SNPSelect: A scalable and flexible targeted sequence-based genotyping solution.

In plant breeding the use of molecular markers has resulted in tremendous improvement of the speed with which new crop varieties are introduced into the market. Single Nucleotide Polymorphism (SNP) genotyping is routinely used for association studies, Linkage Disequilibrium (LD) and Quantitative Trait Locus (QTL) mapping studies, marker-assisted backcrosses and validation of large numbers of novel SNPs. Here we present the KeyGene SNPSelect technology, a scalable and flexible multiplexed, targeted sequence-based, genotyping solution. The multiplex composition of SNPSelect assays can be easily changed between experiments by adding or removing loci, demonstrating their content flexibility. To demonstrate this versatility, we first designed a 1,056-plex maize assay and genotyped a total of 374 samples originating from an F2 and a Recombinant Inbred Line (RIL) population and a maize germplasm collection. Next, subsets of the most informative SNP loci were assembled in 384-plex and 768-plex assays for further genotyping. Indeed, selection of the most informative SNPs allows cost-efficient yet highly informative genotyping in a custom-made fashion, with average call rates between 88.1% (1,056-plex assay) and 99.4% (384-plex assay), and average reproducibility rates between duplicate samples ranging from 98.2% (1056-plex assay) to 99.9% (384-plex assay). The SNPSelect workflow can be completed from a DNA sample to a genotype dataset in less than three days. We propose SNPSelect as an attractive and competitive genotyping solution to meet the targeted genotyping needs in fields such as plant breeding.

Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations.

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike.

Identification of conserved and novel microRNAs that are responsive to heat stress in Brassica rapa.

The species Brassica rapa includes various vegetable crops. Production of these vegetable crops is usually impaired by heat stress. Some microRNAs (miRNAs) in Arabidopsis have been considered to mediate gene silencing in plant response to abiotic stress. However, it remains unknown whether or what miRNAs play a role in heat resistance of B. rapa. To identify genomewide conserved and novel miRNAs that are responsive to heat stress in B. rapa, we defined temperature thresholds of non-heading Chinese cabbage (B. rapa ssp. chinensis) and constructed small RNA libraries from the seedlings that had been exposed to high temperature (46 °C) for 1 h. By deep sequencing and data analysis, we selected a series of conserved and novel miRNAs that responded to heat stress. In total, Chinese cabbage shares at least 35 conserved miRNA families with Arabidopsis thaliana. Among them, five miRNA families were responsive to heat stress. Northern hybridization and real-time PCR showed that the conserved miRNAs bra-miR398a and bra-miR398b were heat-inhibitive and guided heat response of their target gene, BracCSD1; and bra-miR156h and bra-miR156g were heat-induced and its putative target BracSPL2 was down-regulated. According to the criteria of miRNA and miRNA* that form a duplex, 21 novel miRNAs belonging to 19 miRNA families were predicted. Of these, four were identified to be heat-responsive by Northern blotting and/or expression analysis of the putative targets. The two novel miRNAs bra-miR1885b.3 and bra-miR5718 negatively regulated their putative target genes. 5'-Rapid amplification of cDNA ends PCR indicated that three novel miRNAs cleaved the transcripts of their target genes where their precursors may have evolved from. These results broaden our perspective on the important role of miRNA in plant responses to heat.

A novel class of heat-responsive small RNAs derived from the chloroplast genome of Chinese cabbage (Brassica rapa).

BACKGROUND: Non-coding small RNAs play critical roles in various cellular processes in a wide spectrum of eukaryotic organisms. Their responses to abiotic stress have become a popular topic of economic and scientific importance in biological research. Several studies in recent years have reported a small number of non-coding small RNAs that map to chloroplast genomes. However, it remains uncertain whether small RNAs are generated from chloroplast genome and how they respond to environmental stress, such as high temperature. Chinese cabbage is an important vegetable crop, and heat stress usually causes great losses in yields and quality. Under heat stress, the leaves become etiolated due to the disruption and disassembly of chloroplasts. In an attempt to determine the heat-responsive small RNAs in chloroplast genome of Chinese cabbage, we carried out deep sequencing, using heat-treated samples, and analysed the proportion of small RNAs that were matched to chloroplast genome. RESULTS: Deep sequencing provided evidence that a novel subset of small RNAs were derived from the chloroplast genome of Chinese cabbage. The chloroplast small RNAs (csRNAs) include those derived from mRNA, rRNA, tRNA and intergenic RNA. The rRNA-derived csRNAs were preferentially located at the 3'-ends of the rRNAs, while the tRNA-derived csRNAs were mainly located at 5'-termini of the tRNAs. After heat treatment, the abundance of csRNAs decreased in seedlings, except those of 24 nt in length. The novel heat-responsive csRNAs and their locations in the chloroplast were verified by Northern blotting. The regulation of some csRNAs to the putative target genes were identified by real-time PCR. Our results reveal that high temperature suppresses the production of some csRNAs, which have potential roles in transcriptional or post-transcriptional regulation. CONCLUSIONS: In addition to nucleus, the chloroplast is another important organelle that generates a number of small RNAs. Many members of csRNA families are highly sensitive to heat stress. Some csRNAs respond to heat stress by silencing target genes. We suggest that proper temperature is important for production of chloroplast small RNAs, which are associated with plant resistance to abiotic stress.

Sequence-based physical mapping of complex genomes by whole genome profiling.

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.