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Del Gobbo GF, Wang X, Couse M, Mackay L, Goldsmith C, Marshall AE, Liang Y, Lambert C, Zhang S, Dhillon H, Fanslow C, Rowell WJ, Marshall CR, Kernohan KD, Boycott KM. Long-read genome sequencing reveals a novel intronic retroelement insertion in NR5A1 associated with 46,XY differences of sexual development. Am J Med Genet A 2024; 194:e63522. [PMID: 38131126 DOI: 10.1002/ajmg.a.63522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 12/23/2023]
Abstract
Despite significant advancements in rare genetic disease diagnostics, many patients with rare genetic disease remain without a molecular diagnosis. Novel tools and methods are needed to improve the detection of disease-associated variants and understand the genetic basis of many rare diseases. Long-read genome sequencing provides improved sequencing in highly repetitive, homologous, and low-complexity regions, and improved assessment of structural variation and complex genomic rearrangements compared to short-read genome sequencing. As such, it is a promising method to explore overlooked genetic variants in rare diseases with a high suspicion of a genetic basis. We therefore applied PacBio HiFi sequencing in a large multi-generational family presenting with autosomal dominant 46,XY differences of sexual development (DSD), for whom extensive molecular testing over multiple decades had failed to identify a molecular diagnosis. This revealed a rare SINE-VNTR-Alu retroelement insertion in intron 4 of NR5A1, a gene in which loss-of-function variants are an established cause of 46,XY DSD. The insertion segregated among affected family members and was associated with loss-of-expression of alleles in cis, demonstrating a functional impact on NR5A1. This case highlights the power of long-read genome sequencing to detect genomic variants that have previously been intractable to detection by standard short-read genomic testing.
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Affiliation(s)
- Giulia F Del Gobbo
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - Xueqi Wang
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - Madeline Couse
- Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | - Layla Mackay
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Claire Goldsmith
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Aren E Marshall
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - Yijing Liang
- Centre for Computational Medicine, The Hospital for Sick Children, Toronto, Canada
| | | | - Siyuan Zhang
- PacBio of California, Inc, Menlo Park, California, USA
| | | | | | | | | | - Kristin D Kernohan
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
- Newborn Screening Ontario, Ottawa, Canada
| | - Kym M Boycott
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
- Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Canada
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2
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Holt JM, Saunders CT, Rowell WJ, Kronenberg Z, Wenger AM, Eberle M. HiPhase: jointly phasing small, structural, and tandem repeat variants from HiFi sequencing. Bioinformatics 2024; 40:btae042. [PMID: 38269623 PMCID: PMC10868326 DOI: 10.1093/bioinformatics/btae042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 12/13/2023] [Accepted: 01/22/2024] [Indexed: 01/26/2024] Open
Abstract
MOTIVATION In diploid organisms, phasing is the problem of assigning the alleles at heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation, such as structural or tandem repeat variants. However, current phasing tools typically only phase small variants, leaving larger variants unphased. RESULTS We developed HiPhase, a tool that jointly phases SNVs, indels, structural, and tandem repeat variants. The main benefits of HiPhase are (i) dual mode allele assignment for detecting large variants, (ii) a novel application of the A*-algorithm to phasing, and (iii) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. In our assessment, HiPhase produced an average phase block NG50 of 480 kb with 929 switchflip errors and fully phased 93.8% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, structural, and tandem repeat variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. AVAILABILITY AND IMPLEMENTATION HiPhase is available as source code and a pre-compiled Linux binary with a user guide at https://github.com/PacificBiosciences/HiPhase.
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Affiliation(s)
- James M Holt
- Computational Biology, PacBio, 1305 O’Brien Drive, Menlo Park, CA 94025, United States
| | | | - William J Rowell
- Computational Biology, PacBio, 1305 O’Brien Drive, Menlo Park, CA 94025, United States
| | - Zev Kronenberg
- Computational Biology, PacBio, 1305 O’Brien Drive, Menlo Park, CA 94025, United States
| | - Aaron M Wenger
- Computational Biology, PacBio, 1305 O’Brien Drive, Menlo Park, CA 94025, United States
| | - Michael Eberle
- Computational Biology, PacBio, 1305 O’Brien Drive, Menlo Park, CA 94025, United States
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3
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Dolzhenko E, English A, Dashnow H, De Sena Brandine G, Mokveld T, Rowell WJ, Karniski C, Kronenberg Z, Danzi MC, Cheung WA, Bi C, Farrow E, Wenger A, Chua KP, Martínez-Cerdeño V, Bartley TD, Jin P, Nelson DL, Zuchner S, Pastinen T, Quinlan AR, Sedlazeck FJ, Eberle MA. Characterization and visualization of tandem repeats at genome scale. Nat Biotechnol 2024:10.1038/s41587-023-02057-3. [PMID: 38168995 DOI: 10.1038/s41587-023-02057-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/06/2023] [Indexed: 01/05/2024]
Abstract
Tandem repeat (TR) variation is associated with gene expression changes and numerous rare monogenic diseases. Although long-read sequencing provides accurate full-length sequences and methylation of TRs, there is still a need for computational methods to profile TRs across the genome. Here we introduce the Tandem Repeat Genotyping Tool (TRGT) and an accompanying TR database. TRGT determines the consensus sequences and methylation levels of specified TRs from PacBio HiFi sequencing data. It also reports reads that support each repeat allele. These reads can be subsequently visualized with a companion TR visualization tool. Assessing 937,122 TRs, TRGT showed a Mendelian concordance of 98.38%, allowing a single repeat unit difference. In six samples with known repeat expansions, TRGT detected all expansions while also identifying methylation signals and mosaicism and providing finer repeat length resolution than existing methods. Additionally, we released a database with allele sequences and methylation levels for 937,122 TRs across 100 genomes.
