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Asset Tag: haplotype

July 7, 2019  |  

Untangling heteroplasmy, structure, and evolution of an atypical mitochondrial genome by PacBio Sequencing.

The highly compact mitochondrial (mt) genome of terrestrial isopods (Oniscidae) presents two unusual features. First, several loci can individually encode two tRNAs, thanks to single nucleotide polymorphisms at anticodon sites. Within-individual variation (heteroplasmy) at these loci is thought to have been maintained for millions of years because individuals that do not carry all tRNA genes die, resulting in strong balancing selection. Second, the oniscid mtDNA genome comes in two conformations: a ~14 kb linear monomer and a ~28 kb circular dimer comprising two monomer units fused in palindrome. We hypothesized that heteroplasmy actually results from two genome units of the same dimeric molecule carrying different tRNA genes at mirrored loci. This hypothesis, however, contradicts the earlier proposition that dimeric molecules result from the replication of linear monomers-a process that should yield totally identical genome units within a dimer. To solve this contradiction, we used the SMRT (PacBio) technology to sequence mirrored tRNA loci in single dimeric molecules. We show that dimers do present different tRNA genes at mirrored loci; thus covalent linkage, rather than balancing selection, maintains vital variation at anticodons. We also leveraged unique features of the SMRT technology to detect linear monomers closed by hairpins and carrying noncomplementary bases at anticodons. These molecules contain the necessary information to encode two tRNAs at the same locus, and suggest new mechanisms of transition between linear and circular mtDNA. Overall, our analyses clarify the evolution of an atypical mt genome where dimerization counterintuitively enabled further mtDNA compaction. Copyright © 2017 by the Genetics Society of America.

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July 7, 2019  |  

The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model.

Negative frequency-dependent selection (NFDS) is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR-) locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into its molecular basis.

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July 7, 2019  |  

Morphological and genetic analyses of the invasive forest pathogen Phytophthora austrocedri reveal two clonal lineages colonised Britain and Argentina from a common ancestral population.

Phytophthora austrocedri is causing widespread mortality of Austrocedrus chilensis in Argentina and Juniperus communis in Britain. The pathogen has also been isolated from J. horizontalis in Germany. Isolates from Britain, Argentina and Germany are homothallic with no clear differences in the dimensions of sporangia, oogonia or oospores. Argentinian and German isolates grew faster than British isolates across a range of media and had a higher temperature tolerance although most isolates regardless of origin grew best at 15°C and all isolates were killed at 25°C. Argentinian and British isolates caused lesions on both hosts when inoculated onto A. chilensis and J. communis; however the Argentinian isolate caused longer lesions on A. chilensis than on J. communis and vice versa for the British isolate. Genetic analyses of nuclear and mitochondrial loci showed that all British isolates are identical. Argentinian isolates and the German isolate are also identical but differ from the British isolates. Single nucleotide polymorphisms are shared between the British and Argentinian isolates. It is concluded that British isolates and Argentinian isolates conform to two distinct clonal lineages of P. austrocedri founded from the same as-yet unidentified source population. These lineages should be recognised and treated as separate risks by international plant health legislation.

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July 7, 2019  |  

Dense and accurate whole-chromosome haplotyping of individual genomes.

The diploid nature of the human genome is neglected in many analyses done today, where a genome is perceived as a set of unphased variants with respect to a reference genome. This lack of haplotype-level analyses can be explained by a lack of methods that can produce dense and accurate chromosome-length haplotypes at reasonable costs. Here we introduce an integrative phasing strategy that combines global, but sparse haplotypes obtained from strand-specific single-cell sequencing (Strand-seq) with dense, yet local, haplotype information available through long-read or linked-read sequencing. We provide comprehensive guidance on the required sequencing depths and reliably assign more than 95% of alleles (NA12878) to their parental haplotypes using as few as 10 Strand-seq libraries in combination with 10-fold coverage PacBio data or, alternatively, 10X Genomics linked-read sequencing data. We conclude that the combination of Strand-seq with different technologies represents an attractive solution to chart the genetic variation of diploid genomes.

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July 7, 2019  |  

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 10-8and 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. Copyright © 2017 the Author(s). Published by PNAS.

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July 7, 2019  |  

Estimating fitness of viral quasispecies from next-generation sequencing data.

