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June 1, 2021  |  

MaSuRCA Mega-Reads Assembly Technique for haplotype resolved genome assembly of hybrid PacBio and Illumina Data

The developments in DNA sequencing technology over the past several years have enabled large number of scientists to obtain sequences for the genomes of their interest at a fairly low cost. Illumina Sequencing was the dominant whole genome sequencing technology over the past few years due to its low cost. The Illumina reads are short (up to 300bp) and thus most of those draft genomes produced from Illumina data are very fragmented which limits their usability in practical scenarios. Longer reads are needed for more contiguous genomes. Recently Pacbio sequencing made significant advances in developing cost-effective long-read (>10000bp) sequencing technology and their data, although several times more expensive than Illumina, can be used to produce high quality genomes. Pacbio data can be used for de novo assembly, however due to its high error rate high coverage of the genome is required this raising the cost barrier. A solution for cost-effective genomes is to combine Pacbio and Illumina data leveraging the low error rates of the short Illumina reads and the length of the Pacbio reads. We have developed MaSuRCA mega-reads assembler for efficient assembly of hybrid data sets and we demonstrate that it performs well compared to the other published hybrid techniques. Another important benefit of the long reads is their ability to link the haplotype differences. The mega-reads approach corrects each Pacbio read independently and thus haplotype differences are preserved. Thus, leveraging the accuracy of the Illumina data and the length of the Pacbio reads, MaSuRCA mega-reads can produce haplotype-resolved genome assemblies, where each contig has sequence from a single haplotype. We present preliminary results on haplotype-resolved genome assemblies of faux (proof-of-concept) and real data.

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June 1, 2021  |  

Diploid genome assembly and comprehensive haplotype sequence reconstruction

Outside of the simplest cases (haploid, bacteria, or inbreds), genomic information is not carried in a single reference per individual, but rather has higher ploidy (n=>2) for almost all organisms. The existence of two or more highly related sequences within an individual makes it extremely difficult to build high quality, highly contiguous genome assemblies from short DNA fragments. Based on the earlier work on a polyploidy aware assembler, FALCON ( https://github.com/PacificBiosciences/FALCON) , we developed new algorithms and software (“FALCON-unzip”) for de novo haplotype reconstructions from SMRT Sequencing data. We generate two datasets for developing the algorithms and the prototype software: (1) whole genome sequencing data from a highly repetitive diploid fungal (Clavicorona pyxidata) and (2) whole genome sequencing data from an F1 hybrid from two inbred Arabidopsis strains: Cvi-0 and Col-0. For the fungal genome, we achieved an N50 of 1.53 Mb (of the 1n assembly contigs) of the ~42 Mb 1n genome and an N50 of the haplotigs (haplotype specific contigs) of 872 kb from a 95X read length N50 ~16 kb dataset. We found that ~ 45% of the genome was highly heterozygous and ~55% of the genome was highly homozygous. We developed methods to assess the base-level accuracy and local haplotype phasing accuracy of the assembly with short-read data from the Illumina® platform. For the ArabidopsisF1 hybrid genome, we found that 80% of the genome could be separated into haplotigs. The long range accuracy of phasing haplotigs was evaluated by comparing them to the assemblies from the two inbred parental lines. We show that a more complete view of all haplotypes could provide useful biological insights through improved annotation, characterization of heterozygous variants of all sizes, and resolution of differential allele expression. The current Falcon-Unzip method will lead to understand how to solve more difficult polyploid genome assembly problems and improve the computational efficiency for large genome assemblies. Based on this work, we can develop a pipeline enabling routinely assemble diploid or polyploid genomes as haplotigs, representing a comprehensive view of the genomes that can be studied with the information at hand.

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June 1, 2021  |  

Minimization of chimera formation and substitution errors in full-length 16S PCR amplification

