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Glunčić M, Vlahović I, Rosandić M, Paar V. Novel Cascade Alpha Satellite HORs in Orangutan Chromosome 13 Assembly: Discovery of the 59mer HOR-The largest Unit in Primates-And the Missing Triplet 45/27/18 HOR in Human T2T-CHM13v2.0 Assembly. Int J Mol Sci 2024; 25:7596. [PMID: 39062839 PMCID: PMC11276891 DOI: 10.3390/ijms25147596] [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: 06/20/2024] [Revised: 07/05/2024] [Accepted: 07/09/2024] [Indexed: 07/28/2024] Open
Abstract
From the recent genome assembly NHGRI_mPonAbe1-v2.0_NCBI (GCF_028885655.2) of orangutan chromosome 13, we computed the precise alpha satellite higher-order repeat (HOR) structure using the novel high-precision GRM2023 algorithm with Global Repeat Map (GRM) and Monomer Distance (MD) diagrams. This study rigorously identified alpha satellite HORs in the centromere of orangutan chromosome 13, discovering a novel 59mer HOR-the longest HOR unit identified in any primate to date. Additionally, it revealed the first intertwined sequence of three HORs, 18mer/27mer/45mer HORs, with a common aligned "backbone" across all HOR copies. The major 7mer HOR exhibits a Willard's-type canonical copy, although some segments of the array display significant irregularities. In contrast, the 14mer HOR forms a regular Willard's-type HOR array. Surprisingly, the GRM2023 high-precision analysis of chromosome 13 of human genome assembly T2T-CHM13v2.0 reveals the presence of only a 7mer HOR, despite both the orangutan and human genome assemblies being derived from whole genome shotgun sequences.
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Affiliation(s)
- Matko Glunčić
- Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia;
| | - Ines Vlahović
- Department of Interdisciplinary Sciences, Algebra University College, 10000 Zagreb, Croatia;
| | - Marija Rosandić
- University Hospital Centre Zagreb (Ret.), 10000 Zagreb, Croatia;
- Croatian Academy of Sciences and Arts, 10000 Zagreb, Croatia
| | - Vladimir Paar
- Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia;
- Croatian Academy of Sciences and Arts, 10000 Zagreb, Croatia
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Glunčić M, Vlahović I, Rosandić M, Paar V. Precise identification of cascading alpha satellite higher order repeats in T2T-CHM13 assembly of human chromosome 3. Croat Med J 2024; 65:209-219. [PMID: 38868967 PMCID: PMC11157248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 05/28/2024] [Indexed: 06/14/2024] Open
Abstract
AIM To precisely identify and analyze alpha-satellite higher-order repeats (HORs) in T2T-CHM13 assembly of human chromosome 3. METHODS From the recently sequenced complete T2T-CHM13 assembly of human chromosome 3, the precise alpha satellite HOR structure was computed by using the novel high-precision GRM2023 algorithm with global repeat map (GRM) and monomer distance (MD) diagrams. RESULTS The major alpha satellite HOR array in chromosome 3 revealed a novel cascading HOR, housing 17mer HOR copies with subfragments of periods 15 and 2. Within each row in the cascading HOR, the monomers were of different types, but different rows within the same cascading 17mer HOR contained more than one monomer of the same type. Each canonical 17mer HOR copy comprised 17 monomers belonging to 16 different monomer types. Another pronounced 10mer HOR array was of the regular Willard's type. CONCLUSION Our findings emphasize the complexity within the chromosome 3 centromere as well as deviations from expected highly regular patterns.
