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June 1, 2021  |  

Full-length isoform sequencing of the human MCF-7 cell line using PacBio long reads.

While advances in RNA sequencing methods have accelerated our understanding of the human transcriptome, isoform discovery remains a challenge because short read lengths require complicated assembly algorithms to infer the contiguity of full-length transcripts. With PacBio’s long reads, one can now sequence full-length transcript isoforms up to 10 kb. The PacBio Iso- Seq protocol produces reads that originate from independent observations of single molecules, meaning no assembly is needed. Here, we sequenced the transcriptome of the human MCF-7 breast cancer cell line using the Clontech SMARTer® cDNA preparation kit and the PacBio RS II. Using PacBio Iso-Seq bioinformatics software, we obtained 55,770 unique, full-length, high-quality transcript sequences that were subsequently mapped back to the human genome with = 99% accuracy. In addition, we identified both known and novel fusion transcripts. To assess our results, we compared the predicted ORFs from the PacBio data against a published mass spectrometry dataset from the same cell line. 84% of the proteins identified with the Uniprot protein database were recovered by the PacBio predictions. Notably, 251 peptides solely matched to the PacBio generated ORFs and were entirely novel, including abundant cases of single amino acid polymorphisms, cassette exon splicing and potential alternative protein coding frames.

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June 1, 2021  |  

A comprehensive lincRNA analysis: From conifers to trees

We have produced an updated annotation of the Norway spruce genome on the basis of an in siliconormalised set of RNA-Seq data obtained from 1,529 samples and comprising 15.5 billion paired-end Illumina HiSeq reads complemented by 18Mbp of PacBio cDNA data (3.2M sequences). In addition to augmenting and refining the previous protein coding gene annotation, here we focus on the addition of long intergenic non-coding RNA (lincRNA) and micro RNA (miRNA) genes. In addition to non-coding loci, our analyses also identified protein coding genes that had been missed by the initial genome annotation and enabled us to update the annotation of existing gene models. In particular, splice variant information, as supported by PacBio sequencing reads, has been added to the current annotation and previously fragmented gene models have been merged by scaffolding disjoint genomic scaffolds on the basis of transcript evidence. Using this refined annotation, a targeted analysis of the lincRNAs enabled their classification as i) deeply conserved, ii) conserved in seed plants iii) gymnosperm/conifer specific. Concurrently, complementary analyses were performed as part of the aspen genome project and the results of a comparative analysis of the lincRNAs conserved in both Norway spruce and Eurasian aspen enabled us to identify conserved and diverged expression profiles. At present, we are delving further into the expression results with the aim to functionally annotate the lincRNA genes, by developing a co-expression network analyses based GO annotation.

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June 1, 2021  |  

Characterizing haplotype diversity at the immunoglobulin heavy chain locus across human populations using novel long-read sequencing and assembly approaches

The human immunoglobulin heavy chain locus (IGH) remains among the most understudied regions of the human genome. Recent efforts have shown that haplotype diversity within IGH is elevated and exhibits population specific patterns; for example, our re-sequencing of the locus from only a single chromosome uncovered >100 Kb of novel sequence, including descriptions of six novel alleles, and four previously unmapped genes. Historically, this complex locus architecture has hindered the characterization of IGH germline single nucleotide, copy number, and structural variants (SNVs; CNVs; SVs), and as a result, there remains little known about the role of IGH polymorphisms in inter-individual antibody repertoire variability and disease. To remedy this, we are taking a multi-faceted approach to improving existing genomic resources in the human IGH region. First, from whole-genome and fosmid-based datasets, we are building the largest and most ethnically diverse set of IGH reference assemblies to date, by employing PacBio long-read sequencing combined with novel algorithms for phased haplotype assembly. In total, our effort will result in the characterization of >15 phased haplotypes from individuals of Asian, African, and European descent, to be used as a representative reference set by the genomics and immunogenetics community. Second, we are utilizing this more comprehensive sequence catalogue to inform the design and analysis of novel targeted IGH genotyping assays. Standard targeted DNA enrichment methods (e.g., exome capture) are currently optimized for the capture of only very short (100’s of bp) DNA segments. Our platform uses a modified bench protocol to pair existing capture-array technologies with the enrichment of longer fragments of DNA, enabling the use of PacBio sequencing of DNA segments up to 7 Kb. This substantial increase in contiguity disambiguates many of the complex repeated structures inherent to the locus, while yielding the base pair fidelity required to call SNVs. Together these resources will establish a stronger framework for further characterizing IGH genetic diversity and facilitate IGH genomic profiling in the clinical and research settings, which will be key to fully understanding the role of IGH germline variation in antibody repertoire development and disease.

