Short-read DNA Research Articles

Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage

BackgroundIn short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence reconstruction from the reads can be difficult because of the occurrence of uncovered gaps. Reference guided assembly can then improve these assemblies. However, when the available reference is phylogenetically distant from the sequencing reads, the mapping rate of the reads can be extremely low. Some recent improvements in read mapping approaches aim at modifying the reference according to the reads dynamically. Such approaches can significantly improve the alignment rate of the reads onto distant references but the processing of insertions and deletions remains challenging.ResultsHere, we introduce a new algorithm to update the reference sequence according to previously aligned reads. Substitutions, insertions and deletions are performed in the reference sequence dynamically. We evaluate this approach to assemble a western-grey kangaroo mitochondrial amplicon. Our results show that more reads can be aligned and that this method produces assemblies of length comparable to the truth while limiting error rate when classic approaches fail to recover the correct length. Finally, we discuss how the core algorithm of this method could be improved and combined with other approaches to analyse larger genomic sequences.ConclusionsWe introduced an algorithm to perform dynamic alignment of reads on a distant reference. We showed that such approach can improve the reconstruction of an amplicon compared to classically used bioinformatic pipelines. Although not portable to genomic scale in the current form, we suggested several improvements to be investigated to make this method more flexible and allow dynamic alignment to be used for large genome assemblies.

First report of Burkholderia pseudomallei ST412 and ST734 clones harbouring blaOXA-57 but susceptible to imipenem in India.

Melioidosis caused by Burkholderia pseudomallei has become an important clinical threat, especially in Northern Australia and Southeast Asia. However, the genome information on this pathogen is limited. B. pseudomallei isolates identified from bloodstream infections from inpatients were subjected to whole-genome sequencing by IonTorrent PGM and MinION Oxford Nanopore sequencing technologies. Highly accurate complete genomes of two strains, VB3253 and VB2514, were obtained by a hybrid genome assembly method using both short and long DNA reads. Both isolates carried blaPenI and carbapenemase-encoding blaOXA-57 genes, although the isolates were susceptible to imipenem by E-test method with MIC 1 μg/mL. Multiple IS family transposases specific for all non-fermenting Gram-negative bacteria (NFGNBs)—especially IS3 and IS5, which facilitate mobilization of extended-spectrum β-lactamase (ESBL) and carbapenemase genes—were carried in these genomes. This further adds to the complexity of gene transmission. These IS families were identified only upon hybrid genome assembly and would otherwise be missed.

Evaluation of computational genotyping of structural variation for clinical diagnoses.

BackgroundStructural variation (SV) plays a pivotal role in genetic disease. The discovery of SVs based on short DNA sequence reads from next-generation DNA sequence methods is error-prone, with low sensitivity and high false discovery rates. These shortcomings can be partially overcome with extensive orthogonal validation methods or use of long reads, but the current cost precludes their application for routine clinical diagnostics. In contrast, SV genotyping of known sites of SV occurrence is relatively robust and therefore offers a cost-effective clinical diagnostic tool with potentially few false-positive and false-negative results, even when applied to short-read DNA sequence data.ResultsWe assess 5 state-of-the-art SV genotyping software methods, applied to short-read sequence data. The methods are characterized on the basis of their ability to genotype different SV types, spanning different size ranges. Furthermore, we analyze their ability to parse different VCF file subformats and assess their reliance on specific metadata. We compare the SV genotyping methods across a range of simulated and real data including SVs that were not found with Illumina data alone. We assess sensitivity and the ability to filter initial false discovery calls. We determined the impact of SV type and size on the performance for each SV genotyper. Overall, STIX performed the best on both simulated and GiaB based SV calls, demonstrating a good balance between sensitivity and specificty.ConclusionOur results indicate that, although SV genotyping software methods have superior performance to SV callers, there are limitations that suggest the need for further innovation.

Complete Assembly of Escherichia coli Sequence Type 131 Genomes Using Long Reads Demonstrates Antibiotic Resistance Gene Variation within Diverse Plasmid and Chromosomal Contexts.

