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Guichard A, Legeai F, Tagu D, Lemaitre C. MTG-Link: leveraging barcode information from linked-reads to assemble specific loci. BMC Bioinformatics 2023; 24:284. [PMID: 37452278 PMCID: PMC10347852 DOI: 10.1186/s12859-023-05395-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 06/21/2023] [Indexed: 07/18/2023] Open
Abstract
BACKGROUND Local assembly with short and long reads has proven to be very useful in many applications: reconstruction of the sequence of a locus of interest, gap-filling in draft assemblies, as well as alternative allele reconstruction of large Structural Variants. Whereas linked-read technologies have a great potential to assemble specific loci as they provide long-range information while maintaining the power and accuracy of short-read sequencing, there is a lack of local assembly tools for linked-read data. RESULTS We present MTG-Link, a novel local assembly tool dedicated to linked-reads. The originality of the method lies in its read subsampling step which takes advantage of the barcode information contained in linked-reads mapped in flanking regions. We validated our approach on several datasets from different linked-read technologies. We show that MTG-Link is able to assemble successfully large sequences, up to dozens of Kb. We also demonstrate that the read subsampling step of MTG-Link considerably improves the local assembly of specific loci compared to other existing short-read local assembly tools. Furthermore, MTG-Link was able to fully characterize large insertion variants and deletion breakpoints in a human genome and to reconstruct dark regions in clinically-relevant human genes. It also improved the contiguity of a 1.3 Mb locus of biological interest in several individual genomes of the mimetic butterfly Heliconius numata. CONCLUSIONS MTG-Link is an efficient local assembly tool designed for different linked-read sequencing technologies. MTG-Link source code is available at https://github.com/anne-gcd/MTG-Link and as a Bioconda package.
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Affiliation(s)
- Anne Guichard
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France.
- Univ Rennes, Inria, CNRS, IRISA, 35000, Rennes, France.
| | - Fabrice Legeai
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
- Univ Rennes, Inria, CNRS, IRISA, 35000, Rennes, France
| | - Denis Tagu
- IGEPP, INRAE, Institut Agro, Univ Rennes, 35653, Le Rheu, France
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2
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Weisweiler M, Stich B. Benchmarking of structural variant detection in the tetraploid potato genome using linked-read sequencing. Genomics 2023; 115:110568. [PMID: 36702293 DOI: 10.1016/j.ygeno.2023.110568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/12/2023] [Accepted: 01/18/2023] [Indexed: 01/25/2023]
Abstract
It has recently been shown that structural variants (SV) can have a higher impact on gene expression variation compared to single nucleotide variants (SNV) in different plant species. Additionally, SV were associated with phenotypic variation in several crops. However, compared to the established SV detection based on short-read sequencing, less approaches were described for linked-read based SV calling. We therefore evaluated the performance of six linked-read SV callers compared to an established short-read SV caller based on simulated linked-reads in tetraploid potato. The objectives of our study were to i) compare the performance of SV callers based on linked-read sequencing to short-read sequencing, ii) examine the influence of SV type, SV length, haplotype incidence (HI), as well as sequencing coverage on the SV calling performance in the tetraploid potato genome, and iii) evaluate the accuracy of detecting insertions by linked-read compared to short-read sequencing. We observed high break point resolutions (BPR) detecting short SV and slightly lower BPR for large SV. Our observations highlighted the importance of short-read signals provided by Manta and LinkedSV to detect short SV. Manta and NAIBR performed well for detecting larger deletions, inversions, and duplications. Detected large SV were weakly influenced by the HI. Furthermore, we illustrated that large insertions can be assembled by Novel-X. Our results suggest the usage of the short-read and linked-read SV callers Manta, NAIBR, LinkedSV, and Novel-X based on at least 90x linked-read sequencing coverage to ensure the detection of a broad range of SV in the tetraploid potato genome.
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Affiliation(s)
- Marius Weisweiler
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany
| | - Benjamin Stich
- Institute for Quantitative Genetics and Genomics of Plants, Universitätsstraße 1, 40225 Düsseldorf, Germany; Cluster of Excellence on Plant Sciences, From Complex Traits towards Synthetic Modules, Universitätsstraße 1, 40225 Düsseldorf, Germany; Max Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Köln, Germany.
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3
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Meleshko D, Yang R, Marks P, Williams S, Hajirasouliha I. Efficient detection and assembly of non-reference DNA sequences with synthetic long reads. Nucleic Acids Res 2022; 50:e108. [PMID: 35924489 PMCID: PMC9561269 DOI: 10.1093/nar/gkac653] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/10/2022] [Accepted: 08/01/2022] [Indexed: 11/14/2022] Open
Abstract
Recent pan-genome studies have revealed an abundance of DNA sequences in human genomes that are not present in the reference genome. A lion's share of these non-reference sequences (NRSs) cannot be reliably assembled or placed on the reference genome. Improvements in long-read and synthetic long-read (aka linked-read) technologies have great potential for the characterization of NRSs. While synthetic long reads require less input DNA than long-read datasets, they are algorithmically more challenging to use. Except for computationally expensive whole-genome assembly methods, there is no synthetic long-read method for NRS detection. We propose a novel integrated alignment-based and local assembly-based algorithm, Novel-X, that uses the barcode information encoded in synthetic long reads to improve the detection of such events without a whole-genome de novo assembly. Our evaluations demonstrate that Novel-X finds many non-reference sequences that cannot be found by state-of-the-art short-read methods. We applied Novel-X to a diverse set of 68 samples from the Polaris HiSeq 4000 PGx cohort. Novel-X discovered 16 691 NRS insertions of size > 300 bp (total length 18.2 Mb). Many of them are population specific or may have a functional impact.
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Affiliation(s)
- Dmitry Meleshko
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medical College, NY 10021, USA.,Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, NY 10021, USA
| | - Rui Yang
- Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medical College, NY 10021, USA.,Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, NY 10021, USA
| | - Patrick Marks
- 10x Genomics Inc., Stoneridge Mall Road, Pleasanton, CA 94566, USA
| | - Stephen Williams
- 10x Genomics Inc., Stoneridge Mall Road, Pleasanton, CA 94566, USA
| | - Iman Hajirasouliha
- Institute for Computational Biomedicine, Department of Physiology and Biophysics, Weill Cornell Medicine of Cornell University, NY 10021, USA.,Englander Institute for Precision Medicine, The Meyer Cancer Center, Weill Cornell Medicine, NY 10021, USA
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4
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Manthey JD, Girón JC, Hruska JP. Impact of host demography and evolutionary history on endosymbiont molecular evolution: A test in carpenter ants (genus Camponotus) and their Blochmannia endosymbionts. Ecol Evol 2022; 12:e9026. [PMID: 35795355 PMCID: PMC9251289 DOI: 10.1002/ece3.9026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 11/28/2022] Open
Abstract
Obligate endosymbioses are tight associations between symbionts and the hosts they live inside. Hosts and their associated obligate endosymbionts generally exhibit codiversification, which has been documented in taxonomically diverse insect lineages. Host demography (e.g., effective population sizes) may impact the demography of endosymbionts, which may lead to an association between host demography and the patterns and processes of endosymbiont molecular evolution. Here, we used whole-genome sequencing data for carpenter ants (Genus Camponotus; subgenera Camponotus and Tanaemyrmex) and their Blochmannia endosymbionts as our study system to address whether Camponotus demography shapes Blochmannia molecular evolution. Using whole-genome phylogenomics, we confirmed previous work identifying codiversification between carpenter ants and their Blochmannia endosymbionts. We found that Blochmannia genes have evolved at a pace ~30× faster than that of their hosts' molecular evolution and that these rates are positively associated with host rates of molecular evolution. Using multiple tests for selection in Blochmannia genes, we found signatures of positive selection and shifts in selection strength across the phylogeny. Host demography was associated with Blochmannia shifts toward increased selection strengths, but not associated with Blochmannia selection relaxation, positive selection, genetic drift rates, or genome size evolution. Mixed support for relationships between host effective population sizes and Blochmannia molecular evolution suggests weak or uncoupled relationships between host demography and Blochmannia population genomic processes. Finally, we found that Blochmannia genome size evolution was associated with genome-wide estimates of genetic drift and number of genes with relaxed selection pressures.
