CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology

SUMMARY: Analysis of microarray data most often produces lists of genes with similar expression patterns, which are then subdivided into functional categories for biological interpretation. Such functional categorization is most commonly accomplished using Gene Ontology (GO) categories. Although there are several programs that identify and analyze functional categories for human, mouse and yeast genes, none of them accept Arabidopsis thaliana data. In order to address this need for A.thaliana community, we have developed a program that retrieves GO annotations for A.thaliana genes and performs functional category analysis for lists of genes selected by the user. AVAILABILITY: http://www.personal.psu.edu/nhs109/Clench     

MEGO: gene functional module expression based on gene ontology

Existing analysis tools to study the collective properties of gene functional modules cannot return highly homogeneous modules and do not provide quantitative measures of module activity level. By partitioning genes according to multiple gene functional categorization principles and summarizing gene expression values into module expression values, MEGO (module expression based on gene ontology), a standalone microarray data analysis program, is able to extract highly activated gene functional modules that are of much interest to microarray experimenters. With multiple functional categorization principles simultaneously introduced in MEGO, the partition of genes is more delicate, and the collective property of a group of genes is sharpened and easier to capture. The quantitative measures of module activity levels returned by MEGO give users a quick impression of the direction and degree of module regulation. MEGO efficiently determines the answers to frequently asked questions, such as which functional classes have been induced or repressed under a specific experiment and to which levels these functional classes have been affected. MEGO is available free of charge for academic use and may be downloaded from http://www.dxy.cn/mego/MEGOInstall.EXE. Supplementary information can be found on the authors' web page at http://www.dxy.cn/mego/ and at the BioTechniques' web site at http://www. BioTechniques.com/February2005/TuSupplementary.html.     

PiNGO: a Cytoscape plugin to find candidate genes in biological networks

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for a wide range of organisms and Gene Ontology classification schemes, and it can easily be customized for other organisms and functional classifications. PiNGO is implemented as a plugin for Cytoscape, a popular network visualization platform. AVAILABILITY: PiNGO is distributed as an open-source Java package under the GNU General Public License (http://www.gnu.org/), and can be downloaded via the Cytoscape plugin manager. A detailed user guide and tutorial are available on the PiNGO website (http://www.psb.ugent.be/esb/PiNGO.     

Hierarchical tree snipping: clustering guided by prior knowledge

MOTIVATION: Hierarchical clustering is widely used to cluster genes into groups based on their expression similarity. This method first constructs a tree. Next this tree is partitioned into subtrees by cutting all edges at some level, thereby inducing a clustering. Unfortunately, the resulting clusters often do not exhibit significant functional coherence. RESULTS: To improve the biological significance of the clustering, we develop a new framework of partitioning by snipping--cutting selected edges at variable levels. The snipped edges are selected to induce clusters that are maximally consistent with partially available background knowledge such as functional classifications. Algorithms for two key applications are presented: functional prediction of genes, and discovery of functionally enriched clusters of co-expressed genes. Simulation results and cross-validation tests indicate that the algorithms perform well even when the actual number of clusters differs considerably from the requested number. Performance is improved compared with a previously proposed algorithm. AVAILABILITY: A java package is available at http://www.cs.bgu.ac.il/~dotna/ TreeSnipping     

Evolutionary simulations to detect functional lineage-specific genes

MOTIVATION: Supporting the functionality of recent duplicate gene copies is usually difficult, owing to high sequence similarity between duplicate counterparts and shallow phylogenies, which hamper both the statistical and experimental inference. RESULTS: We developed an integrated evolutionary approach to identify functional duplicate gene copies and other lineage-specific genes. By repeatedly simulating neutral evolution, our method estimates the probability that an ORF was selectively conserved and is therefore likely to represent a bona fide coding region. In parallel, our method tests whether the accumulation of non-synonymous substitutions reveals signatures of selective constraint. We show that our approach has high power to identify functional lineage-specific genes using simulated and real data. For example, a coding region of average length (approximately 1400 bp), restricted to hominoids, can be predicted to be functional in approximately 94-100% of cases. Notably, the method may support functionality for instances where classical selection tests based on the ratio of non-synonymous to synonymous substitutions fail to reveal signatures of selection. Our method is available as an automated tool, ReEVOLVER, which will also be useful to systematically detect functional lineage-specific genes of closely related species on a large scale. AVAILABILITY: ReEVOLVER is available at http://www.unil.ch/cig/page7858.html.     

A framework for exhaustively mapping functional missense variants

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin‐like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.     

SCEPTRANS: an online tool for analyzing periodic transcription in yeast

SUMMARY: SCEPTRANS is designed for analysis of microarray timecourse data related to periodic phenomena in the budding yeast. The server allows for easy viewing of temporal profiles of multiple genes in a number of datasets. Additional functionality includes searching for coexpressed genes, periodicity and correlation analysis, integrating functional annotation and localization data as well as advanced operations on sets of genes. AVAILABILITY: Available online at http://sceptrans.org/     

A comprehensive protein-centric ID mapping service for molecular data integration

MOTIVATION: Identifier (ID) mapping establishes links between various biological databases and is an essential first step for molecular data integration and functional annotation. ID mapping allows diverse molecular data on genes and proteins to be combined and mapped to functional pathways and ontologies. We have developed comprehensive protein-centric ID mapping services providing mappings for 90 IDs derived from databases on genes, proteins, pathways, diseases, structures, protein families, protein interaction, literature, ontologies, etc. The services are widely used and have been regularly updated since 2006. AVAILABILITY: www.uniprot.org/mappingandproteininformation-resource.org/pirwww/search/idmapping.shtml CONTACT: huang@dbi.udel.edu.     

