InParanoid 8: orthology analysis between 273 proteomes, mostly eukaryotic.
Bottom Line: Compared to the previous release, this increases the number of species by 173% and the number of pairwise species comparisons by 650%.In turn, the number of ortholog groups has increased by 423%.We present the contents and usages of InParanoid 8, and a detailed analysis of how the proteome content has changed since the previous release.
Affiliation: Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden firstname.lastname@example.org.Show MeSH
Mentions: Overall, most of the proteomes have not changed drastically in the number of sequences or inparalogs, as shown in Figures 3 and 4. If the number of inparalogs changed, then this is normally directly proportional to changes in the number of sequences, and a consequence of a major update in the genome project. We searched for species pairs in which a species had changed more than 1.5-fold in the number of inparalogs and found 28 cases of increase and 170 of decrease. However, all species except three only occurred once; these highly changed species are Brugia malayi, Branchiostoma floridae and Trypanosoma cruzi. Their relative change in the number of sequences is 48% increase, 44% decrease and 45% decrease. This correlates well with the overall change in the number of inparalogs: 45% increase, 45% decrease and 55% decrease. These three species are highlighted in Figure 3 to show that they are outliers. They show just how different a proteome can be defined in different resources; in InParanoid 7 they were taken from NCBI, JGI and GeneDB, respectively. For some species the number of sequences has changed drastically without affecting the overall number of inparalogs much. For example, the aphid Acyrthosiphon pisum has 227% more sequences but overall only 7% more inparalogs, indicating that the added sequences are highly species-specific or that the genome annotation now includes lower quality gene predictions.
Affiliation: Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, Box 1031, SE-17121 Solna, Sweden email@example.com.