The identification and functional annotation of RNA structures conserved in vertebrates.

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization, and protein interaction, and their conservation across species suggests a common functional role.

Genome browsers.

Genome browsers are important tools for studying genomes given the vast amounts of data available. This chapter focuses on providing the reader with the skills necessary to perform relatively simple, yet powerful, analysis relating to the structure of the transcription unit. Studying available data should be one of the very first steps taken in designing experiments.

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.

Multiperm: shuffling multiple sequence alignments while approximately preserving dinucleotide frequencies.

Summary: Assessing the statistical significance of structured RNA predicted from multiple sequence alignments relies on the existence of a good null model. We present here a random shuffling algorithm, Multiperm, that preserves not only the gap and local conservation structure in alignments of arbitrarily many sequences, but also the approximate dinucleotide frequencies. No shuffling algorithm that simultaneously preserves these three characteristics of a multiple (beyond pairwise) alignment has been available to date.

Structural profiles of human miRNA families from pairwise clustering.

Unlabelled: MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs.

WAR: Webserver for aligning structural RNAs.

We present an easy-to-use webserver that makes it possible to simultaneously use a number of state of the art methods for performing multiple alignment and secondary structure prediction for noncoding RNA sequences. This makes it possible to use the programs without having to download the code and get the programs to run. The results of all the programs are presented on a webpage and can easily be downloaded for further analysis.

Comparative genomics beyond sequence-based alignments: RNA structures in the ENCODE regions.

Recent computational scans for non-coding RNAs (ncRNAs) in multiple organisms have relied on existing multiple sequence alignments. However, as sequence similarity drops, a key signal of RNA structure--frequent compensating base changes--is increasingly likely to cause sequence-based alignment methods to misalign, or even refuse to align, homologous ncRNAs, consequently obscuring that structural signal. We have used CMfinder, a structure-oriented local alignment tool, to search the ENCODE regions of vertebrate multiple alignments.

Semiautomated improvement of RNA alignments.

We have developed a semiautomated RNA sequence editor (SARSE) that integrates tools for analyzing RNA alignments. The editor highlights different properties of the alignment by color, and its integrated analysis tools prevent the introduction of errors when doing alignment editing. SARSE readily connects to external tools to provide a flexible semiautomatic editing environment.

Multiple structural alignment and clustering of RNA sequences.

Motivation: An apparent paradox in computational RNA structure prediction is that many methods, in advance, require a multiple alignment of a set of related sequences, when searching for a common structure between them. However, such a multiple alignment is hard to obtain even for few sequences with low sequence similarity without simultaneously folding and aligning them. Furthermore, it is of interest to conduct a multiple alignment of RNA sequence candidates found from searching as few as two genomic sequences.

Thousands of corresponding human and mouse genomic regions unalignable in primary sequence contain common RNA structure.

Human and mouse genome sequences contain roughly 100,000 regions that are unalignable in primary sequence and neighbor corresponding alignable regions between both organisms. These pairs are generally assumed to be nonconserved, although the level of structural conservation between these has never been investigated. Owing to the limitations in computational methods, comparative genomics has been lacking the ability to compare such nonconserved sequence regions for conserved structural RNA elements.

The genome of Sulfolobus acidocaldarius, a model organism of the Crenarchaeota.

Sulfolobus acidocaldarius is an aerobic thermoacidophilic crenarchaeon which grows optimally at 80 degrees C and pH 2 in terrestrial solfataric springs. Here, we describe the genome sequence of strain DSM639, which has been used for many seminal studies on archaeal and crenarchaeal biology. The circular genome carries 2,225,959 bp (37% G+C) with 2,292 predicted protein-encoding genes.

Divergent transcriptional and translational signals in Archaea.

Many Archaea, in contrast to bacteria, produce a high proportion of leaderless transcripts, show a wide variation in their consensus Shine-Dalgarno (S-D) sequences and frequently use GUG and UUG start codons. In order to understand the basis for these differences, 18 complete archaeal genomes were examined for sequence signals that are positionally conserved upstream from genes. These functional motifs include box A promoter sequences for leaderless transcripts and S-D sequences for transcripts with leaders.