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Affiliation(s)
| | - Adam English
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Harriet Dashnow
- Departments of Human Genetics and Biomedical Informatics, University of Utah, Salt Lake City, UT, USA
| | | | - Tom Mokveld
- Pacific Biosciences of California, Menlo Park, CA, USA
| | | | | | | | - Matt C Danzi
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Warren A Cheung
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Chengpeng Bi
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Emily Farrow
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Aaron Wenger
- Pacific Biosciences of California, Menlo Park, CA, USA
| | - Khi Pin Chua
- Pacific Biosciences of California, Menlo Park, CA, USA
| | - Verónica Martínez-Cerdeño
- Institute for Pediatric Regenerative Medicine, Shriner's Hospital for Children and UC Davis School of Medicine, Sacramento, CA, USA
- Department of Pathology & Laboratory Medicine, UC Davis School of Medicine, Sacramento, CA, USA
- MIND Institute, UC Davis School of Medicine, Sacramento, CA, USA
| | - Trevor D Bartley
- Institute for Pediatric Regenerative Medicine, Shriner's Hospital for Children and UC Davis School of Medicine, Sacramento, CA, USA
- Department of Pathology & Laboratory Medicine, UC Davis School of Medicine, Sacramento, CA, USA
| | - Peng Jin
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - David L Nelson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Stephan Zuchner
- Dr. John T. Macdonald Foundation Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Aaron R Quinlan
- Departments of Human Genetics and Biomedical Informatics, University of Utah, Salt Lake City, UT, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
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4
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Cheung WA, Johnson AF, Rowell WJ, Farrow E, Hall R, Cohen ASA, Means JC, Zion TN, Portik DM, Saunders CT, Koseva B, Bi C, Truong TK, Schwendinger-Schreck C, Yoo B, Johnston JJ, Gibson M, Evrony G, Rizzo WB, Thiffault I, Younger ST, Curran T, Wenger AM, Grundberg E, Pastinen T. Direct haplotype-resolved 5-base HiFi sequencing for genome-wide profiling of hypermethylation outliers in a rare disease cohort. Nat Commun 2023; 14:3090. [PMID: 37248219 DOI: 10.1038/s41467-023-38782-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 05/15/2023] [Indexed: 05/31/2023] Open
Abstract
Long-read HiFi genome sequencing allows for accurate detection and direct phasing of single nucleotide variants, indels, and structural variants. Recent algorithmic development enables simultaneous detection of CpG methylation for analysis of regulatory element activity directly in HiFi reads. We present a comprehensive haplotype resolved 5-base HiFi genome sequencing dataset from a rare disease cohort of 276 samples in 152 families to identify rare (~0.5%) hypermethylation events. We find that 80% of these events are allele-specific and predicted to cause loss of regulatory element activity. We demonstrate heritability of extreme hypermethylation including rare cis variants associated with short (~200 bp) and large hypermethylation events (>1 kb), respectively. We identify repeat expansions in proximal promoters predicting allelic gene silencing via hypermethylation and demonstrate allelic transcriptional events downstream. On average 30-40 rare hypermethylation tiles overlap rare disease genes per patient, providing indications for variation prioritization including a previously undiagnosed pathogenic allele in DIP2B causing global developmental delay. We propose that use of HiFi genome sequencing in unsolved rare disease cases will allow detection of unconventional diseases alleles due to loss of regulatory element activity.
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Affiliation(s)
- Warren A Cheung
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Adam F Johnson
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | | | - Emily Farrow
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA
| | | | - Ana S A Cohen
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA
- Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - John C Means
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Tricia N Zion
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | | | | | - Boryana Koseva
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Chengpeng Bi
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Tina K Truong
- Center for Human Genetics and Genomics, Department of Pediatrics, Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, USA
| | - Carl Schwendinger-Schreck
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Byunggil Yoo
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Jeffrey J Johnston
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Margaret Gibson
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Gilad Evrony
- Center for Human Genetics and Genomics, Department of Pediatrics, Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, USA
| | - William B Rizzo
- Child Health Research Institute, Department of Pediatrics, Nebraska Medical Center, Omaha, NE, USA
| | - Isabelle Thiffault
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA
- Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Scott T Younger
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA
| | - Tom Curran
- Children's Mercy Research Institute, Kansas City, MO, USA
| | | | - Elin Grundberg
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA.
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA.
| | - Tomi Pastinen
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA.