The incidence of infections caused by extraintestinal Escherichia coli (ExPEC) is rising globally, which is a major public health concern. ExPEC strains that are resistant to antimicrobials have been associated with excess mortality, prolonged hospital stays, and higher health care costs. E. coli sequence type 131 (ST131) is a major ExPEC clonal group worldwide, with variable plasmid composition, and has an array of genes enabling antimicrobial resistance (AMR). ST131 isolates frequently encode the AMR genes blaCTX-M-14, blaCTX-M-15, and blaCTX-M-27, which are often rearranged, amplified, and translocated by mobile genetic elements (MGEs). Short DNA reads do not fully resolve the architecture of repetitive elements on plasmids to allow MGE structures encoding blaCTX-M genes to be fully determined. Here, we performed long-read sequencing to decipher the genome structures of six E. coli ST131 isolates from six patients. Most long-read assemblies generated entire chromosomes and plasmids as single contigs, in contrast to more fragmented assemblies created with short reads alone. The long-read assemblies highlighted diverse accessory genomes with blaCTX-M-15, blaCTX-M-14, and blaCTX-M-27 genes identified in three, one, and one isolates, respectively. One sample had no blaCTX-M gene. Two samples had chromosomal blaCTX-M-14 and blaCTX-M-15 genes, and the latter was at three distinct locations, likely transposed by the adjacent MGEs: ISEcp1, IS903B, and Tn2 This study showed that AMR genes exist in multiple different chromosomal and plasmid contexts, even between closely related isolates within a clonal group such as E. coli ST131.IMPORTANCE Drug-resistant bacteria are a major cause of illness worldwide, and a specific subtype called Escherichia coli ST131 causes a significant number of these infections. ST131 bacteria become resistant to treatments by modifying their DNA and by transferring genes among one another via large packages of genes called plasmids, like a game of pass-the-parcel. Tackling infections more effectively requires a better understanding of what plasmids are being exchanged and their exact contents. To achieve this, we applied new high-resolution DNA sequencing technology to six ST131 samples from infected patients and compared the output to that of an existing approach. A combination of methods shows that drug resistance genes on plasmids are highly mobile because they can jump into ST131's chromosomes. We found that the plasmids are very elastic and undergo extensive rearrangements even in closely related samples. This application of DNA sequencing technologies illustrates at a new level the highly dynamic nature of ST131 genomes.

Transcriptomics Identifies Modules of Differentially Expressed Genes and Novel Cyclotides in Viola pubescens.

Viola is a large genus with worldwide distribution and many traits not currently exemplified in model plants including unique breeding systems and the production of cyclotides. Here we report de novo genome assembly and transcriptomic analyses of the non-model species Viola pubescens using short-read DNA sequencing data and RNA-Seq from eight diverse tissues. First, V. pubescens genome size was estimated through flow cytometry, resulting in an approximate haploid genome of 455 Mbp. Next, the draft V. pubescens genome was sequenced and assembled resulting in 264,035,065 read pairs and 161,038 contigs with an N50 length of 3,455 base pairs (bp). RNA-Seq data were then assembled into tissue-specific transcripts. Together, the DNA and transcript data generated 38,081 ab initio gene models which were functionally annotated based on homology to Arabidopsis thaliana genes and Pfam domains. Gene expression was visualized for each tissue via principal component analysis and hierarchical clustering, and gene co-expression analysis identified 20 modules of tissue-specific transcriptional networks. Some of these modules highlight genetic differences between chasmogamous and cleistogamous flowers and may provide insight into V. pubescens’ mixed breeding system. Orthologous clustering with the proteomes of A. thaliana and Populus trichocarpa revealed 8,531 sequences unique to V. pubescens, including 81 novel cyclotide precursor sequences. Cyclotides are plant peptides characterized by a stable, cyclic cystine knot motif, making them strong candidates for drug scaffolding and protein engineering. Analysis of the RNA-Seq data for these cyclotide transcripts revealed diverse expression patterns both between transcripts and tissues. The diversity of these cyclotides was also highlighted in a maximum likelihood protein cladogram containing V. pubescens cyclotides and published cyclotide sequences from other Violaceae and Rubiaceae species. Collectively, this work provides the most comprehensive sequence resource for Viola, offers valuable transcriptomic insight into V. pubescens, and will facilitate future functional genomics research in Viola and other diverse plant groups.

