InterPro as a new tool for complete genome analysis: An example of comparative analysis

InterPro, an integrated documentation resource for protein families, protein domains, and functional sites, was developed to amalgamate the individual efforts of the PROSITE, PRINTS, Pfam, and ProDom databases. InterPro can be used for the computational functional classification of newly determined amino acid sequences that lack biochemical characterization and for comparative genome analysis. InterPro contains over 3500 entries for more than 1 000 000 hits in SWISS-PROT and TrEMBL. The database is accessible for text-and sequence-based searches at http://www.ebi.ac.uk/interpro/. InterPro was used for the complete analysis of the proteome of the pathogenic microorganism Mycobacterium tuberculosis and the comparison with the predicted protein-coding sequences of the complete genomes of Bacillus subtilis and Escherichia coli. It was found that 64.8% of proteins in the proteome of M. tuberculosis matched InterPro entries and can be classified by their functions. The comparison with B. subtilis and E. coli provided information on the most common protein families and domains and on the most highly represented protein families in each organism. Thus, InterPro is a useful tool for general comparison of complete proteomes and their compositions.     

Microarray and proteomic analysis of brassinosteroid- and gibberellin-regulated gene and protein expression in rice

Brassinosteroid (BR) and gibberellin (GA) are two groups of plant growth regulators essential for normal plant growth and development. To gain insight into the molecular mechanism by which BR and GA regulate the growth and development of plants, especially the monocot plant rice, it is necessary to identify and analyze more genes and proteins that are regulated by them. With the availability of draft sequences of two major types, japonica and indica rice, it has become possible to analyze expression changes of genes and proteins at genome scale. In this review, we summarize rice functional genomic research by using microarray and proteomic approaches and our recent research results focusing on the comparison of cDNA microarray and proteomic analyses of BR- and GA-regulated gene and protein expression in rice. We believe our findings have important implications for understanding the mechanism by which BR and GA regulate the growth and development of rice.     

Proteome microarray technology and application: higher,wider, and deeper

ABSTRACT

Introduction: Protein microarray is a powerful tool for both biological study and clinical research. The most useful features of protein microarrays are their miniaturized size (low reagent and sample consumption), high sensitivity and their capability for parallel/high-throughput analysis. The major focus of this review is functional proteome microarray.

Areas covered: For proteome microarray, this review will discuss some recently constructed proteome microarrays and new concepts that have been used for constructing proteome microarrays and data interpretation in past few years, such as PAGES, M-NAPPA strategy, VirD technology, and the first protein microarray database. this review will summarize recent proteomic scale applications and address the limitations and future directions of proteome microarray technology.

Expert opinion: Proteome microarray is a powerful tool for basic biological and clinical research. It is expected to see improvements in the currently used proteome microarrays and the construction of more proteome microarrays for other species by using traditional strategies or novel concepts. It is anticipated that the maximum number of features on a single microarray and the number of possible applications will be increased, and the information that can be obtained from proteome microarray experiments will more in-depth in the future.     

人类蛋白质组表达谱蛋白质鉴定的分步搜索策略

大规模蛋白质组表达谱研究的蛋白质鉴定一般采取基于数据库搜索的策略,因此数据库的选择及搜索策略在蛋白质鉴定中非常重要。现有的人类蛋白质数据库远不够完善,而从其他物种的蛋白质数据库中所能得到的补充非常有限,但人类基因组数据库中却可能含有很大的补充空间。在对国际人类蛋白质数据库充分调研、比较的基础上,提出了一种分步搜索的策略。这种策略首先利用一个质量较高、覆盖率相对较大的非冗余数据库进行基本鉴定,随后利用其他蛋白和核酸数据库进行补充鉴定和新蛋白挖掘。该策略能有效地鉴定尽可能多的高可靠蛋白,并能进一步充分利用质谱数据进行补充鉴定和新蛋白挖掘,对大规模蛋白质组表达谱研究具有重要的意义。     

Dynamical analysis of gene networks requires both mRNA and protein expression information

One of the important goals of biology is to understand the relationship between DNA sequence information and nonlinear cellular responses. This relationship is central to the ability to effectively engineer cellular phenotypes, pathways, and characteristics. Expression arrays for monitoring total gene expression based on mRNA can provide quantitative insight into which gene or genes are on or off; but this information is insufficient to fully predict dynamic biological phenomena. Using nonlinear stability analysis we show that a combination of gene expression information at the message level and at the protein level is required to describe even simple models of gene networks. To help illustrate the need for such information we consider a mechanistic model for circadian rhythmicity which shows agreement with experimental observations when protein and mRNA information are included and we propose a framework for acquiring and analyzing experimental and mathematically derived information about gene networks.     

High throughput platform to explore RNA–protein interactomes

RNA binding proteins (RBPs) and RNA interaction is an emerging topic in molecular biology. Many reports showed that such interactions contribute to many cellular processes as well as disease development. Several standard in vitro and in vivo methods were developed to fulfill the needs of this RBP–RNA interaction study to explore their biological functions. However, these methods have their limitations in terms of throughput. In this review, we emphasize two important high throughput methods to studying RBP–RNA interactions, affinity purification and protein microarray. These methods have recently become robust techniques regarding their efficiency in systematically analyzing RBP–RNA interactions. Here, we provide technique overviews, strategies and applications of these methods during biological research. Although these technologies are just beginning to be explored, they will be most important methods in this study.     

