1
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Porubsky D, Dashnow H, Sasani TA, Logsdon GA, Hallast P, Noyes MD, Kronenberg ZN, Mokveld T, Koundinya N, Nolan C, Steely CJ, Guarracino A, Dolzhenko E, Harvey WT, Rowell WJ, Grigorev K, Nicholas TJ, Goldberg ME, Oshima KK, Lin J, Ebert P, Watkins WS, Leung TY, Hanlon VCT, McGee S, Pedersen BS, Happ HC, Jeong H, Munson KM, Hoekzema K, Chan DD, Wang Y, Knuth J, Garcia GH, Fanslow C, Lambert C, Lee C, Smith JD, Levy S, Mason CE, Garrison E, Lansdorp PM, Neklason DW, Jorde LB, Quinlan AR, Eberle MA, Eichler EE. Human de novo mutation rates from a four-generation pedigree reference. Nature 2025:10.1038/s41586-025-08922-2. [PMID: 40269156 DOI: 10.1038/s41586-025-08922-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2024] [Accepted: 03/20/2025] [Indexed: 04/25/2025]
Abstract
Understanding the human de novo mutation (DNM) rate requires complete sequence information1. Here using five complementary short-read and long-read sequencing technologies, we phased and assembled more than 95% of each diploid human genome in a four-generation, twenty-eight-member family (CEPH 1463). We estimate 98-206 DNMs per transmission, including 74.5 de novo single-nucleotide variants, 7.4 non-tandem repeat indels, 65.3 de novo indels or structural variants originating from tandem repeats, and 4.4 centromeric DNMs. Among male individuals, we find 12.4 de novo Y chromosome events per generation. Short tandem repeats and variable-number tandem repeats are the most mutable, with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 16% of de novo single-nucleotide variants are postzygotic in origin with no paternal bias, including early germline mosaic mutations. We place all this variation in the context of a high-resolution recombination map (~3.4 kb breakpoint resolution) and find no correlation between meiotic crossover and de novo structural variants. These near-telomere-to-telomere familial genomes provide a truth set to understand the most fundamental processes underlying human genetic variation.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas A Sasani
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Michelle D Noyes
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Nidhi Koundinya
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Cody J Steely
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Andrea Guarracino
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Kirill Grigorev
- Space Biosciences Research Branch, NASA Ames Research Center, Moffett Field, CA, USA
- Blue Marble Space Institute of Science, Seattle, WA, USA
| | - Thomas J Nicholas
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Michael E Goldberg
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Keisuke K Oshima
- Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiadong Lin
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter Ebert
- Core Unit Bioinformatics, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - W Scott Watkins
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Tiffany Y Leung
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Vincent C T Hanlon
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Sean McGee
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Brent S Pedersen
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hannah C Happ
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Altos Labs, San Diego, CA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Daniel D Chan
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Yanni Wang
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Jordan Knuth
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Joshua D Smith
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Erik Garrison
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Peter M Lansdorp
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Deborah W Neklason
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | | | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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2
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Chen LT, Jager M, Rebergen D, Brink GJ, van den Ende T, Vanderlinden W, Kolbeck P, Pagès-Gallego M, van der Pol Y, Besselink N, Moldovan N, Hami N, Kloosterman WP, van Laarhoven H, Mouliere F, Zweemer R, Lipfert J, Derks S, Marcozzi A, de Ridder J. Nanopore-based consensus sequencing enables accurate multimodal tumor cell-free DNA profiling. Genome Res 2025; 35:886-899. [PMID: 39805703 DOI: 10.1101/gr.279144.124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Accepted: 01/06/2025] [Indexed: 01/16/2025]
Abstract
Shallow genome-wide cell-free DNA sequencing holds great promise for noninvasive cancer monitoring by providing reliable copy number alteration (CNA) and fragmentomic profiles. Single-nucleotide variations (SNVs) are, however, much harder to identify with low sequencing depth due to sequencing errors. Here, we present Nanopore Rolling Circle Amplification (RCA)-enhanced Consensus Sequencing (NanoRCS), which leverages RCA and consensus calling based on genome-wide long-read nanopore sequencing to enable simultaneous multimodal tumor fraction (TF) estimation through SNVs, CNAs, and fragmentomics. The efficacy of NanoRCS is tested on 18 cancer patient samples and seven healthy controls, demonstrating its ability to reliably detect TFs as low as 0.24%. In vitro experiments confirm that SNV measurements are essential for detecting TFs below 3%. NanoRCS provides an opportunity for cost-effective and rapid sample processing, which aligns well with clinical needs, particularly in settings where quick and accurate cancer monitoring is essential for personalized treatment strategies.
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Affiliation(s)
- Li-Ting Chen
- Center for Molecular Medicine University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Myrthe Jager
- Center for Molecular Medicine University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | | | - Geertruid J Brink
- Department of Gynecologic Oncology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
| | - Tom van den Ende
- Department of Medical Oncology, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, 1105 AZ, Amsterdam, The Netherlands
| | - Willem Vanderlinden
- Soft Condensed Matter and Biophysics, Department of Physics and Debye Institute for Nanomaterials Science, Utrecht University, 3584 CC Utrecht, The Netherlands
- School of Physics and Astronomy, University of Edinburgh, EH9 3FD Edinburgh, United Kingdom
| | - Pauline Kolbeck
- Soft Condensed Matter and Biophysics, Department of Physics and Debye Institute for Nanomaterials Science, Utrecht University, 3584 CC Utrecht, The Netherlands
- Department of Physics and Center for NanoScience, LMU Munich, 80799 Munich, Germany
| | - Marc Pagès-Gallego
- Center for Molecular Medicine University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Ymke van der Pol
- Department of Pathology, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Nicolle Besselink
- Center for Molecular Medicine University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
- Oncode Institute, 3521 AL Utrecht, The Netherlands
| | - Norbert Moldovan
- Cancer Center Amsterdam, Imaging and Biomarkers, 1105 AZ, Amsterdam, The Netherlands
- Department of Pathology, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | - Nizar Hami
- Department of Gynecologic Oncology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
| | | | - Hanneke van Laarhoven
- Department of Medical Oncology, Amsterdam UMC, University of Amsterdam, 1105 AZ, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Imaging and Biomarkers, 1105 AZ, Amsterdam, The Netherlands
| | - Florent Mouliere
- Cancer Center Amsterdam, Imaging and Biomarkers, 1105 AZ, Amsterdam, The Netherlands
- Department of Pathology, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1105 AZ, Amsterdam, The Netherlands
- Cancer Research UK National Biomarker Centre, University of Manchester, Manchester M20 4BX, United Kingdom
| | - Ronald Zweemer
- Department of Gynecologic Oncology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands
| | - Jan Lipfert
- Soft Condensed Matter and Biophysics, Department of Physics and Debye Institute for Nanomaterials Science, Utrecht University, 3584 CC Utrecht, The Netherlands
| | - Sarah Derks
- Oncode Institute, 3521 AL Utrecht, The Netherlands
- Department of Pathology, Cancer Centre Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, 1105 AZ, Amsterdam, The Netherlands
| | | | - Jeroen de Ridder
- Center for Molecular Medicine University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, The Netherlands;
- Oncode Institute, 3521 AL Utrecht, The Netherlands
- Cyclomics, 3584 CG Utrecht, The Netherlands
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3
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Yuk J, Kim J, Jung S, Um SH. Engineering Gizmos for Short Cancer Genetic Fragments Discrimination. Chembiochem 2025; 26:e202400867. [PMID: 39910951 DOI: 10.1002/cbic.202400867] [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] [Received: 10/21/2024] [Revised: 02/04/2025] [Accepted: 02/06/2025] [Indexed: 02/07/2025]
Abstract
Currently, mankind is fiercely struggling with cancer. Recently, we have been winning the battle against cancer through precision medicine and accompanying diagnostic methods, and we are raising many hopes with blockbuster drugs. It would be even better if we could read the cancer nucleotide sequence, identify them in advance, and suggest treatments simultaneously. However, this may be an impossible dream because it takes a lot of time and effort to diagnose and ensure all the long gene sequences of cancer at once. Thus, victory will be even closer if a rapid and accurate diagnosis of the cancer-specific gene biomarkers that will soon be imprinted can be made. With the advent of nanotechnology, a new short cancer diagnostic toolkit has been proposed to achieve the goal. This review presents a small diagnostic device that detects certain cancers' genetic fragments (simply 'Gizmo'). The development of numerous diagnostic methods has focused on (1) directly detecting pre-selectively targeted genes using novel diagnostic systems, and (2) indirectly detecting substantial improvements in diagnostic sensitivity only through detection signal amplification without existing gene amplification steps. Our fight against cancer is not a dream, but the result of success, and it is assumed that victory will accelerate as soon as possible.