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Affiliation(s)
- Joseph D. Manthey
- Department of Biological SciencesTexas Tech UniversityLubbockTexasUSA
| | - Jennifer C. Girón
- Department of EntomologyPurdue UniversityWest LafayetteIndianaUSA
- Natural Science Research LaboratoryMuseum of Texas Tech UniversityLubbockTexasUSA
| | - Jack P. Hruska
- Department of Biological SciencesTexas Tech UniversityLubbockTexasUSA
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Lei Y, Meng Y, Guo X, Ning K, Bian Y, Li L, Hu Z, Anashkina AA, Jiang Q, Dong Y, Zhu X. Overview of structural variation calling: Simulation, identification, and visualization. Comput Biol Med 2022; 145:105534. [DOI: 10.1016/j.compbiomed.2022.105534] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 04/09/2022] [Accepted: 04/14/2022] [Indexed: 12/11/2022]
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Yang L. Meerkat: An Algorithm to Reliably Identify Structural Variations and Predict Their Forming Mechanisms. Methods Mol Biol 2022; 2493:107-135. [PMID: 35751812 PMCID: PMC11079867 DOI: 10.1007/978-1-0716-2293-3_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Next-generation sequencing technologies have been widely used to query genetic variants in normal individuals as well as in those with diseases. Large-scale structural variations are a common source of genetic diversity in human population, and some of them have significant contributions to the etiology of diseases. However, the detection of large-scale structural variations from sequencing data remains challenging. Here, we describe Meerkat-an algorithm which can reliably detect structural variations from Illumina short-read sequencing data at basepair resolution. A unique feature of Meerkat is that it can infer the variant forming mechanisms based on the DNA content and features at the breakpoints.
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Affiliation(s)
- Lixing Yang
- Ben May Department for Cancer Research, Department of Human Genetics, Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
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7
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Krannich T, White WTJ, Niehus S, Holley G, Halldórsson BV, Kehr B. Population-scale detection of non-reference sequence variants using colored de Bruijn graphs. Bioinformatics 2021; 38:604-611. [PMID: 34726732 PMCID: PMC8756200 DOI: 10.1093/bioinformatics/btab749] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 09/27/2021] [Accepted: 10/28/2021] [Indexed: 02/03/2023] Open
Abstract
MOTIVATION With the increasing throughput of sequencing technologies, structural variant (SV) detection has become possible across tens of thousands of genomes. Non-reference sequence (NRS) variants have drawn less attention compared with other types of SVs due to the computational complexity of detecting them. When using short-read data, the detection of NRS variants inevitably involves a de novo assembly which requires high-quality sequence data at high coverage. Previous studies have demonstrated how sequence data of multiple genomes can be combined for the reliable detection of NRS variants. However, the algorithms proposed in these studies have limited scalability to larger sets of genomes. RESULTS We introduce PopIns2, a tool to discover and characterize NRS variants in many genomes, which scales to considerably larger numbers of genomes than its predecessor PopIns. In this article, we briefly outline the PopIns2 workflow and highlight our novel algorithmic contributions. We developed an entirely new approach for merging contig assemblies of unaligned reads from many genomes into a single set of NRS using a colored de Bruijn graph. Our tests on simulated data indicate that the new merging algorithm ranks among the best approaches in terms of quality and reliability and that PopIns2 shows the best precision for a growing number of genomes processed. Results on the Polaris Diversity Cohort and a set of 1000 Icelandic human genomes demonstrate unmatched scalability for the application on population-scale datasets. AVAILABILITY AND IMPLEMENTATION The source code of PopIns2 is available from https://github.com/kehrlab/PopIns2. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | - Sebastian Niehus
- Regensburg Center for Interventional Immunology (RCI), 93053 Regensburg, Germany
| | | | - Bjarni V Halldórsson
- deCODE Genetics, Reykjavík 102, Iceland,Department of Engineering, School of Technology, Reykjavík University, Reykjavík 102, Iceland
| | - Birte Kehr
- To whom correspondence should be addressed. or
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Yuan X, Xu X, Zhao H, Duan J. ERINS: Novel Sequence Insertion Detection by Constructing an Extended Reference. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021; 18:1893-1901. [PMID: 31751246 DOI: 10.1109/tcbb.2019.2954315] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Next generation sequencing technology has led to the development of methods for the detection of novel sequence insertions (nsINS). Multiple signatures from short reads are usually extracted to improve nsINS detection performance. However, characterization of nsINSs larger than the mean insert size is still challenging. This article presents a new method, ERINS, to detect nsINS contents and genotypes of full spectrum range size. It integrates the features of structural variations and mapping states of split reads to find nsINS breakpoints, and then adopts a left-most mapping strategy to infer nsINS content by iteratively extending the standard reference at each breakpoint. Finally, it realigns all reads to the extended reference and infers nsINS genotypes through statistical testing on read counts. We test and validate the performance of ERINS on simulation and real sequencing datasets. The simulation experimental results demonstrate that it outperforms several peer methods with respect to sensitivity and precision. The real data application indicates that ERINS obtains high consistent results with those of previously reported and detects nsINSs over 200 base pairs that many other methods fail. In conclusion, ERINS can be used as a supplement to existing tools and will become a routine approach for characterizing nsINSs.
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9
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Yan C, He J, Luo J, Wang J, Zhang G, Luo H. SIns: A Novel Insertion Detection Approach Based on Soft-Clipped Reads. Front Genet 2021; 12:665812. [PMID: 33995493 PMCID: PMC8120196 DOI: 10.3389/fgene.2021.665812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
As a common type of structural variation, an insertion refers to the addition of a DNA sequence into an individual genome and is usually associated with some inherited diseases. In recent years, many methods have been proposed for detecting insertions. However, the accurate calling of insertions is also a challenging task. In this study, we propose a novel insertion detection approach based on soft-clipped reads, which is called SIns. First, based on the alignments between paired reads and the reference genome, SIns extracts breakpoints from soft-clipped reads and determines insertion locations. The insert size information about paired reads is then further clustered to determine the genotype, and SIns subsequently adopts Minia to assemble the insertion sequences. Experimental results show that SIns can achieve better performance than other methods in terms of the F-score value for simulated and true datasets.
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Affiliation(s)
- Chaokun Yan
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Junyi He
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Junwei Luo
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Jianlin Wang
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Ge Zhang
- School of Computer and Information Engineering, Henan University, Kaifeng, China
| | - Huimin Luo
- School of Computer and Information Engineering, Henan University, Kaifeng, China
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10
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Nam K, Nhim S, Robin S, Bretaudeau A, Nègre N, d'Alençon E. Positive selection alone is sufficient for whole genome differentiation at the early stage of speciation process in the fall armyworm. BMC Evol Biol 2020; 20:152. [PMID: 33187468 PMCID: PMC7663868 DOI: 10.1186/s12862-020-01715-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 10/28/2020] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The process of speciation involves differentiation of whole genome sequences between a pair of diverging taxa. In the absence of a geographic barrier and in the presence of gene flow, genomic differentiation may occur when the homogenizing effect of recombination is overcome across the whole genome. The fall armyworm is observed as two sympatric strains with different host-plant preferences across the entire habitat. These two strains exhibit a very low level of genetic differentiation across the whole genome, suggesting that genomic differentiation occurred at an early stage of speciation. In this study, we aim at identifying critical evolutionary forces responsible for genomic differentiation in the fall armyworm. RESULTS These two strains exhibit a low level of genomic differentiation (FST = 0.0174), while 99.2% of 200 kb windows have genetically differentiated sequences (FST > 0). We found that the combined effect of mild positive selection and genetic linkage to selectively targeted loci are responsible for the genomic differentiation. However, a single event of very strong positive selection appears not to be responsible for genomic differentiation. The contribution of chromosomal inversions or tight genetic linkage among positively selected loci causing reproductive barriers is not supported by our data. Phylogenetic analysis shows that the genomic differentiation occurred by sub-setting of genetic variants in one strain from the other. CONCLUSIONS From these results, we concluded that genomic differentiation may occur at the early stage of a speciation process in the fall armyworm and that mild positive selection targeting many loci alone is sufficient evolutionary force for generating the pattern of genomic differentiation. This genomic differentiation may provide a condition for accelerated genomic differentiation by synergistic effects among linkage disequilibrium generated by following events of positive selection. Our study highlights genomic differentiation as a key evolutionary factor connecting positive selection to divergent selection.