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Affiliation(s)
- Matko Glunčić
- Matko Glunčić, Department of Physics, Faculty of Science, University of Zagreb, Bijenička cesta 32, 10000 Zagreb, Croatia,
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Glunčić M, Vlahović I, Rosandić M, Paar V. Novel Concept of Alpha Satellite Cascading Higher-Order Repeats (HORs) and Precise Identification of 15mer and 20mer Cascading HORs in Complete T2T-CHM13 Assembly of Human Chromosome 15. Int J Mol Sci 2024; 25:4395. [PMID: 38673983 PMCID: PMC11050224 DOI: 10.3390/ijms25084395] [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: 03/06/2024] [Revised: 04/08/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024] Open
Abstract
Unraveling the intricate centromere structure of human chromosomes holds profound implications, illuminating fundamental genetic mechanisms and potentially advancing our comprehension of genetic disorders and therapeutic interventions. This study rigorously identified and structurally analyzed alpha satellite higher-order repeats (HORs) within the centromere of human chromosome 15 in the complete T2T-CHM13 assembly using the high-precision GRM2023 algorithm. The most extensive alpha satellite HOR array in chromosome 15 reveals a novel cascading HOR, housing 429 15mer HOR copies, containing 4-, 7- and 11-monomer subfragments. Within each row of cascading HORs, all alpha satellite monomers are of distinct types, as in regular Willard's HORs. However, different HOR copies within the same cascading 15mer HOR contain more than one monomer of the same type. Each canonical 15mer HOR copy comprises 15 monomers belonging to only 9 different monomer types. Notably, 65% of the 429 15mer cascading HOR copies exhibit canonical structures, while 35% display variant configurations. Identified as the second most extensive alpha satellite HOR, another novel cascading HOR within human chromosome 15 encompasses 164 20mer HOR copies, each featuring two subfragments. Moreover, a distinct pattern emerges as interspersed 25mer/26mer structures differing from regular Willard's HORs and giving rise to a 34-monomer subfragment. Only a minor 18mer HOR array of 12 HOR copies is of the regular Willard's type. These revelations highlight the complexity within the chromosome 15 centromeric region, accentuating deviations from anticipated highly regular patterns and hinting at profound information encoding and functional potential within the human centromere.
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Affiliation(s)
- Matko Glunčić
- Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia;
| | - Ines Vlahović
- Algebra LAB, Algebra University College, 10000 Zagreb, Croatia;
| | - Marija Rosandić
- Department of Internal Medicine, University Hospital Centre Zagreb, 10000 Zagreb, Croatia;
- Croatian Academy of Sciences and Arts, 10000 Zagreb, Croatia
| | - Vladimir Paar
- Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia;
- Croatian Academy of Sciences and Arts, 10000 Zagreb, Croatia
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Glunčić M, Vlahović I, Rosandić M, Paar V. Tandem NBPF 3mer HORs (Olduvai triplets) in Neanderthal and two novel HOR tandem arrays in human chromosome 1 T2T-CHM13 assembly. Sci Rep 2023; 13:14420. [PMID: 37660151 PMCID: PMC10475015 DOI: 10.1038/s41598-023-41517-3] [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: 05/24/2023] [Accepted: 08/28/2023] [Indexed: 09/04/2023] Open
Abstract
It is known that the ~ 1.6 kb Neuroblastoma BreakPoint Family (NBPF) repeats are human specific and contributing to cognitive capabilities, with increasing frequency in higher order repeat 3mer HORs (Olduvai triplets). From chimpanzee to modern human there is a discontinuous jump from 0 to ~ 50 tandemly organized 3mer HORs. Here we investigate the structure of NBPF 3mer HORs in the Neanderthal genome assembly of Pääbo et al., comparing it to the results obtained for human hg38.p14 chromosome 1. Our findings reveal corresponding NBPF 3mer HOR arrays in Neanderthals with slightly different monomer structures and numbers of HOR copies compared to humans. Additionally, we compute the NBPF 3mer HOR pattern for the complete telomere-to-telomere human genome assembly (T2T-CHM13) by Miga et al., identifying two novel tandem arrays of NBPF 3mer HOR repeats with 5 and 9 NBPF 3mer HOR copies. We hypothesize that these arrays correspond to novel NBPF genes (here referred to as NBPFA1 and NBPFA2). Further improving the quality of the Neanderthal genome using T2T-CHM13 as a reference would be of great interest in determining the presence of such distant novel NBPF genes in the Neanderthal genome and enhancing our understanding of human evolution.
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Affiliation(s)
- Matko Glunčić
- Faculty of Science, University of Zagreb, 10000, Zagreb, Croatia.