基因表达谱微阵列网络数据库在肿瘤研究中的应用

基因表达谱微阵列数据库是一类可提供存储、查询、下载分析的在线网络数据库,在肿瘤相关领域的研究中提供了大量的数据来源。由于微阵列分析对于无生物/医学信息学专业背景的研究人员仍然有较多困难,致使该数据库的使用尚未普及。本文从数据查询、下载分析和使用方法等方面对常用基因表达谱微阵列数据库进行概述,并对现阶段基因表达微阵列数据库的应用策略进行总结,旨在帮助该领域研究的初学工作者了解数据库的基本知识并推动其在科研工作中的应用。     

Inferring gene networks from time series microarray data using dynamic Bayesian networks

Dynamic Bayesian networks (DBNs) are considered as a promising model for inferring gene networks from time series microarray data. DBNs have overtaken Bayesian networks (BNs) as DBNs can construct cyclic regulations using time delay information. In this paper, a general framework for DBN modelling is outlined. Both discrete and continuous DBN models are constructed systematically and criteria for learning network structures are introduced from a Bayesian statistical viewpoint. This paper reviews the applications of DBNs over the past years. Real data applications for Saccharomyces cerevisiae time series gene expression data are also shown.     

Proteomics: A Paradigm Shift

ABSTRACT

Proteome—the protein complement of a genome—has become the protein renaissance and a key research tool in the post-genomic era. The basic technology involves the routine usage of gel electrophoresis and spectrometry procedures for deciphering the primary protein sequence/structure as well as knowing certain unique post-translational modifications that a particular protein has undergone to perform a specific function in the cell. However, the recent advancements in protein analysis have ushered this science to provide deeper, bigger and more valuable perspectives regarding performance of subtle protein-protein interactions. Applications of this branch of molecular biology are as vast as the subject is and include clinical diagnostics, pharmaceutical and biotechnological industries. The 21st century hails the use of products, procedures and advancements of this science as finer touches required for the grooming of fast-paced technology.     

串联质谱数据的从头解析与蛋白质的数据库搜索鉴定

蛋白质的鉴定是蛋白质组学研究中必不可少的一步。用串联质谱 (tandemmassspectrometry ,MS/MS)可以进行多肽的从头测序 (denovosequencing) ,并搜索数据库以鉴定蛋白质。用图论以及真实谱 理论谱联配 (alignment)的方法对串联质谱得到的多肽图谱进行从头解析 ,得到了可靠的多肽序列 ,并应用到数据库搜索中鉴定了相应的蛋白质。同时 ,还用统计的方法对SwissProt以及TrEMBL蛋白质数据库进行了详细的分析。结果表明 ,3个四肽或者 2个五肽或者 1个八肽一般可以唯一地确定一个蛋白质     

Pervasive gene conversion in chromosomal inversion heterozygotes

Chromosomal inversions shape recombination landscapes, and species differing by inversions may exhibit reduced gene flow in these regions of the genome. Though single crossovers within inversions are not usually recovered from inversion heterozygotes, the recombination barrier imposed by inversions is nuanced by noncrossover gene conversion. Here, we provide a genomewide empirical analysis of gene conversion rates both within species and in species hybrids. We estimate that gene conversion occurs at a rate of 1 × 10^–5 to 2.5 × 10^–5 converted sites per bp per generation in experimental crosses within Drosophila pseudoobscura and between D. pseudoobscura and its naturally hybridizing sister species D. persimilis. This analysis is the first direct empirical assessment of gene conversion rates within inversions of a species hybrid. Our data show that gene conversion rates in interspecies hybrids are at least as high as within‐species estimates of gene conversion rates, and gene conversion occurs regularly within and around inverted regions of species hybrids, even near inversion breakpoints. We also found that several gene conversion events appeared to be mitotic rather than meiotic in origin. Finally, we observed that gene conversion rates are higher in regions of lower local sequence divergence, yet our observed gene conversion rates in more divergent inverted regions were at least as high as in less divergent collinear regions. Given our observed high rates of gene conversion despite the sequence differentiation between species, especially in inverted regions, gene conversion has the potential to reduce the efficacy of inversions as barriers to recombination over evolutionary time.     

A gene selection algorithm based on the gene regulation probability using maximal likelihood estimation

A novel gene selection algorithm based on the gene regulation probability is proposed. In this algorithm, a probabilistic model is established to estimate gene regulation probabilities using the maximum likelihood estimation method and then these probabilities are used to select key genes related by class distinction. The application on the leukemia data-set suggests that the defined gene regulation probability can identify the key genes to the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) class distinction and the result of our proposed algorithm is competitive to those of the previous algorithms.     

cDNA Cloning, Tissue Distribution and Chromosomal Localization of the Human ID4 Gene

A cDNA encoding the human Id4 protein has been isolated froman astrocytoma library. The predicted protein product shares98% identity with the mouse Id4 protein and is markedly differentfrom that already reported. By FISH analysis, the human ID4gene was more precisely mapped to chromosome 6p22.3-p23. Northernblot analysis showed that ID4 is mainly expressed in thyroid,brain and fetal tissue and in some nervous system tumor celllines.     

Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine maxL. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r² = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic plants.