The quasispecies model is ubiquitous in the study of viruses. While having lead to a number of insights that have stood the test of time, the quasispecies model has mostly been discussed in a theoretical fashion with little support of data. With next-generation sequencing (NGS), this situation is changing and a wealth of data can now be produced in a time- and cost-efficient manner. NGS can, after removal of technical errors, yield an exceedingly detailed picture of the viral population structure. The widespread availability of cross-sectional data can be used to study fitness landscapes of viral populations in the quasispecies model. This chapter highlights methods that estimate the strength of selection in selective sweeps, assesses marginal fitness effects of quasispecies, and finally infers the fitness landscape of a viral quasispecies, all on the basis of NGS data.

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July 7, 2019  |  

HapCol: accurate and memory-efficient haplotype assembly from long reads.

Haplotype assembly is the computational problem of reconstructing haplotypes in diploid organisms and is of fundamental importance for characterizing the effects of single-nucleotide polymorphisms on the expression of phenotypic traits. Haplotype assembly highly benefits from the advent of ‘future-generation’ sequencing technologies and their capability to produce long reads at increasing coverage. Existing methods are not able to deal with such data in a fully satisfactory way, either because accuracy or performances degrade as read length and sequencing coverage increase or because they are based on restrictive assumptions.By exploiting a feature of future-generation technologies-the uniform distribution of sequencing errors-we designed an exact algorithm, called HapCol, that is exponential in the maximum number of corrections for each single-nucleotide polymorphism position and that minimizes the overall error-correction score. We performed an experimental analysis, comparing HapCol with the current state-of-the-art combinatorial methods both on real and simulated data. On a standard benchmark of real data, we show that HapCol is competitive with state-of-the-art methods, improving the accuracy and the number of phased positions. Furthermore, experiments on realistically simulated datasets revealed that HapCol requires significantly less computing resources, especially memory. Thanks to its computational efficiency, HapCol can overcome the limits of previous approaches, allowing to phase datasets with higher coverage and without the traditional all-heterozygous assumption. Our source code is available under the terms of the GNU General Public License at http://hapcol.algolab.eu/.bonizzoni@disco.unimib.itSupplementary information: Supplementary data are available at Bioinformatics online.© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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July 7, 2019  |  

Genomic resources and their influence on the detection of the signal of positive selection in genome scans.

Genome scans represent powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful, for example, in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non-model species. Thousands of SNPs called using Reduced Representation Sequencing are increasingly used in genome scans. Besides, genome sequences are also becoming increasingly available, allowing better processing of short-read data, offering physical localization of variants, and improving haplotype reconstruction and data imputation. Ultimately, genome sequences are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genome sequences, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by (i) improving the overall quality of the data, (ii) helping the reconstruction of demographic history for the population studied to decrease false-positive rates and (iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high-quality reference genome can improve the detection of the signal of selection by (i) allowing matching the potential candidate loci to linked coding regions under selection, (ii) rapidly moving the investigation to the gene and function and (iii) ensuring that the highly variable regions of the genomes that include functional genes are also investigated. For all those reasons, using reference genomes in genome scan analyses is highly recommended. © 2015 John Wiley & Sons Ltd.

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July 7, 2019  |  

Read-based phasing of related individuals.

Read-based phasing deduces the haplotypes of an individual from sequencing reads that cover multiple variants, while genetic phasing takes only genotypes as input and applies the rules of Mendelian inheritance to infer haplotypes within a pedigree of individuals. Combining both into an approach that uses these two independent sources of information-reads and pedigree-has the potential to deliver results better than each individually.We provide a theoretical framework combining read-based phasing with genetic haplotyping, and describe a fixed-parameter algorithm and its implementation for finding an optimal solution. We show that leveraging reads of related individuals jointly in this way yields more phased variants and at a higher accuracy than when phased separately, both in simulated and real data. Coverages as low as 2× for each member of a trio yield haplotypes that are as accurate as when analyzed separately at 15× coverage per individual.https://bitbucket.org/whatshap/whatshapt.marschall@mpi-inf.mpg.de.© The Author 2016. Published by Oxford University Press.

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July 7, 2019  |  

Selecting reads for haplotype assembly

Haplotype assembly or read-based phasing is the problem of reconstructing both haplotypes of a diploid genome from next-generation sequencing data. This problem is formalized as the Minimum Error Correction (MEC) problem and can be solved using algorithms such as WhatsHap. The runtime of WhatsHap is exponential in the maximum coverage, which is hence controlled in a pre-processing step that selects reads to be used for phasing. Here, we report on a heuristic algorithm designed to choose beneficial reads for phasing, in particular to increase the connectivity of the phased blocks and the number of correctly phased variants compared to the random selection previously employed in by WhatsHap. The algorithm we describe has been integrated into the WhatsHap software, which is available under MIT licence from https://bitbucket.org/whatshap/whatshap.

