Optimization of Parameters in a DNA Sequenator Using Fluorescence Detection View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1988-07

AUTHORS

Hideki Kambara, Tetsuo Nishikawa, Yoshiko Katayama, Tomoaki Yamaguchi

ABSTRACT

We have developed an automated DNA sequenator using a real-time fluorescence detection method, and achieved excellent sensitivity and rapid analysis by optimizing operating conditions. The sequenator uses unicolor labeling and four-track electrophoresis. Fluoresceine isothiocyanate(FITC)-labeled primers are used to produce labeled DNA families. The fluorescent bands are excited by an Ar laser (488 nm, 10 mW) introduced from the side of a thin gel during electrophoresis. Analysis, with an accuracy greater than 99%, consumes 0.01–0.04 picomole sample for each DNA family, which is almost comparable to the amount used in conventional autoradiography. With the optimized electrophoresis conditions reported here, four hundred bases of DNA can be analyzed within two and a half hours using a four percent polyacrylamide gel. More... »

PAGES

816

Journal

TITLE

Nature Biotechnology

ISSUE

7

VOLUME

6

Related Patents

  • Single Molecule Sequencing Of Captured Nucleic Acids
  • Fluorocarbon Emulsion Stabilizing Surfactants
  • Nucleotide Analogs
  • Dna Detector And Dna Detection Method
  • Dna Detector And Dna Detection Method
  • Multiple Capillary Biochemical Analyzer
  • Dna Polymerase Having Modified Nucleotide Binding Site For Dna Sequencing
  • Multiple Capillary Biochemical Analyzer
  • Method For Determining Dna Sequences
  • Systems And Methods For Reducing Detected Intensity Non-Uniformity In A Laser Beam
  • Manipulation Of Fluids And Reactions In Microfluidic Systems
  • Dna Detector And Dna Detection Method
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Manipulation Of Fluids, Fluid Components And Reactions In Microfluidic Systems
  • In Vitro Evolution In Microfluidic Systems
  • Selection By Compartmentalised Screening
  • Digital Analyte Analysis
  • Systems For Handling Microfludic Droplets
  • 4,7-Dichlorofluorescein Dyes As Molecular Probes
  • Neutral Nucleic Acid Ligands
  • Selection By Compartmentalised Screening
  • Methods And Kits For Analyzing Polynucleotide Sequences
  • Short Cycle Methods For Sequencing Polynucleotides
  • Single Molecule Sequencing Of Captured Nucleic Acids
  • Fluorocarbon Emulsion Stabilizing Surfactants
  • Capillary Array Electrophoresis Apparatus
  • Method Of Primary Screening Of Carriers Having Abnormal Genetic Base Sequences.
  • Dna Detector And Dna Detection Method
  • Dna Detector And Dna Detection Method
  • Dna Detector And Dna Detection Method
  • Sequencing Of Surface Immobilized Polymers Utilizing Microflourescence Detection
  • 4, 7-Dichlorofluorescein Dyes As Molecular Probes
  • Digital Analyte Analysis
  • Manipulation Of Fluids And Reactions In Microfluidic Systems
  • Short Cycle Methods For Sequencing Polynucleotides
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Manipulation Of Fluids And Reactions In Microfluidic Systems
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Selection Of Compartmentalized Screening Method
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Sandwich Assays In Droplets
  • 4,7-Dichlorofluorescein Dyes As Molecular Probes
  • Capillary Array Electrophoresis Apparatus
  • Sample Holding Device For Electrophoresis Apparatus And Sample Injection Method
  • Multiple Capillary Biochemical Analyzer
  • Nucleotide Sequence Determination Employing Matched Dideoxynucleotide Terminator Concentrations
  • Apparatus And Methods For Analyzing Samples
  • Methods And Kits For Analyzing Polynucleotide Sequences
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Digital Analyte Analysis
  • Digital Analyte Analysis
  • Microfluidic Devices And Methods Of Use In The Formation And Control Of Nanoreactors
  • Sample Multiplexing
  • Manipulating Droplet Size
  • Short Cycle Methods For Sequencing Polynucleotides
  • Method Of Determining The Nucleotide Sequence Of Oligonucleotides And Dna Molecules
  • Dna Detector And Dna Detection Method
  • Compartmentalised Combinatorial Chemistry By Microfluidic Control
  • 4,7-Dichlorofluorescein Dyes As Molecular Probes
  • Analysis Of Surface Immobilized Polymers Utilizing Microfluorescence Detection
  • Methods And Apparatus For Analyzing Polynucleotide Sequences By Asynchronous Base Extension
  • Methods And Apparatus For Analyzing Polynucleotide Sequences
  • Methods For Nucleic Acid Amplification
  • Compartmentalised Combinatorial Chemistry By Microfluidic Control
  • Manipulation Of Fluids, Fluid Components And Reactions In Microfluidic Systems
  • 4, 7-Dichlorofluorescein Dyes As Molecular Probes
  • Dna Detector And Dna Detection Method
  • Compartmentalized Screening By Microfluidic Control
  • Microfluidic Devices And Methods Of Use In The Formation And Control Of Nanoreactors
  • Short Cycle Methods For Sequencing Polynucleotides
  • Vitro Evolution In Microfluidic Systems
  • In Vitro Evolution In Microfluidic Systems
  • Microfluidic Devices And Methods Of Use In The Formation And Control Of Nanoreactors
  • Method Of Primary Screening Of Carriers Having Abnormal Genetic Base Sequences
  • Manipulation Of Microfluidic Droplets
  • Digital Analyte Analysis
  • Compositions And Methods For Molecular Labeling
  • Dna Detector And Dna Detection Method
  • Method Of Synthesis And Testing Of Combinatorial Libraries Using Microcapsules
  • Methods For Forming Mixed Droplets
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nbt0788-816

