Abstract: Evolutionary retention of duplicated genes encoding transcription-associated proteins (TAPs, comprising transcription factors and other transcriptional regulators) has been hypothesized to be positively correlated with increasing morphological complexity and paleopolyploidizations, especially within the plant kingdom. Here, we present the most comprehensive set of classification rules for TAPs and its application for genome-wide analyses of plants and algae. Using a dated species tree and phylogenetic comparative (PC) analyses, we define the timeline of TAP loss, gain, and expansion among Viridiplantae and find that two major bursts of gain/expansion occurred, coinciding with the water-to-land transition and the radiation of flowering plants. For the first time, we provide PC proof for the long-standing hypothesis that TAPs are major driving forces behind the evolution of morphological complexity, the latter in Plantae being shaped significantly by polyploidization and subsequent biased paleolog retention. Principal component analysis incorporating the number of TAPs per genome provides an alternate and significant proxy for complexity, ideally suited for PC genomics. Our work lays the ground for further interrogation of the shaping of gene regulatory networks underlying the evolution of organism complexity

Abstract: ppdb (http://ppdb.agr.gifu-u.ac.jp) is a plant promoter database that provides information on transcription start sites (TSSs), core promoter structure (TATA boxes, Initiators, Y Patches, GA and CA elements) and regulatory element groups (REGs) as putative and comprehensive transcriptional regulatory elements. Since the last report in this journal, the database has been updated in three areas to version 3.0. First, new genomes have been included in the database, and now ppdb provides information on Arabidopsis thaliana, rice, Physcomitrella patens and poplar. Second, new TSS tag data (34 million) from A. thaliana, determined by a high throughput sequencer, has been added to give a ∼200-fold increase in TSS data compared with version 1.0. This results in a much higher coverage of ∼27 000 A. thaliana genes and finer positioning of promoters even for genes with low expression levels. Third, microarray data-based predictions have been appended as REG annotations which inform their putative physiological roles