- Department of Pediatrics, School of Medicine, University of Missouri Kansas City, Kansas City, MO, USA.
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5
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Kucuk E, van der Sanden BPGH, O'Gorman L, Kwint M, Derks R, Wenger AM, Lambert C, Chakraborty S, Baybayan P, Rowell WJ, Brunner HG, Vissers LELM, Hoischen A, Gilissen C. Comprehensive de novo mutation discovery with HiFi long-read sequencing. Genome Med 2023; 15:34. [PMID: 37158973 PMCID: PMC10169305 DOI: 10.1186/s13073-023-01183-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 04/19/2023] [Indexed: 05/10/2023] Open
Abstract
BACKGROUND Long-read sequencing (LRS) techniques have been very successful in identifying structural variants (SVs). However, the high error rate of LRS made the detection of small variants (substitutions and short indels < 20 bp) more challenging. The introduction of PacBio HiFi sequencing makes LRS also suited for detecting small variation. Here we evaluate the ability of HiFi reads to detect de novo mutations (DNMs) of all types, which are technically challenging variant types and a major cause of sporadic, severe, early-onset disease. METHODS We sequenced the genomes of eight parent-child trios using high coverage PacBio HiFi LRS (~ 30-fold coverage) and Illumina short-read sequencing (SRS) (~ 50-fold coverage). De novo substitutions, small indels, short tandem repeats (STRs) and SVs were called in both datasets and compared to each other to assess the accuracy of HiFi LRS. In addition, we determined the parent-of-origin of the small DNMs using phasing. RESULTS We identified a total of 672 and 859 de novo substitutions/indels, 28 and 126 de novo STRs, and 24 and 1 de novo SVs in LRS and SRS respectively. For the small variants, there was a 92 and 85% concordance between the platforms. For the STRs and SVs, the concordance was 3.6 and 0.8%, and 4 and 100% respectively. We successfully validated 27/54 LRS-unique small variants, of which 11 (41%) were confirmed as true de novo events. For the SRS-unique small variants, we validated 42/133 DNMs and 8 (19%) were confirmed as true de novo event. Validation of 18 LRS-unique de novo STR calls confirmed none of the repeat expansions as true DNM. Confirmation of the 23 LRS-unique SVs was possible for 19 candidate SVs of which 10 (52.6%) were true de novo events. Furthermore, we were able to assign 96% of DNMs to their parental allele with LRS data, as opposed to just 20% with SRS data. CONCLUSIONS HiFi LRS can now produce the most comprehensive variant dataset obtainable by a single technology in a single laboratory, allowing accurate calling of substitutions, indels, STRs and SVs. The accuracy even allows sensitive calling of DNMs on all variant levels, and also allows for phasing, which helps to distinguish true positive from false positive DNMs.
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Affiliation(s)
- Erdi Kucuk
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Bart P G H van der Sanden
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Luke O'Gorman
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Michael Kwint
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Ronny Derks
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
| | | | | | | | | | | | - Han G Brunner
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands
- GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
- Department of Internal Medicine, Radboud University Medical Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Christian Gilissen
- Department of Human Genetics, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
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6
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Cohen ASA, Farrow EG, Abdelmoity AT, Alaimo JT, Amudhavalli SM, Anderson JT, Bansal L, Bartik L, Baybayan P, Belden B, Berrios CD, Biswell RL, Buczkowicz P, Buske O, Chakraborty S, Cheung WA, Coffman KA, Cooper AM, Cross LA, Curran T, Dang TTT, Elfrink MM, Engleman KL, Fecske ED, Fieser C, Fitzgerald K, Fleming EA, Gadea RN, Gannon JL, Gelineau-Morel RN, Gibson M, Goldstein J, Grundberg E, Halpin K, Harvey BS, Heese BA, Hein W, Herd SM, Hughes SS, Ilyas M, Jacobson J, Jenkins JL, Jiang S, Johnston JJ, Keeler K, Korlach J, Kussmann J, Lambert C, Lawson C, Le Pichon JB, Leeder JS, Little VC, Louiselle DA, Lypka M, McDonald BD, Miller N, Modrcin A, Nair A, Neal SH, Oermann CM, Pacicca DM, Pawar K, Posey NL, Price N, Puckett LMB, Quezada JF, Raje N, Rowell WJ, Rush ET, Sampath V, Saunders CJ, Schwager C, Schwend RM, Shaffer E, Smail C, Soden S, Strenk ME, Sullivan BR, Sweeney BR, Tam-Williams JB, Walter AM, Welsh H, Wenger AM, Willig LK, Yan Y, Younger ST, Zhou D, Zion TN, Thiffault I, Pastinen T. Genomic answers for children: Dynamic analyses of >1000 pediatric rare disease genomes. Genet Med 2022; 24:1336-1348. [PMID: 35305867 DOI: 10.1016/j.gim.2022.02.007] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 02/05/2022] [Accepted: 02/07/2022] [Indexed: 12/17/2022] Open
Abstract
PURPOSE This study aimed to provide comprehensive diagnostic and candidate analyses in a pediatric rare disease cohort through the Genomic Answers for Kids program. METHODS Extensive analyses of 960 families with suspected genetic disorders included short-read exome sequencing and short-read genome sequencing (srGS); PacBio HiFi long-read genome sequencing (HiFi-GS); variant calling for single nucleotide variants (SNV), structural variant (SV), and repeat variants; and machine-learning variant prioritization. Structured phenotypes, prioritized variants, and pedigrees were stored in PhenoTips database, with data sharing through controlled access the database of Genotypes and Phenotypes. RESULTS Diagnostic rates ranged from 11% in patients with prior negative genetic testing to 34.5% in naive patients. Incorporating SVs from genome sequencing added up to 13% of new diagnoses in previously unsolved cases. HiFi-GS yielded increased discovery rate with >4-fold more rare coding SVs compared with srGS. Variants and genes of unknown significance remain the most common finding (58% of nondiagnostic cases). CONCLUSION Computational prioritization is efficient for diagnostic SNVs. Thorough identification of non-SNVs remains challenging and is partly mitigated using HiFi-GS sequencing. Importantly, community research is supported by sharing real-time data to accelerate gene validation and by providing HiFi variant (SNV/SV) resources from >1000 human alleles to facilitate implementation of new sequencing platforms for rare disease diagnoses.