    DOI

    http://dx.doi.org/10.1038/nbt0788-816

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1033150622


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "familyName": "Kambara", 
            "givenName": "Hideki", 
            "type": "Person"
          }, 
          {
            "familyName": "Nishikawa", 
            "givenName": "Tetsuo", 
            "type": "Person"
          }, 
          {
            "familyName": "Katayama", 
            "givenName": "Yoshiko", 
            "type": "Person"
          }, 
          {
            "familyName": "Yamaguchi", 
            "givenName": "Tomoaki", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/325771a0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002991698", 
              "https://doi.org/10.1038/325771a0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0076-6879(80)65059-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008420927"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0165-022x(86)90038-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009603369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0165-022x(86)90038-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009603369"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1085-911", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016045655", 
              "https://doi.org/10.1038/nbt1085-911"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.74.12.5463", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025360556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1086-890", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041063512", 
              "https://doi.org/10.1038/nbt1086-890"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/321674a0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041827788", 
              "https://doi.org/10.1038/321674a0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.2443975", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062537979"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "1988-07", 
        "datePublishedReg": "1988-07-01", 
        "description": "We have developed an automated DNA sequenator using a real-time fluorescence detection method, and achieved excellent sensitivity and rapid analysis by optimizing operating conditions. The sequenator uses unicolor labeling and four-track electrophoresis. Fluoresceine isothiocyanate(FITC)-labeled primers are used to produce labeled DNA families. The fluorescent bands are excited by an Ar laser (488 nm, 10 mW) introduced from the side of a thin gel during electrophoresis. Analysis, with an accuracy greater than 99%, consumes 0.01\u20130.04 picomole sample for each DNA family, which is almost comparable to the amount used in conventional autoradiography. With the optimized electrophoresis conditions reported here, four hundred bases of DNA can be analyzed within two and a half hours using a four percent polyacrylamide gel.", 
        "genre": "non_research_article", 
        "id": "sg:pub.10.1038/nbt0788-816", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1115214", 
            "issn": [
              "1087-0156", 
              "1546-1696"
            ], 
            "name": "Nature Biotechnology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "7", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "6"
          }
        ], 
        "name": "Optimization of Parameters in a DNA Sequenator Using Fluorescence Detection", 
        "pagination": "816", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "9decbdeec530ef12d19b4a178b5824f73884ea73cd86dc122ab1fb95ae838e5b"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/nbt0788-816"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1033150622"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/nbt0788-816", 
          "https://app.dimensions.ai/details/publication/pub.1033150622"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T17:21", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8672_00000442.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/nbt0788-816"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nbt0788-816'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nbt0788-816'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nbt0788-816'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nbt0788-816'


     

    This table displays all metadata directly associated to this object as RDF triples.

