We developed a new program called GeneTack for ab initio frameshift detection in intronless protein-coding nucleotide sequences. The GeneTack program uses a hidden Markov model (HMM) of a genomic sequence with possibly frameshifted protein-coding regions. The Viterbi algorithm nds the maximum likelihood path that discriminates between true adjacent genes and a single gene with a frameshift. We tested GeneTack as well as two other earlier developed programs FrameD and FSFind on 17 prokaryotic genomes with frameshifts introduced randomly into known genes. We observed that the average frameshift prediction accuracy of GeneTack, in terms of (Sn+Sp)/2 values, was higher by a signicant margin than the accuracy of the other two programs. GeneTack was used to screen 1,106 complete prokaryotic genomes and 206,991 genes with frameshifts (fs-genes) were identifed. Our goal was to determine if a frameshift transition was due to (i) a sequencing error, (ii) an indel mutation or (iii) a recoding event. We grouped 102,731 genes with frameshifts (fs-genes) into 19,430 clusters based on sequence similarity between their protein products (fs-proteins), conservation of predicted frameshift position, and its direction. While fs-genes in 2,810 clusters were classied as conserved pseudogenes and fs-genes in 1,200 clusters were classied as hypothetical pseudogenes, 5,632 fs-genes from 239 clusters pos- sessing conserved motifs near frameshifts were predicted to be recoding candidates. Experiments were performed for sequences derived from 20 out of the 239 clusters; programmed ribosomal frameshifting with eciency higher than 10% was observed for four clusters. GeneTack was also applied to 1,165,799 mRNAs from 100 eukaryotic species and 45,295 frameshifts were identied. A clustering approach similar to the one used for prokaryotic fs-genes allowed us to group 12,103 fs-genes into 4,087 clusters. Known programmed frameshift genes were among the obtained clusters. Several clusters may correspond to new examples of dual coding genes. We developed a web interface to browse a database containing all the fs-genes predicted by GeneTack in prokaryotic genomes and eukaryotic mRNA sequences. The fs-genes can be retrieved by similarity search to a given query sequence, by fs- gene cluster browsing, etc. Clusters of fs-genes are characterized with respect to their likely origin, such as pseudogenization, phase variation, programmed frameshifts etc. All the tools and the database of fs-genes are available at the GeneTack web site http://topaz.gatech.edu/GeneTack/

Yes / Rapid advances in short-read DNA sequencing technologies have revolutionized population genomic studies, but there are genomic regions where this technology reaches its limits. Limitations mostly arise due to the difficulties in assembly or alignment to genomic regions of high sequence divergence and high repeat content, which are typical characteristics for loci under strong long-term balancing selection. Studying genetic diversity at such loci therefore remains challenging. Here, we investigate the feasibility and error rates associated with targeted long-read sequencing of a locus under balancing selection. For this purpose, we generated bacterial artificial chromosomes (BACs) containing the Brassicaceae S-locus, a region under strong negative frequency-dependent selection which has previously proven difficult to assemble in its entirety using short reads. We sequence S-locus BACs with single-molecule long-read sequencing technology and conduct de novo assembly of these S-locus haplotypes. By comparing repeated assemblies resulting from independent long-read sequencing runs on the same BAC clone we do not detect any structural errors, suggesting that reliable assemblies are generated, but we estimate an indel error rate of 5.7×10−5. A similar error rate was estimated based on comparison of Illumina short-read sequences and BAC assemblies. Our results show that, until de novo assembly of multiple individuals using long-read sequencing becomes feasible, targeted long-read sequencing of loci under balancing selection is a viable option with low error rates for single nucleotide polymorphisms or structural variation. We further find that short-read sequencing is a valuable complement, allowing correction of the relatively high rate of indel errors that result from this approach. / This study was supported by a grant from the Swedish Research Council to T.S.

No description available.