Browsing by Subject "High-throughput nucleotide sequencing"

Now showing 1 - 7 of 7
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    Adipocyte-Specific ATAC-Seq with Adipose Tissues Using Fluorescence-Activated Nucleus Sorting
    (MyJove Corporation, 2023-03-17) Kim, Kyungchan; Taleb, Solaema; So, Jisun; Wann, Jamie; Roh, Hyun Cheol; Biochemistry and Molecular Biology, School of Medicine
    Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) is a robust technique that enables genome-wide chromatin accessibility profiling. This technique has been useful for understanding the regulatory mechanisms of gene expression in a range of biological processes. Although ATAC-seq has been modified for different types of samples, there have not been effective modifications of ATAC-seq methods for adipose tissues. Challenges with adipose tissues include the complex cellular heterogeneity, large lipid content, and high mitochondrial contamination. To overcome these problems, we have developed a protocol that allows adipocyte-specific ATAC-seq by employing fluorescence-activated nucleus sorting with adipose tissues from the transgenic reporter Nuclear tagging and Translating Ribosome Affinity Purification (NuTRAP) mouse. This protocol produces high-quality data with minimal wasted sequencing reads while reducing the amount of nucleus input and reagents. This paper provides detailed step-by-step instructions for the ATAC-seq method validated for the use of adipocyte nuclei isolated from mouse adipose tissues. This protocol will aid in the investigation of chromatin dynamics in adipocytes upon diverse biological stimulations, which will allow for novel biological insights.
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    CYP2C8, CYP2C9, and CYP2C19 Characterization Using Next-Generation Sequencing and Haplotype Analysis: A GeT-RM Collaborative Project
    (Elsevier, 2022) Gaedigk, Andrea; Boone, Erin C.; Scherer, Steven E.; Lee, Seung-Been; Numanagić, Ibrahim; Sahinalp, Cenk; Smith, Joshua D.; McGee, Sean; Radhakrishnan, Aparna; Qin, Xiang; Wang, Wendy Y.; Farrow, Emily G.; Gonzaludo, Nina; Halpern, Aaron L.; Nickerson, Deborah A.; Miller, Neil A.; Pratt, Victoria M.; Kalman, Lisa V.; Medical and Molecular Genetics, School of Medicine
    Pharmacogenetic tests typically target selected sequence variants to identify haplotypes that are often defined by star (∗) allele nomenclature. Due to their design, these targeted genotyping assays are unable to detect novel variants that may change the function of the gene product and thereby affect phenotype prediction and patient care. In the current study, 137 DNA samples that were previously characterized by the Genetic Testing Reference Material (GeT-RM) program using a variety of targeted genotyping methods were recharacterized using targeted and whole genome sequencing analysis. Sequence data were analyzed using three genotype calling tools to identify star allele diplotypes for CYP2C8, CYP2C9, and CYP2C19. The genotype calls from next-generation sequencing (NGS) correlated well to those previously reported, except when novel alleles were present in a sample. Six novel alleles and 38 novel suballeles were identified in the three genes due to identification of variants not covered by targeted genotyping assays. In addition, several ambiguous genotype calls from a previous study were resolved using the NGS and/or long-read NGS data. Diplotype calls were mostly consistent between the calling algorithms, although several discrepancies were noted. This study highlights the utility of NGS for pharmacogenetic testing and demonstrates that there are many novel alleles that are yet to be discovered, even in highly characterized genes such as CYP2C9 and CYP2C19.
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    Development and evaluation of ActSeq: A targeted next-generation sequencing panel for clinical oncology use
    (PLOS, 2022-04-21) Shi, Zonggao; Lopez, Jacqueline; Kalliney, William; Sutton, Bobbie; Simpson, Joyce; Maggert, Kevin; Liu, Sheng; Wan, Jun; Stack, M. Sharon; Medical and Molecular Genetics, School of Medicine
    Purpose: The demand for high-throughput genetic profiling of somatic mutations in cancer tissues is growing. We sought to establish a targeted next generation sequencing (NGS) panel test for clinical oncology practice. Methods: Customized probes were designed to capture exonic regions of 141 genes selected for the panel, which was aimed for the detection of clinically actionable genetic variations in cancer, including KRAS, NRAS, BRAF, ALK, ROS1, KIT and EGFR. The size of entire targeted regions is 0.8 Mb. Library preparation used NEBNext Ultra II FS kit coupled with target enrichment. Paired-end sequencing was run on Illumina NextSeq 500 at a read length of 150 nt. A bioinformatics workflow focusing on single nucleotide variant and short insertions and deletions (SNV/indel) discovery was established using open source, in-house and commercial software tools. Standard reference DNA samples were used in testing the sensitivity and precision and limit of detection in variant calling. Results: The general performance of the panel was observed in pilot runs. Average total reads per sample ranged from 30 million to 48 million, 73% ~82% unique reads. All runs had more than 99% average mapping rate. Mean target coverage ranged from 727x to 879x. Depth of coverage at 50x or more reached 87% of targeted region and 60% of targeted region received 500x or more coverage depth. Using OncoSpan HD827 DNA, which bears 144 variants (SNV/indel) from 80 genes that are within the targeted region on the panel, our somatic variant calling pipeline reached 97% sensitivity and 100% precision respectively, with near 48 million reads. High concordance with orthogonal approaches in variant detection was further verified with 7 cancer cell lines and 45 clinical specimens. Conclusion: We developed a NGS panel with a focus on clinically actionable gene mutations and validated the performance in library construction, sequencing and variant calling. High concordance with reference materials and orthogonal mutation detection was observed.