Minerva: an alignment- and reference-free approach to deconvolve Linked-Reads for metagenomics.

Emerging Linked-Read technologies (aka read cloud or barcoded short-reads) have revived interest in short-read technology as a viable approach to understand large-scale structures in genomes and metagenomes. Linked-Read technologies, such as the 10x Chromium system, use a microfluidic system and a specialized set of 3′ barcodes (aka UIDs) to tag short DNA reads sourced from the same long fragment of DNA; subsequently, the tagged reads are sequenced on standard short-read platforms. This approach results in interesting compromises. Each long fragment of DNA is only sparsely covered by reads, no information about the ordering of reads from the same fragment is preserved, and 3′ barcodes match reads from roughly 2–20 long fragments of DNA. However, compared to long-read technologies, the cost per base to sequence is far lower, far less input DNA is required, and the per base error rate is that of Illumina short-reads. In this paper, we formally describe a particular algorithmic issue common to Linked-Read technology: the deconvolution of reads with a single 3′ barcode into clusters that represent single long fragments of DNA. We introduce Minerva, a graph-based algorithm that approximately solves the barcode deconvolution problem for metagenomic data (where reference genomes may be incomplete or unavailable). Additionally, we develop two demonstrations where the deconvolution of barcoded reads improves downstream results, improving the specificity of taxonomic assignments and of k-mer-based clustering. To the best of our knowledge, we are the first to address the problem of barcode deconvolution in metagenomics.

Unimodular Hypergraph for DNA Sequencing: A Polynomial Time Algorithm

The paper discusses a hypergraph-based polynomial time algorithm for constructing a DNA sequence corresponding to a given spectrum with no errors. The presence of n-ary relations in the expression of DNA sequencing led to the advent of hypergraphs in DNA sequencing. An efficient algorithm, unimodular hypergraph (UMHG), has been proposed for constructing unimodular hypergraph that represents the short-read DNA sequence of the given spectrum. The performance of the proposed algorithm is evaluated in comparison with prominent algorithms such as greedy, greedy (lag), ant colony optimization(ACO), multi-level ACO, enhanced genetic algorithm (GA), hybrid GA and tabu search against 40 instances. The proposed UMHG algorithm is found to outperform the other algorithms in terms of average similarity score. UMHG is significant in terms of minimum computing time, especially as the spectrum size increases computing time decreases considerably, owing to the unimodularity property.

Rapid preimplantation genetic screening using a handheld, nanopore-based DNA sequencer

To determine if a handheld, nanopore-based DNA sequencer can be used for rapid preimplantation genetic screening (PGS). Laboratory study. Academic medical center. Amplified genomic DNA from euploid and aneuploid trophectoderm biopsy samples (n=9) that was also tested using traditional next generation sequencing (NGS). Short-read DNA library preparation and nanopore-based sequencing using a hand-held MinION sequencer. Comparison of cytogenetic testing result from NGS and nanopore-based sequencing and the time required for library preparation and sequencing. Multiplexed short-read DNA library preparation was completed in 45minutes. Sequencing on a single sample was completed within 20minutes and 5 samples were simultaneously sequenced in under 2hours. Whole-chromosome aneuploidy screening results obtained from nanopore-based sequencing were identical to those obtained using NGS. Here we report the first application of nanopore-based sequencing for PGS on trophectoderm biopsy samples using a novel rapid multiplxed short-read nanopore sequencing library preparation protocol. Sequencing for aneuploidy screening could be performed on a single sample in 20minutes and on 5 samples, simultaneously, within 2hours. Overall, nanopore sequencing is a promising tool to perform rapid PGS onsite, enabling same day testing and embryo transfer, thus obviating the need for complex, large and expensive DNA sequencers or embryo freezing.

