Single Molecule, Real-Time (SMRT) Sequencing provides efficient, streamlined solutions to address new frontiers in plant genomes and transcriptomes. Inherent challenges presented by highly repetitive, low-complexity regions and duplication events are directly addressed with multi- kilobase read lengths exceeding 8.5 kb on average, with many exceeding 20 kb. Differentiating between transcript isoforms that are difficult to resolve with short-read technologies is also now possible. We present solutions available for both reference genome and transcriptome research that best leverage long reads in several plant projects including algae, Arabidopsis, rice, and spinach using only the PacBio platform. Benefits for these applications are further realized with consistent use of size-selection of input sample using the BluePippin™ device from Sage Science. We will share highlights from our genome projects using the latest P5- C3 chemistry to generate high-quality reference genomes with the highest contiguity, contig N50 exceeding 1 Mb, and average base quality of QV50. Additionally, the value of long, intact reads to provide a no-assembly approach to investigate transcript isoforms using our Iso-Seq protocol will be presented for full transcriptome characterization and targeted surveys of genes with complex structures. PacBio provides the most comprehensive assembly with annotation when combining offerings for both genome and transcriptome research efforts. For more focused investigation, PacBio also offers researchers opportunities to easily investigate and survey genes with complex structures.
Reconstruction of the spinach coding genome using full-length transcriptome without a reference genome
For highly complex and large genomes, a well-annotated genome may be computationally challenging and costly, yet the study of alternative splicing events and gene annotations usually rely on the existence of a genome. Long-read sequencing technology provides new opportunities to sequence full-length cDNAs, avoiding computational challenges that short read transcript assembly brings. The use of single molecule, real-time sequencing from PacBio to sequence transcriptomes (the Iso-Seq method), which produces de novo, high-quality, full-length transcripts, has revealed an astonishing amount of alternative splicing in eukaryotic species. With the Iso-Seq method, it is now possible to reconstruct the transcribed regions of the genome using just the transcripts themselves. We present Cogent, a tool for finding gene families and reconstructing the coding genome in the absence of a high-quality reference genome. Cogent uses k-mer similarities to first partition the transcripts into different gene families. Then, for each gene family, the transcripts are used to build a splice graph. Cogent identifies bubbles resulting from sequencing errors, minor variants, and exon skipping events, and attempts to resolve each splice graph down to the minimal set of reconstructed contigs. We apply Cogent to the Iso-Seq data for spinach, Spinacia oleracea, for which there is also a PacBio-based draft genome to validate the reconstruction. The Iso-Seq dataset consists of 68,263 fulllength, Quiver-polished transcript sequences ranging from 528 bp to 6 kbp long (mean: 2.1 kbp). Using the genome mapping as ground truth, we found that 95% (8045/8446) of the Cogent gene families found corresponded to a single genomic loci. For families that contained multiple loci, they were often homologous genes that would be categorized as belonging to the same gene family. Coding genome reconstruction was then performed individually for each gene family. A total of 86% (7283/8446) of the gene families were resolved to a single contig by Cogent, and was validated to be also a single contig in the genome. In 59 cases, Cogent reconstructed a single contig, however the contig corresponded to 2 or more loci in the genome, suggesting possible scaffolding opportunities. In 24 cases, the transcripts had no hits to the genome, though Pfam and BLAST searches of the transcripts show that they were indeed coding, suggesting that the genome is missing certain coding portions. Given the high quality of the spinach genome, we were not surprised to find that Cogent only minorly improved the genome space. However the ability of Cogent to accurately identify gene families and reconstruct the coding genome in a de novo fashion shows that it will be extremely powerful when applied to datasets for which there is no or low-quality reference genome.