| Hauptseite > Publikationsdatenbank > Oxford Nanopore Sequencing: New opportunities for plant genomics? > print |
| 001 | 877352 | ||
| 005 | 20210130005020.0 | ||
| 024 | 7 | _ | |a 10.1093/jxb/eraa263 |2 doi |
| 024 | 7 | _ | |a 0022-0957 |2 ISSN |
| 024 | 7 | _ | |a 1460-2431 |2 ISSN |
| 024 | 7 | _ | |a 2128/25768 |2 Handle |
| 024 | 7 | _ | |a altmetric:82930219 |2 altmetric |
| 024 | 7 | _ | |a pmid:32459850 |2 pmid |
| 024 | 7 | _ | |a WOS:000577073500004 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-02159 |
| 082 | _ | _ | |a 580 |
| 100 | 1 | _ | |a Dumschott, Kathryn |0 P:(DE-Juel1)180850 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Oxford Nanopore Sequencing: New opportunities for plant genomics? |
| 260 | _ | _ | |a Oxford |c 2020 |b Oxford Univ. Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1601042946_15197 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a DNA sequencing was dominated by Sanger’s chain-termination method until the mid-2000s, when it was progressively supplanted by new sequencing technologies that can generate much larger quantities of data in a shorter time. At the forefront of these developments, long-read sequencing technologies (third-generation sequencing) can produce reads that are several kilobases in length. This greatly improves the accuracy of genome assemblies by spanning the highly-repetitive segments that cause difficulty for second-generation short-read technologies. Third-generation sequencing is especially appealing for plant genomes, which can be extremely large with long stretches of highly-repetitive DNA. Until recently, the low basecalling accuracy of third-generation technologies meant that accurate genome assembly required expensive, highcoverage sequencing followed by computational analysis to correct for errors. However, today’s long-read technologies are more accurate and less expensive, making them the method of choice for the assembly of complex genomes. Oxford Nanopore Technologies (ONT), a thirdgeneration platform for the sequencing of native DNA strands, is particularly suitable for the generation of high-quality assemblies of highly-repetitive plant genomes. Here we discuss the benefits of ONT, especially for the plant science community, and describe the issues that remain to be addressed when using ONT for plant genome sequencing. |
| 536 | _ | _ | |a 582 - Plant Science (POF3-582) |0 G:(DE-HGF)POF3-582 |c POF3-582 |f POF III |x 0 |
| 536 | _ | _ | |a 583 - Innovative Synergisms (POF3-583) |0 G:(DE-HGF)POF3-583 |c POF3-583 |f POF III |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Schmidt, Maximilian |0 P:(DE-Juel1)180784 |b 1 |u fzj |
| 700 | 1 | _ | |a Chawla, Harmeet Singh |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Snowdon, Rod |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Usadel, Björn |0 P:(DE-Juel1)145719 |b 4 |
| 773 | _ | _ | |a 10.1093/jxb/eraa263 |g p. eraa263 |0 PERI:(DE-600)1466717-4 |n 18 |p 5313–5322 |t The journal of experimental botany |v 71 |y 2020 |x 1460-2431 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/877352/files/eraa263.pdf |
| 856 | 4 | _ | |y OpenAccess |x pdfa |u https://juser.fz-juelich.de/record/877352/files/eraa263.pdf?subformat=pdfa |
| 909 | C | O | |o oai:juser.fz-juelich.de:877352 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)180850 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)180784 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)145719 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Key Technologies for the Bioeconomy |1 G:(DE-HGF)POF3-580 |0 G:(DE-HGF)POF3-582 |2 G:(DE-HGF)POF3-500 |v Plant Science |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Key Technologies for the Bioeconomy |1 G:(DE-HGF)POF3-580 |0 G:(DE-HGF)POF3-583 |2 G:(DE-HGF)POF3-500 |v Innovative Synergisms |x 1 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2020 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1190 |2 StatID |b Biological Abstracts |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1060 |2 StatID |b Current Contents - Agriculture, Biology and Environmental Sciences |d 2020-01-05 |
| 915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b J EXP BOT : 2018 |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2020-01-05 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0110 |2 StatID |b Science Citation Index |d 2020-01-05 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0111 |2 StatID |b Science Citation Index Expanded |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2020-01-05 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2020-01-05 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b J EXP BOT : 2018 |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0310 |2 StatID |b NCBI Molecular Biology Database |d 2020-01-05 |
| 915 | _ | _ | |a National-Konsortium |0 StatID:(DE-HGF)0430 |2 StatID |d 2020-01-05 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2020-01-05 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2020-01-05 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |d 2020-01-05 |w ger |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2020-01-05 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)IBG-4-20200403 |k IBG-4 |l Bioinformatik |x 0 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)IBG-4-20200403 |
| 980 | 1 | _ | |a FullTexts |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|