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Affiliation(s)
- Kiwoong Nam
- DGIMI, Univ Montpellier, INRAE, Montpellier, France.
| | - Sandra Nhim
- DGIMI, Univ Montpellier, INRAE, Montpellier, France
| | - Stéphanie Robin
- INRAE, UMR-IGEPP, BioInformatics Platform for Agroecosystems Arthropods, Campus Beaulieu, Rennes, France
- INRIA, IRISA, GenOuest Core Facility, Campus de Beaulieu, Rennes, France
| | - Anthony Bretaudeau
- INRAE, UMR-IGEPP, BioInformatics Platform for Agroecosystems Arthropods, Campus Beaulieu, Rennes, France
- INRIA, IRISA, GenOuest Core Facility, Campus de Beaulieu, Rennes, France
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Lee YG, Lee JY, Kim J, Kim YJ. Insertion variants missing in the human reference genome are widespread among human populations. BMC Biol 2020; 18:167. [PMID: 33187521 PMCID: PMC7666470 DOI: 10.1186/s12915-020-00894-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 10/09/2020] [Indexed: 01/07/2023] Open
Abstract
Background Structural variants comprise diverse genomic arrangements including deletions, insertions, inversions, and translocations, which can generally be detected in humans through sequence comparison to the reference genome. Among structural variants, insertions are the least frequently identified variants, mainly due to ascertainment bias in the reference genome, lack of previous sequence knowledge, and low complexity of typical insertion sequences. Though recent developments in long-read sequencing deliver promise in annotating individual non-reference insertions, population-level catalogues on non-reference insertion variants have not been identified and the possible functional roles of these hidden variants remain elusive. Results To detect non-reference insertion variants, we developed a pipeline, InserTag, which generates non-reference contigs by local de novo assembly and then infers the full-sequence of insertion variants by tracing contigs from non-human primates and other human genome assemblies. Application of the pipeline to data from 2535 individuals of the 1000 Genomes Project helped identify 1696 non-reference insertion variants and re-classify the variants as retention of ancestral sequences or novel sequence insertions based on the ancestral state. Genotyping of the variants showed that individuals had, on average, 0.92-Mbp sequences missing from the reference genome, 92% of the variants were common (allele frequency > 5%) among human populations, and more than half of the variants were major alleles. Among human populations, African populations were the most divergent and had the most non-reference sequences, which was attributed to the greater prevalence of high-frequency insertion variants. The subsets of insertion variants were in high linkage disequilibrium with phenotype-associated SNPs and showed signals of recent continent-specific selection. Conclusions Non-reference insertion variants represent an important type of genetic variation in the human population, and our developed pipeline, InserTag, provides the frameworks for the detection and genotyping of non-reference sequences missing from human populations. Supplementary information Supplementary information accompanies this paper at 10.1186/s12915-020-00894-1.
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Affiliation(s)
- Young-Gun Lee
- Department of Integrated Omics for Biomedical Science, WCU Graduate School, Yonsei University, Seoul, Republic of Korea
| | - Jin-Young Lee
- Department of Biochemistry, College of Life Science and Technology, Yonsei University, Seoul, Republic of Korea
| | - Junhyong Kim
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Young-Joon Kim
- Department of Integrated Omics for Biomedical Science, WCU Graduate School, Yonsei University, Seoul, Republic of Korea. .,Department of Biochemistry, College of Life Science and Technology, Yonsei University, Seoul, Republic of Korea.
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12
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Delage WJ, Thevenon J, Lemaitre C. Towards a better understanding of the low recall of insertion variants with short-read based variant callers. BMC Genomics 2020; 21:762. [PMID: 33148192 PMCID: PMC7640490 DOI: 10.1186/s12864-020-07125-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/06/2020] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Since 2009, numerous tools have been developed to detect structural variants using short read technologies. Insertions >50 bp are one of the hardest type to discover and are drastically underrepresented in gold standard variant callsets. The advent of long read technologies has completely changed the situation. In 2019, two independent cross technologies studies have published the most complete variant callsets with sequence resolved insertions in human individuals. Among the reported insertions, only 17 to 28% could be discovered with short-read based tools. RESULTS In this work, we performed an in-depth analysis of these unprecedented insertion callsets in order to investigate the causes of such failures. We have first established a precise classification of insertion variants according to four layers of characterization: the nature and size of the inserted sequence, the genomic context of the insertion site and the breakpoint junction complexity. Because these levels are intertwined, we then used simulations to characterize the impact of each complexity factor on the recall of several structural variant callers. We showed that most reported insertions exhibited characteristics that may interfere with their discovery: 63% were tandem repeat expansions, 38% contained homology larger than 10 bp within their breakpoint junctions and 70% were located in simple repeats. Consequently, the recall of short-read based variant callers was significantly lower for such insertions (6% for tandem repeats vs 56% for mobile element insertions). Simulations showed that the most impacting factor was the insertion type rather than the genomic context, with various difficulties being handled differently among the tested structural variant callers, and they highlighted the lack of sequence resolution for most insertion calls. CONCLUSIONS Our results explain the low recall by pointing out several difficulty factors among the observed insertion features and provide avenues for improving SV caller algorithms and their combinations.
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Affiliation(s)
| | - Julien Thevenon
- Inserm U1209, CNRS UMR 5309, Univ. Grenoble Alpes, Institute for Advanced Biosciences, Grenoble, France & Genetics, Genomics and Reproduction Service, Centre Hospitalo-Universitaire Grenoble-Alpes, Grenoble, France
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13
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Godfroid M, Dagan T, Merker M, Kohl TA, Diel R, Maurer FP, Niemann S, Kupczok A. Insertion and deletion evolution reflects antibiotics selection pressure in a Mycobacterium tuberculosis outbreak. PLoS Pathog 2020; 16:e1008357. [PMID: 32997707 PMCID: PMC7549793 DOI: 10.1371/journal.ppat.1008357] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 10/12/2020] [Accepted: 08/18/2020] [Indexed: 11/18/2022] Open
Abstract
In genome evolution, genetic variants are the source of diversity, which natural selection acts upon. Treatment of human tuberculosis (TB) induces a strong selection pressure for the emergence of antibiotic resistance-conferring variants in the infecting Mycobacterium tuberculosis (MTB) strains. MTB evolution in response to treatment has been intensively studied and mainly attributed to point substitutions. However, the frequency and contribution of insertions and deletions (indels) to MTB genome evolution remains poorly understood. Here, we analyzed a multi-drug resistant MTB outbreak for the presence of high-quality indels and substitutions. We find that indels are significantly enriched in genes conferring antibiotic resistance. Furthermore, we show that indels are inherited during the outbreak and follow a molecular clock with an evolutionary rate of 5.37e-9 indels/site/year, which is 23 times lower than the substitution rate. Inherited indels may co-occur with substitutions in genes along related biological pathways; examples are iron storage and resistance to second-line antibiotics. This suggests that epistatic interactions between indels and substitutions affect antibiotic resistance and compensatory evolution in MTB.