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Affiliation(s)
- Ana S A Cohen
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO
| | - Emily G Farrow
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Joseph T Alaimo
- Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO
| | - Shivarajan M Amudhavalli
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - John T Anderson
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Lalit Bansal
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Lauren Bartik
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Bradley Belden
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | | | - Rebecca L Biswell
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | | | | | | | - Warren A Cheung
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Keith A Coffman
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Ashley M Cooper
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Laura A Cross
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Tom Curran
- Children's Mercy Research Institute, Kansas City, MO
| | - Thuy Tien T Dang
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Mary M Elfrink
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | | | - Erin D Fecske
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Cynthia Fieser
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Keely Fitzgerald
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Emily A Fleming
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Randi N Gadea
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Rose N Gelineau-Morel
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Margaret Gibson
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Jeffrey Goldstein
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Elin Grundberg
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Kelsee Halpin
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Brian S Harvey
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Bryce A Heese
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Wendy Hein
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Suzanne M Herd
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Susan S Hughes
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Mohammed Ilyas
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Jill Jacobson
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Janda L Jenkins
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | | | - Kathryn Keeler
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Jonas Korlach
- Pacific Biosciences of California, Inc, Menlo Park, CA
| | | | | | - Caitlin Lawson
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | | | - Vicki C Little
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | | | | | | | - Neil Miller
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Division of Allergy Immunology Pulmonary and Sleep Medicine, Children's Mercy Kansas City, Kansas City, MO
| | - Ann Modrcin
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Annapoorna Nair
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Shelby H Neal
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | | | - Donna M Pacicca
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Kailash Pawar
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Nyshele L Posey
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Nigel Price
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Laura M B Puckett
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Julio F Quezada
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Nikita Raje
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Division of Neonatology, Children's Mercy Kansas City, Kansas City, MO
| | | | - Eric T Rush
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Division of Genetics, Children's Mercy Kansas City, Kansas City, MO; Department of Internal Medicine, University of Kansas School of Medicine, Kansas City, MO
| | - Venkatesh Sampath
- Division of Neonatology, Children's Mercy Hospital Kansas City, Kansas City, MO
| | - Carol J Saunders
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO
| | - Caitlin Schwager
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Richard M Schwend
- Department of Orthopaedic Surgery, Children's Mercy Kansas City, Kansas City, MO
| | - Elizabeth Shaffer
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Craig Smail
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Sarah Soden
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Meghan E Strenk
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Brooke R Sweeney
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Adam M Walter
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Holly Welsh
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | | | - Laurel K Willig
- Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Yun Yan
- UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO
| | - Scott T Younger
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Dihong Zhou
- Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Tricia N Zion
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO; Division of Genetics, Children's Mercy Kansas City, Kansas City, MO
| | - Isabelle Thiffault
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; Department of Pathology and Laboratory Medicine, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO.
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO; UKMC School of Medicine, University of Missouri Kansas City, Kansas City, MO; Children's Mercy Research Institute, Kansas City, MO.