GeConT: gene context analysis

SUMMARY: The fact that adjacent genes in bacteria are often functionally related is widely known. GeConT (Gene Context Tool) is a web interface designed to visualize genome context of a gene or a group of genes and their orthologs in all the completely sequenced genomes. The graphical information of GeConT can be used to analyze genome annotation, functional ortholog identification or to verify the genomic context congruence of any set of genes that share a common property. AVAILABILITY: http://www.ibt.unam.mx/biocomputo/gecont.html     

Synonymous codon usage and gene function are strongly related in Oryza sativa

The relationship between codon usage and gene function was investigated while considering a dataset of 2106 nuclear genes of Oryza sativa. The results of standard chi(2) test and F-statistic showed that for every 59 synonymous codons, a strongly significant association with gene functional categories existed in rice, indicating that codon usage was generally coordinated with gene function whether it was at the level of individual amino acids or at the level of nucleotides. However, it could not be directly said that the use of every codons differed significantly between any two functional categories. Notably, there existed large difference both in selection for biased codons or selection intensity among functional categories. Therefore, we identified at least two classes of genes: one group of genes, mainly belonging to the "METABOLISM" category, was tended to use G- and/or C-ending codons while the other was more biased to choose codons ending with A and/or U. The latter group contained genes of various functions, especially those genes classified into the "Nuclear Structure" category. These observations will be more important for molecular genetic engineering and genome functional annotation.     

Acquisition of a potential marker for insect transformation: isolation of a novel alcohol dehydrogenase gene from Bactrocera oleae by functional complementation in yeast

The alcohol dehydrogenase genes make up one of the best studied gene families in Drosophila, both in terms of expression and evolution. Moreover, alcohol dehydrogenase genes constitute potential versatile markers in insect transformation experiments. However, due to their rapid evolution, these genes cannot be cloned from other insect genera by DNA hybridization or PCR-based strategies. We have therefore explored an alternative strategy: cloning by functional complementation of appropriate yeast mutants. Here we report that two alcohol dehydrogenase genes from the medfly Ceratitis capitata can functionally replace the yeast enzymes, even though the medfly and yeast genes have evolved independently, acquiring their enzymatic function convergently. Using this method, we have cloned an alcohol dehydrogenase gene from the olive pest Bactrocera oleae. We conclude that functional complementation in yeast can be used to clone alcohol dehydrogenase genes that are unrelated in sequence to those of yeast, thus providing a powerful tool for isolation of dominant insect transformation marker genes. Received: 29 June 1999 / Accepted: 27 October 1999     

源于甘草内生菌的甘草酸合成相关功能基因的宏基因组挖掘*

目的：甘草作为一种传统中药被广泛使用。甘草酸是甘草中的主要活性成分,为五环三萜类化合物,具有抗炎、抗病毒、肝保护等多种药理作用,而且近两年已被用于新型冠状病毒肺炎(COVID-19)的临床治疗。随着代谢工程与合成生物学技术的发展,人们逐渐实现了甘草酸及其前体物的微生物合成。但由于植物基因与微生物底盘不适配等原因,已报道的生物合成法产量较低。近些年,研究者发现植物内生菌拥有丰富的功能特性,可作为植物活性产物合成的潜在资源,在代谢工程领域,具有重要的研究价值及巨大的市场应用前景。因此,拟对甘草内生菌群落进行深入研究,挖掘可用于甘草酸合成的微生物源功能基因。方法：从新疆塔城市额敏县采集了三年生乌拉尔甘草的主根样品,进行了内生菌群落的宏基因组测序,对数据进行了内生菌的群落结构及功能基因多样性分析,并通过功能基因注释与系统发育树分析,挖掘了可能参与甘草酸合成代谢的功能基因。结果：通过对群落结构进行丰度分析,发现甘草根部样品中的优势内生菌菌种为反硝化类固醇杆菌(Steroidobacter denitrificans)、苯丙酸杆菌(Phenylobacterium zucineum)、未分类苯基杆菌(unclassified Phenylobacterium)、苯基杆菌(Phenylobacterium sp.)等;通过COG数据库、KEGG数据库和CAZy数据库对其功能基因进行注释,发现在甘草内生菌中含有123个细胞色素P450(cytochrome P450,CYP450)及520个UDP-糖基转移酶(UGT)编码基因。结论：首次利用宏基因组测序与分析方法来了解乌拉尔甘草内生菌群落结构与功能基因组成,并证明了甘草内生群落中含有丰富的细胞色素P450及UGT编码基因,为后续全面、深入研究甘草内生菌的生物学功能,以及它们如何转变为甘草酸生物合成资源,奠定了理论基础。