A genetic linkage map of black raspberry (Rubus occidentalis) and the mapping of Ag(4) conferring resistance to the aphid Amphorophora agathonica.

KEY MESSAGE: We have constructed a densely populated, saturated genetic linkage map of black raspberry and successfully placed a locus for aphid resistance. Black raspberry (Rubus occidentalis L.) is a high-value crop in the Pacific Northwest of North America with an international marketplace. Few genetic resources are readily available and little improvement has been achieved through breeding efforts to address production challenges involved in growing this crop. Contributing to its lack of improvement is low genetic diversity in elite cultivars and an untapped reservoir of genetic diversity from wild germplasm. In the Pacific Northwest, where most production is centered, the current standard commercial cultivar is highly susceptible to the aphid Amphorophora agathonica Hottes, which is a vector for the Raspberry mosaic virus complex. Infection with the virus complex leads to a rapid decline in plant health resulting in field replacement after only 3-4 growing seasons. Sources of aphid resistance have been identified in wild germplasm and are used to develop mapping populations to study the inheritance of these valuable traits. We have constructed a genetic linkage map using single-nucleotide polymorphism and transferable (primarily simple sequence repeat) markers for F1 population ORUS 4305 consisting of 115 progeny that segregate for aphid resistance. Our linkage map of seven linkage groups representing the seven haploid chromosomes of black raspberry consists of 274 markers on the maternal map and 292 markers on the paternal map including a morphological locus for aphid resistance. This is the first linkage map of black raspberry and will aid in developing markers for marker-assisted breeding, comparative mapping with other Rubus species, and enhancing the black raspberry genome assembly.

Genome-wide mapping of alternative splicing in Arabidopsis thaliana.

Alternative splicing can enhance transcriptome plasticity and proteome diversity. In plants, alternative splicing can be manifested at different developmental stages, and is frequently associated with specific tissue types or environmental conditions such as abiotic stress. We mapped the Arabidopsis transcriptome at single-base resolution using the Illumina platform for ultrahigh-throughput RNA sequencing (RNA-seq). Deep transcriptome sequencing confirmed a majority of annotated introns and identified thousands of novel alternatively spliced mRNA isoforms. Our analysis suggests that at least approximately 42% of intron-containing genes in Arabidopsis are alternatively spliced; this is significantly higher than previous estimates based on cDNA/expressed sequence tag sequencing. Random validation confirmed that novel splice isoforms empirically predicted by RNA-seq can be detected in vivo. Novel introns detected by RNA-seq were substantially enriched in nonconsensus terminal dinucleotide splice signals. Alternative isoforms with premature termination codons (PTCs) comprised the majority of alternatively spliced transcripts. Using an example of an essential circadian clock gene, we show that intron retention can generate relatively abundant PTC(+) isoforms and that this specific event is highly conserved among diverse plant species. Alternatively spliced PTC(+) isoforms can be potentially targeted for degradation by the nonsense mediated mRNA decay (NMD) surveillance machinery or regulate the level of functional transcripts by the mechanism of regulated unproductive splicing and translation (RUST). We demonstrate that the relative ratios of the PTC(+) and reference isoforms for several key regulatory genes can be considerably shifted under abiotic stress treatments. Taken together, our results suggest that like in animals, NMD and RUST may be widespread in plants and may play important roles in regulating gene expression.

Supersplat--spliced RNA-seq alignment.

MOTIVATION: High-throughput sequencing technologies have recently made deep interrogation of expressed transcript sequences practical, both economically and temporally. Identification of intron/exon boundaries is an essential part of genome annotation, yet remains a challenge. Here, we present supersplat, a method for unbiased splice-junction discovery through empirical RNA-seq data. RESULTS: Using a genomic reference and RNA-seq high-throughput sequencing datasets, supersplat empirically identifies potential splice junctions at a rate of approximately 11.4 million reads per hour. We further benchmark the performance of the algorithm by mapping Illumina RNA-seq reads to identify introns in the genome of the reference dicot plant Arabidopsis thaliana and we demonstrate the utility of supersplat for de novo empirical annotation of splice junctions using the reference monocot plant Brachypodium distachyon. AVAILABILITY: Implemented in C++, supersplat source code and binaries are freely available on the web at http://mocklerlab-tools.cgrb.oregonstate.edu/.

QSRA: a quality-value guided de novo short read assembler.

BACKGROUND: New rapid high-throughput sequencing technologies have sparked the creation of a new class of assembler. Since all high-throughput sequencing platforms incorporate errors in their output, short-read assemblers must be designed to account for this error while utilizing all available data. RESULTS: We have designed and implemented an assembler, Quality-value guided Short Read Assembler, created to take advantage of quality-value scores as a further method of dealing with error. Compared to previous published algorithms, our assembler shows significant improvements not only in speed but also in output quality. CONCLUSION: QSRA generally produced the highest genomic coverage, while being faster than VCAKE. QSRA is extremely competitive in its longest contig and N50/N80 contig lengths, producing results of similar quality to those of EDENA and VELVET. QSRA provides a step closer to the goal of de novo assembly of complex genomes, improving upon the original VCAKE algorithm by not only drastically reducing runtimes but also increasing the viability of the assembly algorithm through further error handling capabilities.