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Affiliation(s)
- Maxime Godfroid
- Institute of General Microbiology, Kiel University, Kiel, Germany
| | - Tal Dagan
- Institute of General Microbiology, Kiel University, Kiel, Germany
| | - Matthias Merker
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Thomas A. Kohl
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Roland Diel
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
- Institute for Epidemiology, University Medical Hospital Schleswig-Holstein, Kiel, Germany
- Lungenclinic Grosshansdorf, Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Großhansdorf, Germany
| | - Florian P. Maurer
- National and WHO Supranational Reference Center for Mycobacteria, Research Center Borstel, Borstel, Germany
- Institute of Medical Microbiology, Virology and Hygiene, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Niemann
- Molecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany
- German Center for Infection Research, Partner Site Hamburg-Lübeck-Borstel-Riems, Borstel, Germany
| | - Anne Kupczok
- Institute of General Microbiology, Kiel University, Kiel, Germany
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Langa J, Estonba A, Conklin D. EXFI: Exon and splice graph prediction without a reference genome. Ecol Evol 2020; 10:8880-8893. [PMID: 32884664 PMCID: PMC7452765 DOI: 10.1002/ece3.6587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 06/03/2020] [Accepted: 06/08/2020] [Indexed: 11/19/2022] Open
Abstract
For population genetic studies in nonmodel organisms, it is important to use every single source of genomic information. This paper presents EXFI, a Python pipeline that predicts the splice graph and exon sequences using an assembled transcriptome and raw whole-genome sequencing reads. The main algorithm uses Bloom filters to remove reads that are not part of the transcriptome, to predict the intron-exon boundaries, to then proceed to call exons from the assembly, and to generate the underlying splice graph. The results are returned in GFA1 format, which encodes both the predicted exon sequences and how they are connected to form transcripts. EXFI is written in Python, tested on Linux platforms, and the source code is available under the MIT License at https://github.com/jlanga/exfi.
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Affiliation(s)
- Jorge Langa
- Department of Genetics, Physical Anthropology and Animal PhysiologyFaculty of Science and TechnologyUniversity of the Basque CountryLeioaSpain
| | - Andone Estonba
- Department of Genetics, Physical Anthropology and Animal PhysiologyFaculty of Science and TechnologyUniversity of the Basque CountryLeioaSpain
| | - Darrell Conklin
- Department of Computer Science and Artificial Intelligence, Faculty of Computer ScienceUniversity of the Basque Country UPV/EHUSan SebastiánSpain
- IKERBASQUE, Basque Foundation for ScienceBilbaoSpain
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15
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Guyomar C, Delage W, Legeai F, Mougel C, Simon JC, Lemaitre C. MinYS: mine your symbiont by targeted genome assembly in symbiotic communities. NAR Genom Bioinform 2020; 2:lqaa047. [PMID: 33575599 PMCID: PMC7671366 DOI: 10.1093/nargab/lqaa047] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 05/20/2020] [Accepted: 06/17/2020] [Indexed: 12/17/2022] Open
Abstract
Most metazoans are associated with symbionts. Characterizing the effect of a particular symbiont often requires getting access to its genome, which is usually done by sequencing the whole community. We present MinYS, a targeted assembly approach to assemble a 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, enabling different strains with potential structural variants coexisting in the sample to be distinguished. MinYS was applied to 50 pea aphid resequencing samples, with variable diversity in symbiont communities, 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. Because of its targeted essence, it outperformed standard metagenomic assemblers in terms of both time and assembly quality.
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Affiliation(s)
- Cervin Guyomar
- Univ. Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France
| | - Wesley Delage
- Univ. Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France
| | - Fabrice Legeai
- Institut de Génétique, Environnement et Protection des Plantes (IGEPP), INRAE, Institut Agro, Univ. Rennes, F-35653 Le Rheu, France
| | - Christophe Mougel
- Institut de Génétique, Environnement et Protection des Plantes (IGEPP), INRAE, Institut Agro, Univ. Rennes, F-35653 Le Rheu, France
| | - Jean-Christophe Simon
- Institut de Génétique, Environnement et Protection des Plantes (IGEPP), INRAE, Institut Agro, Univ. Rennes, F-35653 Le Rheu, France
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16
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Feldman D, Kowbel DJ, Cohen A, Glass NL, Hadar Y, Yarden O. Identification and manipulation of Neurospora crassa genes involved in sensitivity to furfural. BIOTECHNOLOGY FOR BIOFUELS 2019; 12:210. [PMID: 31508149 PMCID: PMC6724289 DOI: 10.1186/s13068-019-1550-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 08/24/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Biofuels derived from lignocellulosic biomass are a viable alternative to fossil fuels required for transportation. Following plant biomass pretreatment, the furan derivative furfural is present at concentrations which are inhibitory to yeasts. Detoxification of furfural is thus important for efficient fermentation. Here, we searched for new genetic attributes in the fungus Neurospora crassa that may be linked to furfural tolerance. The fact that furfural is involved in the natural process of sexual spore germination of N. crassa and that this fungus is highly amenable to genetic manipulations makes it a rational candidate for this study. RESULTS Both hypothesis-based and unbiased (random promotor mutagenesis) approaches were performed to identify N. crassa genes associated with the response to furfural. Changes in the transcriptional profile following exposure to furfural revealed that the affected processes were, overall, similar to those observed in Saccharomyces cerevisiae. N. crassa was more tolerant (by ~ 30%) to furfural when carboxymethyl cellulose was the main carbon source as opposed to sucrose, indicative of a link between carbohydrate metabolism and furfural tolerance. We also observed increased tolerance in a Δcre-1 mutant (CRE-1 is a key transcription factor that regulates the ability of fungi to utilize non-preferred carbon sources). In addition, analysis of aldehyde dehydrogenase mutants showed that ahd-2 (NCU00378) was involved in tolerance to furfural as well as the predicted membrane transporter NCU05580 (flr-1), a homolog of FLR1 in S. cerevisiae. Further to the rational screening, an unbiased approach revealed additional genes whose inactivation conferred increased tolerance to furfural: (i) NCU02488, which affected the abundance of the non-anchored cell wall protein NCW-1 (NCU05137), and (ii) the zinc finger protein NCU01407. CONCLUSIONS We identified attributes in N. crassa associated with tolerance or degradation of furfural, using complementary research approaches. The manipulation of the genes involved in furan sensitivity can provide a means for improving the production of biofuel producing strains. Similar research approaches can be utilized in N. crassa and other filamentous fungi to identify additional attributes relevant to other furans or toxic chemicals.
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Affiliation(s)
- Daria Feldman
- Department of Plant Pathology and Microbiology, The R.H. Smith Faculty Agriculture, Food and Environment, The Hebrew University of Jerusalem, 7600001 Rehovot, Israel
| | - David J. Kowbel
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720 USA
| | - Adi Cohen
- Department of Plant Pathology and Microbiology, The R.H. Smith Faculty Agriculture, Food and Environment, The Hebrew University of Jerusalem, 7600001 Rehovot, Israel
| | - N. Louise Glass
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720 USA
- Environmental Genomics and Systems Biology Division, The Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA
| | - Yitzhak Hadar
- Department of Plant Pathology and Microbiology, The R.H. Smith Faculty Agriculture, Food and Environment, The Hebrew University of Jerusalem, 7600001 Rehovot, Israel
| | - Oded Yarden
- Department of Plant Pathology and Microbiology, The R.H. Smith Faculty Agriculture, Food and Environment, The Hebrew University of Jerusalem, 7600001 Rehovot, Israel
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17
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Fuentes RR, Chebotarov D, Duitama J, Smith S, De la Hoz JF, Mohiyuddin M, Wing RA, McNally KL, Tatarinova T, Grigoriev A, Mauleon R, Alexandrov N. Structural variants in 3000 rice genomes. Genome Res 2019; 29:870-880. [PMID: 30992303 PMCID: PMC6499320 DOI: 10.1101/gr.241240.118] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 03/11/2019] [Indexed: 12/24/2022]
Abstract
Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 million individual SV calls that grouped into 1.5 million allelic variants. We found enrichment of long SVs in promoters and an excess of shorter variants in 5′ UTRs. Across the rice genomes, we identified regions of high SV frequency enriched in stress response genes. We demonstrated how SVs may help in finding causative variants in genome-wide association analysis. These new insights into rice genome biology are valuable for understanding the effects SVs have on gene function, with the prospect of identifying novel agronomically important alleles that can be utilized to improve cultivated rice.