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    High-Throughput Assays to Assess the Functional Impact of Genetic Variants: A Road Towards Genomic-Driven Medicine
    (Wiley, 2017-03) Ipe, J.; Swart, M.; Burgess, K.S.; Skaar, Todd C.; Medicine, School of Medicine
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    Myeloma Genome Project Panel is a Comprehensive Targeted Genomics Panel for Molecular Profiling of Patients with Multiple Myeloma
    (American Association for Cancer Research, 2022) Sudha, Parvathi; Ahsan, Aarif; Ashby, Cody; Kausar, Tasneem; Khera, Akhil; Kazeroun, Mohammad H.; Hsu, Chih-Chao; Wang, Lin; Fitzsimons, Evelyn; Salminen, Outi; Blaney, Patrick; Czader, Magdalena; Williams, Jonathan; Zaid, Mohammad I. Abu; Ansari-Pour, Naser; Yong, Kwee L.; van Rhee, Frits; Pierceall, William E.; Morgan, Gareth J.; Flynt, Erin; Gooding, Sarah; Abonour, Rafat; Ramasamy, Karthik; Thakurta, Anjan; Walker, Brian A.; Medicine, School of Medicine
    Purpose: We designed a comprehensive multiple myeloma targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. Experimental design: The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNA). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical FISH (translocations), multiplex ligation probe analysis (MLPA; CNAs), whole-genome sequencing (WGS; CNAs, mutations, translocations), or droplet digital PCR (ddPCR) of known standards (mutations). Results: Canonical immunoglobulin heavy chain translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for 1 patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2 = 0.969. Variant allele frequency (VAF) for 74 mutations were compared between sequencing and ddPCR with concordance of R2 = 0.9849. Conclusions: In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost-effective, comprehensive, clinically actionable, and can be routinely deployed to assist risk stratification at diagnosis or posttreatment to guide sequencing of therapies.
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    Simple and efficient profiling of transcription initiation and transcript levels with STRIPE-seq
    (CSHL Press, 2020-06) Policastro, Robert A.; Raborn, R. Taylor; Brendel, Volker P.; Zentner, Gabriel E.; Biology, School of Science
    Accurate mapping of transcription start sites (TSSs) is key for understanding transcriptional regulation. However, current protocols for genome-wide TSS profiling are laborious and/or expensive. We present Survey of TRanscription Initiation at Promoter Elements with high-throughput sequencing (STRIPE-seq), a simple, rapid, and cost-effective protocol for sequencing capped RNA 5' ends from as little as 50 ng total RNA. Including depletion of uncapped RNA and reaction cleanups, a STRIPE-seq library can be constructed in about 5 h. We show application of STRIPE-seq to TSS profiling in yeast and human cells and show that it can also be effectively used for quantification of transcript levels and analysis of differential gene expression. In conjunction with our ready-to-use computational workflows, STRIPE-seq is a straightforward, efficient means by which to probe the landscape of transcriptional initiation.
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    Use of amplicon-based sequencing for testing fetal identity and monogenic traits with Single Circulating Trophoblast (SCT) as one form of cell-based NIPT
    (PLOS, 2021-04-15) Zhuo, Xinming; Wang, Qun; Vossaert, Liesbeth; Salman, Roseen; Kim, Adriel; Van den Veyver, Ignatia; Breman, Amy; Beaudet, Arthur; Medical and Molecular Genetics, School of Medicine
    A major challenge for cell-based non-invasive prenatal testing (NIPT) is to distinguish individual presumptive fetal cells from maternal cells in female pregnancies. We have sought a rapid, robust, versatile, and low-cost next-generation sequencing method to facilitate this process. Toward this goal, single isolated cells underwent whole genome amplification prior to genotyping. Multiple highly polymorphic genomic regions (including HLA-A and HLA-B) with 10-20 very informative single nucleotide polymorphisms (SNPs) within a 200 bp interval were amplified with a modified method based on other publications. To enhance the power of cell identification, approximately 40 Human Identification SNP (Applied Biosystems) test amplicons were also utilized. Using SNP results to compare to sex chromosome data from NGS as a reliable standard, the true positive rate for genotyping was 83.4%, true negative 6.6%, false positive 3.3%, and false negative 6.6%. These results would not be sufficient for clinical diagnosis, but they demonstrate the general validity of the approach and suggest that deeper genotyping of single cells could be completely reliable. A paternal DNA sample is not required using this method. The assay also successfully detected pathogenic variants causing Tay Sachs disease, cystic fibrosis, and hemoglobinopathies in single lymphoblastoid cells, and disease-causing variants in three cell-based NIPT cases. This method could be applicable for any monogenic diagnosis.