Non-coding RNA prediction and verification in Saccharomyces cerevisiae

In silico genome wide identification of long non-coding RNAs differentially expressed during Candida auris host pathogenesis

Candida auris is an invasive fungal pathogen of high concern due to acquired drug tolerance against antifungals used in clinics. The prolonged persistence on biotic and abiotic surfaces can result in onset of hospital outbreaks causing serious health threat. An in depth understanding of pathology of C. auris is highly desirable for development of efficient therapeutics. Non-coding RNAs play crucial role in fungal pathology. However, the information about ncRNAs is scanty to be utilized. Herein our aim is to identify long noncoding RNAs with potent role in pathobiology of C. auris. Thereby, we analyzed the transcriptomics data of C. auris infection in blood for identification of potential lncRNAs with regulatory role in determining invasion, survival or drug tolerance under infection conditions. Interestingly, we found 275 lncRNAs, out of which 253 matched with lncRNAs reported in Candidamine, corroborating for our accurate data analysis pipeline. Nevertheless, we obtained 23 novel lncRNAs not reported earlier. Three lncRNAs were found to be under expressed throughout the course of infection, in the transcriptomics data. 16 of potent lncRNAs were found to be coexpressed with coding genes, emphasizing for their functional role. Noteworthy, these ncRNAs are expressed from intergenic regions of the genes associated with transporters, metabolism, cell wall biogenesis. This study recommends for possible association between lncRNA expression and C. auris pathogenesis.

Functions of noncoding RNAs in glial development

Glia are widely distributed in the central nervous system and are closely related to cell metabolism, signal transduction, support, cell migration, and other nervous system development processes and functions. Glial development is complex and essential, including the processes of proliferation, differentiation, and migration, and requires precise regulatory networks. Noncoding RNAs (ncRNAs) can be deeply involved in glial development through gene regulation. Here, we review the regulatory roles of ncRNAs in glial development. We briefly describe the classification and functions of noncoding RNAs and focus on microRNAs (miRNAs) and long ncRNAs (lncRNAs), which have been reported to participate extensively during glial formation. The highlight of this summary is that miRNAs and lncRNAs can participate in and regulate the signaling pathways of glial development. The review not only describes how noncoding RNAs participate in nervous system development but also explains the processes of glial development, providing a foundation for subsequent studies on glial development and new insights into the pathogeneses of related neurological diseases.

Discovery of 17 conserved structural RNAs in fungi

Many non-coding RNAs with known functions are structurally conserved: their intramolecular secondary and tertiary interactions are maintained across evolutionary time. Consequently, the presence of conserved structure in multiple sequence alignments can be used to identify candidate functional non-coding RNAs. Here, we present a bioinformatics method that couples iterative homology search with covariation analysis to assess whether a genomic region has evidence of conserved RNA structure. We used this method to examine all unannotated regions of five well-studied fungal genomes (Saccharomyces cerevisiae, Candida albicans, Neurospora crassa, Aspergillus fumigatus, and Schizosaccharomyces pombe). We identified 17 novel structurally conserved non-coding RNA candidates, which include four H/ACA box small nucleolar RNAs, four intergenic RNAs and nine RNA structures located within the introns and untranslated regions (UTRs) of mRNAs. For the two structures in the 3' UTRs of the metabolic genes GLY1 and MET13, we performed experiments that provide evidence against them being eukaryotic riboswitches.

