MinYS: mine your symbiont by targeted genome assembly in symbiotic communities

Most metazoans are associated with symbionts. Characterizing the effect of a particular symbiont often requires to get access to its genome, which is usually done by sequencing the whole community. We present MinYS, a targeted assembly approach to assemble one particular genome of interest from such metagenomic data. First, taking advantage of a reference genome, a subset of the reads is assembled into a set of backbone contigs. Then, this draft assembly is completed using the whole metagenomic readset in a de novo manner. The resulting assembly is output as a genome graph, allowing to distinguish different strains with potential structural variants coexisting in the sample. MinYS was applied to 50 pea aphid re-sequencing samples, with low and high diversity, in order to recover the genome sequence of its obligatory bacterial symbiont, Buchnera aphidicola. It was able to return high quality assemblies (one contig assembly in 90% of the samples), even when using increasingly distant reference genomes, and to retrieve large structural variations in the samples. Due to its targeted essence, it outperformed standard metagenomic assemblers in terms of both time and assembly quality.

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Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes

10.1101/2021.09.15.460475 ◽

2021 ◽

Author(s):

Martin Hunt ◽

Brice Letcher ◽

Kerri M Malone ◽

Giang Nguyen ◽

Michael B Hall ◽

...

Keyword(s):

Current Knowledge ◽

Variant Calling ◽

Rifampicin Resistance ◽

Bacterial Genomes ◽

Single Nucleotide ◽

A Genome ◽

Bacterial Genomics ◽

Single Nucleotide Polymorphism Variation ◽

Reference Genomes ◽

Genome Graph

Short-read variant calling for bacterial genomics is a mature field, and there are many widely-used software tools. Different underlying approaches (eg pileup, local or global assembly, paired-read use, haplotype use) lend each tool different strengths, especially when considering non-SNP (single nucleotide polymorphism) variation or potentially distant reference genomes. It would therefore be valuable to be able to integrate the results from multiple variant callers, using a robust statistical approach to "adjudicate" at loci where there is disagreement between callers. To this end, we present a tool, Minos, for variant adjudication by mapping reads to a genome graph of variant calls. Minos allows users to combine output from multiple variant callers without loss of precision. Minos also addresses a second problem of joint genotyping SNPs and indels in bacterial cohorts, which can also be framed as an adjudication problem. We benchmark on 62 samples from 3 species (Mycobacterium tuberculosis, Staphylococcus aureus, Klebsiella pneumoniae) and an outbreak of 385 M. tuberculosis samples. Finally, we joint genotype a large M. tuberculosis cohort (N≈15k) for which the rifampicin phenotype is known. We build a map of non-synonymous variants in the RRDR (rifampicin resistance determining region) of the rpoB gene and extend current knowledge relating RRDR SNPs to heterogeneity in rifampicin resistance levels. We replicate this finding in a second M. tuberculosis cohort (N≈13k). Minos is released under the MIT license, available at https://github.com/iqbal-lab-org/minos.

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Resolving the Full Spectrum of Human Genome Variation using Linked-Reads

10.1101/230946 ◽

2017 ◽

Cited By ~ 8

Author(s):

Patrick Marks ◽

Sarah Garcia ◽

Alvaro Martinez Barrio ◽

Kamila Belhocine ◽

Jorge Bernate ◽

...

Keyword(s):

Human Genome ◽

Large Scale ◽

De Novo ◽

Simultaneous Detection ◽

Whole Genome ◽

Structural Variations ◽

Full Spectrum ◽

Short Read ◽

Short Reads ◽

A Genome

AbstractLarge-scale population based analyses coupled with advances in technology have demonstrated that the human genome is more diverse than originally thought. To date, this diversity has largely been uncovered using short read whole genome sequencing. However, standard short-read approaches, used primarily due to accuracy, throughput and costs, fail to give a complete picture of a genome. They struggle to identify large, balanced structural events, cannot access repetitive regions of the genome and fail to resolve the human genome into its two haplotypes. Here we describe an approach that retains long range information while harnessing the advantages of short reads. Starting from only ∼1ng of DNA, we produce barcoded short read libraries. The use of novel informatic approaches allows for the barcoded short reads to be associated with the long molecules of origin producing a novel datatype known as ‘Linked-Reads’. This approach allows for simultaneous detection of small and large variants from a single Linked-Read library. We have previously demonstrated the utility of whole genome Linked-Reads (lrWGS) for performing diploid, de novo assembly of individual genomes (Weisenfeld et al. 2017). In this manuscript, we show the advantages of Linked-Reads over standard short read approaches for reference based analysis. We demonstrate the ability of Linked-Reads to reconstruct megabase scale haplotypes and to recover parts of the genome that are typically inaccessible to short reads, including phenotypically important genes such as STRC, SMN1 and SMN2. We demonstrate the ability of both lrWGS and Linked-Read Whole Exome Sequencing (lrWES) to identify complex structural variations, including balanced events, single exon deletions, and single exon duplications. The data presented here show that Linked-Reads provide a scalable approach for comprehensive genome analysis that is not possible using short reads alone.