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Affiliation(s)
- Jisoo Yuk
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA
| | - Jeonghun Kim
- Progeneer Incorporation, #1002, 12, Digital-ro 31-gil, Guro-gu, Seoul, 08380, Korea
| | - Sunghwan Jung
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA
| | - Soong Ho Um
- School of Chemical Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do, 16419, Korea
- Progeneer Incorporation, #1002, 12, Digital-ro 31-gil, Guro-gu, Seoul, 08380, Korea
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4
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Arikan A, Uzun B, Sayan M. Implementation of Multi-Criteria Decision-Making for Selecting Most Effective Genome Sequencing Technology. Diagnostics (Basel) 2025; 15:665. [PMID: 40150010 PMCID: PMC11941383 DOI: 10.3390/diagnostics15060665] [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: 12/06/2024] [Revised: 01/30/2025] [Accepted: 03/06/2025] [Indexed: 03/29/2025] Open
Abstract
Background/Objectives: In recent years, molecular diagnosis has become increasingly critical in identifying human pathogens with unknown genes. Methods: An innovative approach, the fuzzy-based preference ranking organization method for enrichment evaluation (PROMETHEE) technique, one of the most effective multi-criteria decision-making (MCDM) methods, was used to evaluate criteria, including portability, generation type, max read/run, max output data/run, processing time/run, read length, accuracy, diagnostic sensitivity, test minimum loading volume, test cost/run, instrument cost, error rate, throughput capability, ability to sequence the large whole genome, small whole genome, and exome and large panel, mutation detection ability, whole-genome sequencing with single-stranded sequencing, and single-stranded sequencing accuracy, to determine the most suitable sequencing technology. Results: Based on the analysis, the Avidite Base Chemistry (ABC), Nanopore, and Illumina sequencing platforms sequentially emerged as the most favorable options based on their net flows of 0.0346, 0.0041, and 0.0003, respectively. Conclusions: Our findings provide important data to facilitate the selection of genome detection technologies. Through the use of innovative approaches, complex evaluations can be analyzed and the right choices can be made. Importantly, the technique has a degree of subjectivity, so varying conditions may lead to different findings.
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Affiliation(s)
- Ayse Arikan
- DESAM Research Institute, Near East University, TRNC, Mersin 10, 99138 Nicosia, Turkey;
- Department of Medical Microbiology and Clinical Microbiology, Near East University, TRNC, Mersin 10, 99138 Nicosia, Turkey
- Department of Medical Microbiology and Clinical Microbiology, Kyrenia University, TRNC, Mersin 10, 99320 Kyrenia, Turkey
| | - Berna Uzun
- Operational Research Center in Healthcare, Near East University, TRNC, Mersin 10, 99138 Nicosia, Turkey;
- Department of Mathematics, Near East University, TRNC, Mersin 10, 99138 Nicosia, Turkey
| | - Murat Sayan
- DESAM Research Institute, Near East University, TRNC, Mersin 10, 99138 Nicosia, Turkey;
- PCR Unit, Research and Education Hospital, Kocaeli University, 41380 Kocaeli, Turkey
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5
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Olsen TR, Talla P, Sagatelian RK, Furnari J, Bruce JN, Canoll P, Zha S, Sims PA. Scalable co-sequencing of RNA and DNA from individual nuclei. Nat Methods 2025; 22:477-487. [PMID: 39939719 DOI: 10.1038/s41592-024-02579-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 12/09/2024] [Indexed: 02/14/2025]
Abstract
The ideal technology for directly investigating the relationship between genotype and phenotype would analyze both RNA and DNA genome-wide and with single-cell resolution; however, existing tools lack the throughput required for comprehensive analysis of complex tumors and tissues. We introduce a highly scalable method for jointly profiling DNA and expression following nucleosome depletion (DEFND-seq). In DEFND-seq, nuclei are nucleosome-depleted, tagmented and separated into individual droplets for messenger RNA and genomic DNA barcoding. Once nuclei have been depleted of nucleosomes, subsequent steps can be performed using the widely available 10x Genomics droplet microfluidic technology and commercial kits. We demonstrate the production of high-complexity mRNA and gDNA sequencing libraries from thousands of individual nuclei from cell lines, fresh and archived surgical specimens for associating gene expression with both copy number and single-nucleotide variants.
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Affiliation(s)
- Timothy R Olsen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Pranay Talla
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Romella K Sagatelian
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Julia Furnari
- Department of Neurological Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Jeffrey N Bruce
- Department of Neurological Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Peter Canoll
- Department of Pathology & Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | - Shan Zha
- Department of Pathology & Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
- Institute for Cancer Genetics, Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA
| | - Peter A Sims
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, USA.
- Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, USA.
- Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA.
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6
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Lim MH, Kim J, Tu ZJ, Cheng YW. Comparison of Sequencing-by-Synthesis and Avidity Base Chemistry Next-Generation Sequencing Platforms in Identifying Somatic Variants of Hematological Malignancies. J Appl Lab Med 2025:jfaf006. [PMID: 39936404 DOI: 10.1093/jalm/jfaf006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Accepted: 12/09/2024] [Indexed: 02/13/2025]
Abstract
BACKGROUND This study evaluates the performance of the Illumina NextSeq™ 550 and the Element Biosciences AVITI™ next-generation sequencing (NGS) system, in detecting single nucleotide variants (SNVs) and gene fusions. METHODS A set of 66 NGS libraries, consisting of 33 DNA, 24 cDNA, and triplicates of 3 control libraries, were prepared from bone marrow samples targeting 63 genes and related fusions, and initially sequenced using the NextSeq 550 in the Cleveland Clinic's molecular diagnostic laboratory. The same libraries were subsequently sequenced on the AVITI. The resulting data were analyzed using a combination of Cleveland Clinic developed pipelines and ArcherDx virtual machine software. RESULTS The study found that all 105 SNVs and 39 gene fusions identified by the NextSeq 550 were also detected in the AVITI, demonstrating a high degree of concordance between the platforms. The analyses revealed R2 values of 0.86 for read depth and 0.96 for VAF of the 105 DNA variants, and 0.95 for read depth and 0.97 for fusion percentage of the 39 fusion variants. In the reproducibility studies, the VAF and fusion percentage of all variants were within 2 standard deviations of the mean when the same positive controls were sequenced 3 times on the AVITI. CONCLUSIONS These results indicate that the NextSeq 550 and the AVITI provide comparable performance in terms of accuracy and sensitivity for variant detection. Notably, the AVITI chemistry requires substantially lower PhiX input than the NextSeq 550 needs for this application. This results in substantial cost and efficiency benefits.