A regulatory circuit between lncRNA and TOR directs amino acid uptake in yeast

Long non coding RNAs (lncRNAs) have emerged as crucial players of several central cellular processes across eukaryotes. Target of Rapamycin (TOR) is a central regulator of myriad of fundamental cellular processes including amino acid transport under diverse environmental conditions. Here we investigated the role of lncRNA in TOR regulated amino acid uptake in S. cerevisiae. Transcription of lncRNA regulates local gene expression in eukaryotes. In silico analysis of many genome wide studies in S. cerevisiae revealed that transcriptome includes conditional expression of numerous lncRNAs in proximity to amino acid transporters (AATs). Considering regulatory role of these lncRNAs, we selected highly conserved TOR regulated locus of a pair of AATs present in tandem BAP2 and TAT1. We observed that the expression of antisense lncRNA XUT_2F-154 (TBRT) and AATs BAP2 and TAT1 depends on activities of TOR signaling pathway. The expression of TBRT is induced, while that of BAP2 TAT1 is repressed upon TOR inhibition by Torin2. Notably, upon TOR inhibition loss of TBRT contributed to enhanced activities of Bap2 and Tat1 leading to improved growth. Interestingly, nucleosome scanning assay reveal that TOR signaling pathway governs chromatin remodeling at BAP2 biphasic promoter to control the antagonism of TBRT and BAP2 expression. Further TBRT also reprograms local chromatin landscapes to decrease the transcription of TAT1. The current work demonstrates a functional correlation between lncRNA production and TOR governed amino acid uptake in yeast. Thus this work brings forth a novel avenue for identification of potential regulators for therapeutic interventions against TOR mediated diseases.

Large-scale profiling of noncoding RNA function in yeast

Noncoding RNAs (ncRNAs) are emerging as key regulators of cellular function. We have exploited the recently developed barcoded ncRNA gene deletion strain collections in the yeast Saccharomyces cerevisiae to investigate the numerous ncRNAs in yeast with no known function. The ncRNA deletion collection contains deletions of tRNAs, snoRNAs, snRNAs, stable unannotated transcripts (SUTs), cryptic unstable transcripts (CUTs) and other annotated ncRNAs encompassing 532 different individual ncRNA deletions. We have profiled the fitness of the diploid heterozygous ncRNA deletion strain collection in six conditions using batch and continuous liquid culture, as well as the haploid ncRNA deletion strain collections arrayed individually onto solid rich media. These analyses revealed many novel environmental-specific haplo-insufficient and haplo-proficient phenotypes providing key information on the importance of each specific ncRNA in every condition. Co-fitness analysis using fitness data from the heterozygous ncRNA deletion strain collection identified two ncRNA groups required for growth during heat stress and nutrient deprivation. The extensive fitness data for each ncRNA deletion strain has been compiled into an easy to navigate database called Yeast ncRNA Analysis (YNCA). By expanding the original ncRNA deletion strain collection we identified four novel essential ncRNAs; SUT527, SUT075, SUT367 and SUT259/691. We defined the effects of each new essential ncRNA on adjacent gene expression in the heterozygote background identifying both repression and induction of nearby genes. Additionally, we discovered a function for SUT527 in the expression, 3' end formation and localization of SEC4, an essential protein coding mRNA. Finally, using plasmid complementation we rescued the SUT075 lethal phenotype revealing that this ncRNA acts in trans. Overall, our findings provide important new insights into the function of ncRNAs.

RNAStructuromeDB: A genome-wide database for RNA structural inference

RNA plays important roles in almost every aspect of biology, and every aspect of RNA biology is influenced by its folding. This is a particularly important consideration in the era of high-throughput sequencing, when the discovery of novel transcripts far outpaces our knowledge of their functions. To gain a comprehensive picture of biology requires a structural framework for making functional inferences on RNA. To this end we have developed the RNA Structurome Database ( https://structurome.bb.iastate.edu ), a comprehensive repository of RNA secondary structural information that spans the entire human genome. Here, we compile folding information for every base pair of the genome that may be transcribed: coding, noncoding, and intergenic regions, as well as repetitive elements, telomeres, etc. This was done by fragmenting the GRCh38 reference genome into 154,414,320 overlapping sequence fragments and, for each fragment, calculating a set of metrics based on the sequence's folding properties. These data will facilitate a wide array of investigations: e.g. discovery of structured regulatory elements in differential gene expression data or noncoding RNA discovery, as well as allow genome-scale analyses of RNA folding.

