Satoh Atsushi P. Kimura Tomoya Kotani 《Biological procedures online》2018,20(1):6
Background
Subcellular localization of coding and non-coding RNAs has emerged as major regulatory mechanisms of gene expression in various cell types and many organisms. However, techniques that enable detection of the subcellular distribution of these RNAs with high sensitivity and high resolution remain limited, particularly in vertebrate adult tissues and organs. In this study, we examined the expression and localization of mRNAs encoding Pou5f1/Oct4, Mos, Cyclin B1 and Deleted in Azoospermia-like (Dazl) in zebrafish and mouse ovaries by combining tyramide signal amplification (TSA)-based in situ hybridization with paraffin sections which can preserve cell morphology of tissues and organs at subcellular levels. In addition, the distribution of a long non-coding RNA (lncRNA), lncRNA-HSVIII, in mouse testes was examined by the same method.Results
The mRNAs encoding Mos, Cyclin B1 and Dazl were found to assemble into distinct granules that were distributed in different subcellular regions of zebrafish and mouse oocytes, suggesting conserved and specific regulations of these mRNAs. The lncRNA-HSVIII was first detected in the nucleus of spermatocytes at prophase I of the meiotic cell cycle and was then found in the cytoplasm of round spermatids, revealing expression patterns of lncRNA during germ cell development. Collectively, the in situ hybridization method demonstrated in this study achieved the detection and comparison of precise distribution patterns of coding and non-coding RNAs at subcellular levels in single cells of adult tissues and organs.Conclusions
This high-sensitivity and high-resolution in situ hybridization is applicable to many vertebrate species and to various tissues and organs and will be useful for studies on the subcellular regulation of gene expression at the level of RNA localization.16.
Jensen LJ Skovgaard M Sicheritz-Pontén T Jørgensen MK Lundegaard C Pedersen CC Petersen N Ussery D 《BMC genomics》2003,4(1):12
Background
For most sequenced prokaryotic genomes, about a third of the protein coding genes annotated are "orphan proteins", that is, they lack homology to known proteins. These hypothetical genes are typically short and randomly scattered throughout the genome. This trend is seen for most of the bacterial and archaeal genomes published to date.Results
In contrast we have found that a large fraction of the genes coding for such orphan proteins in the Methanopyrus kandleri AV19 genome occur within two large regions. These genes have no known homologs except from other M. kandleri genes. However, analysis of their lengths, codon usage, and Ribosomal Binding Site (RBS) sequences shows that they are most likely true protein coding genes and not random open reading frames.Conclusions
Although these regions can be considered as candidates for massive lateral gene transfer, our bioinformatics analysis suggests that this is not the case. We predict many of the organism specific proteins to be transmembrane and belong to protein families that are non-randomly distributed between the regions. Consistent with this, we suggest that the two regions are most likely unrelated, and that they may be integrated plasmids.17.
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