A multi-amplicon 16S rRNA sequencing and analysis method for improved taxonomic profiling of bacterial communities

Metagenomic sequencing of bacterial samples has become the gold standard for profiling microbial populations, but 16S rRNA profiling remains widely used due to advantages in sample throughput, cost, and sensitivity even though the approach is hampered by primer bias and lack of specificity. We hypothesized that a hybrid approach, that combined targeted PCR amplification with high-throughput sequencing of multiple regions of the genome, would capture many of the advantages of both approaches.We developed a method that identifies and quantifies members of bacterial communities through simultaneous analysis of multiple variable regions of the bacterial 16S rRNA gene. The method combines high-throughput microfluidics for PCR amplification, short read DNA sequencing, and a custom algorithm named MVRSION (Multiple 16S Variable Region Species-Level IdentificatiON) for optimizing taxonomic assignment. MVRSION performance was compared to single variable region analyses (V3 or V4) of five synthetic mixtures of human gut bacterial strains using existing software (QIIME), and the results of community profiling by shotgun sequencing (COPRO-Seq) of fecal DNA samples collected from gnotobiotic mice colonized with a defined, phylogenetically diverse consortium of human gut bacterial strains. Positive predictive values for MVRSION ranged from 65%–91% versus 44%–61% for single region QIIME analyses (p < .01, p < .001), while the abundance estimate r2 for MVRSION compared to COPRO-Seq was 0.77 vs. 0.46 and 0.45 for V3-QIIME and V4-QIIME, respectively.MVRSION represents a generally applicable tool for taxonomic classification that is superior to single-region 16S rRNA methods, resource efficient, highly scalable for assessing the microbial composition of up to thousands of samples concurrently, with multiple applications ranging from whole community profiling to targeted tracking of organisms of interest in diverse habitats as a function of specified variables/perturbations.

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens.

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing high-throughput short-read DNA sequencing. The resulting sequence datasets can not only track what genes in a population that are enriched during selection for positive yeast 2-hybrid interactions, but also give detailed information about the relevant subdomains of proteins sufficient for interaction. Here, we describe a full suite of stand-alone software programs that allow non-experts to perform all the bioinformatics and statistical steps to process and analyze DNA sequence fastq files from a batch yeast 2-hybrid assay. The processing steps covered by these software include: 1) mapping and counting sequence reads corresponding to each candidate protein encoded within a yeast 2-hybrid prey library; 2) a statistical analysis program that evaluates the enrichment profiles; and 3) tools to examine the translational frame and position within the coding region of each enriched plasmid that encodes the interacting proteins of interest.

Rapid Multiplex Small DNA Sequencing on the MinION Nanopore Sequencing Platform.

Real-time sequencing of short DNA reads has a wide variety of clinical and research applications including screening for mutations, target sequences and aneuploidy. We recently demonstrated that MinION, a nanopore-based DNA sequencing device the size of a USB drive, could be used for short-read DNA sequencing. In this study, an ultra-rapid multiplex library preparation and sequencing method for the MinION is presented and applied to accurately test normal diploid and aneuploidy samples’ genomic DNA in under three hours, including library preparation and sequencing. This novel method shows great promise as a clinical diagnostic test for applications requiring rapid short-read DNA sequencing.

