StartLink+: Prediction of Gene Starts in Prokaryotic Genomes by an Algorithm Integrating Independent Sources of Evidence

Algorithms of ab initio gene finding were shown to make sufficiently accurate predictions in prokaryotic genomes. Nonetheless, for up to 15-25% of genes per genome the gene start predictions might differ even when made by the supposedly most accurate tools. To address this discrepancy, we have introduced StartLink+, an approach combining ab initio and multiple sequence alignment based methods. StartLink+ makes predictions for a majority of genes per genome (73% on average); in tests on sets of genes with experimentally verified starts the StartLink+ accuracy was shown to be 98-99%. When StartLink+ predictions made for a large set of prokaryotic genomes were compared with the database annotations we observed that on average the gene start annotations deviated from the predictions for ~5% of genes in AT-rich genomes and for 10-15% of genes in GC-rich genomes.

Genotype-dependent and non-gradient patterns of RSV gene expression

Respiratory syncytial virus (RSV) is a nonsegmented negative-strand (NNS) RNA virus and a leading cause of severe lower respiratory tract illness in infants and the elderly. Transcription of the ten RSV genes proceeds sequentially from the 3’ promoter and requires conserved gene start (GS) and gene end (GE) signals. Previous studies using the prototypical GA1 genotype Long and A2 strains have indicated a gradient of gene transcription. However, recent reports show data that appear inconsistent with a gradient. To better understand RSV transcriptional regulation, mRNA abundances from five RSV genes were measured by quantitative real-time PCR (qPCR) in three cell lines and cotton rats infected with virus isolates belonging to four different genotypes (GA1, ON, GB1, BA). Relative mRNA levels reached steady-state between four and 24 hours post-infection. Steady-state patterns were genotype-specific and non-gradient, where mRNA levels from the G (attachment) gene exceeded those from the more promoter-proximal N (nucleocapsid) gene across isolates. Transcript stabilities could not account for the non-gradient patterns observed, indicating that relative mRNA levels more strongly reflect transcription than decay. While the GS signal sequences were highly conserved, their alignment with N protein in the helical ribonucleocapsid, i.e., N-phase, was variable, suggesting polymerase recognition of GS signal conformation affects transcription initiation. The effect of GS N-phase on transcription efficiency was tested using dicistronic minigenomes. Ratios of minigenome gene expression showed a switch-like dependence on N-phase with a period of seven nucleotides. Our results indicate that RSV gene expression is in part sculpted by polymerases that initiate transcription with a probability dependent on GS signal N-phase.Author SummaryRSV is a major viral pathogen that causes significant morbidity and mortality, especially in young children. Shortly after RSV enters a host cell, transcription from its nonsegmented negative-strand (NNS) RNA genome starts at the 3’ promoter and proceeds sequentially. Transcriptional attenuation is thought to occur at each gene junction, resulting in a gradient of gene expression. However, recent studies showing non-gradient levels of RSV mRNA suggest that transcriptional regulation may have additional mechanisms. We show using RSV isolates belonging to four different genotypes that gene expression is genotype-dependent and one gene (the G or attachment gene) is consistently more highly expressed than an upstream neighbor. We hypothesize that variable alignment of highly conserved gene start (GS) signals with nucleoprotein (i.e., variable GS N-phase) can affect transcription and give rise to non-gradient patterns of gene expression. We show using dicistronic RSV minigenomes wherein the reporter genes differ only in the N-phase of one GS signal that GS N-phase affects gene expression. Our results suggest the existence of a novel mechanism of transcriptional regulation that might play a role in other NNS RNA viruses.