The constituents and intra-communal interactions of microbial populations have garnered increasing interest in areas such as water remediation, agriculture and human health. One popular, efficient method of profiling communities is to amplify and sequence the evolutionarily conserved 16S rRNA sequence. Currently, most targeted amplification focuses on short, hypervariable regions of the 16S sequence. Distinguishing information not spanned by the targeted region is lost and species-level classification is often not possible. SMRT Sequencing easily spans the entire 1.5 kb 16S gene, and in combination with highly-accurate single-molecule sequences, can improve the identification of individual species in a metapopulation. However, when amplifying a mixture of sequences with close similarities, the products may contain chimeras, or recombinant molecules, at rates as high as 20-30%. These PCR artifacts make it difficult to identify novel species, and reduce the amount of productive sequences. We investigated multiple factors that have been hypothesized to contribute to chimera formation, such as template damage, denaturing time before and during cycling, polymerase extension time, and reaction volume. Of the factors tested, we found two major related contributors to chimera formation: the amount of input template into the PCR reaction and the number of PCR cycles. Sequence errors generated during amplification and sequencing can also confound the analysis of complex populations. Circular Consensus Sequencing (CCS) can generate single-molecule reads with >99% accuracy, and the SMRT Analysis software provides filtering of these reads to >99.99% accuracies. Remaining substitution errors in these highly-filtered reads are likely dominated by mis-incorporations during amplification. Therefore, we compared the impact of several commercially-available high-fidelity PCR kits with full-length 16S amplification. We show results of our experiments and describe an optimized protocol for full-length 16S amplification for SMRT Sequencing. These optimizations have broader implications for other applications that use PCR amplification to phase variations across targeted regions and to generate highly accurate reference sequences.

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June 1, 2021  |  

Minimization of chimera formation and substitution errors in full-length 16S PCR amplification

The constituents and intra-communal interactions of microbial populations have garnered increasing interest in areas such as water remediation, agriculture and human health. Amplification and sequencing of the evolutionarily conserved 16S rRNA gene is an efficient method of profiling communities. Currently, most targeted amplification focuses on short, hypervariable regions of the 16S sequence. Distinguishing information not spanned by the targeted region is lost, and species-level classification is often not possible. PacBio SMRT Sequencing easily spans the entire 1.5 kb 16S gene in a single read, producing highly accurate single-molecule sequences that can improve the identification of individual species in a metapopulation.However, this process still relies upon PCR amplification from a mixture of similar sequences, which may result in chimeras, or recombinant molecules, at rates upwards of 20%. These PCR artifacts make it difficult to identify novel species, and reduce the amount of informative sequences. We investigated multiple factors that may contribute to chimera formation, such as template damage, denaturation time before and during thermocycling, polymerase extension time, and reaction volume. We found two related factors that contribute to chimera formation: the amount of input template into the PCR reaction, and the number of PCR cycles.A second problem that can confound analysis is sequence errors generated during amplification and sequencing. With the updated algorithm for circular consensus sequencing (CCS2), single-molecule reads can be filtered to 99.99% predicted accuracy. Substitution errors in these highly filtered reads may be dominated by mis-incorporations during amplification. Sequence differences in full-length 16S amplicons from several commercial high-fidelity PCR kits were compared.We show results of our experiments and describe our optimized protocol for full-length 16S amplification for SMRT Sequencing. These optimizations have broader implications for other applications that use PCR amplification to phase variations across targeted regions and generate highly accurate reference sequences.

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June 1, 2021  |  

Haplotyping of full-length transcript reads from long-read sequencing can reveal allelic imbalances in isoform expression

The Pacific Biosciences Iso-Seq method, which can produce high-quality isoform sequences of 10 kb and longer, has been used to annotate many important plant and animal genomes. Here, we develop an algorithm called IsoPhase that postprocesses Iso-Seq data to retrieve allele specific isoform information. Using simulated data, we show that for both diploid and tetraploid genomes, IsoPhase results in good SNP recovery with low FDR at error rates consistent with CCS reads. We apply IsoPhase to a haplotyperesolved genome assembly and multiple fetal tissue Iso-Seq dataset from a F1 cross of Angus x Brahman cattle subspecies. IsoPhase-called haplotypes were validated by the phased assembly and demonstrate the potential for revealing allelic imbalances in isoform expression.

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June 1, 2021  |  

Comparison of sequencing approaches applied to complex soil metagenomes to resolve proteins of interest