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7
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Wagner J, Olson ND, Harris L, Khan Z, Farek J, Mahmoud M, Stankovic A, Kovacevic V, Yoo B, Miller N, Rosenfeld JA, Ni B, Zarate S, Kirsche M, Aganezov S, Schatz MC, Narzisi G, Byrska-Bishop M, Clarke W, Evani US, Markello C, Shafin K, Zhou X, Sidow A, Bansal V, Ebert P, Marschall T, Lansdorp P, Hanlon V, Mattsson CA, Barrio AM, Fiddes IT, Xiao C, Fungtammasan A, Chin CS, Wenger AM, Rowell WJ, Sedlazeck FJ, Carroll A, Salit M, Zook JM. Benchmarking challenging small variants with linked and long reads. Cell Genom 2022; 2:100128. [PMID: 36452119 PMCID: PMC9706577 DOI: 10.1016/j.xgen.2022.100128] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Ziad Khan
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Ana Stankovic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Vladimir Kovacevic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Byunggil Yoo
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | - Neil Miller
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | | | - Bohan Ni
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Giuseppe Narzisi
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | | | - Wayne Clarke
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Uday S. Evani
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Charles Markello
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Kishwar Shafin
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Xin Zhou
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Arend Sidow
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Vikas Bansal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Peter Ebert
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Tobias Marschall
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Peter Lansdorp
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Vincent Hanlon
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Carl-Adam Mattsson
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | | | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Andrew Carroll
- Google Inc., 1600 Amphitheatre Pkwy., Mountain View, CA 94040, USA
| | - Marc Salit
- Joint Initiative for Metrology in Biology, SLAC National Laboratory, Stanford, CA, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
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8
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Wagner J, Olson ND, Harris L, McDaniel J, Cheng H, Fungtammasan A, Hwang YC, Gupta R, Wenger AM, Rowell WJ, Khan ZM, Farek J, Zhu Y, Pisupati A, Mahmoud M, Xiao C, Yoo B, Sahraeian SME, Miller DE, Jáspez D, Lorenzo-Salazar JM, Muñoz-Barrera A, Rubio-Rodríguez LA, Flores C, Narzisi G, Evani US, Clarke WE, Lee J, Mason CE, Lincoln SE, Miga KH, Ebbert MTW, Shumate A, Li H, Chin CS, Zook JM, Sedlazeck FJ. Curated variation benchmarks for challenging medically relevant autosomal genes. Nat Biotechnol 2022; 40:672-680. [PMID: 35132260 PMCID: PMC9117392 DOI: 10.1038/s41587-021-01158-1] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/10/2021] [Indexed: 11/09/2022]
Abstract
The repetitive nature and complexity of some medically relevant genes poses a challenge for their accurate analysis in a clinical setting. The Genome in a Bottle Consortium has provided variant benchmark sets, but these exclude nearly 400 medically relevant genes due to their repetitiveness or polymorphic complexity. Here, we characterize 273 of these 395 challenging autosomal genes using a haplotype-resolved whole-genome assembly. This curated benchmark reports over 17,000 single-nucleotide variations, 3,600 insertions and deletions and 200 structural variations each for human genome reference GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically relevant genes, including CBS, CRYAA and KCNE1. When masking these false duplications, variant recall can improve from 8% to 100%. Forming benchmarks from a haplotype-resolved whole-genome assembly may become a prototype for future benchmarks covering the whole genome.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Haoyu Cheng
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | | | | | | | | | - Ziad M Khan
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Yiming Zhu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Aishwarya Pisupati
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Byunggil Yoo
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, USA
| | | | - Danny E Miller
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David Jáspez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - José M Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Adrián Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Luis A Rubio-Rodríguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), Santa Cruz de Tenerife, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Hospital Universitario N.S. de Candelaria, Santa Cruz de Tenerife, Spain
| | | | | | | | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | | | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mark T W Ebbert
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Internal Medicine, Division of Biomedical Informatics, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Center for Computational Biology, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Heng Li
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | | | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
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9
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Laine P, Rowell WJ, Paulin L, Kujawa S, Raterman D, Mayhew G, Wendt J, Burgess DL, Partonen T, Paunio T, Auvinen P, Ekholm JM. Alu element in the RNA binding motif protein, X-linked 2 (RBMX2) gene found to be linked to bipolar disorder. PLoS One 2021; 16:e0261170. [PMID: 34914762 PMCID: PMC8675739 DOI: 10.1371/journal.pone.0261170] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 11/24/2021] [Indexed: 11/23/2022] Open
Abstract
Objective We have used long-read single molecule, real-time (SMRT) sequencing to fully characterize a ~12Mb genomic region on chromosome Xq24-q27, significantly linked to bipolar disorder (BD) in an extended family from a genetic sub-isolate. This family segregates BD in at least four generations with 24 affected individuals. Methods We selected 16 family members for targeted sequencing. The selected individuals either carried the disease haplotype, were non-carriers of the disease haplotype, or served as married-in controls. We designed hybrid capture probes enriching for 5-9Kb fragments spanning the entire 12Mb region that were then sequenced to screen for candidate structural variants (SVs) that could explain the increased risk for BD in this extended family. Results Altogether, 201 variants were detected in the critically linked region. Although most of these represented common variants, three variants emerged that showed near-perfect segregation among all BD type I affected individuals. Two of the SVs were identified in or near genes belonging to the RNA Binding Motif Protein, X-Linked (RBMX) gene family—a 330bp Alu (subfamily AluYa5) deletion in intron 3 of the RBMX2 gene and an intergenic 27bp tandem repeat deletion between the RBMX and G protein-coupled receptor 101 (GPR101) genes. The third SV was a 50bp tandem repeat insertion in intron 1 of the Coagulation Factor IX (F9) gene. Conclusions Among the three genetically linked SVs, additional evidence supported the Alu element deletion in RBMX2 as the leading candidate for contributing directly to the disease development of BD type I in this extended family.
