Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints
July 2024
Authors:
Bo Zhou, Carolin Purmann, Hanmin Guo, GiWon Shin, Yiling Huang, Reenal Pattni, Qingxi Meng, Stephanie U. Greer, Tanmoy Roychowdhuryg, Raegan N. Wood, Marcus Ho, Heinrich zu Dohna, Alexej Abyzov, Joachim F. Hallmayer, Wing H. Wong, Hanlee P. Ji, and Alexander E. Urban
Abstract:
“We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS.”
Sage Science Products:
SageHLS with the HLS-CATCH process for purifying HMW genomic targets.
Author Affiliations:
Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA Stanford Maternal and Child Health Research Institute, Stanford University School of Medicine, Stanford, CA
Department of Genetics, Stanford University School of Medicine, Stanford, CA
Department of Statistics, Stanford University, Stanford, CA
Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA
Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
Department of Biology, American University of Beirut, Lebanon
Program on Genetics of Brain Function, Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA
CTLR-Seq Protocol
July 2024
Authors:
Bo Zhou, GiWon Shin,Yiling Huang, Raegan N. Wood, Hanlee P. Ji, Alexander E. Urban
Abstract:
“We developed a generally applicable method CRISPR/Cas9-targeted long read sequencing (CTLR-Seq) to resolve, haplotype-specifically, and at base-pair resolution, large, complex, and highly repetitive genomic regions that had been previously impenetrable to next-generation sequencing analysis, i.e. large segmental duplication (SegDup) regions and their associated genome rearrangements that often stretch hundreds of kilobases. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to haplotype-specifically isolate intact large (100-2000 kb) regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) with up to 250x on-target coverage using nanopore sequencing, allowing for their complete sequence assembly.”
Sage Science Products:
SageHLS with the HLS-CATCH process for purifying HMW genomic targets.
Author Affiliations:
Department of Psychiatry and Behavioral Sciences and Department of Genetics, Stanford University School of Medicine, Stanford, CA
Stanford Child Health Research Institute, Stanford University School of Medicine, Stanford, CA
Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
Protocols.io
DOI: 10.17504/protocols.io.q26g71d7kgwz/v1
Processing frozen archival human DNA samples for large-scale SQK-LSK114 Oxford Nanopore long-read DNA sequencing SOP v1
June 2024
Authors:
Alicia Wenghöfer, Kimberly Paquette, Laksh Malik, Breeana Baker, Cedric Kouam, Kimberley J Billingsley
Abstract:
“As part of the GP2 monogenic network we will generate long-read sequencing data to better understand the genetic architecture of Parkinson’s disease. To generate this large-scale Nanopore data we have developed a protocol for processing and long-read sequencing frozen human DNA samples, ideally targeting an N50 of ~30kb and ~30X coverage. However, with archival human DNA samples, we usually see a drop in DNA quality in terms of DNA length. Therefore, this protocol is focused on attempting to achieve the highest N50 and coverage possible from the input available.“
Sage Science Products:
BluePippin with High-Pass Plus gel cassettes, >10kb High-Pass protocol.
Author Affiliations:
Center for Alzheimer’s and Related Dementias, National Institute on Aging, Bethesda, Maryland
Institute of Neurogenetics, University Hospital Schleswig-Holstein, Luebeck, Germany
Laboratory of Neurogenetics, National Institute on Aging, Bethesda, Maryland
Protocols.io
DOI: 10.17504/protocols.io.5jyl82morl2w/v1
Identifying the best PCR enzyme for library amplification in NGS
April 2024
Authors:
Michael A. Quail, Craig Corton, James Uphill, Jacqueline Keane and Yong Gu
Abstract:
“PCR amplification is a necessary step in many next-generation sequencing (NGS) library preparation methods. Whilst many PCR enzymes are developed to amplify single targets efficiently, accurately and with specificity, few are developed to meet the challenges imposed by NGS PCR, namely unbiased amplification of a wide range of different sizes and GC content. As a result PCR amplification during NGS library prep often results in bias toward GC neutral and smaller fragments. As NGS has matured, optimized NGS library prep kits and polymerase formulations have emerged and in this study we have tested a wide selection of available enzymes for both short-read Illumina library preparation and long fragment amplification ahead of long-read sequencing.
We tested over 20 different hi-fidelity PCR enzymes/NGS amplification mixes on a range of Illumina library templates of varying GC content and composition, and find that both yield and genome coverage uniformity characteristics of the commercially available enzymes varied dramatically. Three enzymes Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) ‘Equinox’ and Takara Ex Premier were found to give a consistent performance, over all genomes, that mirrored closely that observed for PCR-free datasets. We also test a range of enzymes for long-read sequencing by amplifying size fractionated S. cerevisiae DNA of average size 21.6 and 13.4 kb, respectively.
The enzymes of choice for short-read (Illumina) library fragment amplification are Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) ‘Equinox’ and Takara Ex Premier, with RepliQa also being the best performing enzyme from the enzymes tested for long fragment amplification prior to long-read sequencing. “
Sage Science Products:
BluePippin and SageELF were used to fractionate DNA for testing long-range PCR enzymes.
