Learn how Single Molecule, Real-Time (SMRT) Sequencing and the Sequel IIe System and will accelerate your research by delivering highly accurate long reads to provide the most comprehensive view of genomes, transcriptomes and epigenomes.
Procedure & Checklist – Preparing HiFi Libraries from Low DNA Input Using SMRTbell Express Template Prep Kit 2.0
Procedure & Checklist – Preparing HiFi SMRTbell Libraries using SMRTbell Express Template Prep Kit 2.0
The Agilent 5200, 5300, and 5400 Fragment Analyzer instruments are fast, high-resolution benchtop capillary electrophoresis (CE) platforms that utilize proprietary markers to accurately size fragments ranging from 10 to 50 kb. This platform allows important DNA quality checkpoints to be completed in one hour for de novo large-genome sequencing projects and other PacBio applications leveraging multi-kilobase read lengths. The instrument can be used in place of time-consuming QC steps involving pulsed field gel electrophoresis (PFGE), saving time by avoiding multiple overnight gel runs when preparing large-insert SMRTbell libraries. Alternative DNA-sizing instruments cannot accurately resolve large DNA fragments in this range.
Interested to learn about pangenomes? Explore this guide to learn how they provide a more complete picture of the core genes of a given species and how that can provide better biological understanding.
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Explore how high-quality genomes contribute to critical scientific endeavors.
PacBio HiFi reads provide both long read lengths (up to 25 kb) and high accuracy (>99.9%) to quickly and affordably generate contiguous, complete, and correct de novo genome assemblies of even the most complex genomes.
Third generation single molecule sequencing technology from Pacific Biosciences, Moleculo, Oxford Nanopore, and other companies are revolutionizing genomics by enabling the sequencing of long, individual molecules of DNA and RNA. One major advantage of these technologies over current short read sequencing is the ability to sequence much longer molecules, thousands or tens of thousands of nucleotides instead of mere hundreds. This capacity gives researchers substantially greater power to probe into microbial, plant, and animal genomes, but it remains unknown on how to best use these data. To answer this, we systematically evaluated the human genome and 25 other important genomes across the tree of life ranging in size from 1Mbp to 3Gbp in an attempt to answer how long the reads need to be and how much coverage is necessary to completely assemble their chromosomes with single molecule sequencing. We also present a novel error correction and assembly algorithm using a combination of PacBio and pre-assembled Illumina sequencing. This new algorithm greatly outperforms other published hybrid algorithms.
SFAF 2014 Presentation Slides: James Gurtowski of Cold Spring Harbor Laboratory (CSHL) shared assembly results for a variety of eukaryotic genomes, including yeast, arabidopsis, and rice.
Generating de novo reference genome assemblies for non-model organisms is a laborious task that often requires a large amount of data from several sequencing platforms and cytogenetic surveys. By using PacBio sequence data and new library creation techniques, we present a de novo, high quality reference assembly for the goat (Capra hircus) that demonstrates a primarily sequencing-based approach to efficiently create new reference assemblies for Eukaryotic species. This goat reference genome was created using 38 million PacBio P5-C3 reads generated from a San Clemente goat using the Celera Assembler PBcR pipeline with PacBio read self-correction. In order to generate the assembly, corrected and filtered reads were pre-assembled into a consensus model using PBDAGCON, and subsequently assembled using the Celera Assembly version 8.2. We generated 5,902 contigs using this method with a contig N50 size of 2.56 megabases. In order to generate chromosome-sized scaffolds, we used the LACHESIS scaffolding method to identify cis-chromosome Hi-C interactions in order to link contigs together. We then compared our new assembly to the existing goat reference assembly to identify large-scale discrepancies. In our comparison, we identified 247 disagreements between the two assemblies consisting of 123 inversions and 124 chromosome-contig relocations. The high quality of this data illustrates how this methodology can be used to efficiently generate new reference genome assemblies without the use of expensive fluorescent cytometry or large quantities of data from multiple sequencing platforms.
The goat (Capra hircus) remains an important livestock species due to the species’ ability to forage and provide milk, meat and wool in arid environments. The current goat reference assembly and annotation borrows heavily from other loosely related livestock species, such as cattle, and may not reflect the unique structural and functional characteristics of the species. We present preliminary data from a new de novo reference assembly for goat that primarily utilizes 38 million PacBio P5-C3 reads generated from an inbred San Clemente goat. This assembly consists of only 5,902 contigs with a contig N50 size of 2.56 megabases which were grouped into scaffolds using cis-chromosome associations generated by the analysis of Hi-C sequence reads. To provide accurate functional genetic annotation, we utilized existing RNA-seq data and generated new data consisting of over 784 million reads from a combination of 27 different developmental timepoints/tissues. This dataset provides a tangible improvement over existing goat genomics resources by correcting over 247 misassemblies in the current goat reference genome and by annotating predicted gene models with actual expressed transcript data. Our goal is to provide a high quality resource to researchers to enable future genomic selection and functional prediction within the field of goat genomics.
Goat is an important source of milk, meat, and fiber, especially in developing countries. An advantage of goats as livestock is the low maintenance requirements and high adaptability compared to other milk producers. The global population of domestic goats exceeds 800 million. In Africa, goat production is characterized by low productivity levels, and attempts to introduce more productive breeds have met with poor success due in part to nutritional constraints. It has been suggested that incorporation of selective breeding within the herds adapted for survival could represent one approach to improving food security across Africa. A recently produced genome assembly of a Chinese Yunnan breed goat, based on 192 Gb of short reads across a range of insert sizes from 180 bp to 20 kb, reported a contig N50 of 18.7 kb. The scaffold N50 was improved from 2.2 Mb to 3.1 Mb by addition of fosmid end sequence, with an estimated 140 million Ns in gaps and 91% coverage. The assembly has proven somewhat problematic for pursuing genome-wide association analysis with SNP arrays, apparently due in part to errors in ordering of markers using the draft genome. In order to provide a higher quality assembly, we sequenced a highly inbred, San Clemente breed goat genome using 458 SMRT cells on the Pacific Biosciences platform. These cells generated 193.5 Gbases of sequence after processing into subreads, with mean 5110 bases and max subread length of 40.5 kb. This sequence data generated an assembly using the recently reported MHAP error correction approach and Celera Assembler v8.2. The contig N50 was 2.5 Mb, with the largest contig spanning 19.5 Mb. Additional characteristics of the assembly will be presented.
Significant advances in bioinformatics tool development have been made to more efficiently leverage and deliver high-quality genome assemblies with PacBio long-read data. Current data throughput of SMRT Sequencing delivers average read lengths ranging from 10-15 kb with the longest reads exceeding 40 kb. This has resulted in consistent demonstration of a minimum 10-fold improvement in genome assemblies with contig N50 in the megabase range compared to assemblies generated using only short- read technologies. This poster highlights recent advances and resources available for advanced bioinformaticians and developers interested in the current state-of-the-art large genome solutions available as open-source code from PacBio and third-party solutions, including HGAP, MHAP, and ECTools. Resources and tools available on GitHub are reviewed, as well as datasets representing major model research organisms made publically available for community evaluation or interested developers.