Panati and Webpanati - information systems for SNPS.

This paper describes two softwares: Panati and webPanati

Molecular profiling of an interspecific rice population derived from a cross between WAB 56-104 (Oryza sativa) and CG 14 (Oryza glaberrima)

NERICA rices are interspecific inbred progeny derived from crosses between Oryza sativa x O. glaberrima. In this study, we evaluated 70 BC2 interspecific lines, developed by crossing a tropicaljaponica variety (WAB 56-104) as the recurrent parent to an O. glaberrima variety (CG 14) as the donor parent, followed by the use of anther culture to derive doubled haploids (DH) (26 lines) or eightgenerations of inbreeding to fix the lines (44 lines). Seven of these BC2 derived inbred lines have been released as NERICA 1 - NERICA 7. This study examined the relative contribution of each parent and theextent of genetic differences among these 70 sister lines using 130 well-distributed microsatellite markers which cover 1725 cM of the rice genome. The average proportion of O. sativa recurrent parentgenome was 87.4% (1,508 cM), while the observed average proportion of O. glaberrima donor genome was 6.3% (108 cM). Non-parental alleles were detected in 83% of the lines and contributed an average of38 cM per line (~2.2% of genomic DNA). Lines that had undergone eight generations of inbreeding in the field contained significantly more non-parental alleles (av. 2.7%) compared to the DH lines (av. 1.3%)that were developed from BC2 anthers. Using both cluster and principal component analyses, two major groups were detected in these materials. The NERICA varieties (NERICA 1 to 7) clustered in one group while the remaining 63 lines clustered in another group, suggesting that the second group may offer significant opportunities for further selection and variety development

A SWEET solution to rice blight

Bacterial blight is an important disease of rice that is particularly destructive in Southeast Asia and sub-Saharan Africa, exacerbated by the heavy rains of the monsoon seasons. Estimated crop loss due to bacterial blight may be as high as 75%, with millions of hectares of rice affected annually. In this issue, an international team of researchers describes the use of CRISPR editing to generate rice plants that are broadly resistant to the main pathogen that causes rice blight, Xanthomonas oryzae pv. oryzae (Xoo)1. To enhance the durability and management of resistance, the team has also developed a kit to trace the disease, and its virulence and resistance alleles2

New horizons for plant translational research

In this issue, we launch a new article collection "The Promise of Plant Translational Research," featuring articles from leading plant researchers and call for additional plant translational research to be submitted to PLOS Biology for inclusion in this collection. We also discuss in this Editorial why this field has a vital role to play in meeting the challenges of sustainably feeding a growing world population

New Horizons for Plant Translational Research

The world’s human population continues to expand and is predicted to reach ~9 billion by 2040, up from its current level of just over 7 billion. Some estimate that with this rate of population growth, accommodating the increased demand for food will require the world’s agricultural production to increase 50% by 2030. The planet’s water resources are also under pressure. As Pamela Ronald highlights in her accompanying Essay, the amount of fresh water available per person has decreased 4-fold in the last 60 years and of the water that is available ~70% is already used for agriculture. Thus, agricultural production must be intensified to feed more people with less water on the same amount of land (given that little undeveloped arable land remains and what does is being lost to urbanization, desertification, and environmental damage). Furthermore, pathogens that cause devastating crop losses continue to spread in the face of increased global commerce and climate change. Given these challenges, there is a pressing need for plant research to produce solutions to ensure food security in a sustainable and safe way. The need is acute in both developed countries and in the less developed parts of the world, where many people endure chronic malnutrition and suffer the long term consequences on their health and well being. Plant scientists, therefore, urgently need to increase the productivity, pathogen resistance, and sustainability of existing crops, and are challenged to domesticate new crops

A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

Background Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. Results RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. Conclusions Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway

USDA Plant Genome Research Program

The U.S. Congress appropriated funds in 1991 for the USDA Plant Genome Research Program, four years after its initial conception in 1987. The goal of the USDA Plant Genome Research Program is to improve plants (agronomic, horticultural, and forest tree species) by locating marker DNA or genes on chromosomes, determining gene structure, and transferring genes to improve plant performance with accompanying reduced environmental impact to meet marketplace needs and niches. The Plant Genome Research Program is one program with two parts: National Research Initiative and Plant Genome Database (PGD). The PGD is now a real and functioning information and data resource for agricultural and other plant science genome researchers, and it is in the public domain. Additional progress is given according to major plant groups. The PGD is a suite of several information products produced at the National Agricultural Library (NAL) in collaboration with the Agricultural Research Service and Forest Service species coordinators

Gramene QTL database: development, content and applications

Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene-phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research

Development of Genome-wide Simple Sequence Repeat Markers Using Whole-genome Shotgun Sequences of Sorghum (Sorghum bicolor (L.) Moench)

Simple sequence repeat (SSR) markers with a high degree of polymorphism contribute to the molecular dissection of agriculturally important traits in sorghum (Sorghum bicolor (L.) Moench). We designed 5599 non-redundant SSR markers, including regions flanking the SSRs, in whole-genome shotgun sequences of sorghum line ATx623. (AT/TA)n repeats constituted 26.1% of all SSRs, followed by (AG/TC)n at 20.5%, (AC/TG)n at 13.7% and (CG/GC)n at 11.8%. The chromosomal locations of 5012 SSR markers were determined by comparing the locations identified by means of electronic PCR with the predicted positions of 34 008 gene loci. Most SSR markers had a similar distribution to the gene loci. Among 970 markers validated by fragment analysis, 67.8% (658 of 970) markers successfully provided PCR amplification in sorghum line BTx623, with a mean polymorphism rate of 45.1% (297 of 658) for all SSR loci in combinations of 11 sorghum lines and one sudangrass (Sorghum sudanense (Piper) Stapf) line. The product of 5012 and 0.678 suggests that ∼3400 SSR markers could be used to detect SSR polymorphisms and that more than 1500 (45.1% of 3400) markers could reveal SSR polymorphisms in combinations of Sorghum lines

Gramene: a growing plant comparative genomics resource

Gramene (www.gramene.org) is a curated resource for genetic, genomic and comparative genomics data for the major crop species, including rice, maize, wheat and many other plant (mainly grass) species. Gramene is an open-source project. All data and software are freely downloadable through the ftp site (ftp.gramene.org/pub/gramene) and available for use without restriction. Gramene's core data types include genome assembly and annotations, other DNA/mRNA sequences, genetic and physical maps/markers, genes, quantitative trait loci (QTLs), proteins, ontologies, literature and comparative mappings. Since our last NAR publication 2 years ago, we have updated these data types to include new datasets and new connections among them. Completely new features include rice pathways for functional annotation of rice genes; genetic diversity data from rice, maize and wheat to show genetic variations among different germplasms; large-scale genome comparisons among Oryza sativa and its wild relatives for evolutionary studies; and the creation of orthologous gene sets and phylogenetic trees among rice, Arabidopsis thaliana, maize, poplar and several animal species (for reference purpose). We have significantly improved the web interface in order to provide a more user-friendly browsing experience, including a dropdown navigation menu system, unified web page for markers, genes, QTLs and proteins, and enhanced quick search functions