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Affiliation(s)
- Pia Laine
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | | | - Lars Paulin
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Steve Kujawa
- Pacific Biosciences, Menlo Park, CA, United States of America
| | - Denise Raterman
- Roche Sequencing Solutions, Madison, WI, United States of America
| | - George Mayhew
- Roche Sequencing Solutions, Madison, WI, United States of America
| | - Jennifer Wendt
- Roche Sequencing Solutions, Madison, WI, United States of America
| | | | - Timo Partonen
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
| | - Tiina Paunio
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry, University of Helsinki, Helsinki, Finland
| | - Petri Auvinen
- Institute of Biotechnology, University of Helsinki, Helsinki, Finland
| | - Jenny M. Ekholm
- Pacific Biosciences, Menlo Park, CA, United States of America
- * E-mail:
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10
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Chin CS, Wagner J, Zeng Q, Garrison E, Garg S, Fungtammasan A, Rautiainen M, Aganezov S, Kirsche M, Zarate S, Schatz MC, Xiao C, Rowell WJ, Markello C, Farek J, Sedlazeck FJ, Bansal V, Yoo B, Miller N, Zhou X, Carroll A, Barrio AM, Salit M, Marschall T, Dilthey AT, Zook JM. A diploid assembly-based benchmark for variants in the major histocompatibility complex. Nat Commun 2020; 11:4794. [PMID: 32963235 PMCID: PMC7508831 DOI: 10.1038/s41467-020-18564-9] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 08/27/2020] [Indexed: 01/20/2023] Open
Abstract
Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks.
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Affiliation(s)
- Chen-Shan Chin
- DNAnexus, Inc, 1975 W El Camino Real, Suite 204, Mountain View, CA, 94040, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD, 20899, USA
| | - Qiandong Zeng
- Laboratory Corporation of America Holdings, 3400 Computer Drive, Westborough, MA, 01581, USA
| | - Erik Garrison
- University of California, Santa Cruz, 1156 High St, Santa Cruz, CA, 95064, USA
| | - Shilpa Garg
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | | | - Mikko Rautiainen
- Center for Bioinformatics, Saarland University, Saarland Informatics Campus E2.1, 66123, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarland Informatics Campus E1.4, 66123, Saarbrücken, Germany
- Saarland Graduate School for Computer Science, Saarland Informatics Campus E1.3, 66123, Saarbrücken, Germany
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, 11724, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA
| | | | - Charles Markello
- University of California, Santa Cruz, 1156 High St, Santa Cruz, CA, 95064, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
| | - Vikas Bansal
- Department of Pediatrics, University of California San Diego, La Jolla, CA, 92093, USA
| | - Byunggil Yoo
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Neil Miller
- Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Xin Zhou
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
| | - Andrew Carroll
- Google Inc, 1600 Amphitheatre Pkwy, Mountain View, CA, 94043, USA
| | | | - Marc Salit
- Joint Initiative for Metrology in Biology, Stanford, CA, 94305, USA
| | - Tobias Marschall
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Alexander T Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD, 20899, USA.
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11
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Wenger AM, Peluso P, Rowell WJ, Chang PC, Hall RJ, Concepcion GT, Ebler J, Fungtammasan A, Kolesnikov A, Olson ND, Töpfer A, Alonge M, Mahmoud M, Qian Y, Chin CS, Phillippy AM, Schatz MC, Myers G, DePristo MA, Ruan J, Marschall T, Sedlazeck FJ, Zook JM, Li H, Koren S, Carroll A, Rank DR, Hunkapiller MW. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat Biotechnol 2019; 37:1155-1162. [PMID: 31406327 PMCID: PMC6776680 DOI: 10.1038/s41587-019-0217-9] [Citation(s) in RCA: 745] [Impact Index Per Article: 149.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 07/08/2019] [Indexed: 12/30/2022]
Abstract
The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.
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Affiliation(s)
| | | | | | | | | | | | - Jana Ebler
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarbrücken, Germany
- Graduate School of Computer Science, Saarland University, Saarbrücken, Germany
| | | | | | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Michael Alonge
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Gene Myers
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | | | - Jue Ruan
- Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Tobias Marschall
- Center for Bioinformatics, Saarland University, Saarbrücken, Germany
- Max Planck Institute for Informatics, Saarbrücken, Germany
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Heng Li
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, Bethesda, MD, USA
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12
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Tseng E, Rowell WJ, Glenn OC, Hon T, Barrera J, Kujawa S, Chiba-Falek O. The Landscape of SNCA Transcripts Across Synucleinopathies: New Insights From Long Reads Sequencing Analysis. Front Genet 2019; 10:584. [PMID: 31338105 PMCID: PMC6629766 DOI: 10.3389/fgene.2019.00584] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 06/04/2019] [Indexed: 11/21/2022] Open
Abstract
Dysregulation of alpha-synuclein expression has been implicated in the pathogenesis of synucleinopathies, in particular Parkinson's Disease (PD) and Dementia with Lewy bodies (DLB). Previous studies have shown that the alternatively spliced isoforms of the SNCA gene are differentially expressed in different parts of the brain for PD and DLB patients. Similarly, SNCA isoforms with skipped exons can have a functional impact on the protein domains. The large intronic region of the SNCA gene was also shown to harbor structural variants that affect transcriptional levels. Here, we apply the first study of using long read sequencing with targeted capture of both the gDNA and cDNA of the SNCA gene in brain tissues of PD, DLB, and control samples using the PacBio Sequel system. The targeted full-length cDNA (Iso-Seq) data confirmed complex usage of known alternative start sites and variable 3' UTR lengths, as well as novel 5' starts and 3' ends not previously described. The targeted gDNA data allowed phasing of up to 81% of the ~114 kb SNCA region, with the longest phased block exceeding 54 kb. We demonstrate that long gDNA and cDNA reads have the potential to reveal long-range information not previously accessible using traditional sequencing methods. This approach has a potential impact in studying disease risk genes such as SNCA, providing new insights into the genetic etiologies, including perturbations to the landscape the gene transcripts, of human complex diseases such as synucleinopathies.