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Affiliation(s)
- Min Hui Lim
- Genomics Core, Shared Laboratory Resource, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Juwuk Kim
- Genomics Core, Shared Laboratory Resource, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Zheng Jin Tu
- Department of Laboratory Medicine, Diagnostic Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Yu-Wei Cheng
- Genomics Core, Shared Laboratory Resource, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Laboratory Medicine, Diagnostic Institute, Cleveland Clinic, Cleveland, OH, United States
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7
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Wagner J, Olson ND, McDaniel J, Harris L, Pinto BJ, Jáspez D, Muñoz-Barrera A, Rubio-Rodríguez LA, Lorenzo-Salazar JM, Flores C, Sahraeian SME, Narzisi G, Byrska-Bishop M, Evani US, Xiao C, Lake JA, Fontana P, Greenberg C, Freed D, Mootor MFE, Boutros PC, Murray L, Shafin K, Carroll A, Sedlazeck FJ, Wilson M, Zook JM. Small variant benchmark from a complete assembly of X and Y chromosomes. Nat Commun 2025; 16:497. [PMID: 39779690 PMCID: PMC11711550 DOI: 10.1038/s41467-024-55710-z] [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] [Received: 04/29/2024] [Accepted: 12/19/2024] [Indexed: 01/11/2025] Open
Abstract
The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research and clinical laboratories to evaluate variant detection on male sex chromosomes X and Y, we create a small variant benchmark set with 111,725 variants for the Genome in a Bottle HG002 reference material. We develop an active evaluation approach to demonstrate the benchmark set reliably identifies errors in challenging genomic regions and across short and long read callsets. We show how complete assemblies can expand benchmarks to difficult regions, but highlight remaining challenges benchmarking variants in long homopolymers and tandem repeats, complex gene conversions, copy number variable gene arrays, and human satellites.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA
| | - Brendan J Pinto
- Center for Evolution & Medicine and School of Life Sciences, Arizona State University, Tempe, AZ 85281 USA - Department of Zoology, Milwaukee Public Museum, Milwaukee, WI, USA
| | - David Jáspez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Spain
| | - Adrián Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Spain
| | - Luis A Rubio-Rodríguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Spain
| | - José M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Spain
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona, Spain
- CIBER de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario Nuestra Señora de Candelaria, Instituto de Investigación Sanitaria de Canarias, Santa Cruz de Tenerife, Spain
- Facultad de Ciencias de la Salud, Universidad Fernando de Pessoa Canarias, Las Palmas de Gran Canaria, Spain
| | | | | | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Peter Fontana
- Information Technology Laboratory, National Institute of Standards and Technology, 100 Bureau Dr. Mailstop 8940, Gaithersburg, MD, USA
| | - Craig Greenberg
- Information Technology Laboratory, National Institute of Standards and Technology, 100 Bureau Dr. Mailstop 8940, Gaithersburg, MD, USA
| | | | | | - Paul C Boutros
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Kishwar Shafin
- Google Inc, 1600 Amphitheatre Pkwy, Mountain View, CA, USA
| | - Andrew Carroll
- Google Inc, 1600 Amphitheatre Pkwy, Mountain View, CA, USA
| | - Fritz J Sedlazeck
- Baylor College of Medicine Human Genome Sequencing Center, Houston, TX, USA
| | - Melissa Wilson
- Center for Evolution & Medicine and School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr., Gaithersburg, MD, USA.
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8
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Polonis K, Blommel JH, Hughes AEO, Spencer D, Thompson JA, Schroeder MC. Innovations in Short-Read Sequencing Technologies and Their Applications to Clinical Genomics. Clin Chem 2025; 71:97-108. [PMID: 39749506 DOI: 10.1093/clinchem/hvae173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 09/23/2024] [Indexed: 01/04/2025]
Abstract
BACKGROUND Massively parallel sequencing (MPS) of nucleic acids has been a transformative technology for basic and applied genomic science, increasing efficiencies and decreasing costs to enable studies of unprecedented scope and impact. In clinical settings, these technological and scientific advances have led to the development of tests that are increasingly fast, comprehensive, and more frequently employed. Practitioners of genomic medicine have applied these tools across clinical settings, including diagnosis of inherited disorders and cancers and infectious disease detection and surveillance. In recent years, the commercial marketplace for MPS sequencers and reagents has been dominated by a few companies. The growing demand for sequencing has led to the recent emergence of several new sequencing platforms with techniques that may provide alternatives or improvements to existing workflows or allow the adoption of sequencing workflows in new settings. Clinical genomics laboratories will evaluate these platforms from a unique perspective, focusing on how technological advancements can improve patient care. CONTENT This review describes short-read sequencing platforms provided by Illumina, Element Biosciences, MGI, PacBio, Singular Genomics, Thermo Fisher Scientific, and Ultima Genomics. This review discusses their innovative approaches, principles, workflows, and applications. SUMMARY This review aims to inform laboratory geneticists, clinicians, and researchers about emerging short-read technologies and their applications in clinical genomics. By highlighting their principles and potential contributions, we aim to assist laboratories in selecting suitable solutions for their sequencing needs considering key factors such as applications, throughput, and integration with existing laboratory workflows.
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Affiliation(s)
- Katarzyna Polonis
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
| | - Joseph H Blommel
- Advanced Diagnostic Laboratories, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Andrew E O Hughes
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
| | - David Spencer
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
| | | | - Molly C Schroeder
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
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9
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Lambert CLG, van Mierlo G, Bues JJ, Guillaume-Gentil OJ, Deplancke B. The evolution of DNA sequencing with microfluidics. Nat Rev Genet 2025; 26:1-2. [PMID: 39333241 DOI: 10.1038/s41576-024-00783-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2024]
Affiliation(s)
- Camille L G Lambert
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Guido van Mierlo
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Johannes J Bues
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Orane J Guillaume-Gentil
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Bart Deplancke
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
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10
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Ruppeka Rupeika E, D’Huys L, Leen V, Hofkens J. Sequencing and Optical Genome Mapping for the Adventurous Chemist. CHEMICAL & BIOMEDICAL IMAGING 2024; 2:784-807. [PMID: 39735829 PMCID: PMC11673194 DOI: 10.1021/cbmi.4c00060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 10/03/2024] [Accepted: 10/04/2024] [Indexed: 12/31/2024]
Abstract
This review provides a comprehensive overview of the chemistries and workflows of the sequencing methods that have been or are currently commercially available, providing a very brief historical introduction to each method. The main optical genome mapping approaches are introduced in the same manner, although only a subset of these are or have ever been commercially available. The review comes with a deck of slides containing all of the figures for ease of access and consultation.
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Affiliation(s)
| | - Laurens D’Huys
- Faculty
of Science, Chemistry, KU Leuven, Celestijnenlaan 200F, Leuven, Flanders 3001, Belgium
| | - Volker Leen
- Perseus
Biomics B.V., Industriepark
6 bus 3, Tienen 3300, Belgium
| | - Johan Hofkens
- Faculty
of Science, Chemistry, KU Leuven, Celestijnenlaan 200F, Leuven, Flanders 3001, Belgium
- Max
Planck Institute for Polymer Research, Mainz, Rheinland-Pfalz 55128, Germany
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11
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Chamberlin J, Gillen A, Quinlan A. Improved characterization of 3' single-cell RNA-seq libraries with paired-end avidity sequencing. NAR Genom Bioinform 2024; 6:lqae175. [PMID: 39703419 PMCID: PMC11655283 DOI: 10.1093/nargab/lqae175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 11/12/2024] [Accepted: 11/30/2024] [Indexed: 12/21/2024] Open
Abstract
Prevailing poly(dT)-primed 3' single-cell RNA-seq protocols generate barcoded cDNA fragments containing the reverse transcriptase priming site or in principle the polyadenylation site. Direct sequencing across this site was historically difficult because of DNA sequencing errors induced by the homopolymeric primer at the 'barcode' end. Here, we evaluate the capability of 'avidity base chemistry' DNA sequencing from Element Biosciences to sequence through the primer and enable accurate paired-end read alignment and precise quantification of polyadenylation sites. We find that the Element Aviti instrument sequences through the thymine homopolymer into the subsequent cDNA sequence without detectable loss of accuracy. The additional sequence enables direct and independent assignment of reads to polyadenylation sites, which bypasses the complexities and limitations of conventional approaches but does not consistently improve read mapping rates compared to single-end alignment. We also characterize low-level artifacts and demonstrate necessary adjustments to adapter trimming and sequence alignment regardless of platform, particularly in the context of extended read lengths. Our analyses confirm that Element avidity sequencing is an effective alternative to Illumina sequencing for standard single-cell RNA-seq, particularly for polyadenylation site measurement but do not rule out the potential for similar performance from other emerging platforms.