Genomic insights into natural selection in the common loon (Gavia immer): evidence for aquatic adaptation

BackgroundThe common loon (Gavia immer) is one of five species that comprise the avian order Gaviiformes. Loons are specialized divers, reaching depths up to 60 m while staying submerged for intervals up to three minutes. In this study we used comparative genomics to investigate the genetic basis of the common loon adaptations to its ecological niche. We used Illumina short read DNA sequence data from a female bird to produce a draft assembly of the common loon (Gavia immer) genome.ResultsWe identified 14,169 common loon genes, which based on well-resolved avian genomes, represent approximately 80.7% of common loon genes. Evolutionary analyses between common loon and Adelie penguin (Pygoscelis adeliae), red-throated loon (Gavia stellata), chicken (Gallus gallus), northern fulmar (Fulmarus glacialis), and rock pigeon (Columba livia) show 164 positively selected genes in common and red-throated loons. These genes were enriched for a number of protein classes, including those involved in muscle tissue development, immunoglobulin function, hemoglobin iron binding, G-protein coupled receptors, and ATP metabolism.ConclusionsSignatures of positive selection in these areas suggest the genus Gavia may have adapted for underwater diving by modulating their oxidative and metabolic pathways. While more research is required, these adaptations likely result in (1) compensations in oxygen respiration and energetic metabolism, (2) low-light visual acuity, and (3) elevated solute exchange. This work represents the first effort to understand the genomic adaptations of the common loon as well as other Gavia and may have implications for subsequent studies that target particular genes for loon population genetic, ecological or conservation studies.

SHI7 Is a Self-Learning Pipeline for Multipurpose Short-Read DNA Quality Control.

Next-generation sequencing technology is of great importance for many biological disciplines; however, due to technical and biological limitations, the short DNA sequences produced by modern sequencers require numerous quality control (QC) measures to reduce errors, remove technical contaminants, or merge paired-end reads together into longer or higher-quality contigs. Many tools for each step exist, but choosing the appropriate methods and usage parameters can be challenging because the parameterization of each step depends on the particularities of the sequencing technology used, the type of samples being analyzed, and the stochasticity of the instrumentation and sample preparation. Furthermore, end users may not know all of the relevant information about how their data were generated, such as the expected overlap for paired-end sequences or type of adaptors used to make informed choices. This increasing complexity and nuance demand a pipeline that combines existing steps together in a user-friendly way and, when possible, learns reasonable quality parameters from the data automatically. We propose a user-friendly quality control pipeline called SHI7 (canonically pronounced "shizen"), which aims to simplify quality control of short-read data for the end user by predicting presence and/or type of common sequencing adaptors, what quality scores to trim, whether the data set is shotgun or amplicon sequencing, whether reads are paired end or single end, and whether pairs are stitchable, including the expected amount of pair overlap. We hope that SHI7 will make it easier for all researchers, expert and novice alike, to follow reasonable practices for short-read data quality control. IMPORTANCE Quality control of high-throughput DNA sequencing data is an important but sometimes laborious task requiring background knowledge of the sequencing protocol used (such as adaptor type, sequencing technology, insert size/stitchability, paired-endedness, etc.). Quality control protocols typically require applying this background knowledge to selecting and executing numerous quality control steps with the appropriate parameters, which is especially difficult when working with public data or data from collaborators who use different protocols. We have created a streamlined quality control pipeline intended to substantially simplify the process of DNA quality control from raw machine output files to actionable sequence data. In contrast to other methods, our proposed pipeline is easy to install and use and attempts to learn the necessary parameters from the data automatically with a single command.

Targeted Long-Read Sequencing of a Locus Under Long-Term Balancing Selection in Capsella.

Rapid advances in short-read DNA sequencing technologies have revolutionized population genomic studies, but there are genomic regions where this technology reaches its limits. Limitations mostly arise due to the difficulties in assembly or alignment to genomic regions of high sequence divergence and high repeat content, which are typical characteristics for loci under strong long-term balancing selection. Studying genetic diversity at such loci therefore remains challenging. Here, we investigate the feasibility and error rates associated with targeted long-read sequencing of a locus under balancing selection. For this purpose, we generated bacterial artificial chromosomes (BACs) containing the Brassicaceae S-locus, a region under strong negative frequency-dependent selection which has previously proven difficult to assemble in its entirety using short reads. We sequence S-locus BACs with single-molecule long-read sequencing technology and conduct de novo assembly of these S-locus haplotypes. By comparing repeated assemblies resulting from independent long-read sequencing runs on the same BAC clone we do not detect any structural errors, suggesting that reliable assemblies are generated, but we estimate an indel error rate of 5.7×10−5. A similar error rate was estimated based on comparison of Illumina short-read sequences and BAC assemblies. Our results show that, until de novo assembly of multiple individuals using long-read sequencing becomes feasible, targeted long-read sequencing of loci under balancing selection is a viable option with low error rates for single nucleotide polymorphisms or structural variation. We further find that short-read sequencing is a valuable complement, allowing correction of the relatively high rate of indel errors that result from this approach.

