Mark Chaisson

STAR: ultrafast universal RNA-seq aligner

MOTIVATION Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. RESULTS To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. AVAILABILITY AND IMPLEMENTATION STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

An integrated map of structural variation in 2,504 human genomes

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.

Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory

BackgroundRecent methods have been developed to perform high-throughput sequencing of DNA by Single Molecule Sequencing (SMS). While Next-Generation sequencing methods may produce reads up to several hundred bases long, SMS sequencing produces reads up to tens of kilobases long. Existing alignment methods are either too inefficient for high-throughput datasets, or not sensitive enough to align SMS reads, which have a higher error rate than Next-Generation sequencing.ResultsWe describe the method BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands of bases long, with divergence between the read and genome dominated by insertion and deletion error. The method is benchmarked using both simulated reads and reads from a bacterial sequencing project. We also present a combinatorial model of sequencing error that motivates why our approach is effective.ConclusionsThe results indicate that it is possible to map SMS reads with high accuracy and speed. Furthermore, the inferences made on the mapability of SMS reads using our combinatorial model of sequencing error are in agreement with the mapping accuracy demonstrated on simulated reads.

Fragment assembly with short reads

MOTIVATION Current DNA sequencing technology produces reads of about 500-750 bp, with typical coverage under 10x. New sequencing technologies are emerging that produce shorter reads (length 80-200 bp) but allow one to generate significantly higher coverage (30x and higher) at low cost. Modern assembly programs and error correction routines have been tuned to work well with current read technology but were not designed for assembly of short reads. RESULTS We analyze the limitations of assembling reads generated by these new technologies and present a routine for base-calling in reads prior to their assembly. We demonstrate that while it is feasible to assemble such short reads, the resulting contigs will require significant (if not prohibitive) finishing efforts. AVAILABILITY Available from the web at http://www.cse.ucsd.edu/groups/bioinformatics/software.html

Reconstructing complex regions of genomes using long-read sequencing technology

Obtaining high-quality sequence continuity of complex regions of recent segmental duplication remains one of the major challenges of finishing genome assemblies. In the human and mouse genomes, this was achieved by targeting large-insert clones using costly and laborious capillary-based sequencing approaches. Sanger shotgun sequencing of clone inserts, however, has now been largely abandoned, leaving most of these regions unresolved in newer genome assemblies generated primarily by next-generation sequencing hybrid approaches. Here we show that it is possible to resolve regions that are complex in a genome-wide context but simple in isolation for a fraction of the time and cost of traditional methods using long-read single molecule, real-time (SMRT) sequencing and assembly technology from Pacific Biosciences (PacBio). We sequenced and assembled BAC clones corresponding to a 1.3-Mbp complex region of chromosome 17q21.31, demonstrating 99.994% identity to Sanger assemblies of the same clones. We targeted 44 differences using Illumina sequencing and find that PacBio and Sanger assemblies share a comparable number of validated variants, albeit with different sequence context biases. Finally, we targeted a poorly assembled 766-kbp duplicated region of the chimpanzee genome and resolved the structure and organization for a fraction of the cost and time of traditional finishing approaches. Our data suggest a straightforward path for upgrading genomes to a higher quality finished state.

Genetic variation and the de novo assembly of human genomes

The discovery of genetic variation and the assembly of genome sequences are both inextricably linked to advances in DNA-sequencing technology. Short-read massively parallel sequencing has revolutionized our ability to discover genetic variation but is insufficient to generate high-quality genome assemblies or resolve most structural variation. Full resolution of variation is only guaranteed by complete de novo assembly of a genome. Here, we review approaches to genome assembly, the nature of gaps or missing sequences, and biases in the assembly process. We describe the challenges of generating a complete de novo genome assembly using current technologies and the impact that being able to perfectly sequence the genome would have on understanding human disease and evolution. Finally, we summarize recent technological advances that improve both contiguity and accuracy and emphasize the importance of complete de novo assembly as opposed to read mapping as the primary means to understanding the full range of human genetic variation.