| | | | - Marija Rosandić
- University Hospital Centre Zagreb (Ret.), 10000, Zagreb, Croatia
- Croatian Academy of Sciences and Arts, 10000, Zagreb, Croatia
| | - Vladimir Paar
- Faculty of Science, University of Zagreb, 10000, Zagreb, Croatia
- Croatian Academy of Sciences and Arts, 10000, Zagreb, Croatia
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Bosco N, Goldberg A, Zhao X, Mays JC, Cheng P, Johnson AF, Bianchi JJ, Toscani C, Di Tommaso E, Katsnelson L, Annuar D, Mei S, Faitelson RE, Pesselev IY, Mohamed KS, Mermerian A, Camacho-Hernandez EM, Gionco CA, Manikas J, Tseng YS, Sun Z, Fani S, Keegan S, Lippman SM, Fenyö D, Giunta S, Santaguida S, Davoli T. KaryoCreate: A CRISPR-based technology to study chromosome-specific aneuploidy by targeting human centromeres. Cell 2023; 186:1985-2001.e19. [PMID: 37075754 PMCID: PMC10676289 DOI: 10.1016/j.cell.2023.03.029] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 11/17/2022] [Accepted: 03/23/2023] [Indexed: 04/21/2023]
Abstract
Aneuploidy, the presence of chromosome gains or losses, is a hallmark of cancer. Here, we describe KaryoCreate (karyotype CRISPR-engineered aneuploidy technology), a system that enables the generation of chromosome-specific aneuploidies by co-expression of an sgRNA targeting chromosome-specific CENPA-binding ɑ-satellite repeats together with dCas9 fused to mutant KNL1. We design unique and highly specific sgRNAs for 19 of the 24 chromosomes. Expression of these constructs leads to missegregation and induction of gains or losses of the targeted chromosome in cellular progeny, with an average efficiency of 8% for gains and 12% for losses (up to 20%) validated across 10 chromosomes. Using KaryoCreate in colon epithelial cells, we show that chromosome 18q loss, frequent in gastrointestinal cancers, promotes resistance to TGF-β, likely due to synergistic hemizygous deletion of multiple genes. Altogether, we describe an innovative technology to create and study chromosome missegregation and aneuploidy in the context of cancer and beyond.
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Affiliation(s)
- Nazario Bosco
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Aleah Goldberg
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Xin Zhao
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Joseph C Mays
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Pan Cheng
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Adam F Johnson
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Joy J Bianchi
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Cecilia Toscani
- Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy
| | - Elena Di Tommaso
- Department of Biology and Biotechnology Charles Darwin, University of Rome "La Sapienza", 00185 Rome, Italy
| | - Lizabeth Katsnelson
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Dania Annuar
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Sally Mei
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Roni E Faitelson
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Ilan Y Pesselev
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Kareem S Mohamed
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Angela Mermerian
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Elaine M Camacho-Hernandez
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Courtney A Gionco
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Julie Manikas
- Department of Cell Biology, NYU Langone Health, New York, NY, USA
| | - Yi-Shuan Tseng
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Zhengxi Sun
- Department of Pathology and Laura & Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY, USA
| | - Somayeh Fani
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Sarah Keegan
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Scott M Lippman
- Moores Cancer Center, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92093, USA
| | - David Fenyö
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Simona Giunta
- Department of Biology and Biotechnology Charles Darwin, University of Rome "La Sapienza", 00185 Rome, Italy
| | - Stefano Santaguida
- Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy; Department of Oncology and Hemato-Oncology, University of Milan, 20141 Milan, Italy
| | - Teresa Davoli
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
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Gao S, Yang X, Guo H, Zhao X, Wang B, Ye K. HiCAT: a tool for automatic annotation of centromere structure. Genome Biol 2023; 24:58. [PMID: 36978122 PMCID: PMC10053651 DOI: 10.1186/s13059-023-02900-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 03/17/2023] [Indexed: 03/30/2023] Open
Abstract
Significant improvements in long-read sequencing technologies have unlocked complex genomic areas, such as centromeres, in the genome and introduced the centromere annotation problem. Currently, centromeres are annotated in a semi-manual way. Here, we propose HiCAT, a generalizable automatic centromere annotation tool, based on hierarchical tandem repeat mining to facilitate decoding of centromere architecture. We apply HiCAT to simulated datasets, human CHM13-T2T and gapless Arabidopsis thaliana genomes. Our results are generally consistent with previous inferences but also greatly improve annotation continuity and reveal additional fine structures, demonstrating HiCAT's performance and general applicability.
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Affiliation(s)
- Shenghan Gao
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaofei Yang
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
| | - Hongtao Guo
- School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xixi Zhao
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Bo Wang
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Kai Ye
- School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
- Faculty of Science, Leiden University, Leiden, The Netherlands.
