Selection of a Novel Aptamer Against Vitronectin Using Capillary Electrophoresis and Next Generation Sequencing

AbstractcDNA display is an in vitro display technology based on a covalent linkage between a protein and its corresponding mRNA/cDNA, where a stable complex is formed suitable for a wide range of selection conditions. A great advantage of cDNA display is the ability to handle enormous library size (1012) in a microtube scale, in a matter of days. To harness its benefits, we aimed at developing a platform which combines the advantages of cDNA display with high-throughput and accuracy of next-generation sequencing (NGS) for the selection of preferred substrate peptides of transglutaminase 2 (TG2), a protein cross-linking enzyme. After the optimization of the platform by the repeated screening of binary model libraries consisting of the substrate and non-substrate peptides at different ratios, screening and selection of combinatorial peptide library randomized at positions -1, +1, +2, and +3 from the glutamine residue was carried out. Enriched cDNA complexes were analyzed by NGS and bioinformatics, revealing the comprehensive amino acid preference of the TG2 at targeted positions of the peptide backbone. This is the first report on the cDNA display/NGS screening system to yield comprehensive data on TG substrate preference. Although some issues remain to be solved, this platform can be applied to the selection of other TGs and easily adjusted for the selection of other peptide substrates and even larger biomolecules.

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Identification of the rs9277534 HLA-DP expression marker by next generation sequencing for the selection of unrelated donors for hematopoietic cell transplantation

Human Immunology ◽

10.1016/j.humimm.2019.05.010 ◽

2019 ◽

Vol 80 (10) ◽

pp. 828-833 ◽

Cited By ~ 3

Author(s):

Gansuvd Balgansuren ◽

Lois Regen ◽

Maggie Sprague ◽

Nakita Shelton ◽

Effie Petersdorf ◽

...

Keyword(s):

Next Generation Sequencing ◽

Cell Transplantation ◽

Hematopoietic Cell Transplantation ◽

Hematopoietic Cell ◽

Next Generation ◽

Unrelated Donors ◽

Expression Marker ◽

Generation Sequencing ◽

Selection Of

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Bioinformatics and Computational Tools for Next-Generation Sequencing Analysis in Clinical Genetics

Journal of Clinical Medicine ◽

10.3390/jcm9010132 ◽

2020 ◽

Vol 9 (1) ◽

pp. 132 ◽

Cited By ~ 8

Author(s):

Rute Pereira ◽

Jorge Oliveira ◽

Mário Sousa

Keyword(s):

Next Generation Sequencing ◽

Clinical Genetics ◽

Sequencing Analysis ◽

Next Generation ◽

Process Data ◽

Next Generation Sequencing Analysis ◽

Generate Process ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing ◽

Selection Of

Clinical genetics has an important role in the healthcare system to provide a definitive diagnosis for many rare syndromes. It also can have an influence over genetics prevention, disease prognosis and assisting the selection of the best options of care/treatment for patients. Next-generation sequencing (NGS) has transformed clinical genetics making possible to analyze hundreds of genes at an unprecedented speed and at a lower price when comparing to conventional Sanger sequencing. Despite the growing literature concerning NGS in a clinical setting, this review aims to fill the gap that exists among (bio)informaticians, molecular geneticists and clinicians, by presenting a general overview of the NGS technology and workflow. First, we will review the current NGS platforms, focusing on the two main platforms Illumina and Ion Torrent, and discussing the major strong points and weaknesses intrinsic to each platform. Next, the NGS analytical bioinformatic pipelines are dissected, giving some emphasis to the algorithms commonly used to generate process data and to analyze sequence variants. Finally, the main challenges around NGS bioinformatics are placed in perspective for future developments. Even with the huge achievements made in NGS technology and bioinformatics, further improvements in bioinformatic algorithms are still required to deal with complex and genetically heterogeneous disorders.

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Subset selection of high-depth next generation sequencing reads for de novo genome assembly using MapReduce framework

BMC Genomics ◽

10.1186/1471-2164-16-s12-s9 ◽

2015 ◽

Vol 16 (Suppl 12) ◽

pp. S9 ◽

Cited By ~ 4

Author(s):

Chih-Hao Fang ◽

Yu-Jung Chang ◽

Wei-Chun Chung ◽

Ping-Heng Hsieh ◽

Chung-Yen Lin ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genome Assembly ◽

De Novo ◽

Subset Selection ◽

Next Generation ◽

Mapreduce Framework ◽

De Novo Genome Assembly ◽

Generation Sequencing ◽

High Depth ◽

Selection Of

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Analysis of Copy Number Variations in Solid Tumors Using a Next Generation Sequencing Custom Panel

Journal of Molecular Pathology ◽

10.3390/jmp2020013 ◽

2021 ◽

Vol 2 (2) ◽

pp. 123-134

Author(s):

Marta Vives-Usano ◽

Beatriz García Pelaez ◽

Ruth Román Lladó ◽

Mónica Garzón Ibañez ◽

Erika Aldeguer ◽

...

Keyword(s):

Next Generation Sequencing ◽

Copy Number ◽

Copy Number Variations ◽

Next Generation ◽

Ffpe Samples ◽

Custom Panel ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing ◽

Approach Time ◽

Selection Of

Somatic copy number variations (CNV; i.e., amplifications and deletions) have been implicated in the origin and development of multiple cancers and some of these aberrations are designated targets for therapies. Although FISH is still considered the gold standard for CNV detection, the increasing number of potentially druggable amplifications to be assessed makes a gene-by-gene approach time- and tissue-consuming. Here we investigated the potential of next generation sequencing (NGS) custom panels to simultaneously determine CNVs across FFPE solid tumor samples. DNA was purified from cell lines and FFPE samples and analyzed by NGS sequencing using a 20-gene custom panel in the GeneReader Platform®. CNVs were identified using an in-house algorithm based on the UMI read coverage. Retrospective validation of in-house algorithm to identify CNVs showed 97.1% concordance rate with the NGS custom panel. The prospective analysis was performed in a cohort of 243 FFPE samples from patients arriving at our hospital, which included 74 NSCLC tumors, 148 CRC tumors, and 21 other tumors. Of them, 33% presented CNVs by NGS and in 14 cases (5.9%) the CNV was the only alteration detected. We have identified CNV alterations in about one-third of our cohort, including FGFR1, CDK6, CDK4, EGFR, MET, ERBB2, BRAF, or KRAS. Our work highlights the need to include CNV testing as a part of routine NGS analysis in order to uncover clinically relevant gene amplifications that can guide the selection of therapies.

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