利用基因表达谱挖掘差异表达功能类的稳健性

Gene Ontology广泛地应用于基于基因芯片数据的差异表达功能类分析。基因芯片技术存在检测缺失与检测误差等问题。本文探讨上述这二个因素对利用基因表达谱挖掘Gene Ontology中差异表达功能类的影响。结果显示,差异表达功能类对于检测缺失与检测误差干扰等有一定的稳健性。     

Structure-based functional inference in structural genomics

The dramatically increasing number of new protein sequences arising from genomics 4 proteomics requires the need for methods to rapidly and reliably infer the molecular and cellular functions of these proteins. One such approach, structural genomics, aims to delineate the total repertoire of protein folds in nature, thereby providing three-dimensional folding patterns for all proteins and to infer molecular functions of the proteins based on the combined information of structures and sequences. The goal of obtaining protein structures on a genomic scale has motivated the development of high throughput technologies and protocols for macromolecular structure determination that have begun to produce structures at a greater rate than previously possible. These new structures have revealed many unexpected functional inferences and evolutionary relationships that were hidden at the sequence level. Here, we present samples of structures determined at Berkeley Structural Genomics Center and collaborators laboratories to illustrate how structural information provides and complements sequence information to deduce the functional inferences of proteins with unknown molecular functions.Two of the major premises of structural genomics are to discover a complete repertoire of protein folds in nature and to find molecular functions of the proteins whose functions are not predicted from sequence comparison alone. To achieve these objectives on a genomic scale, new methods, protocols, and technologies need to be developed by multi-institutional collaborations worldwide. As part of this effort, the Protein Structure Initiative has been launched in the United States (PSI; www.nigms.nih.gov/funding/psi.html). Although infrastructure building and technology development are still the main focus of structural genomics programs [1–6], a considerable number of protein structures have already been produced, some of them coming directly out of semi-automated structure determination pipelines [6–10]. The Berkeley Structural Genomics Center (BSGC) has focused on the proteins of Mycoplasma or their homologues from other organisms as its structural genomics targets because of the minimal genome size of the Mycoplasmas as well as their relevance to human and animal pathogenicity (http://www.strgen.org). Here we present several protein examples encompassing a spectrum of functional inferences obtainable from their three-dimensional structures in five situations, where the inferences are new and testable, and are not predictable from protein sequence information alone.     

High-throughput analysis of gene expression on tissue sections by in situ hybridization

Genome-scale sequencing projects, high-throughput RNAi screens, systematic gene targeting, and system-biology-based network predictions all depend on a validation of biological significance in order to understand the relevance of a particular finding. Such validation, for the most part, rests on low-throughput technologies. This article provides protocols that, in combination with suitable instrumentation, make possible a semi-automated analysis of gene expression on tissue sections by means of in situ hybridization. Knowledge of gene expression localization has the potential to aid, and thereby accelerate, the validation of gene functions.     

Large-scale T-DNA mutagenesis in Arabidopsis for functional genomic analysis

In planta Agrobacterium-mediated transformation combined with a soil-based herbicide selection for transgenic plants was used to recover large numbers of transgenic Arabidopsis plants for functional genomic studies. A tissue-culture-free system for generating transgenic plants was achieved by infiltrating Arabidopsis plants with Agrobacterium tumefaciens harboring a binary T-DNA vector containing the phosphinothricin acetyltransferase gene from Streptomyces hygroscopicus, and by selecting transgenic Arabidopsis growing in soil by foliar application of the herbicide Finale (phosphinothricin). Analysis of herbicide-resistant plants indicated that all were transgenic and that the T-DNA transformation process occurred late during flower development, resulting in a preponderance of independently derived T-DNA insertions. T-DNA insertions were usually integrated in a concatenated, rearranged form, and using linkage analysis, we estimated that T1 plants carried between one and five T-DNA loci. Using pooling strategies, both DNA and seed pools were generated from about 38,000 Arabidopsis plants representing over 115,000 independent T-DNA insertions. We show the utility of these transgenic lines for identifying insertion mutations using gene sequence and PCR-based screening. Electronic Publication     

Quantitative determination of gene strand bias in prokaryotic genomes

Comparative genometrics of microorganisms is a relatively new area, in which genome properties are translated into numerical indexes. Such indexes can be used for a comprehensive and comparative analysis of microbial genomes, contributing to the understanding of their evolution. This work presents a new method for quantitative determination of gene strand bias in prokaryotic chromosomes, in which data transformation of gene position skew leads to a numerical index that can be applied to quantitative comparisons of genome organization. It was applied in the comparative analysis of 49 completely sequenced Firmicutes genomes, allowing the distinction of groups defined according to their patterns of gene strand preference. The resulting groups revealed that, regarding gene strand bias, reduced genomes are, in general, the more disordered among Firmicutes, while genomes of extremophile organisms comprehend those with the highest degree of genome organization in this phylum.     

Characterization and functional annotation of nested transposable elements in eukaryotic genomes

The movement of transposable elements (TE) in eukaryotic genomes can often result in the occurrence of nested TEs (the insertion of TEs into pre-existing TEs). We performed a general TE assessment using available databases to detect nested TEs and analyze their characteristics and putative functions in eukaryote genomes. A total of 802 TEs were found to be inserted into 690 host TEs from a total number of 11,329 TEs. We reveal that repetitive sequences are associated with an increased occurrence of nested TEs and sequence biased of TE insertion. A high proportion of the genes which were associated with nested TEs are predicted to localize to organelles and participate in nucleic acid and protein binding. Many of these function in metabolic processes, and encode important enzymes for transposition and integration. Therefore, nested TEs in eukaryotic genomes may negatively influence genome expansion, and enrich the diversity of gene expression or regulation.     