RNAseq-based transcriptome comparison of Saccharomyces cerevisiae strains isolated from diverse fermentative environments

Transcriptome analyses play a central role in unraveling the complexity of gene expression regulation in Saccharomyces cerevisiae. This species, one of the most important microorganisms for humans given its industrial applications, shows an astonishing degree of genetic and phenotypic variability among different strains adapted to specific environments. In order to gain novel insights into the Saccharomyces cerevisiae biology of strains adapted to different fermentative environments, we analyzed the whole transcriptome of three strains isolated from wine, flor wine or mezcal fermentations. An RNA-seq transcriptome comparison of the different yeasts in the samples obtained during synthetic must fermentation highlighted the differences observed in the genes that encode mannoproteins, and in those involved in aroma, sugar transport, glycerol and alcohol metabolism, which are important under alcoholic fermentation conditions. These differences were also observed in the physiology of the strains after mannoprotein and aroma determinations. This study offers an essential foundation for understanding how gene expression variations contribute to the fermentation differences of the strains adapted to unequal fermentative environments. Such knowledge is crucial to make improvements in fermentation processes and to define targets for the genetic improvement or selection of wine yeasts.

Structural and Functional Annotation of Long Noncoding RNAs

Protein-coding RNAs represent only a small fraction of the transcriptional output in higher eukaryotes. The remaining RNA species encompass a broad range of molecular functions and regulatory roles, a consequence of the structural polyvalence of RNA polymers. Albeit several classes of small noncoding RNAs are relatively well characterized, the accessibility of affordable high-throughput sequencing is generating a wealth of novel, unannotated transcripts, especially long noncoding RNAs (lncRNAs) that are derived from genomic regions that are antisense, intronic, intergenic, and overlapping protein-coding loci. Parsing and characterizing the functions of noncoding RNAs-lncRNAs in particular-is one of the great challenges of modern genome biology. Here we discuss concepts and computational methods for the identification of structural domains in lncRNAs from genomic and transcriptomic data. In the first part, we briefly review how to identify RNA structural motifs in individual lncRNAs. In the second part, we describe how to leverage the evolutionary dynamics of structured RNAs in a computationally efficient screen to detect putative functional lncRNA motifs using comparative genomics.

Mycoplasma non-coding RNA: identification of small RNAs and targets

Background

Bacterial non-coding RNAs act by base-pairing as regulatory elements in crucial biological processes. We performed the identification of trans-encoded small RNAs (sRNA) from the genomes of Mycoplama hyopneumoniae, Mycoplasma flocculare and Mycoplasma hyorhinis, which are Mycoplasma species that have been identified in the porcine respiratory system.

Results

A total of 47, 15 and 11 putative sRNAs were predicted in M. hyopneumoniae, M. flocculare and M. hyorhinis, respectively. A comparative genomic analysis revealed the presence of species or lineage specific sRNA candidates. Furthermore, the expression profile of some M. hyopneumoniae sRNAs was determined by a reverse transcription amplification approach, in three different culture conditions. All tested sRNAs were transcribed in at least one condition. A detailed investigation revealed a differential expression profile for two M. hyopneumoniae sRNAs in response to oxidative and heat shock stress conditions, suggesting that their expression is influenced by environmental signals. Moreover, we analyzed sRNA-mRNA hybrids and accessed putative target genes for the novel sRNA candidates. The majority of the sRNAs showed interaction with multiple target genes, some of which could be linked to pathogenesis and cell homeostasis activity.

Conclusion

This study contributes to our knowledge of Mycoplasma sRNAs and their response to environmental changes. Furthermore, the mRNA target prediction provides a perspective for the characterization and comprehension of the function of the sRNA regulatory mechanisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3061-z) contains supplementary material, which is available to authorized users.