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Affiliation(s)
| | | | - Omolara-Chinue Glenn
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, United States
| | - Ting Hon
- Pacific Biosciences, Menlo Park, CA, United States
| | - Julio Barrera
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, United States
| | - Steve Kujawa
- Pacific Biosciences, Menlo Park, CA, United States
| | - Ornit Chiba-Falek
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, United States
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13
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Fijneman RJA, Mekkes N, Broek EVD, Stringer B, Glas RA, Komor MA, Rausch C, Lieshout SV, Cuppen E, Smith ML, Sebra RP, Rowell WJ, Ashby M, Carvalho B, Heringa J, Meijer GA, Abeln S. Abstract 1738: Characterization of structural variants within MACROD2 in the pathogenesis of colorectal cancer. Cancer Res 2019. [DOI: 10.1158/1538-7445.am2019-1738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Cancer is caused by somatic DNA alterations, which comprise small nucleotide variants (SNVs), chromosome somatic copy number alterations (SCNAs) and chromosomal breakpoint structural variants (SVs). Previously, we investigated SCNA-associated SVs in colorectal cancer (CRC) and demonstrated that SVs within the MACROD2 gene are highly prevalent. This raises the question whether SVs in MACROD2 may already be present in CRC precursor lesions, i.e. in colorectal adenomas. We have also demonstrated that loss of MACROD2 protein expression is associated with poor response to treatment with 5-fluorouracil-based adjuvant chemotherapy, indicating that MACROD2 function is clinically relevant. The aim of this study is to characterize SVs within MACROD2 in more detail in the pathogenesis of colorectal cancer.
Methods: The frequencies of SCNA-associated SVs in 466 CRCs were compared to those in 118 colorectal adenomas, using array-comparative genomic hybridization. Targeted PacBio long-read sequencing was applied to detect and characterize SVs at nucleotide resolution within MACROD2, in tens of primary CRCs. Illumina whole genome sequencing data of > 450 CRC metastatic lesions, generated by the Hartwig Medical Foundation (HMF; www.hartwigmedicalfoundation.nl), were used for validation purposes.
Results: MACROD2 SCNA-associated SVs were rarely detected among 118 colorectal adenomas (<2%) while being highly prevalent among 466 CRCs (40%). SVs in MACROD2 are currently being characterized at nucleotide resolution by analysis of targeted PacBio long-read sequencing data, the results of which will be presented during the AACR annual meeting. Preliminary analysis of HMF whole genome sequencing data confirms that at least 40% of CRC metastatic lesions are affected by SVs within the MACROD2 gene, most commonly by focal deletions.
Discussion: The current observation that SVs in MACROD2 are nearly absent in adenomas while being highly prevalent in CRCs indicates that MACROD2 is affected at a late stage of colorectal adenoma-to-carcinoma progression. A recent publication by Sakthianandeswaren et al (Cancer Discovery 2018) indicated that loss of MACROD2 promotes chromosomal instability. Taken together, these data support a model in which adenoma-to-carcinoma progression is driven, at least in part, by genomic instability caused by loss of function of the MACROD2 tumor suppressor gene.
Citation Format: Remond J A Fijneman, Nienke Mekkes, Evert van den Broek, Bas Stringer, Roel A. Glas, Malgorzata A. Komor, Christian Rausch, Stef van Lieshout, Edwin Cuppen, Melissa L. Smith, Robert P. Sebra, William J. Rowell, Meredith Ashby, Beatriz Carvalho, Jaap Heringa, Gerrit A. Meijer, Sanne Abeln. Characterization of structural variants within MACROD2 in the pathogenesis of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1738.