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7
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Logsdon GA, Eichler EE. The Dynamic Structure and Rapid Evolution of Human Centromeric Satellite DNA. Genes (Basel) 2022; 14:92. [PMID: 36672831 PMCID: PMC9859433 DOI: 10.3390/genes14010092] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 12/22/2022] [Accepted: 12/24/2022] [Indexed: 12/31/2022] Open
Abstract
The complete sequence of a human genome provided our first comprehensive view of the organization of satellite DNA associated with heterochromatin. We review how our understanding of the genetic architecture and epigenetic properties of human centromeric DNA have advanced as a result. Preliminary studies of human and nonhuman ape centromeres reveal complex, saltatory mutational changes organized around distinct evolutionary layers. Pockets of regional hypomethylation within higher-order α-satellite DNA, termed centromere dip regions, appear to define the site of kinetochore attachment in all human chromosomes, although such epigenetic features can vary even within the same chromosome. Sequence resolution of satellite DNA is providing new insights into centromeric function with potential implications for improving our understanding of human biology and health.
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Affiliation(s)
- Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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8
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Glunčić M, Vlahović I, Rosandić M, Paar V. Tandemly repeated NBPF HOR copies (Olduvai triplets): Possible impact on human brain evolution. Life Sci Alliance 2022; 6:6/1/e202101306. [PMID: 36261226 PMCID: PMC9584774 DOI: 10.26508/lsa.202101306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/24/2022] Open
Abstract
Previously it was found that the neuroblastoma breakpoint family (NBPF) gene repeat units of ∼1.6 kb have an important role in human brain evolution and function. The higher order organization of these repeat units has been discovered by both methods, the higher order repeat (HOR)-searching method and the HLS searching method. Using the HOR searching method with global repeat map algorithm, here we identified the tandemly organized NBPF HORs in the human and nonhuman primate NCBI reference genomes. We identified 50 tandemly organized canonical 3mer NBPF HOR copies (Olduvai triplets), but none in nonhuman primates chimpanzee, gorilla, orangutan, and Rhesus macaque. This discontinuous jump in tandemly organized HOR copy number is in sharp contrast to the known gradual increase in the number of Olduvai domains (NBPF monomers) from nonhuman primates to human, especially from ∼138 in chimpanzee to ∼300 in human genome. Using the same global repeat map algorithm method we have also determined the 3mer tandems of canonical 3mer HOR copies in 20 randomly chosen human genomes (10 male and 10 female). In all cases, we found the same 3mer HOR copy numbers as in the case of the reference human genome, with no mutation. On the other hand, some point mutations with respect to reference genome are found for some NBPF monomers which are not tandemly organized in canonical HORs.
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Affiliation(s)
- Matko Glunčić
- Faculty of Science, University of Zagreb, Zagreb, Croatia
| | | | - Marija Rosandić
- University Hospital Centre Zagreb (ret), Zagreb, Croatia,Croatian Academy of Sciences and Arts, Zagreb, Croatia
| | - Vladimir Paar
- Faculty of Science, University of Zagreb, Zagreb, Croatia,Croatian Academy of Sciences and Arts, Zagreb, Croatia
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9
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Kunyavskaya O, Dvorkina T, Bzikadze AV, Alexandrov I, Pevzner PA. Automated annotation of human centromeres with HORmon. Genome Res 2022; 32:1137-1151. [PMID: 35545449 DOI: 10.1101/gr.276362.121] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 05/06/2022] [Indexed: 11/24/2022]
Abstract
Recent advances in long-read sequencing opened a possibility to address the long-standing questions about the architecture and evolution of human centromeres. They also emphasized the need for centromere annotation (partitioning human centromeres into monomers and higher-order repeats (HORs)). Even though there was a half-century-long series of semi-manual studies of centromere architecture, a rigorous centromere annotation algorithm is still lacking. Moreover, an automated centromere annotation is a prerequisite for studies of genetic diseases associated with centromeres, and evolutionary studies of centromeres across multiple species. Although the monomer decomposition (transforming a centromere into a monocentromere written in the monomer alphabet) and the HOR decomposition (representing a monocentromere in the alphabet of HORs) are currently viewed as two separate problems, we demonstrate that they should be integrated into a single framework in such a way that HOR (monomer) inference affects monomer (HOR) inference. We thus developed the HORmon algorithm that integrates the monomer/HOR inference and automatically generates the human monomers/HORs that are largely consistent with the previous semi-manual inference.