Identification of novel noncoding transcripts in telomerase-negative yeast using RNA-seq

Telomerase is a ribonucleoprotein that maintains the ends of linear chromosomes in most eukaryotes. Loss of telomerase activity results in shortening of telomeric DNA and eventually a specific G2/M cell-cycle arrest known as senescence. In humans, telomere shortening occurs during aging, while inappropriate activation of telomerase is associated with approximately 90% of cancers. Previous studies have identified several classes of noncoding RNAs (ncRNA) also associated with aging-related senescence and cancer, but whether ncRNAs are also involved in short-telomere-induced senescence in yeast is unknown. Here, we report 112 putative novel lncRNAs in the yeast Saccharomyces cerevisiae, 41 of which are only expressed in telomerase-negative yeast. Expression of approximately half of the lncRNAs is strongly correlated with that of adjacent genes, suggesting this subset may influence transcription of neighboring genes. Our results reveal a new potential mechanism governing adaptive changes in senescing and post-senescent survivor yeast cells.

Probing-directed identification of novel structured RNAs

Transcripts often harbor RNA elements, which regulate cell processes co- or post-transcriptionally. The functions of many regulatory RNA elements depend on their structure, thus it is important to determine the structure as well as to scan genomes for structured elements. State of the art ab initio approaches to predict structured RNAs rely on DNA sequence analysis. They use 2 major types of information inferred from a sequence: thermodynamic stability of an RNA structure and evolutionary footprints of base-pair interactions. In recent years, chemical probing of RNA has arisen as an alternative source of structural information. RNA probing experiments detect positions accessible to specific types of chemicals or enzymes indicating their propensity to be in a paired or unpaired state. There exist several strategies to integrate probing data into RNA secondary structure prediction algorithms that substantially improve the prediction quality. However, whether and how probing data could contribute to detection of structured RNAs remains an open question. We previously developed the energy-based approach RNASurface to detect locally optimal structured RNA elements. Here, we integrate probing data into the RNASurface energy model using a general framework. We show that the use of experimental data allows for better discrimination of ncRNAs from other transcripts. Application of RNASurface to genome-wide analysis of the human transcriptome with PARS data identifies previously undetectable segments, with evidence of functionality for some of them.

Budding yeast for budding geneticists: a primer on the Saccharomyces cerevisiae model system

The budding yeast Saccharomyces cerevisiae is a powerful model organism for studying fundamental aspects of eukaryotic cell biology. This Primer article presents a brief historical perspective on the emergence of this organism as a premier experimental system over the course of the past century. An overview of the central features of the S. cerevisiae genome, including the nature of its genetic elements and general organization, is also provided. Some of the most common experimental tools and resources available to yeast geneticists are presented in a way designed to engage and challenge undergraduate and graduate students eager to learn more about the experimental amenability of budding yeast. Finally, a discussion of several major discoveries derived from yeast studies highlights the far-reaching impact that the yeast system has had and will continue to have on our understanding of a variety of cellular processes relevant to all eukaryotes, including humans.

Identification of non-coding RNAs with a new composite feature in the Hybrid Random Forest Ensemble algorithm

To identify non-coding RNA (ncRNA) signals within genomic regions, a classification tool was developed based on a hybrid random forest (RF) with a logistic regression model to efficiently discriminate short ncRNA sequences as well as long complex ncRNA sequences. This RF-based classifier was trained on a well-balanced dataset with a discriminative set of features and achieved an accuracy, sensitivity and specificity of 92.11%, 90.7% and 93.5%, respectively. The selected feature set includes a new proposed feature, SCORE. This feature is generated based on a logistic regression function that combines five significant features-structure, sequence, modularity, structural robustness and coding potential-to enable improved characterization of long ncRNA (lncRNA) elements. The use of SCORE improved the performance of the RF-based classifier in the identification of Rfam lncRNA families. A genome-wide ncRNA classification framework was applied to a wide variety of organisms, with an emphasis on those of economic, social, public health, environmental and agricultural significance, such as various bacteria genomes, the Arthrospira (Spirulina) genome, and rice and human genomic regions. Our framework was able to identify known ncRNAs with sensitivities of greater than 90% and 77.7% for prokaryotic and eukaryotic sequences, respectively. Our classifier is available at http://ncrna-pred.com/HLRF.htm.