Double insertion of transposable elements provides a substrate for the evolution of satellite DNA.

Eukaryotic genomes are replete with repeated sequences in the form of transposable elements (TEs) dispersed across the genome or as satellite arrays, large stretches of tandemly repeated sequences. Many satellites clearly originated as TEs, but it is unclear how mobile genetic parasites can transform into megabase-sized tandem arrays. Comprehensive population genomic sampling is needed to determine the frequency and generative mechanisms of tandem TEs, at all stages from their initial formation to their subsequent expansion and maintenance as satellites. The best available population resources, short-read DNA sequences, are often considered to be of limited utility for analyzing repetitive DNA due to the challenge of mapping individual repeats to unique genomic locations. Here we develop a new pipeline called ConTExt that demonstrates that paired-end Illumina data can be successfully leveraged to identify a wide range of structural variation within repetitive sequence, including tandem elements. By analyzing 85 genomes from five populations of Drosophila melanogaster, we discover that TEs commonly form tandem dimers. Our results further suggest that insertion site preference is the major mechanism by which dimers arise and that, consequently, dimers form rapidly during periods of active transposition. This abundance of TE dimers has the potential to provide source material for future expansion into satellite arrays, and we discover one such copy number expansion of the DNA transposon hobo to approximately 16 tandem copies in a single line. The very process that defines TEs—transposition—thus regularly generates sequences from which new satellites can arise.

HPViewer: sensitive and specific genotyping of human papillomavirus in metagenomic DNA.

Shotgun DNA sequencing provides sensitive detection of all 182 HPV types in tissue and body fluid. However, existing computational methods either produce false positives misidentifying HPV types due to shared sequences among HPV, human and prokaryotes, or produce false negative since they identify HPV by assembled contigs requiring large abundant of HPV reads. We designed HPViewer with two custom HPV reference databases masking simple repeats and homology sequences respectively and one homology distance matrix to hybridize these two databases. It directly identified HPV from short DNA reads rather than assembled contigs. Using 100 100 simulated samples, we revealed that HPViewer was robust for samples containing either high or low number of HPV reads. Using 12 shotgun sequencing samples from respiratory papillomatosis, HPViewer was equal to VirusTAP, and Vipie and better than HPVDetector with the respect to specificity and was the most sensitive method in the detection of HPV types 6 and 11. We demonstrated that contigs-based approaches had disadvantages of detection of HPV. In 1573 sets of metagenomic data from 18 human body sites, HPViewer identified 104 types of HPV in a body-site associated pattern and 89 types of HPV co-occurring in one sample with other types of HPV. We demonstrated HPViewer was sensitive and specific for HPV detection in metagenomic data. HPViewer can be accessed at https://github.com/yuhanH/HPViewer/. Supplementary data are available at Bioinformatics online.

HLA Typing from Short-Read Sequencing Data with OptiType.

The established standards for HLA genotyping rely on targeted DNA sequencing techniques. However, the increasing abundance of short-read sequencing data has prompted a demand for computational tools capable of HLA typing from general purpose sequencing data as well. OptiType is a software that performs HLA typing from short-read DNA and RNA sequencing data, and this chapter guides the user through its installation and usage.

A hybrid-hierarchical genome assembly strategy to sequence the invasive golden mussel, Limnoperna fortunei.