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Affiliation(s)
- John T Chamberlin
- Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way #140, Salt Lake City, UT 84112, USA
| | - Austin E Gillen
- RNA Bioscience Initiative, University of Colorado School of Medicine, 12801 E 17th Ave, Aurora, CO 80045, USA
- Division of Hematology, University of Colorado School of Medicine, 12700 East 19th Ave, Aurora, CO 80045, USA
- Rocky Mountain Regional VA Medical Center, 1700 N Wheeling St, Aurora, CO 80045, USA
| | - Aaron R Quinlan
- Department of Biomedical Informatics, University of Utah School of Medicine, 421 Wakara Way #140, Salt Lake City, UT 84112, USA
- Department of Human Genetics, University of Utah School of Medicine, 15 N 2030 E, Salt Lake City, UT 84112, USA
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12
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McDonald AL, Boddicker AM, Savenkova MI, Brabb IM, Qi X, Moré DD, Cunha CW, Zhao J, Duttke SH. Efficient small fragment sequencing of human, cattle, and bison miRNA, small RNA, or csRNA-seq libraries using AVITI. BMC Genomics 2024; 25:1157. [PMID: 39614157 DOI: 10.1186/s12864-024-11013-7] [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] [Received: 06/04/2024] [Accepted: 11/08/2024] [Indexed: 12/01/2024] Open
Abstract
BACKGROUND Next-Generation Sequencing (NGS) catalyzed breakthroughs across various scientific domains. Illumina's sequencing by synthesis method has long been central to NGS, but new sequencing methods like Element Biosciences' AVITI technology are emerging. AVITI is reported to offer improved signal-to-noise ratios and cost reductions. However, its reliance on rolling circle amplification, which can be affected by polymer size, raises questions about its effectiveness in sequencing small RNAs (sRNAs) such as microRNAs (miRNAs), small nucleolar RNAs (snoRNAs), and many others. These sRNAs are crucial regulators of gene expression and involved in various biological processes. Additionally, capturing capped small RNAs (csRNA-seq) is a powerful method for mapping active or "nascent" RNA polymerase II transcription initiation in tissues and clinical samples. RESULTS Here, we report a new protocol for seamlessly sequencing short fragments on the AVITI and demonstrate that AVITI and Illumina sequencing technologies equivalently capture human, cattle (Bos taurus), and bison (Bison bison) sRNA or csRNA sequencing libraries, increasing confidence in both sequencing approaches. Additionally, analysis of generated nascent transcription start site (TSS) data for cattle and bison revealed inaccuracies in their current genome annotations, underscoring the potential and necessity to translate small and nascent RNA sequencing methodologies to livestock. CONCLUSIONS Our accelerated and optimized protocol bridges the advantages of AVITI sequencing with critical methods that rely on sequencing short fragments. This advance bolsters the utility of AVITI technology alongside traditional Illumina platforms, offering new opportunities for NGS applications.
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Affiliation(s)
- Anna L McDonald
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | | | - Marina I Savenkova
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | - Ian M Brabb
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | | | - Daniela D Moré
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA, 99164, USA
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, 99164, USA
| | - Cristina W Cunha
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA, 99164, USA
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA, 99164, USA
| | | | - Sascha H Duttke
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA.
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13
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Zhou B, Arthur JG, Guo H, Kim T, Huang Y, Pattni R, Wang T, Kundu S, Luo JXJ, Lee H, Nachun DC, Purmann C, Monte EM, Weimer AK, Qu PP, Shi M, Jiang L, Yang X, Fullard JF, Bendl J, Girdhar K, Kim M, Chen X, Greenleaf WJ, Duncan L, Ji HP, Zhu X, Song G, Montgomery SB, Palejev D, Zu Dohna H, Roussos P, Kundaje A, Hallmayer JF, Snyder MP, Wong WH, Urban AE. Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders. Cell 2024; 187:6687-6706.e25. [PMID: 39353437 DOI: 10.1016/j.cell.2024.09.014] [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] [Received: 09/12/2023] [Revised: 07/01/2024] [Accepted: 09/10/2024] [Indexed: 10/04/2024]
Abstract
Complex structural variations (cxSVs) are often overlooked in genome analyses due to detection challenges. We developed ARC-SV, a probabilistic and machine-learning-based method that enables accurate detection and reconstruction of cxSVs from standard datasets. By applying ARC-SV across 4,262 genomes representing all continental populations, we identified cxSVs as a significant source of natural human genetic variation. Rare cxSVs have a propensity to occur in neural genes and loci that underwent rapid human-specific evolution, including those regulating corticogenesis. By performing single-nucleus multiomics in postmortem brains, we discovered cxSVs associated with differential gene expression and chromatin accessibility across various brain regions and cell types. Additionally, cxSVs detected in brains of psychiatric cases are enriched for linkage with psychiatric GWAS risk alleles detected in the same brains. Furthermore, our analysis revealed significantly decreased brain-region- and cell-type-specific expression of cxSV genes, specifically for psychiatric cases, implicating cxSVs in the molecular etiology of major neuropsychiatric disorders.
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Affiliation(s)
- Bo Zhou
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
| | - Joseph G Arthur
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Hanmin Guo
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Taeyoung Kim
- School of Computer Science and Engineering, Pusan National University, Busan 46241, South Korea
| | - Yiling Huang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Reenal Pattni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Tao Wang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Soumya Kundu
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Jay X J Luo
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - HoJoon Lee
- Division of Oncology, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Daniel C Nachun
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Carolin Purmann
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Emma M Monte
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Annika K Weimer
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ping-Ping Qu
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Minyi Shi
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Lixia Jiang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Xinqiong Yang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Minsu Kim
- School of Computer Science and Engineering, Pusan National University, Busan 46241, South Korea
| | - Xi Chen
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | | | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Xiang Zhu
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA; Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Giltae Song
- School of Computer Science and Engineering, Pusan National University, Busan 46241, South Korea; Center for Artificial Intelligence Research, Pusan National University, Busan 46241, South Korea
| | - Stephen B Montgomery
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Dean Palejev
- Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia 1113, Bulgaria
| | - Heinrich Zu Dohna
- Department of Biology, American University of Beirut, Beirut 11-0236, Lebanon
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA; Mental Illness Research Education and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Joachim F Hallmayer
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Wing H Wong
- Department of Statistics, Stanford University, Stanford, CA 94305, USA; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
| | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA; Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA 94305, USA.