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July 7, 2019  |  

Long single-molecule reads can resolve the complexity of the influenza virus composed of rare, closely related mutant variants

As a result of a high rate of mutations and recombination events, an RNA-virus exists as a heterogeneous “swarm” of mutant variants. The long read length offered by single-molecule sequencing technologies allows each mutant variant to be sequenced in a single pass. However, high error rate limits the ability to reconstruct heterogeneous viral population composed of rare, related mutant variants. In this paper, we present 2SNV, a method able to tolerate the high error-rate of the single-molecule protocol and reconstruct mutant variants. 2SNV uses linkage between single nucleotide variations to efficiently distinguish them from read errors. To benchmark the sensitivity of 2SNV, we performed a single-molecule sequencing experiment on a sample containing a titrated level of known viral mutant variants. Our method is able to accurately reconstruct clone with frequency of 0.2 % and distinguish clones that differed in only two nucleotides distantly located on the genome. 2SNV outperforms existing methods for full-length viral mutant reconstruction. The open source implementation of 2SNV is freely available for download at http://?alan.?cs.?gsu.?edu/?NGS/???q=?content/?2snv.

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July 7, 2019  |  

Probabilistic viral quasispecies assembly

Viruses are pathogens that cause infectious diseases. The swarm of virions is subject to the host’s immune pressure and possibly antiviral therapy. It may escape this selective pressure and gain selective advantage by acquiring one or more of the genomic alterations: single-nucleotide variants (SNVs), loss or gain of one or more amino acids, large deletions, for example, due to alternative splicing, or recombination of different strains. Genotypic antiretroviral drug resistance testing is performed via sequencing. Next-generation sequencing (NGS) technologies revolutionized assessing viral genetic diversity experimentally. In viral quasispecies analysis, there are two main goals: the identification of low-frequency variants and haplotype assembly on a whole-genome scale. PacBio performs single-molecule sequencing. This chapter elaborates human haplotyping and its relationship to probabilistic viral haplotype reconstruction methods. Viral quasispecies assembly has the potential to replace the current de facto diversity estimation by SNV calling. With advances in library preparation, increasing sensitivity of sequencing platforms, and more sophisticated models, it might be possible to detect all or most viral strains in a single individual.

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July 7, 2019  |  

WhatsHap: fast and accurate read-based phasing

Read-based phasing allows to reconstruct the haplotype structure of a sample purely from sequencing reads. While phasing is a required step for answering questions about population genetics, compound heterozygosity, and to aid in clinical decision making, there has been a lack of an accurate, usable and standards-based software. WhatsHap is a production-ready tool for highly accurate read-based phasing. It was designed from the beginning to leverage third-generation sequencing technologies, whose long reads can span many variants and are therefore ideal for phasing. WhatsHap works also well with second-generation data, is easy to use and will phase not only SNVs, but also indels and other variants. It is unique in its ability to combine read-based with genetic phasing, allowing to further improve accuracy if multiple related samples are provided.

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July 7, 2019  |  

Exploiting next-generation sequencing to solve the haplotyping puzzle in polyploids: a simulation study.

Haplotypes are the units of inheritance in an organism, and many genetic analyses depend on their precise determination. Methods for haplotyping single individuals use the phasing information available in next-generation sequencing reads, by matching overlapping single-nucleotide polymorphisms while penalizing post hoc nucleotide corrections made. Haplotyping diploids is relatively easy, but the complexity of the problem increases drastically for polyploid genomes, which are found in both model organisms and in economically relevant plant and animal species. Although a number of tools are available for haplotyping polyploids, the effects of the genomic makeup and the sequencing strategy followed on the accuracy of these methods have hitherto not been thoroughly evaluated.We developed the simulation pipeline haplosim to evaluate the performance of three haplotype estimation algorithms for polyploids: HapCompass, HapTree and SDhaP, in settings varying in sequencing approach, ploidy levels and genomic diversity, using tetraploid potato as the model. Our results show that sequencing depth is the major determinant of haplotype estimation quality, that 1?kb PacBio circular consensus sequencing reads and Illumina reads with large insert-sizes are competitive and that all methods fail to produce good haplotypes when ploidy levels increase. Comparing the three methods, HapTree produces the most accurate estimates, but also consumes the most resources. There is clearly room for improvement in polyploid haplotyping algorithms.

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January 23, 2017  |  

Tutorial: Long Amplicon Analysis application

This tutorial provides an overview of the Long Amplicon Analysis (LAA) application. The LAA algorithm generates highly accurate, phased and full-length consensus sequences from long amplicons. Applications of LAA include…

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