The conserved chimeric transcript UPGRADE2 is associated with unreduced pollen formation and is exclusively found in apomictic Boechera species

In apomictic Boechera spp., meiotic diplospory leads to the circumvention of meiosis and the suppression of recombination to produce unreduced male and female gametes (i.e. apomeiosis). Here, we have established an early flower developmental staging system and have performed microarray-based comparative gene expression analyses of the pollen mother cell stage in seven diploid sexual and seven diploid apomictic genotypes to identify candidate factors for unreduced pollen formation. We identified a transcript unique to apomictic Boechera spp. called UPGRADE2 (BspUPG2), which is highly up-regulated in their pollen mother cells. BspUPG2 is highly conserved among apomictic Boechera spp. genotypes but has no homolog in sexual Boechera spp. or in any other taxa. BspUPG2 undergoes posttranscriptional processing but lacks a prominent open reading frame. Together with the potential of stably forming microRNA-like secondary structures, we hypothesize that BspUPG2 functions as a long regulatory noncoding messenger RNA-like RNA. BspUPG2 has apparently arisen through a three-step process initiated by ancestral gene duplication of the original BspUPG1 locus, followed by sequential insertions of segmentally duplicated gene fragments, with final exonization of its sequence structure. Its genesis reflects the hybridization history that characterizes the genus Boechera.

A new system for comparative functional genomics of Saccharomyces yeasts

Whole-genome sequencing, particularly in fungi, has progressed at a tremendous rate. More difficult, however, is experimental testing of the inferences about gene function that can be drawn from comparative sequence analysis alone. We present a genome-wide functional characterization of a sequenced but experimentally understudied budding yeast, Saccharomyces bayanus var. uvarum (henceforth referred to as S. bayanus), allowing us to map changes over the 20 million years that separate this organism from S. cerevisiae. We first created a suite of genetic tools to facilitate work in S. bayanus. Next, we measured the gene-expression response of S. bayanus to a diverse set of perturbations optimized using a computational approach to cover a diverse array of functionally relevant biological responses. The resulting data set reveals that gene-expression patterns are largely conserved, but significant changes may exist in regulatory networks such as carbohydrate utilization and meiosis. In addition to regulatory changes, our approach identified gene functions that have diverged. The functions of genes in core pathways are highly conserved, but we observed many changes in which genes are involved in osmotic stress, peroxisome biogenesis, and autophagy. A surprising number of genes specific to S. bayanus respond to oxidative stress, suggesting the organism may have evolved under different selection pressures than S. cerevisiae. This work expands the scope of genome-scale evolutionary studies from sequence-based analysis to rapid experimental characterization and could be adopted for functional mapping in any lineage of interest. Furthermore, our detailed characterization of S. bayanus provides a valuable resource for comparative functional genomics studies in yeast.

Noncoding RNAs in chromatin organization and transcription regulation: an epigenetic view

The Genome of a eukaryotic cell harbors genetic material in the form of DNA which carries the hereditary information encoded in their bases. Nucleotide bases of DNA are transcribed into complimentary RNA bases which are further translated into protein, performing defined set of functions. The central dogma of life ensures sequential flow of genetic information among these biopolymers. Noncoding RNAs (ncRNAs) serve as exceptions for this principle as they do not code for any protein. Nevertheless, a major portion of the human transcriptome comprises noncoding RNAs. These RNAs vary in size, as well as they vary in the spatio-temporal distribution. These ncRnAs are functional and are shown to be involved in diverse cellular activities. Precise location and expression of ncRNA is essential for the cellular homeostasis. Failures of these events ultimately results in numerous disease conditions including cancer. The present review lists out the various classes of ncRNAs with a special emphasis on their role in chromatin organization and transcription regulation.

Identification and annotation of noncoding RNAs in Saccharomycotina

The importance of ncRNAs in biological processes makes their annotation an essential component of any genome-sequencing project. The identification of ncRNAs in genomes requires specific expertise and tools that are distinct from the traditional protein gene annotation tools. Here, we describe the assembly of two automatic annotation pipelines, integrating publicly available tools, for homology and de novo ncRNA search in genomes. We applied both pipelines to 10 Saccharomycotina genomes and were able to find and annotate 693 ncRNA genes, corresponding to 81% of the ncRNAs expected for those genomes assuming the number of ncRNAs in Saccharomyces cerevisiae (86) as a reference. Several new ncRNAs, not yet known in the Saccharomycotina clade, were also detected. The results show the feasibility of automatic search for ncRNAs in full genomes and the utility of such approaches in large multi-genome sequencing and annotation projects.