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14
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Laureyssen C, Küçükali F, Van Dongen J, Gawor K, Tomé SO, Ronisz A, Otto M, von Arnim CAF, Van Damme P, Vandenberghe R, Thal DR, Sleegers K. Hypothesis-based investigation of known AD risk variants reveals the genetic underpinnings of neuropathological lesions observed in Alzheimer's-type dementia. Acta Neuropathol 2024; 148:55. [PMID: 39424714 PMCID: PMC11489263 DOI: 10.1007/s00401-024-02815-w] [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] [Received: 07/16/2024] [Revised: 10/08/2024] [Accepted: 10/08/2024] [Indexed: 10/21/2024]
Abstract
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Besides neurofibrillary tangles and amyloid beta (Aβ) plaques, a wide range of co-morbid neuropathological features can be observed in AD brains. Since AD has a very strong genetic background and displays a wide phenotypic heterogeneity, this study aims at investigating the genetic underpinnings of co-morbid and hallmark neuropathological lesions. This was realized by obtaining the genotypes for 75 AD risk variants from low-coverage whole-genome sequencing data for 325 individuals from the Leuven Brain Collection. Association testing with deeply characterized neuropathological lesions revealed a strong and likely direct effect of rs117618017, a SNP in exon 1 of APH1B, with tau-related pathology. Second, a relation between APOE and granulovacuolar degeneration, a proxy for necroptosis, was also discovered in addition to replication of the well-known association of APOE with AD hallmark neuropathological lesions. Additionally, several nominal associations with AD risk genes were detected for pTDP pathology, α-synuclein lesions and pTau-related pathology. These findings were confirmed in a meta-analysis with three independent cohorts. For example, we replicated a prior association between TPCN1 (rs6489896) and LATE-NC risk. Furthermore, we identified new putative LATE-NC-linked SNPs, including rs7068231, located upstream of ANK3. We found association between BIN1 (rs6733839) and α-synuclein pathology, and replicated a prior association between USP6NL (rs7912495) and Lewy body pathology. Additionally, we also found that UMAD1 (rs6943429) was nominally associated with Lewy body pathology. Overall, these results contribute to a broader general understanding of how AD risk variants discovered in large-scale clinical genome-wide association studies are involved in the pathological mechanisms of AD and indicate the importance of downstream elimination of phenotypic heterogeneity introduced in these studies.
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Affiliation(s)
- Celeste Laureyssen
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jasper Van Dongen
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Klara Gawor
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Sandra O Tomé
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Alicja Ronisz
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
| | - Markus Otto
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | | | - Philip Van Damme
- Laboratory for Neurobiology, VIB-KU Leuven, Louvain, Belgium
- Department of Neurology, UZ Leuven, Louvain, Belgium
| | - Rik Vandenberghe
- Department of Neurology, UZ Leuven, Louvain, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven Brain Institute, Louvain, Belgium
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, KU Leuven, Louvain, Belgium
- Department of Pathology, University Hospital Leuven, Louvain, Belgium
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, Campus Drie Eiken, Universiteitsplein 1, 2610, Antwerp, Belgium.
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
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15
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Zhang C, Wu R, Sun F, Lin Y, Liang Y, Teng J, Liu N, Ouyang Q, Qian L, Yan H. Parallel molecular data storage by printing epigenetic bits on DNA. Nature 2024; 634:824-832. [PMID: 39443776 PMCID: PMC11499255 DOI: 10.1038/s41586-024-08040-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 09/11/2024] [Indexed: 10/25/2024]
Abstract
DNA storage has shown potential to transcend current silicon-based data storage technologies in storage density, longevity and energy consumption1-3. However, writing large-scale data directly into DNA sequences by de novo synthesis remains uneconomical in time and cost4. We present an alternative, parallel strategy that enables the writing of arbitrary data on DNA using premade nucleic acids. Through self-assembly guided enzymatic methylation, epigenetic modifications, as information bits, can be introduced precisely onto universal DNA templates to enact molecular movable-type printing. By programming with a finite set of 700 DNA movable types and five templates, we achieved the synthesis-free writing of approximately 275,000 bits on an automated platform with 350 bits written per reaction. The data encoded in complex epigenetic patterns were retrieved high-throughput by nanopore sequencing, and algorithms were developed to finely resolve 240 modification patterns per sequencing reaction. With the epigenetic information bits framework, distributed and bespoke DNA storage was implemented by 60 volunteers lacking professional biolab experience. Our framework presents a new modality of DNA data storage that is parallel, programmable, stable and scalable. Such an unconventional modality opens up avenues towards practical data storage and dual-mode data functions in biomolecular systems.
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Affiliation(s)
- Cheng Zhang
- School of Computer Science, Key Laboratory of High Confidence Software Technologies, Peking University, Beijing, China.
| | - Ranfeng Wu
- School of Computer Science, Key Laboratory of High Confidence Software Technologies, Peking University, Beijing, China
| | - Fajia Sun
- Center for Quantitative Biology, Peking University, Beijing, China
| | - Yisheng Lin
- School of Computer Science, Key Laboratory of High Confidence Software Technologies, Peking University, Beijing, China
| | - Yuan Liang
- School of Computer Science, Key Laboratory of High Confidence Software Technologies, Peking University, Beijing, China
- School of Control and Computer Engineering, North China Electric Power University, Beijing, China
| | - Jiongjiong Teng
- School of Control and Computer Engineering, North China Electric Power University, Beijing, China
| | - Na Liu
- 2nd Physics Institute, University of Stuttgart, Stuttgart, Germany
- Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Qi Ouyang
- Center for Quantitative Biology, Peking University, Beijing, China.
| | - Long Qian
- Center for Quantitative Biology, Peking University, Beijing, China.
| | - Hao Yan
- Center for Molecular Design and Biomimetics, Biodesign Institute, Arizona State University, Tempe, AZ, USA.
- School of Molecular Sciences, Arizona State University, Tempe, AZ, USA.
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16
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Cobley JN. Exploring the unmapped cysteine redox proteoform landscape. Am J Physiol Cell Physiol 2024; 327:C844-C866. [PMID: 39099422 DOI: 10.1152/ajpcell.00152.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 07/16/2024] [Accepted: 07/16/2024] [Indexed: 08/06/2024]
Abstract
Cysteine redox proteoforms define the diverse molecular states that proteins with cysteine residues can adopt. A protein with one cysteine residue must adopt one of two binary proteoforms: reduced or oxidized. Their numbers scale: a protein with 10 cysteine residues must assume one of 1,024 proteoforms. Although they play pivotal biological roles, the vast cysteine redox proteoform landscape comprising vast numbers of theoretical proteoforms remains largely uncharted. Progress is hampered by a general underappreciation of cysteine redox proteoforms, their intricate complexity, and the formidable challenges that they pose to existing methods. The present review advances cysteine redox proteoform theory, scrutinizes methodological barriers, and elaborates innovative technologies for detecting unique residue-defined cysteine redox proteoforms. For example, chemistry-enabled hybrid approaches combining the strengths of top-down mass spectrometry (TD-MS) and bottom-up mass spectrometry (BU-MS) for systematically cataloguing cysteine redox proteoforms are delineated. These methods provide the technological means to map uncharted redox terrain. To unravel hidden redox regulatory mechanisms, discover new biomarkers, and pinpoint therapeutic targets by mining the theoretical cysteine redox proteoform space, a community-wide initiative termed the "Human Cysteine Redox Proteoform Project" is proposed. Exploring the cysteine redox proteoform landscape could transform current understanding of redox biology.