Methods Excerpt:
“Sheared S. cerevisiae DNA was size fractionated using Sage Sciences ELF or Bluepippin instruments yielding modal fragment sizes of 21.6 and 13.3 kb, respectively. After adapter ligation 1 ng of each of these were used as a template for long range PCR with a range of enzymes using manufacturers recommended cycling conditions…”
Author Affiliations:
Wellcome Sanger Institute, Hinxton, Cambs.,UK
Department of Medicine, University of Cambridge, Cambridge, Cambs., UK
Microbial Genomics
Whole genome sequencing identifies associations for nonsyndromic sagittal craniosynostosis with the intergenic region of BMP2 and noncoding RNA gene LINC01428
April 2024
Authors:
Anthony M. Musolf, Cristina M. Justice, Zeynep Erdogan-Yildirim, Seppe Goovaerts, Araceli Cuellar, John R. Shaffer, Mary L. Marazita, Peter Claes, Seth M. Weinberg, Jae Li, Craig Senders, Marike Zwienenberg, Emil Simeonov, Radka Kaneva, Tony Roscioli, Lorena Di Pietro, Marta Barba, Wanda Lattanzi, Michael L. Cunningham, Paul A. Romitti & Simeon A. Boyadjiev
Abstract:
“Craniosynostosis (CS) is a major birth defect resulting from premature fusion of cranial sutures. Nonsyndromic CS occurs more frequently than syndromic CS, with sagittal nonsyndromic craniosynostosis (sNCS) presenting as the most common CS phenotype. Previous genome-wide association and targeted sequencing analyses of sNCS have identified multiple associated loci, with the strongest association on chromosome 20. Herein, we report the first whole-genome sequencing study of sNCS using 63 proband-parent trios. Sequencing data for these trios were analyzed using the transmission disequilibrium test (TDT) and rare variant TDT (rvTDT) to identify high-risk rare gene variants. Sequencing data were also examined for copy number variants (CNVs) and de novo variants. TDT analysis identified a highly significant locus at 20p12.3, localized to the intergenic region between BMP2 and the noncoding RNA gene LINC01428. Three variants (rs6054763, rs6054764, rs932517) were identified as potential causal variants due to their probability of being transcription factor binding sites, deleterious combined annotation dependent depletion scores, and high minor allele enrichment in probands. Morphometric analysis of cranial vault shape in an unaffected cohort validated the effect of these three single nucleotide variants (SNVs) on dolichocephaly. No genome-wide significant rare variants, de novo loci, or CNVs were identified. Future efforts to identify risk variants for sNCS should include sequencing of larger and more diverse population samples and increased omics analyses, such as RNA-seq and ATAC-seq. “
Sage Science Products:
PippinHT was used to size select whole genome libraries for Oxford Nanopore Promethion sequencing.
Methods Excerpt:
“…3–5 µg of genomic DNA was sheared using a Megaruptor 3 (Diagenode) and purified using Ampure XP beads. Sheared DNA was size selected using the PippinHT instrument (Sage Science) with a target range of 16–20 kb fragments. Next, 1 µg of fragmented, purified, and size-selected DNA in a volume of 47 µl was used in the SQK-LSK109 library preparation protocol per manufacturer’s instructions (Oxford Nanopore Technologies). DNA was end-repaired using the NEBNext FFPE DNA Repair Mix and NEBNext Ultra II End Repair/dA-tailing modules, followed by purification with AMPure XP beads (1:1 vol ratio) and elution to a final volume of 60 µl. Adapters were ligated, and the final library resuspended in Long Fragment Buffer (Oxford Nanopore Technologies). The resulting final library yield was 1.2–2.2 µg per specimen. Libraries were loaded onto PromethION Flowcells (R9.4.1) with 20 femtomolar (fM) loading. After 24 h, all specimens were nuclease washed and reloaded with 20 fM of library. Total sequencing run time was 72 h.”
Author Affiliations:
Statistical Genetics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Baltimore, MD
Neurobehavioral Clinical Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health (NIH), Bethesda, MD
Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA
Department of Human Genetics, KU Leuven, Leuven, Belgium
Department of Electrical Engineering, ESAT-PSI, KU Leuven, Leuven, Belgium
Medical Imaging Research Center, University Hospitals Leuven, Leuven, Belgium
Department of Pediatrics, University of California Davis, Sacramento, CA
Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA
Bioinformatics Core, Genome Center, University of California Davis, Davis, CA
Department of Otolaryngology, Head and Neck Surgery, University of California Davis, Sacramento, CA
Department of Neurosurgery, University of California Davis, Sacramento, CA
Pediatric Clinic, Alexandrovska University Hospital, Medical University of Sofia, 1431, Sofia, Bulgaria
Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical Faculty, Medical University of Sofia, 1431, Sofia, Bulgaria
Neuroscience Research Australia, University of New South Wales, Sydney, Australia
Department of Life Sciences and Public Health, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
Fondazione Policlinico Universitario A. Gemelli, IRCCS, 00168, Rome, Italy
Seattle Children’s Craniofacial Center, Center of Developmental Biology and Regenerative Medicine and Division of Craniofacial Medicine, Department of Pediatrics, University of Washington, Seattle, WA
Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, IA
Nature Scientific Reports
DOI:10.1038/s41598-024-58343-w