A comparative genome-wide study of ncRNAs in trypanosomatids

Background

Recent studies have provided extensive evidence for multitudes of non-coding RNA (ncRNA) transcripts in a wide range of eukaryotic genomes. ncRNAs are emerging as key players in multiple layers of cellular regulation. With the availability of many whole genome sequences, comparative analysis has become a powerful tool to identify ncRNA molecules. In this study, we performed a systematic genome-wide in silico screen to search for novel small ncRNAs in the genome of Trypanosoma brucei using techniques of comparative genomics.

Results

In this study, we identified by comparative genomics, and validated by experimental analysis several novel ncRNAs that are conserved across multiple trypanosomatid genomes. When tested on known ncRNAs, our procedure was capable of finding almost half of the known repertoire through homology over six genomes, and about two-thirds of the known sequences were found in at least four genomes. After filtering, 72 conserved unannotated sequences in at least four genomes were found, 29 of which, ranging in size from 30 to 392 nts, were conserved in all six genomes. Fifty of the 72 candidates in the final set were chosen for experimental validation. Eighteen of the 50 (36%) were shown to be expressed, and for 11 of them a distinct expression product was detected, suggesting that they are short ncRNAs. Using functional experimental assays, five of the candidates were shown to be novel H/ACA and C/D snoRNAs; these included three sequences that appear as singletons in the genome, unlike previously identified snoRNA molecules that are found in clusters. The other candidates appear to be novel ncRNA molecules, and their function is, as yet, unknown.

Conclusions

Using comparative genomic techniques, we predicted 72 sequences as ncRNA candidates in T. brucei. The expression of 50 candidates was tested in laboratory experiments. This resulted in the discovery of 11 novel short ncRNAs in procyclic stage T. brucei, which have homologues in the other trypansomatids. A few of these molecules are snoRNAs, but most of them are novel ncRNA molecules. Based on this study, our analysis suggests that the total number of ncRNAs in trypanosomatids is in the range of several hundred.

Non-coding RNA detection methods combined to improve usability, reproducibility and precision

Background

Non-coding RNAs gain more attention as their diverse roles in many cellular processes are discovered. At the same time, the need for efficient computational prediction of ncRNAs increases with the pace of sequencing technology. Existing tools are based on various approaches and techniques, but none of them provides a reliable ncRNA detector yet. Consequently, a natural approach is to combine existing tools. Due to a lack of standard input and output formats combination and comparison of existing tools is difficult. Also, for genomic scans they often need to be incorporated in detection workflows using custom scripts, which decreases transparency and reproducibility.

Results

We developed a Java-based framework to integrate existing tools and methods for ncRNA detection. This framework enables users to construct transparent detection workflows and to combine and compare different methods efficiently. We demonstrate the effectiveness of combining detection methods in case studies with the small genomes of Escherichia coli, Listeria monocytogenes and Streptococcus pyogenes. With the combined method, we gained 10% to 20% precision for sensitivities from 30% to 80%. Further, we investigated Streptococcus pyogenes for novel ncRNAs. Using multiple methods--integrated by our framework--we determined four highly probable candidates. We verified all four candidates experimentally using RT-PCR.

Conclusions

We have created an extensible framework for practical, transparent and reproducible combination and comparison of ncRNA detection methods. We have proven the effectiveness of this approach in tests and by guiding experiments to find new ncRNAs. The software is freely available under the GNU General Public License (GPL), version 3 at http://www.sbi.uni-rostock.de/moses along with source code, screen shots, examples and tutorial material.