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Affiliation(s)
- Roven Rommel Fuentes
- International Rice Research Institute, Laguna 4031, Philippines.,Bioinformatics Group, Wageningen University and Research, 6708 PB Wageningen, the Netherlands
| | | | - Jorge Duitama
- Systems and Computing Engineering Department, Universidad de Los Andes, Bogotá 111711, Colombia.,Agrobiodiversity Research Area, International Center for Tropical Agriculture (CIAT), Cali 6713, Colombia
| | - Sean Smith
- Biology Department, Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey 08102, USA
| | - Juan Fernando De la Hoz
- Agrobiodiversity Research Area, International Center for Tropical Agriculture (CIAT), Cali 6713, Colombia
| | | | - Rod A Wing
- International Rice Research Institute, Laguna 4031, Philippines.,Arizona Genomics Institute, University of Arizona, Tucson, Arizona 85721, USA.,King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | | | - Tatiana Tatarinova
- Department of Biology, University of La Verne, La Verne, California 91750, USA.,Vavilov Institute of General Genetics, Moscow 119333, Russia.,A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow 127051, Russia.,Laboratory of Forest Genomics, Siberian Federal University, Krasnoyarsk 660041, Russia
| | - Andrey Grigoriev
- Biology Department, Center for Computational and Integrative Biology, Rutgers University, Camden, New Jersey 08102, USA
| | - Ramil Mauleon
- International Rice Research Institute, Laguna 4031, Philippines
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18
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Daval S, Belcour A, Gazengel K, Legrand L, Gouzy J, Cottret L, Lebreton L, Aigu Y, Mougel C, Manzanares-Dauleux MJ. Computational analysis of the Plasmodiophora brassicae genome: mitochondrial sequence description and metabolic pathway database design. Genomics 2018; 111:1629-1640. [PMID: 30447277 DOI: 10.1016/j.ygeno.2018.11.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 09/23/2018] [Accepted: 11/12/2018] [Indexed: 10/27/2022]
Abstract
Plasmodiophora brassicae is an obligate biotrophic pathogenic protist responsible for clubroot, a root gall disease of Brassicaceae species. In addition to the reference genome of the P. brassicae European e3 isolate and the draft genomes of Canadian or Chinese isolates, we present the genome of eH, a second European isolate. Refinement of the annotation of the eH genome led to the identification of the mitochondrial genome sequence, which was found to be bigger than that of Spongospora subterranea, another plant parasitic Plasmodiophorid phylogenetically related to P. brassicae. New pathways were also predicted, such as those for the synthesis of spermidine, a polyamine up-regulated in clubbed regions of roots. A P. brassicae pathway genome database was created to facilitate the functional study of metabolic pathways in transcriptomics approaches. These available tools can help in our understanding of the regulation of P. brassicae metabolism during infection and in response to diverse constraints.
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Affiliation(s)
- Stéphanie Daval
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France.
| | - Arnaud Belcour
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France
| | - Kévin Gazengel
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France
| | - Ludovic Legrand
- LIPM, INRA, CNRS, Université de Toulouse, Castanet Tolosan, France
| | - Jérôme Gouzy
- LIPM, INRA, CNRS, Université de Toulouse, Castanet Tolosan, France
| | - Ludovic Cottret
- LIPM, INRA, CNRS, Université de Toulouse, Castanet Tolosan, France
| | - Lionel Lebreton
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France
| | - Yoann Aigu
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France
| | - Christophe Mougel
- IGEPP, INRA, AGROCAMPUS OUEST, Université Rennes, Domaine de la Motte, Le Rheu F-35653, France
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19
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Guyomar C, Legeai F, Jousselin E, Mougel C, Lemaitre C, Simon JC. Multi-scale characterization of symbiont diversity in the pea aphid complex through metagenomic approaches. MICROBIOME 2018; 6:181. [PMID: 30305166 PMCID: PMC6180509 DOI: 10.1186/s40168-018-0562-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Accepted: 09/20/2018] [Indexed: 05/27/2023]
Abstract
BACKGROUND Most metazoans are involved in durable relationships with microbes which can take several forms, from mutualism to parasitism. The advances of NGS technologies and bioinformatics tools have opened opportunities to shed light on the diversity of microbial communities and to give some insights into the functions they perform in a broad array of hosts. The pea aphid is a model system for the study of insect-bacteria symbiosis. It is organized in a complex of biotypes, each adapted to specific host plants. It harbors both an obligatory symbiont supplying key nutrients and several facultative symbionts bringing additional functions to the host, such as protection against biotic and abiotic stresses. However, little is known on how the symbiont genomic diversity is structured at different scales: across host biotypes, among individuals of the same biotype, or within individual aphids, which limits our understanding on how these multi-partner symbioses evolve and interact. RESULTS We present a framework well adapted to the study of genomic diversity and evolutionary dynamics of the pea aphid holobiont from metagenomic read sets, based on mapping to reference genomes and whole genome variant calling. Our results revealed that the pea aphid microbiota is dominated by a few heritable bacterial symbionts reported in earlier works, with no discovery of new microbial associates. However, we detected a large and heterogeneous genotypic diversity associated with the different symbionts of the pea aphid. Partitioning analysis showed that this fine resolution diversity is distributed across the three considered scales. Phylogenetic analyses highlighted frequent horizontal transfers of facultative symbionts between host lineages, indicative of flexible associations between the pea aphid and its microbiota. However, the evolutionary dynamics of symbiotic associations strongly varied depending on the symbiont, reflecting different histories and possible constraints. In addition, at the intra-host scale, we showed that different symbiont strains may coexist inside the same aphid host. CONCLUSIONS We present a methodological framework for the detailed analysis of NGS data from microbial communities of moderate complexity and gave major insights into the extent of diversity in pea aphid-symbiont associations and the range of evolutionary trajectories they could take.
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Affiliation(s)
- Cervin Guyomar
- INRA, UMR 1349 INRA/Agrocampus Ouest/Université Rennes 1, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Le Rheu, France
- Université Rennes 1, Inria, CNRS, IRISA, F-35000, Rennes, France
| | - Fabrice Legeai
- INRA, UMR 1349 INRA/Agrocampus Ouest/Université Rennes 1, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Le Rheu, France
- Université Rennes 1, Inria, CNRS, IRISA, F-35000, Rennes, France
| | - Emmanuelle Jousselin
- INRA, UMR CBGP (INRA/IRD/Cirad/Montpellier SupAgro), Campus International de Baillarguet, Montpellier, France
| | - Christophe Mougel
- INRA, UMR 1349 INRA/Agrocampus Ouest/Université Rennes 1, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Le Rheu, France
| | - Claire Lemaitre
- Université Rennes 1, Inria, CNRS, IRISA, F-35000, Rennes, France
| | - Jean-Christophe Simon
- INRA, UMR 1349 INRA/Agrocampus Ouest/Université Rennes 1, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Le Rheu, France.
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20
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Carrier G, Baroukh C, Rouxel C, Duboscq-Bidot L, Schreiber N, Bougaran G. Draft genomes and phenotypic characterization of Tisochrysis lutea strains. Toward the production of domesticated strains with high added value. ALGAL RES 2018. [DOI: 10.1016/j.algal.2017.10.017] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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21
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Abstract
Although recent developments in DNA sequencing have allowed for great leaps in both the quality and quantity of genome assembly projects, de novo assemblies still lack the efficiency and accuracy required for studying genetic variation of individuals. Thus, efficient and accurate methods for calling and genotyping genetic variants are fundamental to studying the genomes of individuals. We study the problem of genotyping insertion variants. We assume that the location of the insertion is given, and the task is to find the insertion sequence. Insertions are the hardest structural variant to genotype, because the insertion sequence must be assembled from the reads, whereas genotyping other structural variants only requires transformations of the reference genome. The current methods for constructing insertion variants are mostly linked to variation calling methods and are only able to construct small insertions. A sub-problem in genome assembly, the gap filling problem, provides techniques that are readily applicable to insertion genotyping. Gap filling takes the context and length of a missing sequence in a genome assembly and attempts to assemble the intervening sequence. In this paper we show how tools and methods for gap filling can be used to assemble insertion variants by modeling the problem of insertion genotyping as filling gaps in the reference genome. We further give a general read filtering scheme to make the method scalable to large data sets. Our results show that gap filling methods are competitive against insertion genotyping tools. We further show that read filtering improves performance of insertion genotyping especially for long insertions. Our experiments show that on long insertions the new proposed method is the most accurate one, whereas on short insertions it has comparable performance as compared against existing tools.