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Affiliation(s)
- James N Cobley
- School of Life Sciences, University of Dundee, Dundee, United Kingdom
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17
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Yang J, Su Q, Song C, Luo H, Jiang H, Ni M, Meng F. A comprehensive adsorption and desorption study on the interaction of DNA oligonucleotides with TiO 2 nanolayers. Phys Chem Chem Phys 2024; 26:22681-22695. [PMID: 39158972 DOI: 10.1039/d4cp02260b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/21/2024]
Abstract
The utilization of TiO2 nanolayers that possess excellent biocompatibility and physical properties in DNA sensing and sequencing remains largely to be explored. To examine their applicability in gene sequencing, a comprehensive study on the interaction of DNA oligonucleotides with TiO2 nanolayers was performed through adsorption and desorption experiments. TiO2 nanolayers with 10 nm thickness were fabricated via magnetron sputtering onto a 6-inch silicon wafer. A simple chip block method, validated via quartz crystal microbalance experiments with dissipation monitoring (QCM-D), was proposed to study the adsorption behaviors and interaction mechanisms under a variety of critical influencing factors, including DNA concentration, length, and type, adsorption time, pH, and metal ions. It is determined that the adsorption takes 2 h to reach saturation in the MES solution and the adsorption capacity is significantly enhanced by lowering the pH due to the isoelectric point being pH = 6 for TiO2. The adsorption percentages of nucleobases are largely similar in the MES solution while following 5T = 5G > 5C > 5A in HEPES buffer for an adsorption duration of 2.5 h. Through pre-adsorption experiments, it is deduced that DNA oligonucleotides are horizontally adsorbed on the nanolayer. This further demonstrates that mono-, di-, and tri-valent metal ions promote the adsorption, whereas Zn2+ has strong adsorption by inducing DNA condensation. Based on the desorption experiments, it is revealed that electrostatic force dominates the adsorption over van der Waals force and hydrogen bonds. The phosphate group is the main functional group for adsorption, and the adsorption strength increases with the length of the oligonucleotide. This study provides comprehensive data on the adsorption of DNA oligonucleotides onto TiO2 nanolayers and clarifies the interaction mechanisms therein, which will be valuable for applications of TiO2 in DNA-related applications.
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Affiliation(s)
- Jin Yang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- MGI Tech, Shenzhen 518083, China.
| | - Qiong Su
- MGI Tech, Shenzhen 518083, China.
| | | | | | | | - Ming Ni
- MGI Tech, Shenzhen 518083, China.
| | - Fanchao Meng
- Institute for Advanced Studies in Precision Materials, Yantai University, Yantai, Shandong 264005, China.
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18
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Porubsky D, Dashnow H, Sasani TA, Logsdon GA, Hallast P, Noyes MD, Kronenberg ZN, Mokveld T, Koundinya N, Nolan C, Steely CJ, Guarracino A, Dolzhenko E, Harvey WT, Rowell WJ, Grigorev K, Nicholas TJ, Oshima KK, Lin J, Ebert P, Watkins WS, Leung TY, Hanlon VCT, McGee S, Pedersen BS, Goldberg ME, Happ HC, Jeong H, Munson KM, Hoekzema K, Chan DD, Wang Y, Knuth J, Garcia GH, Fanslow C, Lambert C, Lee C, Smith JD, Levy S, Mason CE, Garrison E, Lansdorp PM, Neklason DW, Jorde LB, Quinlan AR, Eberle MA, Eichler EE. A familial, telomere-to-telomere reference for human de novo mutation and recombination from a four-generation pedigree. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.05.606142. [PMID: 39149261 PMCID: PMC11326147 DOI: 10.1101/2024.08.05.606142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Using five complementary short- and long-read sequencing technologies, we phased and assembled >95% of each diploid human genome in a four-generation, 28-member family (CEPH 1463) allowing us to systematically assess de novo mutations (DNMs) and recombination. From this family, we estimate an average of 192 DNMs per generation, including 75.5 de novo single-nucleotide variants (SNVs), 7.4 non-tandem repeat indels, 79.6 de novo indels or structural variants (SVs) originating from tandem repeats, 7.7 centromeric de novo SVs and SNVs, and 12.4 de novo Y chromosome events per generation. STRs and VNTRs are the most mutable with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations, documenting de novo SVs, and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length, and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 17% of de novo SNVs are postzygotic in origin with no paternal bias. We place all this variation in the context of a high-resolution recombination map (~3.5 kbp breakpoint resolution). We observe a strong maternal recombination bias (1.36 maternal:paternal ratio) with a consistent reduction in the number of crossovers with increasing paternal (r=0.85) and maternal (r=0.65) age. However, we observe no correlation between meiotic crossover locations and de novo SVs, arguing against non-allelic homologous recombination as a predominant mechanism. The use of multiple orthogonal technologies, near-telomere-to-telomere phased genome assemblies, and a multi-generation family to assess transmission has created the most comprehensive, publicly available "truth set" of all classes of genomic variants. The resource can be used to test and benchmark new algorithms and technologies to understand the most fundamental processes underlying human genetic variation.
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Affiliation(s)
- David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Harriet Dashnow
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Thomas A Sasani
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Glennis A Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pille Hallast
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Michelle D Noyes
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Nidhi Koundinya
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Cody J Steely
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
- Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Andrea Guarracino
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William J Rowell
- Department of Internal Medicine, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Kirill Grigorev
- Blue Marble Space Institute of Science, Seattle, WA, USA
- Core Unit Bioinformatics, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Thomas J Nicholas
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Keisuke K Oshima
- Present address: Department of Genetics, Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jiadong Lin
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter Ebert
- Core Unit Bioinformatics, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- Center for Digital Medicine, Heinrich Heine University, Düsseldorf, Germany
| | - W Scott Watkins
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Tiffany Y Leung
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | | | - Sean McGee
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Brent S Pedersen
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Michael E Goldberg
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hannah C Happ
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Hyeonsoo Jeong
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Present address: Altos Labs, San Diego, CA, USA
| | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Daniel D Chan
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | - Yanni Wang
- Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada
| | - Jordan Knuth
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Gage H Garcia
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Joshua D Smith
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Shawn Levy
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Erik Garrison
- Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Deborah W Neklason
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | | | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
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19
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Sehgal A, Ziaei Jam H, Shen A, Gymrek M. Genome-wide detection of somatic mosaicism at short tandem repeats. Bioinformatics 2024; 40:btae485. [PMID: 39078205 PMCID: PMC11319640 DOI: 10.1093/bioinformatics/btae485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 06/30/2024] [Accepted: 07/29/2024] [Indexed: 07/31/2024] Open
Abstract
MOTIVATION Somatic mosaicism has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6 bp and comprise >1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs is lacking. RESULTS We introduce prancSTR, a novel method for detecting mosaic STRs from individual high-throughput sequencing datasets. prancSTR is designed to detect loci characterized by a single high-frequency mosaic allele, but can also detect loci with multiple mosaic alleles. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mosaic STRs in simulated data, demonstrate its feasibility by identifying candidate mosaic STRs in Illumina whole genome sequencing data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project, and evaluate the use of prancSTR on Element and PacBio data. In addition to prancSTR, we present simTR, a novel simulation framework which simulates raw sequencing reads with realistic error profiles at STRs. AVAILABILITY AND IMPLEMENTATION prancSTR and simTR are freely available at https://github.com/gymrek-lab/trtools. Detailed documentation is available at https://trtools.readthedocs.io/.
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Affiliation(s)
- Aarushi Sehgal
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Helyaneh Ziaei Jam
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Andrew Shen
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
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20
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Chamberlin JT, Gillen AE, Quinlan AR. Improved characterization of single-cell RNA-seq libraries with paired-end avidity sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.10.602909. [PMID: 39026715 PMCID: PMC11257511 DOI: 10.1101/2024.07.10.602909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Prevailing poly(dT)-primed 3' single-cell RNA-seq protocols generate barcoded cDNA fragments containing the reverse transcriptase priming site, which is expected to be the poly(A) tail or a genomic adenine homopolymer. Direct sequencing across this priming site was historically difficult because of DNA sequencing errors induced by the homopolymeric primer at the 'barcode' end. Here, we evaluate the capability of "avidity base chemistry" DNA sequencing from Element Biosciences to sequence through this homopolymer accurately, and the impact of the additional cDNA sequence on read alignment and precise quantification of polyadenylation site usage. We find that the Element Aviti instrument sequences through the thymine homopolymer into the subsequent cDNA sequence without detectable loss of accuracy. The resulting paired-end alignments enable direct and independent assignment of reads to polyadenylation sites, which bypasses complexities and limitations of conventional approaches but does not consistently improve read mapping rates compared to single-end alignment. We also characterize low-level artifacts and arrive at an adjusted adapter trimming and alignment workflow that significantly improves the alignment of sequence data from Element and Illumina, particularly in the context of extended read lengths. Our analyses confirm that Element avidity sequencing is an effective alternative to Illumina sequencing for standard single-cell RNA-seq, particularly for polyadenylation site analyses but do not rule out the potential for similar performance from other emerging platforms.