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Chromosome-length genome assembly and structural variations of the primal Basenji dog (Canis lupus familiaris) genome

BMC Genomics ◽

10.1186/s12864-021-07493-6 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Richard J. Edwards ◽

Matt A. Field ◽

James M. Ferguson ◽

Olga Dudchenko ◽

Jens Keilwagen ◽

...

Keyword(s):

Reference Genome ◽

De Novo ◽

Genome Structure ◽

Canis Lupus Familiaris ◽

Structural Variations ◽

German Shepherd ◽

High Quality ◽

Entire Family ◽

The Impact ◽

Reference Genomes

Abstract Background Basenjis are considered an ancient dog breed of central African origins that still live and hunt with tribesmen in the African Congo. Nicknamed the barkless dog, Basenjis possess unique phylogeny, geographical origins and traits, making their genome structure of great interest. The increasing number of available canid reference genomes allows us to examine the impact the choice of reference genome makes with regard to reference genome quality and breed relatedness. Results Here, we report two high quality de novo Basenji genome assemblies: a female, China (CanFam_Bas), and a male, Wags. We conduct pairwise comparisons and report structural variations between assembled genomes of three dog breeds: Basenji (CanFam_Bas), Boxer (CanFam3.1) and German Shepherd Dog (GSD) (CanFam_GSD). CanFam_Bas is superior to CanFam3.1 in terms of genome contiguity and comparable overall to the high quality CanFam_GSD assembly. By aligning short read data from 58 representative dog breeds to three reference genomes, we demonstrate how the choice of reference genome significantly impacts both read mapping and variant detection. Conclusions The growing number of high-quality canid reference genomes means the choice of reference genome is an increasingly critical decision in subsequent canid variant analyses. The basal position of the Basenji makes it suitable for variant analysis for targeted applications of specific dog breeds. However, we believe more comprehensive analyses across the entire family of canids is more suited to a pangenome approach. Collectively this work highlights the importance the choice of reference genome makes in all variation studies.

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NovoGraph: Human genome graph construction from multiple long-read de novo assemblies

F1000Research ◽

10.12688/f1000research.15895.2 ◽

2018 ◽

Vol 7 ◽

pp. 1391

Author(s):

Evan Biederstedt ◽

Jeffrey C. Oliver ◽

Nancy F. Hansen ◽

Aarti Jajoo ◽

Nathan Dunn ◽

...

Keyword(s):

Human Genome ◽

De Novo ◽

Wide Spectrum ◽

Third Party ◽

Sequencing Data ◽

Multiple Sequence ◽

Human Genomes ◽

A Genome ◽

Long Read ◽

Genome Graph

Genome graphs are emerging as an important novel approach to the analysis of high-throughput human sequencing data. By explicitly representing genetic variants and alternative haplotypes in a mappable data structure, they can enable the improved analysis of structurally variable and hyperpolymorphic regions of the genome. In most existing approaches, graphs are constructed from variant call sets derived from short-read sequencing. As long-read sequencing becomes more cost-effective and enables de novo assembly for increasing numbers of whole genomes, a method for the direct construction of a genome graph from sets of assembled human genomes would be desirable. Such assembly-based genome graphs would encompass the wide spectrum of genetic variation accessible to long-read-based de novo assembly, including large structural variants and divergent haplotypes. Here we present NovoGraph, a method for the construction of a human genome graph directly from a set of de novo assemblies. NovoGraph constructs a genome-wide multiple sequence alignment of all input contigs and creates a graph by merging the input sequences at positions that are both homologous and sequence-identical. NovoGraph outputs resulting graphs in VCF format that can be loaded into third-party genome graph toolkits. To demonstrate NovoGraph, we construct a genome graph with 23,478,835 variant sites and 30,582,795 variant alleles from de novo assemblies of seven ethnically diverse human genomes (AK1, CHM1, CHM13, HG003, HG004, HX1, NA19240). Initial evaluations show that mapping against the constructed graph reduces the average mismatch rate of reads from sample NA12878 by approximately 0.2%, albeit at a slightly increased rate of reads that remain unmapped.

