BMC Genomics 2009, 10:435 http://www.biomedcentral.com/1471-2164/10/435 questions can only be answered by detailed experimental characterization of these molecules; our analysis here pro- vides a rich data source for prioritizing likely candidates of functional importance as transcribed pseudogenes. Methods 1. Collection of data Complete genome sequences of mammals were obtained from http://www.ensembl.org (Ensembl release 47 for human genome; Ensembl release 48 for other mammals, namely, rhesus monkey, mouse, rat, cow and dog). Pseu- dogene annotations for both processed and nonprocessed categories, were obtained from [http://www.pseudog ene.org; [37,38]] and for VEGA pseudogenes from http:// vega.sanger.ac.uk/, for disrupted mRNAs (dmRNAs) from Harrison and Yu [16] and for other transcribed processed pseudogenes from Harrison et al. [14]. The Blastx program [39] was used to determine the parent protein coding genes for VEGA pseudogenes (using E-value < 1e-09 as sig- nificance threshold), whereas for other datasets the anno- tations were readily available at the respective websites mentioned above. 2. Screening for putative transcribed pseudogenes Transcription data for human and mouse were taken from RefSeq database [40], Unigene database at the NCBI http:/ /www.ncbi.nlm.nih.gov, H-InvDB database http:// www.h-invitational.jp/ and Fantom3 database http:// fantom3.gsc.riken.jp/. To identify putative transcribed pseudogenes, individual transcript sequences were mapped onto the respective genomes using GMAP soft- ware [41] with match criteria of >99% sequence identity and >99% sequence coverage. Transcript sequences that mapped to pseudogenes were aligned to parent protein sequences of respective pseudogenes to identify disable- ments such as frame shift or premature stop codon using the 'GeneWise' program (Wise2 - version 2.1.20 package downloaded from the European Bioinformatics Institute, http://www.ebi.ac.uk/Tools/Wise2/index.html) [42]. The disablement positions in pseudogenes and transcript sequences were then used as 'anchors' to confirm the tran- scription of pseudogenes as in previous analyses [14,15,43]. Additional data file (file 1) contains the list of transcribed human pseudogenes. For a schematic repre- sentation of the annotation pipeline, see Figure. 7. 3. Identification of orthologous pseudogenes in various sequenced mammalian genomes Orthologous counterparts to a human pseudogene are detected by the presence of a homologous sequence at the syntenic position in the other mammalian genome. Based on this criterion, a search was carried out within 100 kb nucleotides distance of the exact syntenic coordinate (because genes can shuffle locally) in the target mammal as indicated in the synteny maps, to locate the ortholo- gous pseudogenes. 'GeneWise' tool [42] was used, to align the above-obtained genomic DNA sequence and the human parental protein sequence, and to detect disable- ments in the alignment. The following mammals were included in the analysis: monkey, mouse, rat, cow and dog. The pair wise synteny map data for the various mam- mals were obtained from http://genome.ucsc.edu/. 4. Analysis for pseudogene sequence conservation Flanking sequences 5' and 3' of human pseudogenes were individually obtained, of length equal to the length of the human pseudogene, and were each globally aligned using 'needle' module of EMBOSS package http:// www.ebi.ac.uk to the corresponding flanking region sequences (10000 nucleotides 5' and 3') of monkey in a sliding window of size also equal to the length of human pseudogene. The window in which best identity score was obtained was considered as the most optimum alignment between the flanking regions, representing syntenic regions. The Wilcoxon signed rank test was used for assessing the statistical significance of the difference between the degrees of homology calculated between two orthologous pseudogenes and that between the respective (orthologous) flanking regions. Cases with pair wise sequence identities <40% were excluded. 5. Analysis of lengths and GC percentage of pseudogenes and their flanking regions For sequence length and GC percentage calculations, only the exonic segments of pseudogenes were considered. One thousand nucleotides upstream and downstream of a pseudogenes were considered as flanking regions. GC content is calculated as the sum of guanine and cytosine nucleotides divided by the total number of nucleotides represented in terms of percentage. 6. Ka/Ks ratio calculations 'PAL2NAL' [44] was used to construct codon alignments between protein sequences (conceptual amino acid trans- lation sequences in the case of pseudogenes) and corre- sponding DNA sequences, separately, for orthologous pseudogenes and parental protein coding genes. 'PAML 4' package [45] was used to calculate Ka/Ks ratios. Orthologs of human parental protein coding genes were identified using a similar approach as that for pseudogene orthologs discussed above, and also obtained from Ensembl data- base. We derived a simulation protocol to calculate Ka/Ks val- ues for evolution without coding-sequence selection pres- sures. This simulation protocol is as follows: (i) the nucleotide distance (Dnt) between a sequence and its ortholog was calculated, using the program DNADIST [46]; (ii) for each sequence, samples of 500 simulated sequences were generated, by randomly mutating the Page 11 of 14 (page number not for citation purposes)