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Affiliation(s)
- John T Chamberlin
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA
| | - Austin E Gillen
- RNA Bioscience Initiative, University of Colorado School of Medicine, Aurora, CO, 80045, USA
- Division of Hematology, University of Colorado School of Medicine, Aurora, CO, 80045, USA
- Rocky Mountain Regional VA Medical Center, Aurora, CO, 80045, USA
| | - Aaron R Quinlan
- Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA
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21
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Hale B, Watts C, Conatser M, Brown E, Wijeratne AJ. Fine-scale characterization of the soybean rhizosphere microbiome via synthetic long reads and avidity sequencing. ENVIRONMENTAL MICROBIOME 2024; 19:46. [PMID: 38997772 PMCID: PMC11241880 DOI: 10.1186/s40793-024-00590-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 07/03/2024] [Indexed: 07/14/2024]
Abstract
BACKGROUND The rhizosphere microbiome displays structural and functional dynamism driven by plant, microbial, and environmental factors. While such plasticity is a well-evidenced determinant of host health, individual and community-level microbial activity within the rhizosphere remain poorly understood, due in part to the insufficient taxonomic resolution achieved through traditional marker gene amplicon sequencing. This limitation necessitates more advanced approaches (e.g., long-read sequencing) to derive ecological inferences with practical application. To this end, the present study coupled synthetic long-read technology with avidity sequencing to investigate eukaryotic and prokaryotic microbiome dynamics within the soybean (Glycine max) rhizosphere under field conditions. RESULTS Synthetic long-read sequencing permitted de novo reconstruction of the entire 18S-ITS1-ITS2 region of the eukaryotic rRNA operon as well as all nine hypervariable regions of the 16S rRNA gene. All full-length, mapped eukaryotic amplicon sequence variants displayed genus-level classification, and 44.77% achieved species-level classification. The resultant eukaryotic microbiome encompassed five kingdoms (19 genera) of protists in addition to fungi - a depth unattainable with conventional short-read methods. In the prokaryotic fraction, every full-length, mapped amplicon sequence variant was resolved at the species level, and 23.13% at the strain level. Thirteen species of Bradyrhizobium were thereby distinguished in the prokaryotic microbiome, with strain-level identification of the two Bradyrhizobium species most reported to nodulate soybean. Moreover, the applied methodology delineated structural and compositional dynamism in response to experimental parameters (i.e., growth stage, cultivar, and biostimulant application), unveiled a saprotroph-rich core microbiome, provided empirical evidence for host selection of mutualistic taxa, and identified key microbial co-occurrence network members likely associated with edaphic and agronomic properties. CONCLUSIONS This study is the first to combine synthetic long-read technology and avidity sequencing to profile both eukaryotic and prokaryotic fractions of a plant-associated microbiome. Findings herein provide an unparalleled taxonomic resolution of the soybean rhizosphere microbiota and represent significant biological and technological advancements in crop microbiome research.
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Affiliation(s)
- Brett Hale
- AgriGro Incorporated, Doniphan, MO, USA
- Arkansas Biosciences Institute, Arkansas State University, State University, AR, USA
- College of Science and Mathematics, Arkansas State University, State University, AR, USA
| | - Caitlin Watts
- College of Agriculture, Arkansas State University, State University, AR, USA
- Department of Animal Sciences, Purdue University, West Lafayette, IN, USA
| | - Matthew Conatser
- College of Agriculture, Arkansas State University, State University, AR, USA
| | - Edward Brown
- College of Agriculture, Arkansas State University, State University, AR, USA
| | - Asela J Wijeratne
- Arkansas Biosciences Institute, Arkansas State University, State University, AR, USA.
- College of Science and Mathematics, Arkansas State University, State University, AR, USA.
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22
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Jugas R, Vitkova H. ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing. BMC Bioinformatics 2024; 25:233. [PMID: 38982375 PMCID: PMC11234778 DOI: 10.1186/s12859-024-05843-1] [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] [Received: 01/31/2024] [Accepted: 06/13/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results. RESULTS We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool. CONCLUSIONS The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .
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Affiliation(s)
- Robin Jugas
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic
| | - Helena Vitkova
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.
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23
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Jia H, Tan S, Zhang YE. Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae024. [PMID: 38991976 PMCID: PMC11423848 DOI: 10.1093/gpbjnl/qzae024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 07/13/2024]
Abstract
Next-generation sequencing (NGS), represented by Illumina platforms, has been an essential cornerstone of basic and applied research. However, the sequencing error rate of 1 per 1000 bp (10-3) represents a serious hurdle for research areas focusing on rare mutations, such as somatic mosaicism or microbe heterogeneity. By examining the high-fidelity sequencing methods developed in the past decade, we summarized three major factors underlying errors and the corresponding 12 strategies mitigating these errors. We then proposed a novel framework to classify 11 preexisting representative methods according to the corresponding combinatory strategies and identified three trends that emerged during methodological developments. We further extended this analysis to eight long-read sequencing methods, emphasizing error reduction strategies. Finally, we suggest two promising future directions that could achieve comparable or even higher accuracy with lower costs in both NGS and long-read sequencing.
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Affiliation(s)
- Hangxing Jia
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shengjun Tan
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yong E Zhang
- CAS Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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24
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Zhang J, Yao Y, Tan Y, Hu HY, Zeng LX, Zhang GQ. Genetic analysis of seven patients with inherited ichthyosis and Nagashima‑type palmoplantar keratoderma. Mol Med Rep 2024; 30:111. [PMID: 38695247 PMCID: PMC11094583 DOI: 10.3892/mmr.2024.13235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/22/2024] [Indexed: 05/18/2024] Open
Abstract
Inherited ichthyosis comprises a series of heterogeneous dermal conditions; it mainly manifests as widespread hyperkeratosis, xerosis and scaling of the skin. At times, overlapping symptoms require differential diagnosis between ichthyosis and several other similar disorders. The present study reports seven patients with confirmed or suspected to be associated with ichthyosis by conducting a thorough clinical and genetic investigation. Genetic testing was conducted using whole‑exome sequencing, with Sanger sequencing as the validation method. The MEGA7 program was used to analyze the conservation of amino acid residues affected by the detected missense variants. The enrolled patients exhibited ichthyosis‑like but distinct clinical manifestations. Genetic analysis identified diagnostic variations in the FLG, STS, KRT10 and SERPINB7 genes and clarified the carrying status of each variant in the respective family members. The two residues affected by the detected missense variants remained conserved across multiple species. Of note, the two variants, namely STS: c.452C>T(p.P151L) and c.647_650del(p.L216fs) are novel. In conclusion, a clear genetic differential diagnosis was made for the enrolled ichthyosis‑associated patients; the study findings also extended the mutation spectrum of ichthyosis and provided solid evidence for the counseling of the affected families.