Regulatory RNAs in brain function and disorders

Regulatory RNAs are being increasingly investigated in neurons, and important roles in brain function have been revealed. Regulatory RNAs are non-protein-coding RNAs (npcRNAs) that comprise a heterogeneous group of molecules, varying in size and mechanism of action. Regulatory RNAs often exert post-transcriptional control of gene expression, resulting in gene silencing or gene expression stimulation. Here, we review evidence that regulatory RNAs are implicated in neuronal development, differentiation, and plasticity. We will also discuss npcRNA dysregulation that may be involved in pathological states of the brain such as neurodevelopmental disorders, neurodegeneration, and epilepsy.

Computational evidence for functionality of noncoding mouse transcripts

Large-scale studies of mammalian genome transcription reveal that a large proportion of the genome is transcribed. It remains an open question whether the identified transcripts are functional. Here, we searched for computational evidence to support the functionality of 34,030 noncoding RNA (ncRNA) transcripts reported by the Fantom3 project. We show that compared to control sets, the Fantom ncRNA transcripts set is more conserved with human and rat. We also demonstrate that homologs of the Fantom ncRNA sequences in human and rat have more matches to ESTs. The conserved subgroup of sequences exhibits elevated expression levels in brain tissues. Finally, on average, the Fantom ncRNA sequences have lower minimal free energy of folding than the control sets. Taken together, these observations suggest that, as a group, the Fantom ncRNA set has properties that are different from random sets. Therefore, many of these transcripts may indeed have biological function.

Exploring the ncRNA-ncRNA patterns based on bridging rules

ncRNAs play an important role in the regulation of gene expression. However, many of their functions have not yet been fully discovered. There are complicated relationships between ncRNAs in different categories. Finding these relationships can contribute to identify ncRNAs' functions and properties. We extend the association rule to represent the relationship between two ncRNAs. Based on this rule, we can speculate the ncRNA's function when it interacts with other ncRNAs. We propose two measures to explore the relationships between ncRNAs in different categories. Entropy theory is to calculate how close two ncRNAs are. Association rule is to represent the interactions between ncRNAs. We use three datasets from miRBase and RNAdb. Two from miRBase are designed for finding relationships between miRNAs; the other from RNAdb is designed for relationships among miRNA, snoRNA and piRNA. We evaluate our measures from both biological significance and performance perspectives. All the cross-species patterns regarding miRNA that we found are proven correct using miRNAMap 2.0. In addition, we find novel cross-genomes patterns such as (hsa-mir-190b-->hsa-mir-153-2). According to the patterns we find, we can (1) explore one ncRNA's function from another with known function and (2) speculate the functions of both of them based on the relationship even we do no understand either of them. Our methods' merits also include: (1) they are suitable for any ncRNA datasets and (2) they are not sensitive to the parameters.

De novo prediction of structured RNAs from genomic sequences

Growing recognition of the numerous, diverse and important roles played by non-coding RNA in all organisms motivates better elucidation of these cellular components. Comparative genomics is a powerful tool for this task and is arguably preferable to any high-throughput experimental technology currently available, because evolutionary conservation highlights functionally important regions. Conserved secondary structure, rather than primary sequence, is the hallmark of many functionally important RNAs, because compensatory substitutions in base-paired regions preserve structure. Unfortunately, such substitutions also obscure sequence identity and confound alignment algorithms, which complicates analysis greatly. This paper surveys recent computational advances in this difficult arena, which have enabled genome-scale prediction of cross-species conserved RNA elements. These predictions suggest that a wealth of these elements indeed exist.

Functional annotations for the Saccharomyces cerevisiae genome: the knowns and the known unknowns

The quest to characterize each of the genes of the yeast Saccharomyces cerevisiae has propelled the development and application of novel high-throughput (HTP) experimental techniques. To handle the enormous amount of information generated by these techniques, new bioinformatics tools and resources are needed. Gene Ontology (GO) annotations curated by the Saccharomyces Genome Database (SGD) have facilitated the development of algorithms that analyze HTP data and help predict functions for poorly characterized genes in S. cerevisiae and other organisms. Here, we describe how published results are incorporated into GO annotations at SGD and why researchers can benefit from using these resources wisely to analyze their HTP data and predict gene functions.