Long-read sequence assembly of the gorilla genome

Improving on the gorilla genome Access to complete, high-quality genomes of nonhuman primates will also help us understand human biology. Gordon et al. used long-read sequencing technology to improve genome data on our close relative the gorilla. Sequencing from a single individual decreased assembly fragmentation and recovered previously missed genes and noncoding loci. Mapping short-read sequences from additional gorillas helped reconstruct a “pan” gorilla sequence documenting genetic variation. Comparison with human genomes revealed species-specific differences ranging in size from one to thousands of bases in length, including some that are likely to affect gene regulation. Science, this issue p. 10.1126/science.aae0344 A new approach to looking at the gorilla genome improves estimates of the differences between humans and gorillas. INTRODUCTION The accurate sequence and assembly of genomes is critical to our understanding of evolution and genetic variation. Despite advances in short-read sequencing technology that have decreased cost and increased throughput, whole-genome assembly of mammalian genomes remains problematic because of the presence of repetitive DNA. RATIONALE The goal of this study was to sequence and assemble the genome of the western lowland gorilla by using primarily single-molecule, real-time (SMRT) sequencing technology and a novel assembly algorithm that takes advantage of long (>10 kbp) sequence reads. We specifically compare the properties of this assembly to gorilla genome assemblies that were generated by using more routine short sequence read approaches in order to determine the value and biological impact of a long-read genome assembly. RESULTS We generated 74.8-fold SMRT whole-genome shotgun sequence from peripheral blood DNA isolated from a western lowland gorilla (Gorilla gorilla gorilla) named Susie. We applied a string graph assembly algorithm, Falcon, and consensus algorithm, Quiver, to generate a 3.1-Gbp assembly with a contig N50 of 9.6 Mbp. Short-read sequence data from an additional six gorilla genomes was mapped so as to reduce indel errors and improve the accuracy of the final assembly. We estimate that 98.9% of the gorilla euchromatin has been assembled into 1854 sequence contigs. The assembly represents an improvement in contiguity: >800-fold with respect to the published gorilla genome assembly and >180-fold with respect to a more recently released upgrade of the gorilla assembly. Most of the sequence gaps are now closed, considerably increasing the yield of complete gene models. We estimate that 87% of the missing exons and 94% of the incomplete genes are recovered. We find that the sequence of most full-length common repeats is resolved, with the most significant gains occurring for the longest and most G+C–rich retrotransposons. Although complex regions such as the major histocompatibility locus are accurately sequenced and assembled, both heterochromatin and large, high-identity segmental duplications are not because read lengths are insufficiently long to traverse these repetitive structures. The long-read assembly produces a much finer map of structural variation down to 50 bp in length, facilitating the discovery of thousands of lineage-specific structural variant differences that have occurred since divergence from the human and chimpanzee lineages. This includes the disruption of specific genes and loss of predicted regulatory regions between the two species. We show that use of the new gorilla genome assembly changes estimates of divergence and diversity, resulting in subtle but substantial effects on previous population genetic inferences, such as the timing of species bottlenecks and changes in the effective population size over the course of evolution. CONCLUSION The genome assembly that results from using the long-read data provides a more complete picture of gene content, structural variation, and repeat biology, improving population genetic and evolutionary inferences. Long-read sequencing technology now makes it practical for individual laboratories to generate high-quality reference genomes for complex mammalian genomes. Long-read sequence assembly of the gorilla genome. (A) Susie, a female Western lowland gorilla, was used as the reference sample for full-genome sequencing and assembly [photograph courtesy of Max Block]. (B and C) A treemaps representing the differences in fragmentation of the long-read and short-read gorilla genome assemblies. The rectangles are the largest contigs that cumulatively make up 300 Mbp (~10%) of the assembly. Accurate sequence and assembly of genomes is a critical first step for studies of genetic variation. We generated a high-quality assembly of the gorilla genome using single-molecule, real-time sequence technology and a string graph de novo assembly algorithm. The new assembly improves contiguity by two to three orders of magnitude with respect to previously released assemblies, recovering 87% of missing reference exons and incomplete gene models. Although regions of large, high-identity segmental duplications remain largely unresolved, this comprehensive assembly provides new biological insight into genetic diversity, structural variation, gene loss, and representation of repeat structures within the gorilla genome. The approach provides a path forward for the routine assembly of mammalian genomes at a level approaching that of the current quality of the human genome.