Background: Long-read sequencing presents several potential advantages for providing more complete gene profiling of metagenomic samples. Long reads can capture multiple genes in a single read, and longer reads typically result in assemblies with better contiguity, especially for higher abundance organisms. However, a major challenge with using long reads has been the higher cost per base, which may lead to insufficient coverage of low-abundance species. Additionally, lower single-pass accuracy can make gene discovery for low-abundance organisms difficult. Methods: To evaluate the pros and cons of long reads for metagenomics, we directly compared PacBio and Illumina sequencing on a soil-derived sample, which included spike-in controls of known concentrations of pure referenced samples. For PacBio sequencing, a 10 kb library was sequenced on the Sequel System with 3.0 chemistry. Highly accurate long reads (HiFi reads) with Q20 and higher were generated for downstream analyses using PacBio Circular Consensus Sequencing (CCS) mode. Results were assessed according to the following criteria: DNA extraction capacity, bioinformatics pipeline status, % of proteins with ambiguous AA’s, total unique error-free genes/$1000, total proteins observed in spike-ins/$1000, proteins of interest/$1000, median length of contigs with proteins, and assembly requirements. Results: Both methods had areas of superior performance. DNA extraction capacity was higher for Illumina, the bioinformatics pipeline is well-tested, and there was a lower proportion of proteins with ambiguous AA’s. On the other hand, with PacBio, twice as many unique error-free genes, twice as many total proteins from spike-ins, and ~6 times more proteins of interest were found per $1000 cost. PacBio data produced on average 5 times longer contigs capturing proteins of interest. Additionally, assembly was not required for gene or protein finding, as was the case with Illumina data. Conclusions: In this comparison of PacBio Sequel System with Illumina NextSeq on a complex microbiome, we conclude that the sequencing system of choice may vary, depending on the goals and resources for the project. PacBio sequencing requires a longer DNA extraction method, and the bioinformatics pipeline may require development. On the other hand, the Sequel System generates hundreds of thousands of long HiFi reads per SMRT Cell, producing more genes, more proteins, and longer contigs, thereby offering more information about the metagenomic samples for a lower cost.

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June 1, 2021  |  

Beyond Contiguity: Evaluating the accuracy of de novo genome assemblies

HiFi reads (>99% accurate, 15-20 kb) from the PacBio Sequel II System consistently provide complete and contiguous genome assemblies. In addition to completeness and contiguity, accuracy is of critical importance, as assembly errors complicate downstream analysis, particularly by disrupting gene frames. Metrics used to assess assembly accuracy include: 1) in-frame gene count, 2) kmer consistency, and 3) concordance to a benchmark, where discordances are interpreted as assembly errors. Genome in a Bottle (GIAB) provides a benchmark for the human genome with estimated accuracy of 99.9999% (Q60). Concordance for human HiFi assemblies exceeds Q50, which provides excellent genomes for downstream analysis, but presents a challenge that any new benchmark must significantly exceed Q50 or the discordance will represent the error rate of the benchmark. To establish benchmarks for Oryza sativa and Drosophila melanogaster, we collected draft references, Illumina short reads, and PacBio HiFi reads. By species, the benchmark was defined as regions of normal coverage that are not within 5 bp of a small variant or 50 bp of a structural variant. For both species, the benchmark regions span around 60% of the genome and HiFi assemblies achieve Q50 accuracy, which is notably more accurate than assemblies with other technologies and meets typical standards for a finished, reference-grade assembly. Here we present a protocol to generate benchmarks for any sample that rival the GIAB benchmark in accuracy. These benchmarks allow the comparison and improvement of genome assemblies and highlight the superior accuracy of assemblies generated with PacBio HiFi reads.

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June 1, 2021  |  

Comprehensive variant detection in a human genome with highly accurate long reads

Introduction: Long-read sequencing has been applied successfully to assemble genomes and detect structural variants. However, due to high raw-read error rates (10-15%), it has remained difficult to call small variants from long reads. Recent improvements in library preparation and sequencing chemistry have increased length, accuracy, and throughput of PacBio circular consensus sequencing (CCS) reads, resulting in 15-20kb reads with average read quality above 99%. Materials and Methods: We sequenced a library from human reference sample HG002 to 18-fold coverage on the PacBio Sequel II with two SMRT Cells 8M. The CCS algorithm was used to generate highly accurate (average 99.9%) 12.9kb reads, which were mapped to the hg19 reference with pbmm2. We detected small variants using Google DeepVariant with a model trained for CCS and phased the variants using WhatsHap. Structural variants were detected with pbsv. Variant calls were evaluated against Genome in a Bottle (GIAB) benchmarks. Results: With these reads, DeepVariant achieves SNP and Indel F1 scores of 99.70% and 96.59% against the GIAB truth set, and pbsv achieves 97.72% recall on structural variants longer than 50bp. Using WhatsHap, small variants were phased into haplotype blocks with 145kb N50. The improved mappability of long reads allows us to align to and detect variants in medically relevant genes such as CYP2D6 and PMS2 that have proven “difficult-to-map” with short reads. Conclusions: These highly accurate long reads combine the mappability and ability to detect structural variants of long reads with the accuracy and ability to detect small variants of short reads.

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April 21, 2020  |  

Tandem repeats lead to sequence assembly errors and impose multi-level challenges for genome and protein databases.

The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with ‘ready-to-use’ deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.

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