Target Capture Sequencing Unravels Rubus Evolution.

Rubus (Rosaceae) comprises more than 500 species with additional commercially cultivated raspberries and blackberries. The most recent (> 100 years old) global taxonomic treatment of the genus defined 12 subgenera; two subgenera were subsequently described and some species were rearranged. Intra- and interspecific ploidy levels and hybridization make phylogenetic estimation of Rubus challenging. Our objectives were to estimate the phylogeny of 94 taxonomically and geographically diverse species and three cultivars using chloroplast DNA sequences and target capture of approximately 1,000 low copy nuclear genes; estimate divergence times between major Rubus clades; and examine the historical biogeography of species diversification. Target capture sequencing identified eight major groups within Rubus. Subgenus Orobatus and Subg. Anoplobatus were monophyletic, while other recognized subgenera were para- or polyphyletic. Multiple hybridization events likely occurred across the phylogeny at subgeneric levels, e.g., Subg. Rubus (blackberries) × Subg. Idaeobatus (raspberries) and Subg. Idaeobatus × Subg. Cylactis (Arctic berries) hybrids. The raspberry heritage within known cultivated blackberry hybrids was confirmed. The most recent common ancestor of the genus was most likely distributed in North America. Multiple distribution events occurred during the Miocene (about 20 Ma) from North America into Asia and Europe across the Bering land bridge and southward crossing the Panamanian Isthmus. Rubus species diversified greatly in Asia during the Miocene. Rubus taxonomy does not reflect phylogenetic relationships and subgeneric revision is warranted. The most recent common ancestor migrated from North America towards Asia, Europe, and Central and South America early in the Miocene then diversified. Ancestors of the genus Rubus may have migrated to Oceania by long distance bird dispersal. This phylogeny presents a roadmap for further Rubus systematics research. In conclusion, the target capture dataset provides high resolution between species though it also gave evidence of gene tree/species tree and cytonuclear discordance. Discordance may be due to hybridization or incomplete lineage sorting, rather than a lack of phylogenetic signal. This study illustrates the importance of using multiple phylogenetic methods when examining complex groups and the utility of software programs that estimate signal conflict within datasets.

A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria.

Phenotyping has become the rate-limiting step in using large-scale genomic data to understand and improve agricultural crops. Here, the Bellwether Phenotyping Platform for controlled-environment plant growth and automated multimodal phenotyping is described. The system has capacity for 1140 plants, which pass daily through stations to record fluorescence, near-infrared, and visible images. Plant Computer Vision (PlantCV) was developed as open-source, hardware platform-independent software for quantitative image analysis. In a 4-week experiment, wild Setaria viridis and domesticated Setaria italica had fundamentally different temporal responses to water availability. While both lines produced similar levels of biomass under limited water conditions, Setaria viridis maintained the same water-use efficiency under water replete conditions, while Setaria italica shifted to less efficient growth. Overall, the Bellwether Phenotyping Platform and PlantCV software detected significant effects of genotype and environment on height, biomass, water-use efficiency, color, plant architecture, and tissue water status traits. All ∼ 79,000 images acquired during the course of the experiment are publicly available.

Comparative analyses of C4 and C3 photosynthesis in developing leaves of maize and rice.

C4 and C3 photosynthesis differ in the efficiency with which they consume water and nitrogen. Engineering traits of the more efficient C4 photosynthesis into C3 crops could substantially increase crop yields in hot, arid conditions. To identify differences between C4 and C3 photosynthetic mechanisms, we profiled metabolites and gene expression in the developing leaves of Zea mays (maize), a C4 plant, and Oryza sativa (rice), a C3 plant, using a statistical method named the unified developmental model (UDM). Candidate cis-regulatory elements and transcription factors that might regulate photosynthesis were identified, together with differences between C4 and C3 nitrogen and carbon metabolism. The UDM algorithms could be applied to analyze and compare development in other species. These data sets together with community viewers to access and mine them provide a resource for photosynthetic research that will inform efforts to engineer improvements in carbon fixation in economically valuable grass crops.

Detection and quantification of alternative splicing variants using RNA-seq.

Next-generation sequencing has enabled genome-wide studies of alternative pre-mRNA splicing, allowing for empirical determination, characterization, and quantification of the expressed RNAs in a sample in toto. As a result, RNA sequencing (RNA-seq) has shown tremendous power to drive biological discoveries. At the same time, RNA-seq has created novel challenges that necessitate the development of increasingly sophisticated computational approaches and bioinformatic tools. In addition to the analysis of massive datasets, these tools also need to facilitate questions and analytical approaches driven by such rich data. HTS and RNA-seq are still in a stage of very rapid evolution and are, therefore, only introduced in general terms. This chapter mainly focuses on the methods for discovery, detection, and quantification of alternatively spliced transcript variants.