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Affiliation(s)
- Olga Kunyavskaya
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University
| | | | - Ivan Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University
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Altemose N, Glennis A, Bzikadze AV, Sidhwani P, Langley SA, Caldas GV, Hoyt SJ, Uralsky L, Ryabov FD, Shew CJ, Sauria MEG, Borchers M, Gershman A, Mikheenko A, Shepelev VA, Dvorkina T, Kunyavskaya O, Vollger MR, Rhie A, McCartney AM, Asri M, Lorig-Roach R, Shafin K, Aganezov S, Olson D, de Lima LG, Potapova T, Hartley GA, Haukness M, Kerpedjiev P, Gusev F, Tigyi K, Brooks S, Young A, Nurk S, Koren S, Salama SR, Paten B, Rogaev EI, Streets A, Karpen GH, Dernburg AF, Sullivan BA, Straight AF, Wheeler TJ, Gerton JL, Eichler EE, Phillippy AM, Timp W, Dennis MY, O'Neill RJ, Zook JM, Schatz MC, Pevzner PA, Diekhans M, Langley CH, Alexandrov IA, Miga KH. Complete genomic and epigenetic maps of human centromeres. Science 2022; 376:eabl4178. [PMID: 35357911 PMCID: PMC9233505 DOI: 10.1126/science.abl4178] [Citation(s) in RCA: 287] [Impact Index Per Article: 95.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Existing human genome assemblies have almost entirely excluded repetitive sequences within and near centromeres, limiting our understanding of their organization, evolution, and functions, which include facilitating proper chromosome segregation. Now, a complete, telomere-to-telomere human genome assembly (T2T-CHM13) has enabled us to comprehensively characterize pericentromeric and centromeric repeats, which constitute 6.2% of the genome (189.9 megabases). Detailed maps of these regions revealed multimegabase structural rearrangements, including in active centromeric repeat arrays. Analysis of centromere-associated sequences uncovered a strong relationship between the position of the centromere and the evolution of the surrounding DNA through layered repeat expansions. Furthermore, comparisons of chromosome X centromeres across a diverse panel of individuals illuminated high degrees of structural, epigenetic, and sequence variation in these complex and rapidly evolving regions.
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Affiliation(s)
- Nicolas Altemose
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - A. Glennis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA
| | - Pragya Sidhwani
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Sasha A. Langley
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Lev Uralsky
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
| | | | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | | | | | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | | | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Olga Kunyavskaya
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Ryan Lorig-Roach
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Daniel Olson
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | | | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | | | - Fedor Gusev
- Vavilov Institute of General Genetics, Moscow, Russia
| | - Kristof Tigyi
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Shelise Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alice Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sofie R. Salama
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Gary H. Karpen
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- BioEngineering and BioMedical Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Abby F. Dernburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Travis J. Wheeler
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research, Kansas City, MO, USA
- University of Kansas Medical School, Department of Biochemistry and Molecular Biology and Cancer Center, University of Kansas, Kansas City, KS, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | - Rachel J. O'Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California at San Diego, San Diego, CA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Charles H. Langley
- Department of Evolution and Ecology, University of California Davis, Davis, CA, USA
| | - Ivan A. Alexandrov
- Vavilov Institute of General Genetics, Moscow, Russia
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
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11
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Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PG, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome. Science 2022; 376:44-53. [PMID: 35357919 PMCID: PMC9186530 DOI: 10.1126/science.abj6987] [Citation(s) in RCA: 1530] [Impact Index Per Article: 510.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.
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Affiliation(s)
- Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego; La Jolla, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
| | - Lev Uralsky
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | | | | | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | | | | | | | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Richard Durbin
- Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics, University of Cambridge; Cambridge, UK
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | | | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Robert S. Fulton
- Department of Genetics, Washington University School of Medicine; St. Louis, MO, USA
| | | | - Erik Garrison
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- University of Tennessee Health Science Center; Memphis, TN, USA
| | - Patrick G.S. Grady
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | | | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine; New Haven, CT, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
- Department of Computational and Data Sciences, Indian Institute of Science; Bangalore KA, India
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | | | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University in St. Louis; St. Louis, MO, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | - Valerie V. Maduro
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics; Düsseldorf, Germany
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital; Seattle, WA, USA
| | - James C. Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Eugene W. Myers
- Max-Planck Institute of Molecular Cell Biology and Genetics; Dresden, Germany
| | - Nathan D. Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research; Kansas City, MO, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School; Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University; Moscow, Russia
| | | | - Steven L. Salzberg
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine; Houston TX, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Ying Sims
- Wellcome Sanger Institute; Cambridge, UK
| | | | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan Sović
- Pacific Biosciences; Menlo Park, CA, USA
- Digital BioLogic d.o.o.; Ivanić-Grad, Croatia
| | | | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine; Durham, NC, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | | | - Justin Wagner
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Brian P. Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Alice C. Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Urvashi Surti
- Department of Pathology, University of Pittsburgh; Pittsburgh, PA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan A. Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences; Moscow, Russia
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research; Kansas City, MO, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical School; Kansas City, MO, USA
| | - Rachel J. O’Neill
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
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12
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Abstract
We are entering a new era in genomics where entire centromeric regions are accurately represented in human reference assemblies. Access to these high-resolution maps will enable new surveys of sequence and epigenetic variation in the population and offer new insight into satellite array genomics and centromere function. Here, we focus on the sequence organization and evolution of alpha satellites, which are credited as the genetic and genomic definition of human centromeres due to their interaction with inner kinetochore proteins and their importance in the development of human artificial chromosome assays. We provide an overview of alpha satellite repeat structure and array organization in the context of these high-quality reference data sets; discuss the emergence of variation-based surveys; and provide perspective on the role of this new source of genetic and epigenetic variation in the context of chromosome biology, genome instability, and human disease.
