Molecular Basis of C-30 Product Regioselectivity of Legume Oxidases Involved in High-Value Triterpenoid Biosynthesis

The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.

Background Medicago truncatula, a close relative of alfalfa, is a preeminent model for studying nitrogen fixation, symbiosis, and legume genomics. The Medicago sequencing project began in 2003 with the goal to decipher sequences originated from the euchromatic portion of the genome. The initial sequencing approach was based on a BAC tiling path, culminating in a BAC-based assembly (Mt3.5) as well as an in-depth analysis of the genome published in 2011. Results Here we describe a further improved and refined version of the M. truncatula genome (Mt4.0) based on de novo whole genome shotgun assembly of a majority of Illumina and 454 reads using ALLPATHS-LG. The ALLPATHS-LG scaffolds were anchored onto the pseudomolecules on the basis of alignments to both the optical map and the genotyping-by-sequencing (GBS) map. The Mt4.0 pseudomolecules encompass ~360 Mb of actual sequences spanning 390 Mb of which ~330 Mb align perfectly with the optical map, presenting a drastic improvement over the BAC-based Mt3.5 which only contained 70% sequences (~250 Mb) of the current version. Most of the sequences and genes that previously resided on the unanchored portion of Mt3.5 have now been incorporated into the Mt4.0 pseudomolecules, with the exception of ~28 Mb of unplaced sequences. With regard to gene annotation, the genome has been re-annotated through our gene prediction pipeline, which integrates EST, RNA-seq, protein and gene prediction evidences. A total of 50,894 genes (31,661 high confidence and 19,233 low confidence) are included in Mt4.0 which overlapped with ~82% of the gene loci annotated in Mt3.5. Of the remaining genes, 14% of the Mt3.5 genes have been deprecated to an “unsupported” status and 4% are absent from the Mt4.0 predictions. Conclusions Mt4.0 and its associated resources, such as genome browsers, BLAST-able datasets and gene information pages, can be found on the JCVI Medicago web site (http://www.jcvi.org/medicago). The assembly and annotation has been deposited in GenBank (BioProject: PRJNA10791). The heavily curated chromosomal sequences and associated gene models of Medicago will serve as a better reference for legume biology and comparative genomics.

The substrate recognition regions in cytochrome P450 family 2 (CYP2) proteins were inferred by group-to-group alignment of CYP2 sequences and those of bacterial P450s, including Pseudomonas putida P450 101A (P450cam), whose substrate-binding residues have been definitely identified by x-ray crystallography of a substrate-bound form (Poulos T. L., Finzel, B. C., and Howard, A. J. (1987) J. Mol. Biol. 195, 687-700). The six putative substrate recognition sites, SRSs, thus identified are dispersively located along the primary structure and constitute about 16% of the total residues. All the reported point mutations and chimeric fragments that significantly affect the substrate specificities of the parental CYP2 enzymes fell within or overlapped some of the six SRSs. Analysis of nucleotide substitution patterns in closely related members in four subfamilies, CYP2A, 2B, 2C, and 2D, consistently indicated that the SRSs have accumulated more nonsynonymous (amino acid-changing) substitutions than the rest of the sequence. This observation supports the idea that diversification of duplicate genes of drug-metabolizing P450s occurs primarily in substrate recognition regions to cope with an increasing number of foreign compounds.