June 1, 2021  |  

Using whole exome sequencing and bacterial pathogen sequencing to investigate the genetic basis of pulmonary non-tuberculous mycobacterial infections.

Pulmonary non-tuberculous mycobacterial (PNTM) infections occur in patients with chronic lung disease, but also in a distinct group of elderly women without lung defects who share a common body morphology: tall and lean with scoliosis, pectus excavatum, and mitral valve prolapse. In order to characterize the human host susceptibility to PNTM, we performed whole exome sequencing (WES) of 44 individuals in extended families of patients with active PNTM as well as 55 additional unrelated individuals with PNTM. This unique collection of familial cohorts in PNTM represents an important opportunity for a high yield search for genes that regulate mucosal immunity. An average of 58 million 100bp paired-end Illumina reads per exome were generated and mapped to the hg19 reference genome. Following variant detection and classification, we identified 58,422 potentially high-impact SNPs, 97.3% of which were missense mutations. Segregating variants using the family pedigrees as well as comparisons to the unrelated individuals identified multiple potential variants associated with PNTM. Validations of these candidate variants in a larger PNTM cohort are underway. In addition to WES, we sequenced the genomes of 52 mycobacterial isolates, including 9 from these PNTM patients, to integrate host PNTM susceptibility with mycobacterial genotypes and gain insights into the key factors involved in this devastating disease. These genomes were sequenced using a combination of 454, Illumina, and PacBio platforms and assembled using multiple genome assemblers. The resulting genome sequences were used to identify mycobacterial genotypes associated with virulence, invasion, and drug resistance.


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.


June 1, 2021  |  

Analysis of full-length metagenomic 16S genes by Single Molecule, Real-Time Sequencing

High-throughput sequencing of the complete 16S rRNA gene has become a valuable tool for characterizing microbial communities. However, the short reads produced by second-generation sequencing cannot provide taxonomic classification below the genus level. In this study, we demonstrate the capability of PacBio’s Single Molecule, Real-Time (SMRT) Sequencing to generate community profiles using mock microbial community samples from BEI Resources. We also evaluate multiplexing capabilities using PacBio barcodes on pooled samples comprising heterogeneous 16S amplicon populations representing soil, fecal, and mock communities.


June 1, 2021  |  

How to Compare and Cluster Every Known Genome in about an Hour

Given a massive collection of sequences, it is infeasible to perform pairwise alignment for basic tasks like sequence clustering and search. To address this problem, we demonstrate that the MinHash technique, first applied to clustering web pages, can be applied to biological sequences with similar effect, and extend this idea to include biologically relevant distance and significance measures. Our new tool, Mash, uses MinHash locality-sensitive hashing to reduce large sequences to a representative sketch and rapidly estimate pairwise distances between genomes or metagenomes. Using Mash, we explored several use cases, including a 5,000-fold size reduction and clustering of all 55,000 NCBI RefSeq genomes in 46 CPU hours. The resulting 93 MB sketch database includes all RefSeq genomes, effectively delineates known species boundaries, reconstructs approximate phylogenies, and can be searched in seconds using assembled genomes or raw sequencing runs from Illumina, Pacific Biosciences, and Oxford Nanopore. For metagenomics, Mash scales to thousands of samples and can replicate Human Microbiome Project and Global Ocean Survey results in a fraction of the time. Other potential applications include any problem where an approximate, global sequence distance is acceptable, e.g. to triage and cluster sequence data, assign species labels to unknown genomes, quickly identify mis- tracked samples, and search massive genomic databases. In addition, the Mash distance metric is based on simple set intersections, which are compatible with homomorphic encryption schemes. To facilitate integration with other software, Mash is implemented as a lightweight C++ toolkit and freely released under a BSD license athttps://github.com/marbl/mash


June 1, 2021  |  

Immune regions are no longer incomprehensible with SMRT Sequencing

The complex immune regions of the genome, including MHC and KIR, contain large copy number variants (CNVs), a high density of genes, hyper-polymorphic gene alleles, and conserved extended haplotypes (CEH) with enormous linkage disequilibrium (LDs). This level of complexity and inherent biases of short-read sequencing make it challenging for extracting immune region haplotype information from reference-reliant, shotgun sequencing and GWAS methods. As NGS based genome and exome sequencing and SNP arrays have become a routine for population studies, numerous efforts are being made for developing software to extract and or impute the immune gene information from these datasets. Despite these efforts, the fine mapping of causal variants of immune genes for their well-documented association with cancer, drug-induced hypersensitivity and immune-related diseases, has been slower than expected. This has in many ways limited our understanding of the mechanisms leading to immune disease. In the present work, we demonstrate the advantages of long reads delivered by SMRT Sequencing for assembling complete haplotypes of MHC and KIR gene clusters, as well as calling correct genotypes of genes comprised within them. All the genotype information is detected at allele- level with full phasing information across SNP-poor regions. Genotypes were called correctly from targeted gene amplicons, haplotypes, as well as from a completely assembled 5 Mb contig of the MHC region from a de novo assembly of whole genome shotgun data. De novo analysis pipeline used in all these approaches allowed for reference-free analysis without imputation, a key for interrogation without prior knowledge about ethnic backgrounds. These methods are thus easily adoptable for previously uncharacterized human or non-human species.


