Searching for evolutionary distant RNA homologs within genomic sequences using partition function posterior probabilities

Multiple sequence alignment using Probcons and Probalign

Sequence alignment remains a fundamental task in bioinformatics. The literature contains programs that employ a host of exact and heuristic strategies available in computer science. Probcons was the first program to construct maximum expected accuracy sequence alignments with hidden Markov models and at the time of its publication achieved the highest accuracies on standard protein multiple alignment benchmarks. Probalign followed this strategy except that it used a partition function approach instead of hidden Markov models. Several programs employing both strategies have been published since then. In this chapter we describe Probcons and Probalign.

Detecting and comparing non-coding RNAs in the high-throughput era

In recent years there has been a growing interest in the field of non-coding RNA. This surge is a direct consequence of the discovery of a huge number of new non-coding genes and of the finding that many of these transcripts are involved in key cellular functions. In this context, accurately detecting and comparing RNA sequences has become important. Aligning nucleotide sequences is a key requisite when searching for homologous genes. Accurate alignments reveal evolutionary relationships, conserved regions and more generally any biologically relevant pattern. Comparing RNA molecules is, however, a challenging task. The nucleotide alphabet is simpler and therefore less informative than that of amino-acids. Moreover for many non-coding RNAs, evolution is likely to be mostly constrained at the structural level and not at the sequence level. This results in very poor sequence conservation impeding comparison of these molecules. These difficulties define a context where new methods are urgently needed in order to exploit experimental results to their full potential. This review focuses on the comparative genomics of non-coding RNAs in the context of new sequencing technologies and especially dealing with two extremely important and timely research aspects: the development of new methods to align RNAs and the analysis of high-throughput data.

Novel type of linear mitochondrial genomes with dual flip-flop inversion system in apicomplexan parasites, Babesia microti and Babesia rodhaini

Background

Mitochondrial (mt) genomes vary considerably in size, structure and gene content. The mt genomes of the phylum Apicomplexa, which includes important human pathogens such as the malaria parasite Plasmodium, also show marked diversity of structure. Plasmodium has a concatenated linear mt genome of the smallest size (6-kb); Babesia and Theileria have a linear monomeric mt genome (6.5-kb to 8.2-kb) with terminal inverted repeats; Eimeria, which is distantly related to Plasmodium and Babesia/Theileria, possesses a mt genome (6.2-kb) with a concatemeric form similar to that of Plasmodium; Cryptosporidium, the earliest branching lineage within the phylum Apicomplexa, has no mt genome. We are interested in the evolutionary origin of linear mt genomes of Babesia/Theileria, and have investigated mt genome structures in members of archaeopiroplasmid, a lineage branched off earlier from Babesia/Theileria.

Results

The complete mt genomes of archaeopiroplasmid parasites, Babesia microti and Babesia rodhaini, were sequenced. The mt genomes of B. microti (11.1-kb) and B. rodhaini (6.9-kb) possess two pairs of unique inverted repeats, IR-A and IR-B. Flip-flop inversions between two IR-As and between two IR-Bs appear to generate four distinct genome structures that are present at an equi-molar ratio. An individual parasite contained multiple mt genome structures, with 20 copies and 2 – 3 copies per haploid nuclear genome in B. microti and B. rodhaini, respectively.

Conclusion

We found a novel linear monomeric mt genome structure of B. microti and B. rhodhaini equipped with dual flip-flop inversion system, by which four distinct genome structures are readily generated. To our knowledge, this study is the first to report the presence of two pairs of distinct IR sequences within a monomeric linear mt genome. The present finding provides insight into further understanding of evolution of mt genome structure.

BlastR--fast and accurate database searches for non-coding RNAs

We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

Bioinformatics for RNomics

Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.

PLAST-ncRNA: Partition function Local Alignment Search Tool for non-coding RNA sequences

Alignment-based programs are valuable tools for finding potential homologs in genome sequences. Previously, it has been shown that partition function posterior probabilities attuned to local alignment achieve a high accuracy in identifying distantly similar non-coding RNA sequences that are hidden in a large genome. Here, we present an online implementation of that alignment algorithm based on such probabilities. Our server takes as input a query RNA sequence and a large genome sequence, and outputs a list of hits that are above a mean posterior probability threshold. The output is presented in a format suited to local alignment. It can also be viewed within the PLAST alignment viewer applet that provides a list of all hits found and highlights regions of high posterior probability within each local alignment. The server is freely available at http://plastrna.njit.edu.

Divergence of the mitochondrial genome structure in the apicomplexan parasites, Babesia and Theileria

Mitochondrial (mt) genomes from diverse phylogenetic groups vary considerably in size, structure, and organization. The genus Plasmodium, causative agent of malaria, of the phylum Apicomplexa, has the smallest mt genome in the form of a circular and/or tandemly repeated linear element of 6 kb, encoding only three protein genes (cox1, cox3, and cob). The closely related genera Babesia and Theileria also have small mt genomes (6.6 kb) that are monomeric linear with an organization distinct from Plasmodium. To elucidate the structural divergence and evolution of mt genomes between Babesia/Theileria and Plasmodium, we determined five new sequences from Babesia bigemina, B. caballi, B. gibsoni, Theileria orientalis, and T. equi. Together with previously reported sequences of B. bovis, T. annulata, and T. parva, all eight Babesia and Theileria mt genomes are linear molecules with terminal inverted repeats (TIRs) on both ends containing three protein-coding genes (cox1, cox3, and cob) and six large subunit (LSU) ribosomal RNA (rRNA) gene fragments. The organization and transcriptional direction of protein-coding genes and the rRNA gene fragments were completely conserved in the four Babesia species. In contrast, notable variation occurred in the four Theileria species. Although the genome structures of T. annulata and T. parva were nearly identical to those of Babesia, an inversion in the 3-kb central region was found in T. orientalis. Moreover, the T. equi mt genome is the largest (8.2 kb) and most divergent with unusually long TIR sequences, in which cox3 and two LSU rRNA gene fragments are located. The T. equi mt genome showed little synteny to the other species. These results suggest that the Theileria mt genome is highly diverse with lineage-specific evolution in two Theileria species: genome inversion in T. orientalis and gene-embedded long TIR in T. equi.

Non-coding RNA annotation of the genome of Trichoplax adhaerens

A detailed annotation of non-protein coding RNAs is typically missing in initial releases of newly sequenced genomes. Here we report on a comprehensive ncRNA annotation of the genome of Trichoplax adhaerens, the presumably most basal metazoan whose genome has been published to-date. Since blast identified only a small fraction of the best-conserved ncRNAs--in particular rRNAs, tRNAs and some snRNAs--we developed a semi-global dynamic programming tool, GotohScan, to increase the sensitivity of the homology search. It successfully identified the full complement of major and minor spliceosomal snRNAs, the genes for RNase P and MRP RNAs, the SRP RNA, as well as several small nucleolar RNAs. We did not find any microRNA candidates homologous to known eumetazoan sequences. Interestingly, most ncRNAs, including the pol-III transcripts, appear as single-copy genes or with very small copy numbers in the Trichoplax genome.