Wen‐Chi Chang

High oil and protein content make tetraploid peanut a leading oil and food legume. Here we report a high-quality peanut genome sequence, comprising 2.54 Gb with 20 pseudomolecules and 83,709 protein-coding gene models. We characterize gene functional groups implicated in seed size evolution, seed oil content, disease resistance and symbiotic nitrogen fixation. The peanut B subgenome has more genes and general expression dominance, temporally associated with long-terminal-repeat expansion in the A subgenome that also raises questions about the A-genome progenitor. The polyploid genome provided insights into the evolution of Arachis hypogaea and other legume chromosomes. Resequencing of 52 accessions suggests that independent domestications formed peanut ecotypes. Whereas 0.42-0.47 million years ago (Ma) polyploidy constrained genetic variation, the peanut genome sequence aids mapping and candidate-gene discovery for traits such as seed size and color, foliar disease resistance and others, also providing a cornerstone for functional genomics and peanut improvement.

The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN.itps.ncku.edu.tw/) is an effective resource for predicting regulatory elements and reconstructing transcriptional regulatory networks for plant genes. In this release (PlantPAN 3.0), 17 230 TFs were collected from 78 plant species. To explore regulatory landscapes, genomic locations of TFBSs have been captured from 662 public ChIP-seq samples using standard data processing. A total of 1 233 999 regulatory linkages were identified from 99 regulatory factors (TFs, histones and other DNA-binding proteins) and their target genes across seven species. Additionally, this new version added 2449 matrices extracted from ChIP-seq peaks for cis-regulatory element prediction. In addition to integrated ChIP-seq data, four major improvements were provided for more comprehensive information of TF binding events, including (i) 1107 experimentally verified TF matrices from the literature, (ii) gene regulation network comparison between two species, (iii) 3D structures of TFs and TF-DNA complexes and (iv) condition-specific co-expression networks of TFs and their target genes extended to four species. The PlantPAN 3.0 can not only be efficiently used to investigate critical cis- and trans-regulatory elements in plant promoters, but also to reconstruct high-confidence relationships among TF-targets under specific conditions.

Transcription factors (TFs) are sequence-specific DNA-binding proteins acting as critical regulators of gene expression. The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN2.itps.ncku.edu.tw) provides an informative resource for detecting transcription factor binding sites (TFBSs), corresponding TFs, and other important regulatory elements (CpG islands and tandem repeats) in a promoter or a set of plant promoters. Additionally, TFBSs, CpG islands, and tandem repeats in the conserve regions between similar gene promoters are also identified. The current PlantPAN release (version 2.0) contains 16 960 TFs and 1143 TF binding site matrices among 76 plant species. In addition to updating of the annotation information, adding experimentally verified TF matrices, and making improvements in the visualization of transcriptional regulatory networks, several new features and functions are incorporated. These features include: (i) comprehensive curation of TF information (response conditions, target genes, and sequence logos of binding motifs, etc.), (ii) co-expression profiles of TFs and their target genes under various conditions, (iii) protein-protein interactions among TFs and their co-factors, (iv) TF-target networks, and (v) downstream promoter elements. Furthermore, a dynamic transcriptional regulatory network under various conditions is provided in PlantPAN 2.0. The PlantPAN 2.0 is a systematic platform for plant promoter analysis and reconstructing transcriptional regulatory networks.

BACKGROUND: The elucidation of transcriptional regulation in plant genes is important area of research for plant scientists, following the mapping of various plant genomes, such as A. thaliana, O. sativa and Z. mays. A variety of bioinformatic servers or databases of plant promoters have been established, although most have been focused only on annotating transcription factor binding sites in a single gene and have neglected some important regulatory elements (tandem repeats and CpG/CpNpG islands) in promoter regions. Additionally, the combinatorial interaction of transcription factors (TFs) is important in regulating the gene group that is associated with the same expression pattern. Therefore, a tool for detecting the co-regulation of transcription factors in a group of gene promoters is required. RESULTS: This study develops a database-assisted system, PlantPAN (Plant Promoter Analysis Navigator), for recognizing combinatorial cis-regulatory elements with a distance constraint in sets of plant genes. The system collects the plant transcription factor binding profiles from PLACE, TRANSFAC (public release 7.0), AGRIS, and JASPER databases and allows users to input a group of gene IDs or promoter sequences, enabling the co-occurrence of combinatorial transcription factor binding sites (TFBSs) within a defined distance (20 bp to 200 bp) to be identified. Furthermore, the new resource enables other regulatory features in a plant promoter, such as CpG/CpNpG islands and tandem repeats, to be displayed. The regulatory elements in the conserved regions of the promoters across homologous genes are detected and presented. CONCLUSION: In addition to providing a user-friendly input/output interface, PlantPAN has numerous advantages in the analysis of a plant promoter. Several case studies have established the effectiveness of PlantPAN. This novel analytical resource is now freely available at http://PlantPAN.mbc.nctu.edu.tw.

The dbPTM (http://dbPTM.mbc.nctu.edu.tw/) has been maintained for over 10 years with the aim to provide functional and structural analyses for posttranslational modifications (PTMs). In this update, dbPTM not only integrates more experimentally validated PTMs from available databases and through manual curation of literature but also provides PTMdisease associations based on non-synonymous single nucleotide polymorphisms (nsSNPs). The high-throughput deep sequencing technology has led to a surge in the data generated through analysis of association between SNPs and diseases, both in terms of growth amount and scope. This update thus integrated disease-associated nsSNPs from db-SNP based on genome-wide association studies. The PTM substrate sites located at a specified distance in terms of the amino acids encoded from nsSNPs were deemed to have an association with the involved diseases. In recent years, increasing evidence for crosstalk between PTMs has been reported. Although mass spectrometry-based proteomics has substantially improved our knowledge about substrate site specificity of single PTMs, the fact that the crosstalk of combinatorial PTMs may act in concert with the regulation of protein function and activity is neglected. Because of the relatively limited information about concurrent frequency and functional relevance of PTM crosstalk, in this update, the PTM sites neighboring other PTM sites in a specified window length were subjected to motif discovery and functional enrichment analysis. This update highlights the current challenges in PTM crosstalk investigation and breaks the bottleneck of how proteomics may contribute to understanding PTM codes, revealing the next level of data complexity and proteomic limitation in prospective PTM research.