miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.     

Analyses of a Glycine max Degradome Library Identify microRNA Targets and MicroRNAs that Trigger Secondary SiRNA Biogenesis

Plant microRNAs (miRNAs) regulate gene expression mainly by guiding cleavage of target mRNAs. In this study, a degradome library constructed from different soybean (Glycine max (L.) Merr.) tissues was deep-sequenced. 428 potential targets of small interfering RNAs and 25 novel miRNA families were identified. A total of 211 potential miRNA targets, including 174 conserved miRNA targets and 37 soybean-specific miRNA targets, were identified. Among them, 121 targets were first discovered in soybean. The signature distribution of soybean primary miRNAs (pri-miRNAs) showed that most pri-miRNAs had the characteristic pattern of Dicer processing. The biogenesis of TAS3 small interfering RNAs (siRNAs) was conserved in soybean, and nine Auxin Response Factors were identified as TAS3 siRNA targets. Twenty-three miRNA targets produced secondary small interfering RNAs (siRNAs) in soybean. These targets were guided by five miRNAs: gma-miR393, gma-miR1508, gma-miR1510, gma-miR1514, and novel-11. Multiple targets of these secondary siRNAs were detected. These 23 miRNA targets may be the putative novel TAS genes in soybean. Global identification of miRNA targets and potential novel TAS genes will contribute to research on the functions of miRNAs in soybean.     

PlasmoGF: an integrated system for comparative genomics and phylogenetic analysis of Plasmodium gene families

Summary: Malaria, one of the world's most common diseases, iscaused by the intracellular protozoan parasite known as Plasmodium.Recently, with the arrival of several malaria parasite genomes,we established an integrated system named PlasmoGF for comparativegenomics and phylogenetic analysis of Plasmodium gene families.Gene families were clustered using the Markov Cluster algorithmimplemented in TribeMCL program and could be searched usingkeywords, gene-family information, domain composition, GeneOntology and BLAST. Moreover, a number of useful bioinformaticstools were implemented to facilitate the analysis of these putativePlasmodium gene families, including gene retrieval, annotation,sequence alignment, phylogeny construction and visualization.In the current version, PlasmoGF contained 8980 sets of genefamilies derived from six malaria parasite genomes: Plasmodium.falciparum, P. berghei, P. knowlesi, P. chabaudi, P. vivax andP. yoelii. The availability of such a highly integrated systemwould be of great interest for the community of researchersworking on malaria parasite phylogenomics. Availability: PlasmoGF is freely available at http://bioinformatics.zj.cn/pgf/ Contact: xiaokunli{at}163.net; baoqy{at}genomics.org.cn; fuz3{at}psu.edu Associate Editor: Jonathan Wren The authors wish it to be known that, in their opinion, thefirst two authors should be regarded as joint First Authors.     

Model-based analysis of non-specific binding for background correction of high-density oligonucleotide microarrays

Motivation: High-density DNA microarrays provide us with usefultools for analyzing DNA and RNA comprehensively. However, thebackground signal caused by the non-specific binding (NSB) betweenprobe and target makes it difficult to obtain accurate measurements.To remove the background signal, there is a set of backgroundprobes on Affymetrix Exon arrays to represent the amount ofnon-specific signals, and an accurate estimation of non-specificsignals using these background probes is desirable for improvementof microarray analyses. Results: We developed a thermodynamic model of NSB on shortnucleotide microarrays in which the NSBs are modeled by duplexformation of probes and multiple hypothetical targets. We fittedthe observed signal intensities of the background probes withthose expected by the model to obtain the model parameters.As a result, we found that the presented model can improve theaccuracy of prediction of non-specific signals in comparisonwith previously proposed methods. This result will provide auseful method to correct for the background signal in oligonucleotidemicroarray analysis. Availability: The software is implemented in the R languageand can be downloaded from our website (http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/MSNS/). Contact: furusawa{at}ist.osaka-u.ac.jp Supplementary information: Supplementary data are availableat Bioinformatics online. The authors wish it to be known that, in their opinion, thefirst two authors should be regarded as joint First Authors. Associate Editor: Trey Ideker     

DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra

Summary: DeconMSn accurately determines the monoisotopic massand charge state of parent ions from high-resolution tandemmass spectrometry data, offering significant improvement forLTQ_FT and LTQ_Orbitrap instruments over the commercially deliveredThermo Fisher Scientific's extract_msn tool. Optimal parention mass tolerance values can be determined using accurate massinformation, thus improving peptide identifications for high-massmeasurement accuracy experiments. For low-resolution data fromLCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-basedcharge detection algorithm that identifies the most likely chargeof a parent species through peak characteristics of its fragmentationpattern. Availability: http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/ Contact: rds{at}pnl.gov Supplementary information: PowerPoint presentation/Poster onhttp://ncrr.pnl.gov/software/. Associate Editor: Alfonso Valencia     

Tree-guided Bayesian inference of population structures

Motivation: Inferring population structures using genetic datasampled from a group of individuals is a challenging task. Manymethods either consider a fixed population number or ignorethe correlation between populations. As a result, they can losesensitivity and specificity in detecting subtle stratifications.In addition, when a large number of genetic markers are used,many existing algorithms perform rather inefficiently. Result: We propose a new Bayesian method to infer populationstructures using multiple unlinked single nucleotide polymorphisms(SNPs). Our approach explicitly considers the population correlationthrough a tree hierarchy, and treat the population number asa random variable. Using both simulated and real datasets ofworldwide samples, we demonstrate that an incorporated treecan consistently improve the power in detecting subtle populationstratifications. A tree-based model often involves a large numberof unknown parameters, and the corresponding estimation procedurecan be highly inefficient. We further implement a partitionmethod to analytically integrate out all nuisance parametersin the tree. As a result, our method can analyze large SNP datasetswith significantly improved convergence rate. Availability: http://www.stat.psu.edu/~yuzhang/tips.tar Contact: yuzhang{at}stat.psu.edu Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Keith Crandall     

GlycoBase and autoGU: tools for HPLC-based glycan analysis

Summary: The development of robust high-performance liquid chromatography(HPLC) technologies continues to improve the detailed analysisand sequencing of glycan structures released from glycoproteins.Here, we present a database (GlycoBase) and analytical tool(autoGU) to assist the interpretation and assignment of HPLC-glycanprofiles. GlycoBase is a relational database which containsthe HPLC elution positions for over 350 2-AB labelled N-glycanstructures together with predicted products of exoglycosidasedigestions. AutoGU assigns provisional structures to each integratedHPLC peak and, when used in combination with exoglycosidasedigestions, progressively assigns each structure automaticallybased on the footprint data. These tools are potentially verypromising and facilitate basic research as well as the quantitativehigh-throughput analysis of low concentrations of glycans releasedfrom glycoproteins. Availability: http://glycobase.ucd.ie Contact: matthew.campbell{at}nibrt.ie Associate Editor: Limsoon Wong Present address: Dublin-Oxford Glycobiology Laboratory, NationalInstitute for Bioprocessing Research and Training, Conway Institute,University College Dublin, Dublin, Ireland. Present address: Ludger Ltd, Culham Science Centre, Abingdon,Oxfordshire OX14 3EB., UK.     

Competing endogenous RNA database

A given mRNA can be regulated by interactions with miRNAs and in turn the availability of these miRNAs can be regulated by their interactions with alternate mRNAs. The concept of regulation of a given mRNA by alternate mRNA (competing endogenous mRNA) by virtue of interactions with miRNAs through shared miRNA response elements is poised to become a fundamental genetic regulatory mechanism. The molecular basis of the mRNA-mRNA cross talks is via miRNA response elements, which can be predicted based on both molecular interaction and evolutionary conservation. By examining the co-occurrence of miRNA response elements in the mRNAs on a genome-wide basis we predict competing endogenous RNA for specific mRNAs targeted by miRNAs. Comparison of the mRNAs predicted to regulate PTEN with recently published work, indicate that the results presented within the competing endogenous RNA database (ceRDB) have biological relevance.