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June 1, 2021  |  

From RNA to full-length transcripts: The PacBio Iso-Seq method for transcriptome analysis and genome annotation

A single gene may encode a surprising number of proteins, each with a distinct biological function. This is especially true in complex eukaryotes. Short- read RNA sequencing (RNA-seq) works by physically shearing transcript isoforms into smaller pieces and bioinformatically reassembling them, leaving opportunity for misassembly or incomplete capture of the full diversity of isoforms from genes of interest. The PacBio Isoform Sequencing (Iso-Seq™) method employs long reads to sequence transcript isoforms from the 5’ end to their poly-A tails, eliminating the need for transcript reconstruction and inference. These long reads result in complete, unambiguous information about alternatively spliced exons, transcriptional start sites, and poly- adenylation sites. This allows for the characterization of the full complement of isoforms within targeted genes, or across an entire transcriptome. Here we present improved genome annotations for two avian models of vocal learning, Anna’s hummingbird (Calypte anna) and zebra finch (Taeniopygia guttata), using the Iso-Seq method. We present graphical user interface and command line analysis workflows for the data sets. From brain total RNA, we characterize more than 15,000 isoforms in each species, 9% and 5% of which were previously unannotated in hummingbird and zebra finch, respectively. We highlight one example where capturing full-length transcripts identifies additional exons and UTRs.

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June 1, 2021  |  

Full-length transcript profiling with the Iso-Seq method for improved genome annotations

Incomplete annotation of genomes represents a major impediment to understanding biological processes, functional differences between species, and evolutionary mechanisms. Often, genes that are large, embedded within duplicated genomic regions, or associated with repeats are difficult to study by short-read expression profiling and assembly. In addition, most genes in eukaryotic organisms produce alternatively spliced isoforms, broadening the diversity of proteins encoded by the genome, which are difficult to resolve with short-read methods. Short-read RNA sequencing (RNA-seq) works by physically shearing transcript isoforms into smaller pieces and bioinformatically reassembling them, leaving opportunity for misassembly or incomplete capture of the full diversity of isoforms from genes of interest. In contrast, Single Molecule, Real-Time (SMRT) Sequencing directly sequences full-length transcripts without the need for assembly and imputation. Here we apply the Iso-Seq method (long-read RNA sequencing) to detect full-length isoforms and the new IsoPhase algorithm to retrieve allele-specific isoform information for two avian models of vocal learning, Anna’s hummingbird (Calypte anna) and zebra finch (Taeniopygia guttata).

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June 1, 2021  |  

Scalability and reliability improvements to the Iso-Seq analysis pipeline enables higher throughput sequencing of full-length cancer transcripts

The characterization of gene expression profiles via transcriptome sequencing has proven to be an important tool for characterizing how genomic rearrangements in cancer affect the biological pathways involved in cancer progression and treatment response. More recently, better resolution of transcript isoforms has shown that this additional level of information may be useful in stratifying patients into cancer subtypes with different outcomes and responses to treatment.1 The Iso-Seq protocol developed at PacBio is uniquely able to deliver full-length, high-quality cDNA sequences, allowing the unambiguous determination of splice variants, identifying potential biomarkers and yielding new insights into gene fusion events. Recent improvements to the Iso-Seq bioinformatics pipeline increases the speed and scalability of data analysis while boosting the reliability of isoform detection and cross-platform usability. Here we report evaluation of Sequel Iso-Seq runs of human UHRR samples with spiked-in synthetic RNA controls and show that the new pipeline is more CPU efficient and recovers more human and synthetic isoforms while reducing the number of false positives. We also share the results of sequencing the well-characterized HCC-1954 breast cancer and normal breast cell lines, which will be made publicly available. Combined with the recent simplification of the Iso-Seq sample preparation2, the new analysis pipeline completes a streamlined workflow for revealing the most comprehensive picture of transcriptomes at the throughput needed to characterize cancer samples.

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