June 1, 2021  |  

The MHC Diversity in Africa Project (MDAP) pilot – 125 African high resolution HLA types from 5 populations

The major histocompatibility complex (MHC), or human leukocyte antigen (HLA) in humans, is a highly diverse gene family with a key role in immune response to disease; and has been implicated in auto-immune disease, cancer, infectious disease susceptibility, and vaccine response. It has clinical importance in the field of solid organ and bone marrow transplantation, where donors and recipient matching of HLA types is key to transplanted organ outcomes. The Sanger based typing (SBT) methods currently used in clinical practice do not capture the full diversity across this region, and require specific reference sequences to deconvolute ambiguity in HLA types. However, reference databases are based largely on European populations, and the full extent of diversity in Africa remains poorly understood. Here, we present the first systematic characterisation of HLA diversity within Africa in the pilot phase of the MHC Diversity in Africa Project, together with an evaluation of methods to carry out scalable cost-effective, as well as reliable, typing of this region in African populations.To sample a geographically representative panel of African populations we obtained 125 samples, 25 each from the Zulu (South Africa), Igbo (Nigeria), Kalenjin (Kenya), Moroccan and Ashanti (Ghana) groups. For methods validation we included two controls from the International Histocompatibility Working Group (IHWG) collection with known typing information. Sanger typing and Illumina HiSeq X sequencing of these samples indicated potentially novel Class I and Class II alleles; however, we found poor correlation between HiSeq X sequencing and SBT for both classes. Long Range PCR and high resolution PacBio RS-II typing of 4 of these samples identified 7 novel Class II alleles, highlighting the high levels of diversity in these populations, and the need for long read sequencing approaches to characterise this comprehensively. We have now expanded this approach to the entire pilot set of 125 samples. We present these confirmed types and discuss a workflow for scaling this to 5000 individuals across Africa.The large number of new alleles identified in our pilot suggests the high level of African HLA diversity and the utility of high resolution methods. The MDAP project will provide a framework for accurate HLA typing, in addition to providing an invaluable resource for imputation in GWAS, boosting power to identify and resolve HLA disease associations.


June 1, 2021  |  

Using the PacBio IsoSeq method to search for novel colorectal cancer biomarkers

Early detection of colorectal cancer (CRC) and its precursor lesions (adenomas) is crucial to reduce mortality rates. The fecal immunochemical test (FIT) is a non-invasive CRC screening test that detects the blood-derived protein hemoglobin. However, FIT sensitivity is suboptimal especially in detection of CRC precursor lesions. As adenoma-to-carcinoma progression is accompanied by alternative splicing, tumor-specific proteins derived from alternatively spliced RNA transcripts might serve as candidate biomarkers for CRC detection.


June 1, 2021  |  

Joint calling and PacBio SMRT Sequencing for indel and structural variant detection in populations

Fast and effective variant calling algorithms have been crucial to the successful application of DNA sequencing in human genetics. In particular, joint calling – in which reads from multiple individuals are pooled to increase power for shared variants – is an important tool for population surveys of variation. Joint calling was applied by the 1000 Genomes Project to identify variants across many individuals each sequenced to low coverage (about 5-fold). This approach successfully found common small variants, but broadly missed structural variants and large indels for which short-read sequencing has limited sensitivity. To support use of large variants in rare disease and common trait association studies, it is necessary to perform population-scale surveys with a technology effective at detecting indels and structural variants, such as PacBio SMRT Sequencing. For these studies, it is important to have a joint calling workflow that works with PacBio reads. We have developed pbsv, an indel and structural variant caller for PacBio reads, that provides a two-step joint calling workflow similar to that used to build the ExAC database. The first stage, discovery, is performed separately for each sample and consolidates whole genome alignments into a sparse representation of potentially variant loci. The second stage, calling, is performed on all samples together and considers only the signatures identified in the discovery stage. We applied the pbsv joint calling workflow to PacBio reads from twenty human genomes, with coverage ranging from 5-fold to 80-fold per sample for a total of 460-fold. The analysis required only 102 CPU hours, and identified over 800,000 indels and structural variants, including hundreds of inversions and translocations, many times more than discovered with short-read sequencing. The workflow is scalable to thousands of samples. The ongoing application of this workflow to thousands of samples will provide insight into the evolution and functional importance of large variants in human evolution and disease.


June 1, 2021  |  

Microbiome profiling at the strain level using rRNA amplicons

Strain level microbiome profiling is needed for a full understanding of how microbial communities influence human health. Microbiome profiling of rRNA gene amplicons is a well-understood method that is rapid and inexpensive, but standard 16S rRNA gene methods generally cannot differentiate closely related strains. Whole genome/shotgun microbiome profiling is considered a higher-resolution alternative, but with decreased throughput and significantly increased sequencing costs and analysis burden. With both methods there are also challenges with microbial lysis, DNA preparation, and taxonomic analysis. Specialized microbiome-focused protocols were developed to achieve strain-level taxonomic differentiation using a rapid, high throughput rRNA gene assay. The protocol integrates lysis and DNA preparation improvements with a unique high information content amplicon and associated novel database to enable taxonomic differentiation of closely related microbial strains.


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