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Affiliation(s)
- Riku Walve
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - Leena Salmela
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - Veli Mäkinen
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
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22
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Kavak P, Lin YY, Numanagić I, Asghari H, Güngör T, Alkan C, Hach F. Discovery and genotyping of novel sequence insertions in many sequenced individuals. Bioinformatics 2017; 33:i161-i169. [PMID: 28881988 PMCID: PMC5870608 DOI: 10.1093/bioinformatics/btx254] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
MOTIVATION Despite recent advances in algorithms design to characterize structural variation using high-throughput short read sequencing (HTS) data, characterization of novel sequence insertions longer than the average read length remains a challenging task. This is mainly due to both computational difficulties and the complexities imposed by genomic repeats in generating reliable assemblies to accurately detect both the sequence content and the exact location of such insertions. Additionally, de novo genome assembly algorithms typically require a very high depth of coverage, which may be a limiting factor for most genome studies. Therefore, characterization of novel sequence insertions is not a routine part of most sequencing projects. RESULT Here, we present Pamir, a new algorithm to efficiently and accurately discover and genotype novel sequence insertions using either single or multiple genome sequencing datasets. Pamir is able to detect breakpoint locations of the insertions and calculate their zygosity (i.e. heterozygous versus homozygous) by analyzing multiple sequence signatures, matching one-end-anchored sequences to small-scale de novo assemblies of unmapped reads, and conducting strand-aware local assembly. We test the efficacy of Pamir on both simulated and real data, and demonstrate its potential use in accurate and routine identification of novel sequence insertions in genome projects. AVAILABILITY AND IMPLEMENTATION Pamir is available at https://github.com/vpc-ccg/pamir . CONTACT fhach@{sfu.ca, prostatecentre.com } or calkan@cs.bilkent.edu.tr. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Pınar Kavak
- Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey
| | - Yen-Yi Lin
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Ibrahim Numanagić
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Hossein Asghari
- School of Computing Science, Simon Fraser University, Burnaby, Canada
| | - Tunga Güngör
- Department of Computer Engineering, Boğaziçi University, Istanbul, Turkey
| | - Can Alkan
- Department of Computer Engineering, Bilkent University, Ankara, Turkey
| | - Faraz Hach
- School of Computing Science, Simon Fraser University, Burnaby, Canada
- Vancouver Prostate Centre, Vancouver, Canada
- Department of Urologic Sciences, University of British Columbia, Vancouver, Canada
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23
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Complete genome sequence of Ostreid herpesvirus type 1 µVar isolated during mortality events in the Pacific oyster Crassostrea gigas in France and Ireland. Virology 2017; 509:239-251. [PMID: 28672223 DOI: 10.1016/j.virol.2017.06.027] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 06/14/2017] [Accepted: 06/23/2017] [Indexed: 12/13/2022]
Abstract
Infections with Ostreid herpesvirus 1 (OsHV-1) microvariants in young Pacific oysters are associated with massive mortality events and significant economic losses. Previous studies, focusing on few regions of the genome, have revealed the genomic diversity of these genotypes with respect to the reference type. We used a NGS process to sequence the whole genome of the OsHV-1 µVar in infected individuals, collected during mortality events in France and Ireland. The final genome length of OsHV-1 µVar was approximately 205kbp, shorter than the reference genotype and the overall genome organisation resembled herpes simplex viruses. 94.4% similarity was observed with the OsHV-1 reference genotype. Large indels, including five deletions and three insertions were found to induce the loss and the addition of several ORFs, summed with codon substitutions in 64% of genes shared with the reference type. This diversity raises the question of the exact origin and evolution of OsHV-1 µVar.
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24
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Rudewicz J, Soueidan H, Uricaru R, Bonnefoi H, Iggo R, Bergh J, Nikolski M. MICADo - Looking for Mutations in Targeted PacBio Cancer Data: An Alignment-Free Method. Front Genet 2016; 7:214. [PMID: 28008336 PMCID: PMC5143680 DOI: 10.3389/fgene.2016.00214] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Accepted: 11/23/2016] [Indexed: 12/11/2022] Open
Abstract
Targeted sequencing is commonly used in clinical application of NGS technology since it enables generation of sufficient sequencing depth in the targeted genes of interest and thus ensures the best possible downstream analysis. This notwithstanding, the accurate discovery and annotation of disease causing mutations remains a challenging problem even in such favorable context. The difficulty is particularly salient in the case of third generation sequencing technology, such as PacBio. We present MICADo, a de Bruijn graph based method, implemented in python, that makes possible to distinguish between patient specific mutations and other alterations for targeted sequencing of a cohort of patients. MICADo analyses NGS reads for each sample within the context of the data of the whole cohort in order to capture the differences between specificities of the sample with respect to the cohort. MICADo is particularly suitable for sequencing data from highly heterogeneous samples, especially when it involves high rates of non-uniform sequencing errors. It was validated on PacBio sequencing datasets from several cohorts of patients. The comparison with two widely used available tools, namely VarScan and GATK, shows that MICADo is more accurate, especially when true mutations have frequencies close to backgound noise. The source code is available at http://github.com/cbib/MICADo.
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Affiliation(s)
- Justine Rudewicz
- Centre de BioInformatique de Bordeaux, University of BordeauxBordeaux, France; Laboratoire Bordelais de Recherche en Informatique, Centre National de la Recherche Scientifique, University of BordeauxBordeaux, France; Bergonié Cancer Institute, Institut National de la Santé et de la Recherche Médicale U1218, University of BordeauxBordeaux, France
| | - Hayssam Soueidan
- Centre de BioInformatique de Bordeaux, University of BordeauxBordeaux, France; Laboratoire Bordelais de Recherche en Informatique, Centre National de la Recherche Scientifique, University of BordeauxBordeaux, France
| | - Raluca Uricaru
- Centre de BioInformatique de Bordeaux, University of BordeauxBordeaux, France; Laboratoire Bordelais de Recherche en Informatique, Centre National de la Recherche Scientifique, University of BordeauxBordeaux, France
| | - Hervé Bonnefoi
- Bergonié Cancer Institute, Institut National de la Santé et de la Recherche Médicale U1218, University of Bordeaux Bordeaux, France
| | - Richard Iggo
- Bergonié Cancer Institute, Institut National de la Santé et de la Recherche Médicale U1218, University of Bordeaux Bordeaux, France
| | - Jonas Bergh
- Karolinska Institute and University Hospital Stockholm, Sweden
| | - Macha Nikolski
- Centre de BioInformatique de Bordeaux, University of BordeauxBordeaux, France; Laboratoire Bordelais de Recherche en Informatique, Centre National de la Recherche Scientifique, University of BordeauxBordeaux, France
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25
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Rustagi N, Hampton OA, Li J, Xi L, Gibbs RA, Plon SE, Kimmel M, Wheeler DA. ITD assembler: an algorithm for internal tandem duplication discovery from short-read sequencing data. BMC Bioinformatics 2016; 17:188. [PMID: 27121965 PMCID: PMC4847212 DOI: 10.1186/s12859-016-1031-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Accepted: 04/12/2016] [Indexed: 11/13/2022] Open
Abstract
Background Detection of tandem duplication within coding exons, referred to as internal tandem duplication (ITD), remains challenging due to inefficiencies in alignment of ITD-containing reads to the reference genome. There is a critical need to develop efficient methods to recover these important mutational events. Results In this paper we introduce ITD Assembler, a novel approach that rapidly evaluates all unmapped and partially mapped reads from whole exome NGS data using a De Bruijn graphs approach to select reads that harbor cycles of appropriate length, followed by assembly using overlap-layout-consensus. We tested ITD Assembler on The Cancer Genome Atlas AML dataset as a truth set. ITD Assembler identified the highest percentage of reported FLT3-ITDs when compared to other ITD detection algorithms, and discovered additional ITDs in FLT3, KIT, CEBPA, WT1 and other genes. Evidence of polymorphic ITDs in 54 genes were also found. Novel ITDs were validated by analyzing the corresponding RNA sequencing data. Conclusions ITD Assembler is a very sensitive tool which can detect partial, large and complex tandem duplications. This study highlights the need to more effectively look for ITD’s in other cancers and Mendelian diseases. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1031-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Navin Rustagi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA. .,Department of Statistics, Rice University, Houston, TX, USA.
| | - Oliver A Hampton
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jie Li
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Dermatology, Xiangya Hospital, Central South University, Hunan, China
| | - Liu Xi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Sharon E Plon
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Department of Pediatrics/Hematology-Oncology, Texas Children's Hospital, Houston, TX, USA
| | - Marek Kimmel
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - David A Wheeler
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
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26
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Yamagata K, Yamanishi A, Kokubu C, Takeda J, Sese J. COSMOS: accurate detection of somatic structural variations through asymmetric comparison between tumor and normal samples. Nucleic Acids Res 2016; 44:e78. [PMID: 26833260 PMCID: PMC4856976 DOI: 10.1093/nar/gkw026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2015] [Accepted: 01/11/2016] [Indexed: 11/13/2022] Open
Abstract
An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.