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Genome Graphs

10.1101/101378 ◽

2017 ◽

Cited By ~ 34

Author(s):

Adam M. Novak ◽

Glenn Hickey ◽

Erik Garrison ◽

Sean Blum ◽

Abram Connelly ◽

...

Keyword(s):

Reference Genome ◽

Human Genetics ◽

De Novo ◽

Variant Calling ◽

Reference Structure ◽

Read Mapping ◽

Human Reference Genome ◽

A Genome ◽

Universal Reference ◽

Genome Graph

AbstractThere is increasing recognition that a single, monoploid reference genome is a poor universal reference structure for human genetics, because it represents only a tiny fraction of human variation. Adding this missing variation results in a structure that can be described as a mathematical graph: a genome graph. We demonstrate that, in comparison to the existing reference genome (GRCh38), genome graphs can substantially improve the fractions of reads that map uniquely and perfectly. Furthermore, we show that this fundamental simplification of read mapping transforms the variant calling problem from one in which many non-reference variants must be discovered de-novo to one in which the vast majority of variants are simply re-identified within the graph. Using standard benchmarks as well as a novel reference-free evaluation, we show that a simplistic variant calling procedure on a genome graph can already call variants at least as well as, and in many cases better than, a state-of-the-art method on the linear human reference genome. We anticipate that graph-based references will supplant linear references in humans and in other applications where cohorts of sequenced individuals are available.

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Chromosome-length genome assembly and structural variations of the primal Basenji dog (Canis lupus familiaris) genome

10.21203/rs.3.rs-135125/v1 ◽

2020 ◽

Author(s):

Richard J Edwards ◽

Matt A. Field ◽

James M. Ferguson ◽

Olga Dudchenko ◽

Jens Keilwagen ◽

...

Keyword(s):

Reference Genome ◽

De Novo ◽

Genome Structure ◽

Canis Lupus Familiaris ◽

Structural Variations ◽

German Shepherd ◽

High Quality ◽

Entire Family ◽

The Impact ◽

Reference Genomes

Abstract Background Basenjis are considered an ancient dog breed of central African origins that still live and hunt with tribesmen in the African Congo. Nicknamed the barkless dog, Basenjis possess unique phylogeny, geographical origins and traits, making their genome structure of great interest. The increasing number of available canid reference genomes allows us to examine the impact the choice of reference genome makes with regard to reference genome quality and breed relatedness. Results Here, we report two high quality de novo Basenji genome assemblies: a female, China (CanFam_Bas), and a male, Wags. We conduct pairwise comparisons and report structural variations between assembled genomes of three dog breeds: Basenji (CanFam_Bas), Boxer (CanFam3.1) and German Shepherd Dog (GSD) (CanFam_GSD). CanFam_Bas is superior to CanFam3.1 in terms of genome contiguity and comparable overall to the high quality CanFam_GSD assembly. By aligning short read data from 58 representative dog breeds to three reference genomes, we demonstrate how the choice of reference genome significantly impacts both read mapping and variant detection. Conclusions The growing number of high-quality canid reference genomes means the choice of reference genome is an increasingly critical decision in subsequent canid variant analyses. The basal position of the Basenji makes it suitable for variant analysis for targeted applications of specific dog breeds. However, we believe more comprehensive analyses across the entire family of canids is more suited to a pangenome approach. Collectively this work highlights the importance the choice of reference genome makes in all variation studies.