Extensive sequencing of seven human genomes to characterize benchmark reference materials.

The Genome in a Bottle Consortium, hosted by the National Institute of Standards and Technology (NIST) is creating reference materials and data for human genome sequencing, as well as methods for genome comparison and benchmarking. Here, we describe a large, diverse set of sequencing data for seven human genomes; five are current or candidate NIST Reference Materials. The pilot genome, NA12878, has been released as NIST RM 8398. We also describe data from two Personal Genome Project trios, one of Ashkenazim Jewish ancestry and one of Chinese ancestry. The data come from 12 technologies: BioNano Genomics, Complete Genomics paired-end and LFR, Ion Proton exome, Oxford Nanopore, Pacific Biosciences, SOLiD, 10X Genomics GemCode WGS, and Illumina exome and WGS paired-end, mate-pair, and synthetic long reads. Cell lines, DNA, and data from these individuals are publicly available. Therefore, we expect these data to be useful for revealing novel information about the human genome and improving sequencing technologies, SNP, indel, and structural variant calling, and de novo assembly.

Paired de bruijn graphs: a novel approach for incorporating mate pair information into genome assemblers.

The recent proliferation of next generation sequencing with short reads has enabled many new experimental opportunities but, at the same time, has raised formidable computational challenges in genome assembly. One of the key advances that has led to an improvement in contig lengths has been mate pairs, which facilitate the assembly of repeating regions. Mate pairs have been algorithmically incorporated into most next generation assemblers as various heuristic post-processing steps to correct the assembly graph or to link contigs into scaffolds. Such methods have allowed the identification of longer contigs than would be possible with single reads; however, they can still fail to resolve complex repeats. Thus, improved methods for incorporating mate pairs will have a strong effect on contig length in the future. Here, we introduce the paired de Bruijn graph, a generalization of the de Bruijn graph that incorporates mate pair information into the graph structure itself instead of analyzing mate pairs at a post-processing step. This graph has the potential to be used in place of the de Bruijn graph in any de Bruijn graph based assembler, maintaining all other assembly steps such as error-correction and repeat resolution. Through assembly results on simulated perfect data, we argue that this can effectively improve the contig sizes in assembly.

Discovery and genotyping of structural variation from long-read haploid genome sequence data

In an effort to more fully understand the full spectrum of human genetic variation, we generated deep single-molecule, real-time (SMRT) sequencing data from two haploid human genomes. By using an assembly-based approach (SMRT-SV), we systematically assessed each genome independently for structural variants (SVs) and indels resolving the sequence structure of 461,553 genetic variants from 2 bp to 28 kbp in length. We find that >89% of these variants have been missed as part of analysis of the 1000 Genomes Project even after adjusting for more common variants (MAF > 1%). We estimate that this theoretical human diploid differs by as much as ∼16 Mbp with respect to the human reference, with long-read sequencing data providing a fivefold increase in sensitivity for genetic variants ranging in size from 7 bp to 1 kbp compared with short-read sequence data. Although a large fraction of genetic variants were not detected by short-read approaches, once the alternate allele is sequence-resolved, we show that 61% of SVs can be genotyped in short-read sequence data sets with high accuracy. Uncoupling discovery from genotyping thus allows for the majority of this missed common variation to be genotyped in the human population. Interestingly, when we repeat SV detection on a pseudodiploid genome constructed in silico by merging the two haploids, we find that ∼59% of the heterozygous SVs are no longer detected by SMRT-SV. These results indicate that haploid resolution of long-read sequencing data will significantly increase sensitivity of SV detection.