Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera(1) and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium(2), and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness

Application of single nucleotide polymorphisms (SNPs) is revolutionizing human bio-medical research. However, discovery of polymorphisms in low polymorphic species is still a challenging and costly endeavor, despite widespread availability of Sanger sequencing technology. We present CRoPS™ as a novel approach for polymorphism discovery by combining the power of reproducible genome complexity reduction of AFLP® with Genome Sequencer (GS) 20/GS FLX next-generation sequencing technology. With CRoPS, hundreds-of-thousands of sequence reads derived from complexity-reduced genome sequences of two or more samples are processed and mined for SNPs using a fully-automated bioinformatics pipeline. We show that over 75% of putative maize SNPs discovered using CRoPS are successfully converted to SNPWave® assays, confirming them to be true SNPs derived from unique (single-copy) genome sequences. By using CRoPS, polymorphism discovery will become affordable in organisms with high levels of repetitive DNA in the genome and/or low levels of polymorphism in the (breeding) germplasm without the need for prior sequence information.

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.

We present whole genome profiling (WGP), a novel next-generation sequencing-based physical mapping technology for construction of bacterial artificial chromosome (BAC) contigs of complex genomes, using Arabidopsis thaliana as an example. WGP leverages short read sequences derived from restriction fragments of two-dimensionally pooled BAC clones to generate sequence tags. These sequence tags are assigned to individual BAC clones, followed by assembly of BAC contigs based on shared regions containing identical sequence tags. Following in silico analysis of WGP sequence tags and simulation of a map of Arabidopsis chromosome 4 and maize, a WGP map of Arabidopsis thaliana ecotype Columbia was constructed de novo using a six-genome equivalent BAC library. Validation of the WGP map using the Columbia reference sequence confirmed that 350 BAC contigs (98%) were assembled correctly, spanning 97% of the 102-Mb calculated genome coverage. We demonstrate that WGP maps can also be generated for more complex plant genomes and will serve as excellent scaffolds to anchor genetic linkage maps and integrate whole genome sequence data.

BackgroundPlant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse.ResultsIn this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented.ConclusionsAcceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-016-0144-4) contains supplementary material, which is available to authorized users.

Reverse genetics approaches rely on the detection of sequence alterations in target genes to identify allelic variants among mutant or natural populations. Current (pre-) screening methods such as TILLING and EcoTILLING are based on the detection of single base mismatches in heteroduplexes using endonucleases such as CEL 1. However, there are drawbacks in the use of endonucleases due to their relatively poor cleavage efficiency and exonuclease activity. Moreover, pre-screening methods do not reveal information about the nature of sequence changes and their possible impact on gene function. We present KeyPoint™ technology, a high-throughput mutation/polymorphism discovery technique based on massive parallel sequencing of target genes amplified from mutant or natural populations. KeyPoint combines multi-dimensional pooling of large numbers of individual DNA samples and the use of sample identification tags (“sample barcoding”) with next-generation sequencing technology. We show the power of KeyPoint by identifying two mutants in the tomato eIF4E gene based on screening more than 3000 M2 families in a single GS FLX sequencing run, and discovery of six haplotypes of tomato eIF4E gene by re-sequencing three amplicons in a subset of 92 tomato lines from the EU-SOL core collection. We propose KeyPoint technology as a broadly applicable amplicon sequencing approach to screen mutant populations or germplasm collections for identification of (novel) allelic variation in a high-throughput fashion.

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Bread wheat (Triticum aestivum L.) is the most important staple food crop for 35% of the world's population. International efforts are underway to facilitate an increase in wheat production, of which the International Wheat Genome Sequencing Consortium (IWGSC) plays an important role. As part of this effort, we have developed a sequence-based physical map of wheat chromosome 6A using whole-genome profiling (WGP™). The bacterial artificial chromosome (BAC) contig assembly tools fingerprinted contig (fpc) and linear topological contig (ltc) were used and their contig assemblies were compared. A detailed investigation of the contigs structure revealed that ltc created a highly robust assembly compared with those formed by fpc. The ltc assemblies contained 1217 contigs for the short arm and 1113 contigs for the long arm, with an L50 of 1 Mb. To facilitate in silico anchoring, WGP™ tags underlying BAC contigs were extended by wheat and wheat progenitor genome sequence information. Sequence data were used for in silico anchoring against genetic markers with known sequences, of which almost 79% of the physical map could be anchored. Moreover, the assigned sequence information led to the ‘decoration’ of the respective physical map with 3359 anchored genes. Thus, this robust and genetically anchored physical map will serve as a framework for the sequencing of wheat chromosome 6A, and is of immediate use for map-based isolation of agronomically important genes/quantitative trait loci located on this chromosome.