Dinucleotide controlled null models for comparative RNA gene prediction

We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content.SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered.SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: http://sourceforge.net/projects/sissiz webcite.Comparative genome analysis is currently the most widely used strategy to detect and annotate noncoding RNAs (ncRNAs) [1,2]. In the past few years a series of different algorithms have been developed that predict functional ncRNAs on the basis of conserved secondary structure [3-10]. Some of these methods have been used to predict novel ncRNAs on a genome wide scale [7,11-14]. In combination with experimental verification (microarray, RT-PCR, Northern blot) these methods could successfully uncover many examples of novel nc