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Affiliation(s)
- Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, California 95064, USA; .,Department of Biomolecular Engineering, University of California, Santa Cruz, California 95064, USA
| | - Ivan A Alexandrov
- Department of Genomics and Human Genetics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119991, Russia; .,Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg 199004, Russia.,Research Center of Biotechnology of the Russian Academy of Sciences, Moscow 119071, Russia
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13
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Dvorkina T, Kunyavskaya O, Bzikadze AV, Alexandrov I, Pevzner PA. CentromereArchitect: inference and analysis of the architecture of centromeres. Bioinformatics 2021; 37:i196-i204. [PMID: 34252949 PMCID: PMC8336445 DOI: 10.1093/bioinformatics/btab265] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Motivation Recent advances in long-read sequencing technologies led to rapid progress in centromere assembly in the last year and, for the first time, opened a possibility to address the long-standing questions about the architecture and evolution of human centromeres. However, since these advances have not been yet accompanied by the development of the centromere-specific bioinformatics algorithms, even the fundamental questions (e.g. centromere annotation by deriving the complete set of human monomers and high-order repeats), let alone more complex questions (e.g. explaining how monomers and high-order repeats evolved) about human centromeres remain open. Moreover, even though there was a four-decade-long series of studies aimed at cataloging all human monomers and high-order repeats, the rigorous algorithmic definitions of these concepts are still lacking. Thus, the development of a centromere annotation tool is a prerequisite for follow-up personalized biomedical studies of centromeres across the human population and evolutionary studies of centromeres across various species. Results We describe the CentromereArchitect, the first tool for the centromere annotation in a newly sequenced genome, apply it to the recently generated complete assembly of a human genome by the Telomere-to-Telomere consortium, generate the complete set of human monomers and high-order repeats for ‘live’ centromeres, and reveal a vast set of hybrid monomers that may represent the focal points of centromere evolution. Availability and implementation CentromereArchitect is publicly available on https://github.com/ablab/stringdecomposer/tree/ismb2021 Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg 199034, Russia
| | - Olga Kunyavskaya
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg 199034, Russia
| | - Andrey V Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, CA 92093, USA
| | - Ivan Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg 199034, Russia
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California, San Diego, CA 92093, USA
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14
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Haschka T, Ponger L, Escudé C, Mozziconacci J. MNHN-Tree-Tools: A toolbox for tree inference using multi-scale clustering of a set of sequences. Bioinformatics 2021; 37:3947-3949. [PMID: 34100911 DOI: 10.1093/bioinformatics/btab430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 05/12/2021] [Accepted: 06/07/2021] [Indexed: 01/23/2023] Open
Abstract
SUMMARY Genomic sequences are widely used to infer the evolutionary history of a given group of individuals. Many methods have been developed for sequence clustering and tree building. In the early days of genome sequencing, these were often limited to hundreds of sequences, but due to the surge of high throughput sequencing, it is now common to have millions of sampled sequences at hand. We introduce MNHN-Tree-Tools, a high performance set of algorithms that builds multi-scale, nested clusters of sequences found in a FASTA file. MNHN-Tree-Tools does not rely on sequence alignment and can thus be used on large datasets to infer a sequence tree. Herein we outline two applications: A human alpha-satellite repeats classification and a tree of life derivation from 16S/18S rDNA sequences. CODE AVAILABILITY Open source with a Zlib License via the Git protocol: https://gitlab.in2p3.fr/mnhn-tools/mnhn-tree-tools. SUPPLEMENTARY INFORMATION An in depth discussion about the algorithm with numerical simulations: https://gitlab.in2p3.fr/mnhn-tools/tree-tools-algorithms-document/-/raw/master/article.pdf. MANUAL A detailed users guide and tutorial: https://gitlab.in2p3.fr/mnhn-tools/mnhn-tree-tools-manual/-/raw/master/manual.pdf. WEBSITE AND FAQ http://treetools.haschka.net.