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MoMI-G: modular multi-scale integrated genome graph browser

BMC Bioinformatics ◽

10.1186/s12859-019-3145-2 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 3

Author(s):

Toshiyuki T. Yokoyama ◽

Yoshitaka Sakamoto ◽

Masahide Seki ◽

Yutaka Suzuki ◽

Masahiro Kasahara

Keyword(s):

Human Cancer ◽

Read Depth ◽

Structural Variants ◽

Structural Variations ◽

Multi Scale ◽

Long Reads ◽

A Genome ◽

Long Read ◽

Complex Structural ◽

Genome Graph

Abstract Background Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded. Results We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1. Conclusions Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. Software availability MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

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Chromosome-length genome assembly and structural variations of the primal Basenji dog (Canis lupus familiaris) genome

10.1101/2020.11.11.379073 ◽

2020 ◽

Cited By ~ 1

Author(s):

Richard J. Edwards ◽

Matt A. Field ◽

James M. Ferguson ◽

Olga Dudchenko ◽

Jens Keilwagen ◽

...

Keyword(s):

Reference Genome ◽

De Novo ◽

Genome Structure ◽

Canis Lupus Familiaris ◽

Structural Variations ◽

German Shepherd ◽

High Quality ◽

Entire Family ◽

The Impact ◽

Reference Genomes

AbstractBackgroundBasenjis are considered an ancient dog breed of central African origins that still live and hunt with tribesmen in the African Congo. Nicknamed the barkless dog, Basenjis possess unique phylogeny, geographical origins and traits, making their genome structure of great interest. The increasing number of available canid reference genomes allows us to examine the impact the choice of reference genome makes with regard to reference genome quality and breed relatedness.ResultsHere, we report two high quality de novo Basenji genome assemblies: a female, China (CanFam_Bas), and a male, Wags. We conduct pairwise comparisons and report structural variations between assembled genomes of three dog breeds: Basenji (CanFam_Bas), Boxer (CanFam3.1) and German Shepherd Dog (GSD) (CanFam_GSD). CanFam_Bas is superior to CanFam3.1 in terms of genome contiguity and comparable overall to the high quality CanFam_GSD assembly. By aligning short read data from 58 representative dog breeds to three reference genomes, we demonstrate how the choice of reference genome significantly impacts both read mapping and variant detection.ConclusionsThe growing number of high-quality canid reference genomes means the choice of reference genome is an increasingly critical decision in subsequent canid variant analyses. The basal position of the Basenji makes it suitable for variant analysis for targeted applications of specific dog breeds. However, we believe more comprehensive analyses across the entire family of canids is more suited to a pangenome approach. Collectively this work highlights the importance the choice of reference genome makes in all variation studies.

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NovoGraph: Genome graph construction from multiple long-read de novo assemblies

F1000Research ◽

10.12688/f1000research.15895.1 ◽

2018 ◽

Vol 7 ◽

pp. 1391 ◽

Cited By ~ 1

Author(s):

Evan Biederstedt ◽

Jeffrey C. Oliver ◽

Nancy F. Hansen ◽

Aarti Jajoo ◽

Nathan Dunn ◽

...

Keyword(s):

Sequence Alignment ◽

Multiple Sequence Alignment ◽

High Throughput Sequencing ◽

De Novo ◽

Wide Spectrum ◽

Multiple Sequence ◽

Human Genomes ◽

A Genome ◽

Long Read ◽

Genome Graph

Genome graphs are emerging as an important novel approach to the analysis of high-throughput sequencing data. By explicitly representing genetic variants and alternative haplotypes in a mappable data structure, they can enable the improved analysis of structurally variable and hyperpolymorphic regions of the genome. In most existing approaches, graphs are constructed from variant call sets derived from short-read sequencing. As long-read sequencing becomes more cost-effective and enables de novo assembly for increasing numbers of whole genomes, a method for the direct construction of a genome graph from sets of assembled human genomes would be desirable. Such assembly-based genome graphs would encompass the wide spectrum of genetic variation accessible to long-read-based de novo assembly, including large structural variants and divergent haplotypes. Here we present NovoGraph, a method for the construction of a genome graph directly from a set of de novo assemblies. NovoGraph constructs a genome-wide multiple sequence alignment of all input contigs and uses a simple criterion of homologous-identical recombination to convert the multiple sequence alignment into a graph. NovoGraph outputs resulting graphs in VCF format that can be loaded into third-party genome graph toolkits. To demonstrate NovoGraph, we construct a genome graph with 23,478,835 variant sites and 30,582,795 variant alleles from de novo assemblies of seven ethnically diverse human genomes (AK1, CHM1, CHM13, HG003, HG004, HX1, NA19240). Initial evaluations show that mapping against the constructed graph reduces the average mismatch rate of reads from sample NA12878 by approximately 0.2%, albeit at a slightly increased rate of reads that remain unmapped.

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