Exploring the switchgrass transcriptome using second-generation sequencing technology.

BACKGROUND: Switchgrass (Panicum virgatum L.) is a C4 perennial grass and widely popular as an important bioenergy crop. To accelerate the pace of developing high yielding switchgrass cultivars adapted to diverse environmental niches, the generation of genomic resources for this plant is necessary. The large genome size and polyploid nature of switchgrass makes whole genome sequencing a daunting task even with current technologies. Exploring the transcriptional landscape using next generation sequencing technologies provides a viable alternative to whole genome sequencing in switchgrass. PRINCIPAL FINDINGS: Switchgrass cDNA libraries from germinating seedlings, emerging tillers, flowers, and dormant seeds were sequenced using Roche 454 GS-FLX Titanium technology, generating 980,000 reads with an average read length of 367 bp. De novo assembly generated 243,600 contigs with an average length of 535 bp. Using the foxtail millet genome as a reference greatly improved the assembly and annotation of switchgrass ESTs. Comparative analysis of the 454-derived switchgrass EST reads with other sequenced monocots including Brachypodium, sorghum, rice and maize indicated a 70-80% overlap. RPKM analysis demonstrated unique transcriptional signatures of the four tissues analyzed in this study. More than 24,000 ESTs were identified in the dormant seed library. In silico analysis indicated that there are more than 2000 EST-SSRs in this collection. Expression of several orphan ESTs was confirmed by RT-PCR. SIGNIFICANCE: We estimate that about 90% of the switchgrass gene space has been covered in this analysis. This study nearly doubles the amount of EST information for switchgrass currently in the public domain. The celerity and economical nature of second-generation sequencing technologies provide an in-depth view of the gene space of complex genomes like switchgrass. Sequence analysis of closely related members of the NAD(+)-malic enzyme type C4 grasses such as the model system Setaria viridis can serve as a viable proxy for the switchgrass genome.

Development and evaluation of a genome-wide 6K SNP array for diploid sweet cherry and tetraploid sour cherry.

High-throughput genome scans are important tools for genetic studies and breeding applications. Here, a 6K SNP array for use with the Illumina Infinium® system was developed for diploid sweet cherry (Prunus avium) and allotetraploid sour cherry (P. cerasus). This effort was led by RosBREED, a community initiative to enable marker-assisted breeding for rosaceous crops. Next-generation sequencing in diverse breeding germplasm provided 25 billion basepairs (Gb) of cherry DNA sequence from which were identified genome-wide SNPs for sweet cherry and for the two sour cherry subgenomes derived from sweet cherry (avium subgenome) and P. fruticosa (fruticosa subgenome). Anchoring to the peach genome sequence, recently released by the International Peach Genome Initiative, predicted relative physical locations of the 1.9 million putative SNPs detected, preliminarily filtered to 368,943 SNPs. Further filtering was guided by results of a 144-SNP subset examined with the Illumina GoldenGate® assay on 160 accessions. A 6K Infinium® II array was designed with SNPs evenly spaced genetically across the sweet and sour cherry genomes. SNPs were developed for each sour cherry subgenome by using minor allele frequency in the sour cherry detection panel to enrich for subgenome-specific SNPs followed by targeting to either subgenome according to alleles observed in sweet cherry. The array was evaluated using panels of sweet (n = 269) and sour (n = 330) cherry breeding germplasm. Approximately one third of array SNPs were informative for each crop. A total of 1825 polymorphic SNPs were verified in sweet cherry, 13% of these originally developed for sour cherry. Allele dosage was resolved for 2058 polymorphic SNPs in sour cherry, one third of these being originally developed for sweet cherry. This publicly available genomics resource represents a significant advance in cherry genome-scanning capability that will accelerate marker-locus-trait association discovery, genome structure investigation, and genetic diversity assessment in this diploid-tetraploid crop group.

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm.

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.

The genome of woodland strawberry (Fragaria vesca).

The woodland strawberry, Fragaria vesca (2n = 2x = 14), is a versatile experimental plant system. This diminutive herbaceous perennial has a small genome (240 Mb), is amenable to genetic transformation and shares substantial sequence identity with the cultivated strawberry (Fragaria × ananassa) and other economically important rosaceous plants. Here we report the draft F. vesca genome, which was sequenced to ×39 coverage using second-generation technology, assembled de novo and then anchored to the genetic linkage map into seven pseudochromosomes. This diploid strawberry sequence lacks the large genome duplications seen in other rosids. Gene prediction modeling identified 34,809 genes, with most being supported by transcriptome mapping. Genes critical to valuable horticultural traits including flavor, nutritional value and flowering time were identified. Macrosyntenic relationships between Fragaria and Prunus predict a hypothetical ancestral Rosaceae genome that had nine chromosomes. New phylogenetic analysis of 154 protein-coding genes suggests that assignment of Populus to Malvidae, rather than Fabidae, is warranted.