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Affiliation(s)
- Thomas Haschka
- Muséum National d'Histoire Naturelle, Structure et Instabilité des Génomes, UMR7196, Paris 75231, France
| | - Loic Ponger
- Muséum National d'Histoire Naturelle, Structure et Instabilité des Génomes, UMR7196, Paris 75231, France
| | - Christophe Escudé
- Muséum National d'Histoire Naturelle, Structure et Instabilité des Génomes, UMR7196, Paris 75231, France
| | - Julien Mozziconacci
- Muséum National d'Histoire Naturelle, Structure et Instabilité des Génomes, UMR7196, Paris 75231, France.,Institut Universitaire de France
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15
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Dvorkina T, Bzikadze AV, Pevzner PA. The string decomposition problem and its applications to centromere analysis and assembly. Bioinformatics 2021; 36:i93-i101. [PMID: 32657390 PMCID: PMC7428072 DOI: 10.1093/bioinformatics/btaa454] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Motivation Recent attempts to assemble extra-long tandem repeats (such as centromeres) faced the challenge of translating long error-prone reads from the nucleotide alphabet into the alphabet of repeat units. Human centromeres represent a particularly complex type of high-order repeats (HORs) formed by chromosome-specific monomers. Given a set of all human monomers, translating a read from a centromere into the monomer alphabet is modeled as the String Decomposition Problem. The accurate translation of reads into the monomer alphabet turns the notoriously difficult problem of assembling centromeres from reads (in the nucleotide alphabet) into a more tractable problem of assembling centromeres from translated reads. Results We describe a StringDecomposer (SD) algorithm for solving this problem, benchmark it on the set of long error-prone Oxford Nanopore reads generated by the Telomere-to-Telomere consortium and identify a novel (rare) monomer that extends the set of known X-chromosome specific monomers. Our identification of a novel monomer emphasizes the importance of identification of all (even rare) monomers for future centromere assembly efforts and evolutionary studies. To further analyze novel monomers, we applied SD to the set of recently generated long accurate Pacific Biosciences HiFi reads. This analysis revealed that the set of known human monomers and HORs remains incomplete. SD opens a possibility to generate a complete set of human monomers and HORs for using in the ongoing efforts to generate the complete assembly of the human genome. Availability and implementation StringDecomposer is publicly available on https://github.com/ablab/stringdecomposer. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg 199034, Russia
| | - Andrey V Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego, CA 92093, USA
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California, San Diego, CA 92093, USA
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16
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Bury L, Moodie B, Ly J, McKay LS, Miga KH, Cheeseman IM. Alpha-satellite RNA transcripts are repressed by centromere-nucleolus associations. eLife 2020; 9:59770. [PMID: 33174837 PMCID: PMC7679138 DOI: 10.7554/elife.59770] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 11/09/2020] [Indexed: 01/03/2023] Open
Abstract
Although originally thought to be silent chromosomal regions, centromeres are instead actively transcribed. However, the behavior and contributions of centromere-derived RNAs have remained unclear. Here, we used single-molecule fluorescence in-situ hybridization (smFISH) to detect alpha-satellite RNA transcripts in intact human cells. We find that alpha-satellite RNA-smFISH foci levels vary across cell lines and over the cell cycle, but do not remain associated with centromeres, displaying localization consistent with other long non-coding RNAs. Alpha-satellite expression occurs through RNA polymerase II-dependent transcription, but does not require established centromere or cell division components. Instead, our work implicates centromere–nucleolar interactions as repressing alpha-satellite expression. The fraction of nucleolar-localized centromeres inversely correlates with alpha-satellite transcripts levels across cell lines and transcript levels increase substantially when the nucleolus is disrupted. The control of alpha-satellite transcripts by centromere-nucleolar contacts provides a mechanism to modulate centromere transcription and chromatin dynamics across diverse cell states and conditions.