BackgroundFor more than 25 years, the golden mussel, Limnoperna fortunei, has aggressively invaded South American freshwaters, having travelled more than 5000 km upstream across 5 countries. Along the way, the golden mussel has outcompeted native species and economically harmed aquaculture, hydroelectric powers, and ship transit. We have sequenced the complete genome of the golden mussel to understand the molecular basis of its invasiveness and search for ways to control it.FindingsWe assembled the 1.6-Gb genome into 20 548 scaffolds with an N50 length of 312 Kb using a hybrid and hierarchical assembly strategy from short and long DNA reads and transcriptomes. A total of 60 717 coding genes were inferred from a customized transcriptome-trained AUGUSTUS run. We also compared predicted protein sets with those of complete molluscan genomes, revealing an exacerbation of protein-binding domains in L. fortunei.ConclusionsWe built one of the best bivalve genome assemblies available using a cost-effective approach using Illumina paired-end, mate-paired, and PacBio long reads. We expect that the continuous and careful annotation of L. fortunei’s genome will contribute to the investigation of bivalve genetics, evolution, and invasiveness, as well as to the development of biotechnological tools for aquatic pest control.

Microhaplotypes provide increased power from short‐read DNA sequences for relationship inference

The accelerating rate at which DNA sequence data are now generated by high-throughput sequencing instruments provides both opportunities and challenges for population genetic and ecological investigations of animals and plants. We show here how the common practice of calling genotypes from a single SNP per sequenced region ignores substantial additional information in the phased short-read sequences that are provided by these sequencing instruments. We target sequenced regions with multiple SNPs in kelp rockfish (Sebastes atrovirens) to determine "microhaplotypes" and then call these microhaplotypes as alleles at each locus. We then demonstrate how these multi-allelic marker data from such loci dramatically increase power for relationship inference. The microhaplotype approach decreases false-positive rates by several orders of magnitude, relative to calling bi-allelic SNPs, for two challenging analytical procedures, full-sibling and single parent-offspring pair identification. We also show how the identification of half-sibling pairs requires so much data that physical linkage becomes a consideration, and that most published studies that attempt to do so are dramatically underpowered. The advent of phased short-read DNA sequence data, in conjunction with emerging analytical tools for their analysis, promises to improve efficiency by reducing the number of loci necessary for a particular level of statistical confidence, thereby lowering the cost of data collection and reducing the degree of physical linkage amongst markers used for relationship estimation. Such advances will facilitate collaborative research and management for migratory and other widespread species.

Ultraaccurate genome sequencing and haplotyping of single human cells

Accurate detection of variants and long-range haplotypes in genomes of single human cells remains very challenging. Common approaches require extensive in vitro amplification of genomes of individual cells using DNA polymerases and high-throughput short-read DNA sequencing. These approaches have two notable drawbacks. First, polymerase replication errors could generate tens of thousands of false-positive calls per genome. Second, relatively short sequence reads contain little to no haplotype information. Here we report a method, which is dubbed SISSOR (single-stranded sequencing using microfluidic reactors), for accurate single-cell genome sequencing and haplotyping. A microfluidic processor is used to separate the Watson and Crick strands of the double-stranded chromosomal DNA in a single cell and to randomly partition megabase-size DNA strands into multiple nanoliter compartments for amplification and construction of barcoded libraries for sequencing. The separation and partitioning of large single-stranded DNA fragments of the homologous chromosome pairs allows for the independent sequencing of each of the complementary and homologous strands. This enables the assembly of long haplotypes and reduction of sequence errors by using the redundant sequence information and haplotype-based error removal. We demonstrated the ability to sequence single-cell genomes with error rates as low as 10-8 and average 500-kb-long DNA fragments that can be assembled into haplotype contigs with N50 greater than 7 Mb. The performance could be further improved with more uniform amplification and more accurate sequence alignment. The ability to obtain accurate genome sequences and haplotype information from single cells will enable applications of genome sequencing for diverse clinical needs.