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Affiliation(s)
- Koichi Yamagata
- Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan
| | - Ayako Yamanishi
- Department of Genome Biology, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | - Chikara Kokubu
- Department of Genome Biology, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | - Junji Takeda
- Department of Genome Biology, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | - Jun Sese
- Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, 135-0064, Japan
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27
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Zhang Z, Wang J, Luo J, Ding X, Zhong J, Wang J, Wu FX, Pan Y. Sprites: detection of deletions from sequencing data by re-aligning split reads. Bioinformatics 2016; 32:1788-96. [PMID: 26833342 DOI: 10.1093/bioinformatics/btw053] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2015] [Accepted: 01/25/2016] [Indexed: 01/22/2023] Open
Abstract
MOTIVATION Advances of next generation sequencing technologies and availability of short read data enable the detection of structural variations (SVs). Deletions, an important type of SVs, have been suggested in association with genetic diseases. There are three types of deletions: blunt deletions, deletions with microhomologies and deletions with microsinsertions. The last two types are very common in the human genome, but they pose difficulty for the detection. Furthermore, finding deletions from sequencing data remains challenging. It is highly appealing to develop sensitive and accurate methods to detect deletions from sequencing data, especially deletions with microhomology and deletions with microinsertion. RESULTS We present a novel method called Sprites (SPlit Read re-alIgnment To dEtect Structural variants) which finds deletions from sequencing data. It aligns a whole soft-clipping read rather than its clipped part to the target sequence, a segment of the reference which is determined by spanning reads, in order to find the longest prefix or suffix of the read that has a match in the target sequence. This alignment aims to solve the problem of deletions with microhomologies and deletions with microinsertions. Using both simulated and real data we show that Sprites performs better on detecting deletions compared with other current methods in terms of F-score. AVAILABILITY AND IMPLEMENTATION Sprites is open source software and freely available at https://github.com/zhangzhen/sprites CONTACT jxwang@mail.csu.edu.cnSupplementary data: Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Zhen Zhang
- School of Information Science and Engineering, Central South University, Changsha, 410083, China, College of Information and Communication Engineering, Hunan Institute of Science and Technology, Yueyang, 414006, China
| | - Jianxin Wang
- School of Information Science and Engineering, Central South University, Changsha, 410083, China
| | - Junwei Luo
- School of Information Science and Engineering, Central South University, Changsha, 410083, China
| | - Xiaojun Ding
- School of Information Science and Engineering, Central South University, Changsha, 410083, China
| | - Jiancheng Zhong
- School of Information Science and Engineering, Central South University, Changsha, 410083, China
| | - Jun Wang
- Department of Molecular Physiology & Biophysics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Fang-Xiang Wu
- Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada and
| | - Yi Pan
- Department of Computer Science, Georgia State University, Atlanta, GA 30302-4110, USA
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28
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Qian Y, Kehr B, Halldórsson BV. PopAlu: population-scale detection of Alu polymorphisms. PeerJ 2015; 3:e1269. [PMID: 26417547 PMCID: PMC4582951 DOI: 10.7717/peerj.1269] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 09/04/2015] [Indexed: 11/20/2022] Open
Abstract
Alu elements are sequences of approximately 300 basepairs that together comprise more than 10% of the human genome. Due to their recent origin in primate evolution some Alu elements are polymorphic in humans, present in some individuals while absent in others. We present PopAlu, a tool to detect polymorphic Alu elements on a population scale from paired-end sequencing data. PopAlu uses read pair distance and orientation as well as split reads to identify the location and precise breakpoints of polymorphic Alus. Genotype calling enables us to differentiate between homozygous and heterozygous carriers, making the output of PopAlu suitable for use in downstream analyses such as genome-wide association studies (GWAS). We show on a simulated dataset that PopAlu calls Alu elements inserted and deleted with respect to a reference genome with high accuracy and high precision. Our analysis of real data of a human trio from the 1000 Genomes Project confirms that PopAlu is able to produce highly accurate genotype calls. To our knowledge, PopAlu is the first tool that identifies polymorphic Alu elements from multiple individuals simultaneously, pinpoints the precise breakpoints and calls genotypes with high accuracy.
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Affiliation(s)
- Yu Qian
- Bioinformatics Research Center, Aarhus University , Aarhus , Denmark
| | - Birte Kehr
- deCODE genetics/Amgen , Reykjavík , Iceland
| | - Bjarni V Halldórsson
- deCODE genetics/Amgen , Reykjavík , Iceland ; Institute of Biomedical and Neural Engineering, School of Science and Engineering, Reykjavik University , Reykjavík , Iceland
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29
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Hawkey J, Hamidian M, Wick RR, Edwards DJ, Billman-Jacobe H, Hall RM, Holt KE. ISMapper: identifying transposase insertion sites in bacterial genomes from short read sequence data. BMC Genomics 2015; 16:667. [PMID: 26336060 PMCID: PMC4558774 DOI: 10.1186/s12864-015-1860-2] [Citation(s) in RCA: 97] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 08/18/2015] [Indexed: 11/23/2022] Open
Abstract
Background Insertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, directly from paired-end short read data. Results ISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 97 % of known IS insertions in the analysis of simulated reads, and 98 % in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was able to correctly detect insertions for average genome-wide read depths >20x, although read depths >50x were required to obtain confident calls that were highly-supported by evidence from reads. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-specific insertions and multiple insertion hotspots. Conclusions ISMapper provides a rapid and robust method for identifying IS insertion sites directly from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.
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Affiliation(s)
- Jane Hawkey
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia. .,Faculty of Veterinary and Agricultural Science, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Mohammad Hamidian
- School of Molecular Bioscience, The University of Sydney, Sydney, 2006, Australia.
| | - Ryan R Wick
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - David J Edwards
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Helen Billman-Jacobe
- Faculty of Veterinary and Agricultural Science, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Ruth M Hall
- School of Molecular Bioscience, The University of Sydney, Sydney, 2006, Australia.
| | - Kathryn E Holt
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia.
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30
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Schröder J, Girirajan S, Papenfuss AT, Medvedev P. Improving the Power of Structural Variation Detection by Augmenting the Reference. PLoS One 2015; 10:e0136771. [PMID: 26322511 PMCID: PMC4556445 DOI: 10.1371/journal.pone.0136771] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 08/07/2015] [Indexed: 11/18/2022] Open
Abstract
The uses of the Genome Reference Consortium’s human reference sequence can be roughly categorized into three related but distinct categories: as a representative species genome, as a coordinate system for identifying variants, and as an alignment reference for variation detection algorithms. However, the use of this reference sequence as simultaneously a representative species genome and as an alignment reference leads to unnecessary artifacts for structural variation detection algorithms and limits their accuracy. We show how decoupling these two references and developing a separate alignment reference can significantly improve the accuracy of structural variation detection, lead to improved genotyping of disease related genes, and decrease the cost of studying polymorphism in a population.