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Affiliation(s)
| | | | | | - Bas Stringer
- 3Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Roel A. Glas
- 1Netherlands Cancer Inst., Amsterdam, Netherlands
| | | | | | | | - Edwin Cuppen
- 4Hartwig Medical Foundation, Amsterdam, Netherlands
| | - Melissa L. Smith
- 5Icahn Institute of Data Science and Genomics Technology; Icahn School of Medicine at Mount Sinai, New York, NY
| | - Robert P. Sebra
- 5Icahn Institute of Data Science and Genomics Technology; Icahn School of Medicine at Mount Sinai, New York, NY
| | | | | | | | - Jaap Heringa
- 3Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | | | - Sanne Abeln
- 3Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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14
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Aso Y, Sitaraman D, Ichinose T, Kaun KR, Vogt K, Belliart-Guérin G, Plaçais PY, Robie AA, Yamagata N, Schnaitmann C, Rowell WJ, Johnston RM, Ngo TTB, Chen N, Korff W, Nitabach MN, Heberlein U, Preat T, Branson KM, Tanimoto H, Rubin GM. Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila. eLife 2014; 3:e04580. [PMID: 25535794 PMCID: PMC4273436 DOI: 10.7554/elife.04580] [Citation(s) in RCA: 394] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Accepted: 11/07/2014] [Indexed: 12/11/2022] Open
Abstract
Animals discriminate stimuli, learn their predictive value and use this knowledge to modify their behavior. In Drosophila, the mushroom body (MB) plays a key role in these processes. Sensory stimuli are sparsely represented by ∼2000 Kenyon cells, which converge onto 34 output neurons (MBONs) of 21 types. We studied the role of MBONs in several associative learning tasks and in sleep regulation, revealing the extent to which information flow is segregated into distinct channels and suggesting possible roles for the multi-layered MBON network. We also show that optogenetic activation of MBONs can, depending on cell type, induce repulsion or attraction in flies. The behavioral effects of MBON perturbation are combinatorial, suggesting that the MBON ensemble collectively represents valence. We propose that local, stimulus-specific dopaminergic modulation selectively alters the balance within the MBON network for those stimuli. Our results suggest that valence encoded by the MBON ensemble biases memory-based action selection. DOI:http://dx.doi.org/10.7554/eLife.04580.001 An animal's survival depends on its ability to respond appropriately to its environment, approaching stimuli that signal rewards and avoiding any that warn of potential threats. In fruit flies, this behavior requires activity in a region of the brain called the mushroom body, which processes sensory information and uses that information to influence responses to stimuli. Aso et al. recently mapped the mushroom body of the fruit fly in its entirety. This work showed, among other things, that the mushroom body contained 21 different types of output neurons. Building on this work, Aso et al. have started to work out how this circuitry enables flies to learn to associate a stimulus, such as an odor, with an outcome, such as the presence of food. Two complementary techniques—the use of molecular genetics to block neuronal activity, and the use of light to activate neurons (a technique called optogenetics)—were employed to study the roles performed by the output neurons in the mushroom body. Results revealed that distinct groups of output cells must be activated for flies to avoid—as opposed to approach—odors. Moreover, the same output neurons are used to avoid both odors and colors that have been associated with punishment. Together, these results indicate that the output cells do not encode the identity of stimuli: rather, they signal whether a stimulus should be approached or avoided. The output cells also regulate the amount of sleep taken by the fly, which is consistent with the mushroom body having a broader role in regulating the fly's internal state. The results of these experiments—combined with new knowledge about the detailed structure of the mushroom body—lay the foundations for new studies that explore associative learning at the level of individual circuits and their component cells. Given that the organization of the mushroom body has much in common with that of the mammalian brain, these studies should provide insights into the fundamental principles that underpin learning and memory in other species, including humans. DOI:http://dx.doi.org/10.7554/eLife.04580.002
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Affiliation(s)
- Yoshinori Aso
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Divya Sitaraman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - Karla R Kaun
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Katrin Vogt
- Max Planck Institute of Neurobiology, Martinsried, Germany
| | - Ghislain Belliart-Guérin
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, Centre National de la Recherche Scientifique, ESPCI, Paris, France
| | - Pierre-Yves Plaçais
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, Centre National de la Recherche Scientifique, ESPCI, Paris, France
| | - Alice A Robie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | | | - William J Rowell
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Rebecca M Johnston
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Teri-T B Ngo
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Nan Chen
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Michael N Nitabach
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Ulrike Heberlein
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | - Thomas Preat
- Genes and Dynamics of Memory Systems, Brain Plasticity Unit, Centre National de la Recherche Scientifique, ESPCI, Paris, France
| | - Kristin M Branson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
| | | | - Gerald M Rubin
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
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15
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Abstract
Infection results in the rapid activation of immunity genes in the Drosophila fat body. Two classes of transcription factors have been implicated in this process: the REL-containing proteins, Dorsal, Dif, and Relish, and the GATA factor Serpent. Here we present evidence that REL-GATA synergy plays a pervasive role in the immune response. SELEX assays identified consensus binding sites that permitted the characterization of several immunity regulatory DNAs. The distribution of REL and GATA sites within these DNAs suggests that most or all fat-specific immunity genes contain a common organization of regulatory elements: closely linked REL and GATA binding sites positioned in the same orientation and located near the transcription start site. Aspects of this "regulatory code" are essential for the immune response. These results suggest that immunity regulatory DNAs contain constrained organizational features, which may be a general property of eukaryotic enhancers.
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Affiliation(s)
- Kate Senger
- Department of Molecular and Cellular Biology, Division of Genetics and Development, University of California, Berkeley, Berkeley, CA 94720, USA
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