MAPLE 2.3.0: an improved system for evaluating the functionomes of genomes and metagenomes

MAPLE is an automated system for inferring the potential comprehensive functions harbored by genomes and metagenomes. To reduce runtime in MAPLE analyzing the massive amino acid datasets of over 1 million sequences, we improved it by adapting the KEGG automatic annotation server to use GHOSTX and verified no substantial difference in the MAPLE results between the original and new implementations.     

Generation,annotation, and analysis of ESTs from four different <Emphasis Type="Italic">Trichoderma</Emphasis> strains grown under conditions related to biocontrol

The functional genomics project “TrichoEST” was developed focused on different taxonomic groups of Trichoderma with biocontrol potential. Four cDNA libraries were constructed, using similar growth conditions, from four different Trichoderma strains: Trichoderma longibrachiatum T52, Trichoderma asperellum T53, Trichoderma virens T59, and Trichoderma sp. T78. In this study, we present the analysis of the 8,160 expressed sequence tags (ESTs) generated. Each EST library was independently assembled and 1,000–1,300 unique sequences were identified in each strain. First, we queried our collection of ESTs against the NCBI nonredundant database using the BLASTX algorithm. Moreover, using the Gene Ontology hierarchy, we performed the annotation of 40.9% of the unique sequences. Later, based on the EST abundance, we examined the highly expressed genes in the four strains. A hydrophobin was found as the gene expressed at the highest level in two of the strains, but we also found that other unique sequences similar to the HEX1, QID3, and NMT1 proteins were highly represented in at least two of the Trichoderma strains. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Computational evaluation of TIS annotation for prokaryotic genomes

Background  

Accurate annotation of translation initiation sites (TISs) is essential for understanding the translation initiation mechanism. However, the reliability of TIS annotation in widely used databases such as RefSeq is uncertain due to the lack of experimental benchmarks.     

Complexity of automated gene annotation

Describing the determinants of robustness of biological systems has become one of the central questions in systems biology. Despite the increasing research efforts, it has proven difficult to arrive at a unifying definition for this important concept. We argue that this is due to the multifaceted nature of the concept of robustness and the possibility to formally capture it at different levels of systemic formalisms (e.g., topology and dynamic behavior). Here we provide a comprehensive review of the existing definitions of robustness pertaining to metabolic networks. As kinetic approaches have been excellently reviewed elsewhere, we focus on definitions of robustness proposed within graph-theoretic and constraint-based formalisms.     

Combining data from genomes, Y2H and 3D structure indicates that BolA is a reductase interacting with a glutaredoxin

Genomes, functional genomics data and 3D structure reflect different aspects of protein function. Here, we combine these data to predict that BolA, a widely distributed protein family with unknown function, is a reductase that interacts with a glutaredoxin. Comparisons at the 3D structure level as well as at the sequence profile level indicate homology between BolA and OsmC, an enzyme that reduces organic peroxides. Complementary to this, comparative analyses of genomes and genomics data provide strong evidence of an interaction between BolA and the mono-thiol glutaredoxin family. The interaction between BolA and a mono-thiol glutaredoxin is of particular interest because BolA does not, in contrast to its homolog OsmC, have evolutionarily conserved cysteines to provide it with reducing equivalents. We propose that BolA uses the mono-thiol glutaredoxin as the source for these.     

基因表达系列分析技术在真菌功能基因组学中的应用

基因表达系列分析( SAGE)是一种在mRNA水平上高通量、快速、灵敏分析细胞或组织基因表达信息,并在基因组学研究中广泛应用的技术.该技术不仅能够全面地分析特定组织或细胞表达的基因,比较不同时空条件下基因表达的差异,还可以在全基因组范围内获得基因的表达谱,从而发现新基因.综述基因表达系列分析技术在材料用量、标签长度、技术流程和标签测序等方面的研究进展及该技术在病原真菌、工业真菌和食用真菌功能基因组学中的应用.     

Learnability-based further prediction of gene functions in Gene Ontology

Currently the functional annotations of many genes are not specific enough, limiting their further application in biology and medicine. It is necessary to push the gene functional annotations deeper in Gene Ontology (GO), or to predict further annotated genes with more specific GO terms. A framework of learnability-based further prediction of gene functions in GO is proposed in this paper. Local classifiers are constructed in local classification spaces rooted at qualified parent nodes in GO, and their classification performances are evaluated with the averaged Tanimoto index (ATI). Classification spaces with higher ATIs are selected out, and genes annotated only to the parent classes are predicted to child classes. Through learnability-based further predicting, the functional annotations of annotated genes are made more specific. Experiments on the fibroblast serum response dataset reported further functional predictions for several human genes and also gave interesting clues to the varied learnability between classes of different GO ontologies, different levels, and different numbers of child classes.     

Functional analysis of the yeast genome

Just as Saccharomyces cerevisiae itself provides a model for so many processes essential to eukaryotic life, we anticipate that the methods and the mindset that have moved yeast biological research "beyond the genome" provide a prototype for making similar progress in other organisms. In this review I describe the experimental processes, results and utility of the current large-scale experimental approaches that use genomic data to provide a functional analysis of the yeast genome. Electronic Publication