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Affiliation(s)
- Leah Bury
- Whitehead Institute for Biomedical Research, Cambridge, United States
| | - Brittania Moodie
- Whitehead Institute for Biomedical Research, Cambridge, United States
| | - Jimmy Ly
- Whitehead Institute for Biomedical Research, Cambridge, United States.,Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
| | - Liliana S McKay
- Whitehead Institute for Biomedical Research, Cambridge, United States
| | - Karen Hh Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, United States
| | - Iain M Cheeseman
- Whitehead Institute for Biomedical Research, Cambridge, United States.,Department of Biology, Massachusetts Institute of Technology, Cambridge, United States
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17
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Bzikadze AV, Pevzner PA. Automated assembly of centromeres from ultra-long error-prone reads. Nat Biotechnol 2020; 38:1309-1316. [PMID: 32665660 PMCID: PMC10718184 DOI: 10.1038/s41587-020-0582-4] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Accepted: 05/29/2020] [Indexed: 12/12/2022]
Abstract
Centromeric variation has been linked to cancer and infertility, but centromere sequences contain multiple tandem repeats and can only be assembled manually from long error-prone reads. Here we describe the centroFlye algorithm for centromere assembly using long error-prone reads, and apply it to assemble human centromeres on chromosomes 6 and X. Our analyses reveal putative breakpoints in the manual reconstruction of the human X centromere, demonstrate that human X chromosome is partitioned into repeat subfamilies and provide initial insights into centromere evolution. We anticipate that centroFlye could be applied to automatically close remaining multimegabase gaps in the reference human genome.
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Affiliation(s)
- Andrey V Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA
| | - Pavel A Pevzner
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
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Miga KH. Centromere studies in the era of 'telomere-to-telomere' genomics. Exp Cell Res 2020; 394:112127. [PMID: 32504677 DOI: 10.1016/j.yexcr.2020.112127] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 05/23/2020] [Accepted: 05/30/2020] [Indexed: 12/17/2022]
Abstract
We are entering into an exciting era of genomics where truly complete, high-quality assemblies of human chromosomes are available end-to-end, or from 'telomere-to-telomere' (T2T). This technological advance offers a new opportunity to include endogenous human centromeric regions in high-resolution, sequence-based studies. These emerging reference maps are expected to reveal a new functional landscape in the human genome, where centromere proteins, transcriptional regulation, and spatial organization can be examined with base-level resolution across different stages of development and disease. Such studies will depend on innovative assembly methods of extremely long tandem repeats (ETRs), or satellite DNAs, paired with the development of new, orthogonal validation methods to ensure accuracy and completeness. This review reflects the progress in centromere genomics, credited by recent advancements in long-read sequencing and assembly methods. In doing so, I will discuss the challenges that remain and the promise for a new period of scientific discovery for satellite DNA biology and centromere function.
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Affiliation(s)
- Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, CA, 95064, USA.
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Discovery of 33mer in chromosome 21 - the largest alpha satellite higher order repeat unit among all human somatic chromosomes. Sci Rep 2019; 9:12629. [PMID: 31477765 PMCID: PMC6718397 DOI: 10.1038/s41598-019-49022-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 08/13/2019] [Indexed: 11/10/2022] Open
Abstract
The centromere is important for segregation of chromosomes during cell division in eukaryotes. Its destabilization results in chromosomal missegregation, aneuploidy, hallmarks of cancers and birth defects. In primate genomes centromeres contain tandem repeats of ~171 bp alpha satellite DNA, commonly organized into higher order repeats (HORs). In spite of crucial importance, satellites have been understudied because of gaps in sequencing - genomic “black holes”. Bioinformatical studies of genomic sequences open possibilities to revolutionize understanding of repetitive DNA datasets. Here, using robust (Global Repeat Map) algorithm we identified in hg38 sequence of human chromosome 21 complete ensemble of alpha satellite HORs with six long repeat units (≥20 mers), five of them novel. Novel 33mer HOR has the longest HOR unit identified so far among all somatic chromosomes and novel 23mer reverse HOR is distant far from the centromere. Also, we discovered that for hg38 assembly the 33mer sequences in chromosomes 21, 13, 14, and 22 are 100% identical but nearby gaps are present; that seems to require an additional more precise sequencing. Chromosome 21 is of significant interest for deciphering the molecular base of Down syndrome and of aneuploidies in general. Since the chromosome identifier probes are largely based on the detection of higher order alpha satellite repeats, distinctions between alpha satellite HORs in chromosomes 21 and 13 here identified might lead to a unique chromosome 21 probe in molecular cytogenetics, which would find utility in diagnostics. It is expected that its complete sequence analysis will have profound implications for understanding pathogenesis of diseases and development of new therapeutic approaches.
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