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Affiliation(s)
- Jing Zhang
- Department of Gynecology and Obstetrics, Beijing Jishuitan Hospital, Capital Medical University, Beijing 102208, P.R. China
| | - Yue Yao
- Department of Dermatology, The First Hospital of Hebei Medical University, Candidate Branch of National Clinical Research Center for Skin Diseases, Hebei Provincial Innovation Center of Dermatology and Medical Cosmetology Technology, Shijiazhuang, Hebei 050030, P.R. China
| | - Ya Tan
- Department of Obstetrics and Gynecology, Peking University International Hospital, Beijing 102206, P.R. China
| | - Hua-Ying Hu
- Jiaen Genetics Laboratory, Beijing Jiaen Hospital, Beijing 100191, P.R. China
| | - Lin-Xi Zeng
- Department of Dermatology, The First Hospital of Hebei Medical University, Candidate Branch of National Clinical Research Center for Skin Diseases, Hebei Provincial Innovation Center of Dermatology and Medical Cosmetology Technology, Shijiazhuang, Hebei 050030, P.R. China
| | - Guo-Qiang Zhang
- Department of Dermatology, The First Hospital of Hebei Medical University, Candidate Branch of National Clinical Research Center for Skin Diseases, Hebei Provincial Innovation Center of Dermatology and Medical Cosmetology Technology, Shijiazhuang, Hebei 050030, P.R. China
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25
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McDonald AL, Boddicker AM, Savenkova MI, Brabb IM, Qi X, Moré DD, Cunha CW, Zhao J, Duttke SH. Efficient small fragment sequencing of human, cow, and bison miRNA, small RNA or csRNA-seq libraries using AVITI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.28.596343. [PMID: 38854037 PMCID: PMC11160585 DOI: 10.1101/2024.05.28.596343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Next-Generation Sequencing (NGS) catalyzed breakthroughs across various scientific domains. Illumina's sequencing by synthesis method has long been essential for NGS but emerging technologies like Element Biosciences' sequencing by avidity (AVITI) represent a novel approach. It has been reported that AVITI offers improved signal-to-noise ratios and cost reductions. However, the method relies on rolling circle amplification which can be impacted by polymer size, raising questions about its efficacy sequencing small RNAs (sRNA) molecules including microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and others that are crucial regulators of gene expression and involved in various biological processes. In addition, capturing capped small RNAs (csRNA-seq) has emerged as a powerful method to map active or "nascent" RNA polymerase II transcription initiation in tissues and clinical samples. Here, we report a new protocol for seamlessly sequencing short DNA fragments on the AVITI and demonstrate that AVITI and Illumina sequencing technologies equivalently capture human, cattle (Bos taurus) and the bison (Bison bison) sRNA or csRNA sequencing libraries, augmenting the confidence in both approaches. Additionally, analysis of generated nascent transcription start sites (TSSs) data for cattle and bison revealed inaccuracies in their current genome annotations and highlighted the possibility and need to translate small RNA sequencing methodologies to livestock. Our accelerated and optimized protocol therefore bridges the advantages of AVITI sequencing and critical methods that rely on sequencing short DNA fragments.
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Affiliation(s)
- Anna L McDonald
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | | | - Marina I Savenkova
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | - Ian M Brabb
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
| | | | - Daniela D Moré
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA 99164, USA
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA 99164, USA
| | - Cristina W Cunha
- Animal Disease Research Unit, Agricultural Research Service, United States Department of Agriculture, Pullman, WA 99164, USA
- Department of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA 99164, USA
| | | | - Sascha H Duttke
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, USA
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26
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Chan ICC, Panchot A, Schmidt E, McNulty S, Wiley BJ, Liu J, Turner K, Moukarzel L, Wong WSW, Tran D, Beeler JS, Batchi-Bouyou AL, Machiela MJ, Karyadi DM, Krajacich BJ, Zhao J, Kruglyak S, Lajoie B, Levy S, Patel M, Kantoff PW, Mason CE, Link DC, Druley TE, Stopsack KH, Bolton KL. ArCH: improving the performance of clonal hematopoiesis variant calling and interpretation. Bioinformatics 2024; 40:btae121. [PMID: 38485690 PMCID: PMC11014783 DOI: 10.1093/bioinformatics/btae121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 01/17/2024] [Accepted: 03/13/2024] [Indexed: 04/14/2024] Open
Abstract
MOTIVATION The acquisition of somatic mutations in hematopoietic stem and progenitor stem cells with resultant clonal expansion, termed clonal hematopoiesis (CH), is associated with increased risk of hematologic malignancies and other adverse outcomes. CH is generally present at low allelic fractions, but clonal expansion and acquisition of additional mutations leads to hematologic cancers in a small proportion of individuals. With high depth and high sensitivity sequencing, CH can be detected in most adults and its clonal trajectory mapped over time. However, accurate CH variant calling is challenging due to the difficulty in distinguishing low frequency CH mutations from sequencing artifacts. The lack of well-validated bioinformatic pipelines for CH calling may contribute to lack of reproducibility in studies of CH. RESULTS Here, we developed ArCH, an Artifact filtering Clonal Hematopoiesis variant calling pipeline for detecting single nucleotide variants and short insertions/deletions by combining the output of four variant calling tools and filtering based on variant characteristics and sequencing error rate estimation. ArCH is an end-to-end cloud-based pipeline optimized to accept a variety of inputs with customizable parameters adaptable to multiple sequencing technologies, research questions, and datasets. Using deep targeted sequencing data generated from six acute myeloid leukemia patient tumor: normal dilutions, 31 blood samples with orthogonal validation, and 26 blood samples with technical replicates, we show that ArCH improves the sensitivity and positive predictive value of CH variant detection at low allele frequencies compared to standard application of commonly used variant calling approaches. AVAILABILITY AND IMPLEMENTATION The code for this workflow is available at: https://github.com/kbolton-lab/ArCH.
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Affiliation(s)
- Irenaeus C C Chan
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Alex Panchot
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Evelyn Schmidt
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Brian J Wiley
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Jie Liu
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Kimberly Turner
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Lea Moukarzel
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, United States
| | - Wendy S W Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20814, United States
| | - Duc Tran
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - J Scott Beeler
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20814, United States
| | - Danielle M Karyadi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20814, United States
| | - Benjamin J Krajacich
- Department of Genomic Applications, Element BioSciences, San Diego, CA 92121, United States
| | - Junhua Zhao
- Department of Genomic Applications, Element BioSciences, San Diego, CA 92121, United States
| | - Semyon Kruglyak
- Department of Genomic Applications, Element BioSciences, San Diego, CA 92121, United States
| | - Bryan Lajoie
- Department of Genomic Applications, Element BioSciences, San Diego, CA 92121, United States
| | - Shawn Levy
- Department of Genomic Applications, Element BioSciences, San Diego, CA 92121, United States
| | - Minal Patel
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, United States
| | - Philip W Kantoff
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY 10065, United States
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York City, NY 10065, United States
| | - Daniel C Link
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Konrad H Stopsack
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, United States
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02130, United States
| | - Kelly L Bolton
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
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Dorey A, Howorka S. Nanopore DNA sequencing technologies and their applications towards single-molecule proteomics. Nat Chem 2024; 16:314-334. [PMID: 38448507 DOI: 10.1038/s41557-023-01322-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 07/14/2023] [Indexed: 03/08/2024]
Abstract
Sequencing of nucleic acids with nanopores has emerged as a powerful tool offering rapid readout, high accuracy, low cost and portability. This label-free method for sequencing at the single-molecule level is an achievement on its own. However, nanopores also show promise for the technologically even more challenging sequencing of polypeptides, something that could considerably benefit biological discovery, clinical diagnostics and homeland security, as current techniques lack portability and speed. Here we survey the biochemical innovations underpinning commercial and academic nanopore DNA/RNA sequencing techniques, and explore how these advances can fuel developments in future protein sequencing with nanopores.
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Affiliation(s)
- Adam Dorey
- Department of Chemistry & Institute of Structural Molecular Biology, University College London, London, UK.
| | - Stefan Howorka
- Department of Chemistry & Institute of Structural Molecular Biology, University College London, London, UK.
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