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Affiliation(s)
- Jan Schröder
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia; Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia; Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Santhosh Girirajan
- Genomic Sciences Institute of the Huck, The Pennsylvania State University, State College, United States of America; Department of Computer Science and Engineering, The Pennsylvania State University, State College, United States of America
| | - Anthony T Papenfuss
- The Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia; Department of Medical Biology, The University of Melbourne, Melbourne, Australia; Peter MacCallum Cancer Centre, Melbourne, Australia
| | - Paul Medvedev
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, State College, United States of America; Genomic Sciences Institute of the Huck, The Pennsylvania State University, State College, United States of America; Department of Computer Science and Engineering, The Pennsylvania State University, State College, United States of America
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31
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Kehr B, Melsted P, Halldórsson BV. PopIns: population-scale detection of novel sequence insertions. Bioinformatics 2015; 32:961-7. [PMID: 25926346 DOI: 10.1093/bioinformatics/btv273] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 04/22/2015] [Indexed: 01/05/2023] Open
Abstract
MOTIVATION The detection of genomic structural variation (SV) has advanced tremendously in recent years due to progress in high-throughput sequencing technologies. Novel sequence insertions, insertions without similarity to a human reference genome, have received less attention than other types of SVs due to the computational challenges in their detection from short read sequencing data, which inherently involves de novo assembly. De novo assembly is not only computationally challenging, but also requires high-quality data. Although the reads from a single individual may not always meet this requirement, using reads from multiple individuals can increase power to detect novel insertions. RESULTS We have developed the program PopIns, which can discover and characterize non-reference insertions of 100 bp or longer on a population scale. In this article, we describe the approach we implemented in PopIns. It takes as input a reads-to-reference alignment, assembles unaligned reads using a standard assembly tool, merges the contigs of different individuals into high-confidence sequences, anchors the merged sequences into the reference genome, and finally genotypes all individuals for the discovered insertions. Our tests on simulated data indicate that the merging step greatly improves the quality and reliability of predicted insertions and that PopIns shows significantly better recall and precision than the recent tool MindTheGap. Preliminary results on a dataset of 305 Icelanders demonstrate the practicality of the new approach. AVAILABILITY AND IMPLEMENTATION The source code of PopIns is available from http://github.com/bkehr/popins CONTACT birte.kehr@decode.is SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Birte Kehr
- deCODE genetics/Amgen, Reykjavík, Iceland
| | - Páll Melsted
- deCODE genetics/Amgen, Reykjavík, Iceland, Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Reykjavík, Iceland and
| | - Bjarni V Halldórsson
- deCODE genetics/Amgen, Reykjavík, Iceland, Institute of Biomedical and Neural Engineering, Reykjavík University, Reykjavík, Iceland
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32
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Mohiyuddin M, Mu JC, Li J, Bani Asadi N, Gerstein MB, Abyzov A, Wong WH, Lam HYK. MetaSV: an accurate and integrative structural-variant caller for next generation sequencing. Bioinformatics 2015; 31:2741-4. [PMID: 25861968 PMCID: PMC4528635 DOI: 10.1093/bioinformatics/btv204] [Citation(s) in RCA: 92] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2014] [Accepted: 04/07/2015] [Indexed: 12/05/2022] Open
Abstract
Summary: Structural variations (SVs) are large genomic rearrangements that vary significantly in size, making them challenging to detect with the relatively short reads from next-generation sequencing (NGS). Different SV detection methods have been developed; however, each is limited to specific kinds of SVs with varying accuracy and resolution. Previous works have attempted to combine different methods, but they still suffer from poor accuracy particularly for insertions. We propose MetaSV, an integrated SV caller which leverages multiple orthogonal SV signals for high accuracy and resolution. MetaSV proceeds by merging SVs from multiple tools for all types of SVs. It also analyzes soft-clipped reads from alignment to detect insertions accurately since existing tools underestimate insertion SVs. Local assembly in combination with dynamic programming is used to improve breakpoint resolution. Paired-end and coverage information is used to predict SV genotypes. Using simulation and experimental data, we demonstrate the effectiveness of MetaSV across various SV types and sizes. Availability and implementation: Code in Python is at http://bioinform.github.io/metasv/. Contact:rd@bina.com Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - John C Mu
- Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA
| | - Jian Li
- Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA
| | | | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Wing H Wong
- Department of Statistics, Stanford University, Stanford, CA 94035, USA and Department of Health Research and Policy, Stanford University, Stanford, CA 94035, USA
| | - Hugo Y K Lam
- Bina Technologies, Roche Sequencing, Redwood City, CA 94065, USA
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33
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Glusman G, Severson A, Dhankani V, Robinson M, Farrah T, Mauldin DE, Stittrich AB, Ament SA, Roach JC, Brunkow ME, Bodian DL, Vockley JG, Shmulevich I, Niederhuber JE, Hood L. Identification of copy number variants in whole-genome data using Reference Coverage Profiles. Front Genet 2015; 6:45. [PMID: 25741365 PMCID: PMC4330915 DOI: 10.3389/fgene.2015.00045] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2014] [Accepted: 01/30/2015] [Indexed: 12/20/2022] Open
Abstract
The identification of DNA copy numbers from short-read sequencing data remains a challenge for both technical and algorithmic reasons. The raw data for these analyses are measured in tens to hundreds of gigabytes per genome; transmitting, storing, and analyzing such large files is cumbersome, particularly for methods that analyze several samples simultaneously. We developed a very efficient representation of depth of coverage (150–1000× compression) that enables such analyses. Current methods for analyzing variants in whole-genome sequencing (WGS) data frequently miss copy number variants (CNVs), particularly hemizygous deletions in the 1–100 kb range. To fill this gap, we developed a method to identify CNVs in individual genomes, based on comparison to joint profiles pre-computed from a large set of genomes. We analyzed depth of coverage in over 6000 high quality (>40×) genomes. The depth of coverage has strong sequence-specific fluctuations only partially explained by global parameters like %GC. To account for these fluctuations, we constructed multi-genome profiles representing the observed or inferred diploid depth of coverage at each position along the genome. These Reference Coverage Profiles (RCPs) take into account the diverse technologies and pipeline versions used. Normalization of the scaled coverage to the RCP followed by hidden Markov model (HMM) segmentation enables efficient detection of CNVs and large deletions in individual genomes. Use of pre-computed multi-genome coverage profiles improves our ability to analyze each individual genome. We make available RCPs and tools for performing these analyses on personal genomes. We expect the increased sensitivity and specificity for individual genome analysis to be critical for achieving clinical-grade genome interpretation.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Dale L Bodian
- Inova Translational Medicine Institute, Inova Health System Falls Church, VA, USA
| | - Joseph G Vockley
- Inova Translational Medicine Institute, Inova Health System Falls Church, VA, USA
| | | | - John E Niederhuber
- Inova Translational Medicine Institute, Inova Health System Falls Church, VA, USA
| | - Leroy Hood
- Institute for Systems Biology Seattle, WA, USA
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34
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Holtgrewe M, Kuchenbecker L, Reinert K. Methods for the detection and assembly of novel sequence in high-throughput sequencing data. Bioinformatics 2015; 31:1904-12. [PMID: 25649620 DOI: 10.1093/bioinformatics/btv051] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Accepted: 01/26/2015] [Indexed: 01/04/2023] Open
Abstract
MOTIVATION Large insertions of novel sequence are an important type of structural variants. Previous studies used traditional de novo assemblers for assembling non-mapping high-throughput sequencing (HTS) or capillary reads and then tried to anchor them in the reference using paired read information. RESULTS We present approaches for detecting insertion breakpoints and targeted assembly of large insertions from HTS paired data: BASIL and ANISE. On near identity repeats that are hard for assemblers, ANISE employs a repeat resolution step. This results in far better reconstructions than obtained by the compared methods. On simulated data, we found our insert assembler to be competitive with the de novo assemblers ABYSS and SGA while yielding already anchored inserted sequence as opposed to unanchored contigs as from ABYSS/SGA. On real-world data, we detected novel sequence in a human individual and thoroughly validated the assembled sequence. ANISE was found to be superior to the competing tool MindTheGap on both simulated and real-world data. AVAILABILITY AND IMPLEMENTATION ANISE and BASIL are available for download at http://www.seqan.de/projects/herbarium under a permissive open source license.
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Affiliation(s)
- Manuel Holtgrewe
- Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Leon Kuchenbecker
- Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Knut Reinert
- Department of Computer Science, Freie Universität Berlin and Max Planck Institute for Molecular Genetics, Berlin, Germany
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