Here we present Primer3Plus, a new web interface to the popular Primer3 primer design program as an enhanced alternative for the CGI- scripts that come with Primer3. Primer3 consists of a command line program and a web interface. The web interface is one large form showing all of the possible options. This makes the interface powerful, but at the same time confusing for occasional users. Primer3Plus provides an intuitive user interface using present-day web technologies and has been developed in close collaboration with molecular biologists and technicians regularly designing primers. It focuses on the task at hand, and hides detailed settings from the user until these are needed. We also added functionality to automate specific tasks like designing primers for cloning or step-wise sequencing. Settings and designed primer sequences can be stored locally for later use. Primer3Plus supports a range of common sequence formats, such as FASTA. Finally, primers selected by Primer3Plus can be sent to an order form, allowing tight integration into laboratory ordering systems. Moreover, the open architecture of Primer3Plus allows easy expansion or integration of external software packages. The Primer3Plus Perl source code is available under GPL license from SourceForge. Primer3Plus is available at http://www.bioinformatics.nl/primer3plus.

Highlight textThe genotype-by-environment interactions of five parental environments with seed and plant performance are mediated by distinct genetic and molecular pathways, and the selective pressures that have shaped their natural variation.

The Hawaiian strain (CB4856) of Caenorhabditis elegans is one of the most divergent from the canonical laboratory strain N2 and has been widely used in developmental, population, and evolutionary studies. To enhance the utility of the strain, we have generated a draft sequence of the CB4856 genome, exploiting a variety of resources and strategies. When compared against the N2 reference, the CB4856 genome has 327,050 single nucleotide variants (SNVs) and 79,529 insertion–deletion events that result in a total of 3.3 Mb of N2 sequence missing from CB4856 and 1.4 Mb of sequence present in CB4856 but not present in N2. As previously reported, the density of SNVs varies along the chromosomes, with the arms of chromosomes showing greater average variation than the centers. In addition, we find 61 regions totaling 2.8 Mb, distributed across all six chromosomes, which have a greatly elevated SNV density, ranging from 2 to 16% SNVs. A survey of other wild isolates show that the two alternative haplotypes for each region are widely distributed, suggesting they have been maintained by balancing selection over long evolutionary times. These divergent regions contain an abundance of genes from large rapidly evolving families encoding F-box, MATH, BATH, seven-transmembrane G-coupled receptors, and nuclear hormone receptors, suggesting that they provide selective advantages in natural environments. The draft sequence makes available a comprehensive catalog of sequence differences between the CB4856 and N2 strains that will facilitate the molecular dissection of their phenotypic differences. Our work also emphasizes the importance of going beyond simple alignment of reads to a reference genome when assessing differences between genomes.

Desiccation tolerance is common in seeds and various other organisms, but only a few angiosperm species possess vegetative desiccation tolerance. These 'resurrection species' may serve as ideal models for the ultimate design of crops with enhanced drought tolerance. To understand the molecular and genetic mechanisms enabling vegetative desiccation tolerance, we produced a high-quality whole-genome sequence for the resurrection plant Xerophyta viscosa and assessed transcriptome changes during its dehydration. Data revealed induction of transcripts typically associated with desiccation tolerance in seeds and involvement of orthologues of ABI3 and ABI5, both key regulators of seed maturation. Dehydration resulted in both increased, but predominantly reduced, transcript abundance of genomic 'clusters of desiccation-associated genes' (CoDAGs), reflecting the cessation of growth that allows for the expression of desiccation tolerance. Vegetative desiccation tolerance in X. viscosa was found to be uncoupled from drought-induced senescence. We provide strong support for the hypothesis that vegetative desiccation tolerance arose by redirection of genetic information from desiccation-tolerant seeds.

Plants are fascinating and complex organisms. A comprehensive understanding of the organization, function and evolution of plant genes is essential to disentangle important biological processes and to advance crop engineering and breeding strategies. The ultimate aim in deciphering complex biological processes is the discovery of causal genes and regulatory mechanisms controlling these processes. The recent surge of omics data has opened the door to a system-wide understanding of the flow of biological information underlying complex traits. However, dealing with the corresponding large data sets represents a challenging endeavor that calls for the development of powerful bioinformatics methods. A popular approach is the construction and analysis of gene networks. Such networks are often used for genome-wide representation of the complex functional organization of biological systems. Network based on similarity in gene expression are called (gene) co-expression networks. One of the major application of gene co-expression networks is the functional annotation of unknown genes. Constructing co-expression networks is generally straightforward. In contrast, the resulting network of connected genes can become very complex, which limits its biological interpretation. Several strategies can be employed to enhance the interpretation of the networks. A strategy in coherence with the biological question addressed needs to be established to infer reliable networks. Additional benefits can be gained from network-based strategies using prior knowledge and data integration to further enhance the elucidation of gene regulatory relationships. As a result, biological networks provide many more applications beyond the simple visualization of co-expressed genes. In this study we review the different approaches for co-expression network inference in plants. We analyse integrative genomics strategies used in recent studies that successfully identified candidate genes taking advantage of gene co-expression networks. Additionally, we discuss promising bioinformatics approaches that predict networks for specific purposes.