Availability

http://www.oncomir.umn.edu/cefinder/     

The evolution of plant microRNAs: insights from a basal eudicot sacred lotus

microRNAs (miRNAs) are important noncoding small RNAs that regulate mRNAs in eukaryotes. However, under which circumstances different miRNAs/miRNA families exhibit different evolutionary trajectories in plants remains unclear. In this study, we sequenced the small RNAs and degradome from a basal eudicot, sacred lotus (Nelumbo nucifera or lotus), to identify miRNAs and their targets. Combining with public miRNAs, we predicted 57 pre‐eudicot miRNA families from different evolutionary stages. We found that miRNA families featuring older age, higher copy and target number tend to show lower propensity for miRNA family loss (PGL) and stronger signature of purifying selection during divergence of temperate and tropical lotus. Further analyses of lotus genome revealed that there is an association between loss of miRNA families in descendent plants and in duplicated genomes. Gene dosage balance is crucial in maintaining those preferentially retained MIRNA duplicates by imposing stronger purifying selection. However, these factors and selection influencing miRNA family evolution are not applicable to the putative MIRNA‐likes. Additionally, the MIRNAs participating in lotus pollen–pistil interaction, a conserved process in angiosperms, also have a strong signature of purifying selection. Functionally, sequence divergence in MIRNAs escalates expression divergence of their target genes between temperate and tropical lotus during rhizome and leaf growth. Overall, our study unravels several important factors and selection that determine the miRNA family distribution in plants and duplicated genomes, and provides evidence for functional impact of MIRNA sequence evolution.     

Thermodynamic Roles of Solubility in Taste Responses of Amino Acids

Bitter, sour and sweet responses of amino acids were relatedto their solubilities S_w, which are virtually equal to the reciprocalsof activity coefficients at infinite dilution in water _w, andalso related to their excess partial molar entropies of transferTS_t^E. Chem. Senses 21: 405–409, 1996. Present address: 5-32-12 Tamanawa, Kamakura-shi, 247 Japan     

A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments

Motivation: The proliferation of public data repositories createsa need for meta-analysis methods to efficiently evaluate, integrateand validate related datasets produced by independent groups.A t-based approach has been proposed to integrate effect sizefrom multiple studies by modeling both intra- and between-studyvariation. Recently, a non-parametric ‘rank product’method, which is derived based on biological reasoning of fold-changecriteria, has been applied to directly combine multiple datasetsinto one meta study. Fisher's Inverse ² method, which only dependson P-values from individual analyses of each dataset, has beenused in a couple of medical studies. While these methods addressthe question from different angles, it is not clear how theycompare with each other. Results: We comparatively evaluate the three methods; t-basedhierarchical modeling, rank products and Fisher's Inverse ²test with P-values from either the t-based or the rank productmethod. A simulation study shows that the rank product method,in general, has higher sensitivity and selectivity than thet-based method in both individual and meta-analysis, especiallyin the setting of small sample size and/or large between-studyvariation. Not surprisingly, Fisher's ² method highly dependson the method used in the individual analysis. Application toreal datasets demonstrates that meta-analysis achieves morereliable identification than an individual analysis, and rankproducts are more robust in gene ranking, which leads to a muchhigher reproducibility among independent studies. Though t-basedmeta-analysis greatly improves over the individual analysis,it suffers from a potentially large amount of false positiveswhen P-values serve as threshold. We conclude that careful meta-analysisis a powerful tool for integrating multiple array studies. Contact: fxhong{at}jimmy.harvard.edu Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: David Rocke Present address: Department of Biostatistics and ComputationalBiology, Dana-Farber Cancer Institute, Harvard School of PublicHealth, 44 Binney Street, Boston, MA 02115, USA.