    99 TRIPLES      21 PREDICATES      35 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/nbt0788-816 schema:about anzsrc-for:06
    2 anzsrc-for:0604
    3 schema:author N84042ea0238b413a97202d5a042e567f
    4 schema:citation sg:pub.10.1038/321674a0
    5 sg:pub.10.1038/325771a0
    6 sg:pub.10.1038/nbt1085-911
    7 sg:pub.10.1038/nbt1086-890
    8 https://doi.org/10.1016/0165-022x(86)90038-2
    9 https://doi.org/10.1016/s0076-6879(80)65059-9
    10 https://doi.org/10.1073/pnas.74.12.5463
    11 https://doi.org/10.1126/science.2443975
    12 schema:datePublished 1988-07
    13 schema:datePublishedReg 1988-07-01
    14 schema:description We have developed an automated DNA sequenator using a real-time fluorescence detection method, and achieved excellent sensitivity and rapid analysis by optimizing operating conditions. The sequenator uses unicolor labeling and four-track electrophoresis. Fluoresceine isothiocyanate(FITC)-labeled primers are used to produce labeled DNA families. The fluorescent bands are excited by an Ar laser (488 nm, 10 mW) introduced from the side of a thin gel during electrophoresis. Analysis, with an accuracy greater than 99%, consumes 0.01–0.04 picomole sample for each DNA family, which is almost comparable to the amount used in conventional autoradiography. With the optimized electrophoresis conditions reported here, four hundred bases of DNA can be analyzed within two and a half hours using a four percent polyacrylamide gel.
    15 schema:genre non_research_article
    16 schema:inLanguage en
    17 schema:isAccessibleForFree false
    18 schema:isPartOf Nc60b91fb4fd84e52b68ea3884d49a198
    19 Ne9fefc8fb08847dc8fb2c2d4008d665b
    20 sg:journal.1115214
    21 schema:name Optimization of Parameters in a DNA Sequenator Using Fluorescence Detection
    22 schema:pagination 816
    23 schema:productId N25d629236d0d4a49a032bf555624028c
    24 N4ec7a0fd5986475e9c8603bd08286e61
    25 Nc5cd9e0526314115a2fcd8d23018b3a3
    26 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033150622
    27 https://doi.org/10.1038/nbt0788-816
    28 schema:sdDatePublished 2019-04-10T17:21
    29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    30 schema:sdPublisher Nf4114ca227ff4b1884e5916d1c050e5a
    31 schema:url https://www.nature.com/articles/nbt0788-816
    32 sgo:license sg:explorer/license/
    33 sgo:sdDataset articles
    34 rdf:type schema:ScholarlyArticle
    35 N1ce0c36d62514b6c88dac2c0ec1ccbc4 rdf:first Nc845730a734c4d6ebf84579ecb341324
    36 rdf:rest Nd83750803a714a8b865e3c0befd77dc0
    37 N25d629236d0d4a49a032bf555624028c schema:name doi
    38 schema:value 10.1038/nbt0788-816
    39 rdf:type schema:PropertyValue
    40 N4225b0873b884b6b9273449f4e3776be schema:familyName Yamaguchi
    41 schema:givenName Tomoaki
    42 rdf:type schema:Person
    43 N4cfa0249183543c2ac456b8dabbd7cc5 schema:familyName Kambara
    44 schema:givenName Hideki
    45 rdf:type schema:Person
    46 N4ec7a0fd5986475e9c8603bd08286e61 schema:name dimensions_id
    47 schema:value pub.1033150622
    48 rdf:type schema:PropertyValue
    49 N84042ea0238b413a97202d5a042e567f rdf:first N4cfa0249183543c2ac456b8dabbd7cc5
    50 rdf:rest N1ce0c36d62514b6c88dac2c0ec1ccbc4
    51 Nade2d4f5ffb14db990446dfe923fe7c7 rdf:first N4225b0873b884b6b9273449f4e3776be
    52 rdf:rest rdf:nil
    53 Nc4bfe693ddde4a0c987378eea0f336bd schema:familyName Katayama
    54 schema:givenName Yoshiko
    55 rdf:type schema:Person
    56 Nc5cd9e0526314115a2fcd8d23018b3a3 schema:name readcube_id
    57 schema:value 9decbdeec530ef12d19b4a178b5824f73884ea73cd86dc122ab1fb95ae838e5b
    58 rdf:type schema:PropertyValue
    59 Nc60b91fb4fd84e52b68ea3884d49a198 schema:issueNumber 7
    60 rdf:type schema:PublicationIssue
    61 Nc845730a734c4d6ebf84579ecb341324 schema:familyName Nishikawa
    62 schema:givenName Tetsuo
    63 rdf:type schema:Person
    64 Nd83750803a714a8b865e3c0befd77dc0 rdf:first Nc4bfe693ddde4a0c987378eea0f336bd
    65 rdf:rest Nade2d4f5ffb14db990446dfe923fe7c7
    66 Ne9fefc8fb08847dc8fb2c2d4008d665b schema:volumeNumber 6
    67 rdf:type schema:PublicationVolume
    68 Nf4114ca227ff4b1884e5916d1c050e5a schema:name Springer Nature - SN SciGraph project
    69 rdf:type schema:Organization
    70 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    71 schema:name Biological Sciences
    72 rdf:type schema:DefinedTerm
    73 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    74 schema:name Genetics
    75 rdf:type schema:DefinedTerm
    76 sg:journal.1115214 schema:issn 1087-0156
    77 1546-1696
    78 schema:name Nature Biotechnology
    79 rdf:type schema:Periodical
    80 sg:pub.10.1038/321674a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041827788
    81 https://doi.org/10.1038/321674a0
    82 rdf:type schema:CreativeWork
    83 sg:pub.10.1038/325771a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002991698
    84 https://doi.org/10.1038/325771a0
    85 rdf:type schema:CreativeWork
    86 sg:pub.10.1038/nbt1085-911 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016045655
    87 https://doi.org/10.1038/nbt1085-911
    88 rdf:type schema:CreativeWork
    89 sg:pub.10.1038/nbt1086-890 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041063512
    90 https://doi.org/10.1038/nbt1086-890
    91 rdf:type schema:CreativeWork
    92 https://doi.org/10.1016/0165-022x(86)90038-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009603369
    93 rdf:type schema:CreativeWork
    94 https://doi.org/10.1016/s0076-6879(80)65059-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008420927
    95 rdf:type schema:CreativeWork
    96 https://doi.org/10.1073/pnas.74.12.5463 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025360556
    97 rdf:type schema:CreativeWork
    98 https://doi.org/10.1126/science.2443975 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062537979
    99 rdf:type schema:CreativeWork
     




    Preview window. Press ESC to close (or click here)


    ...