Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping.
Identifieur interne : 000C51 ( Main/Exploration ); précédent : 000C50; suivant : 000C52Optimized Sequence Library Design for Efficient In Vitro Interaction Mapping.
Auteurs : Yaron Orenstein [États-Unis] ; Robert Puccinelli [États-Unis] ; Ryan Kim [États-Unis] ; Polly Fordyce [États-Unis] ; Bonnie Berger [États-Unis]Source :
- Cell systems [ 2405-4712 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Oligonucléotides.
- synthèse chimique : Oligonucléotides.
- Algorithmes, Analyse de séquence d'ADN, Banque de gènes, Biologie informatique, Cartographie d'interactions entre protéines, Logiciel, Protéines de liaison à l'ADN.
English descriptors
- KwdEn :
- MESH :
- chemical , chemical synthesis : Oligonucleotides.
- chemical , genetics : Oligonucleotides.
- chemical : DNA-Binding Proteins.
- methods : Computational Biology, Protein Interaction Mapping, Sequence Analysis, DNA.
- Algorithms, Gene Library, Software.
Abstract
Sequence libraries that cover all k-mers enable universal, unbiased measurements of binding to both oligonucleotides and peptides. While the number of k-mers grows exponentially in k, space on all experimental platforms is limited. Here, we shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet simultaneously. We present the JokerCAKE (joker covering all k-mers) algorithm for generating a short sequence such that each k-mer appears at least p times with at most one joker character per k-mer. By running our algorithm on a range of parameters and alphabets, we show that JokerCAKE produces near-optimal sequences. Moreover, through comparison with data from hundreds of DNA-protein binding experiments and with new experimental results for both standard and JokerCAKE libraries, we establish that accurate binding scores can be inferred for high-affinity k-mers using JokerCAKE libraries. JokerCAKE libraries allow researchers to search a significantly larger sequence space using the same number of experimental measurements and at the same cost.
DOI: 10.1016/j.cels.2017.07.006
PubMed: 28957657
Affiliations:
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Electronic address: bab@mit.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139</wicri:regionArea><placeName><region type="state">Massachusetts</region></placeName></affiliation></author></analytic><series><title level="j">Cell systems</title><idno type="ISSN">2405-4712</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Computational Biology (methods)</term><term>DNA-Binding Proteins</term><term>Gene Library</term><term>Oligonucleotides (chemical synthesis)</term><term>Oligonucleotides (genetics)</term><term>Protein Interaction Mapping (methods)</term><term>Sequence Analysis, DNA (methods)</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Analyse de séquence d'ADN ()</term><term>Banque de gènes</term><term>Biologie informatique ()</term><term>Cartographie d'interactions entre protéines ()</term><term>Logiciel</term><term>Oligonucléotides (génétique)</term><term>Oligonucléotides (synthèse chimique)</term><term>Protéines de liaison à l'ADN</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemical synthesis" xml:lang="en"><term>Oligonucleotides</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Oligonucleotides</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>DNA-Binding Proteins</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Oligonucléotides</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term><term>Protein Interaction Mapping</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" qualifier="synthèse chimique" xml:lang="fr"><term>Oligonucléotides</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Gene Library</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Analyse de séquence d'ADN</term><term>Banque de gènes</term><term>Biologie informatique</term><term>Cartographie d'interactions entre protéines</term><term>Logiciel</term><term>Protéines de liaison à l'ADN</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Sequence libraries that cover all k-mers enable universal, unbiased measurements of binding to both oligonucleotides and peptides. While the number of k-mers grows exponentially in k, space on all experimental platforms is limited. Here, we shrink k-mer library sizes by using joker characters, which represent all characters in the alphabet simultaneously. We present the JokerCAKE (joker covering all k-mers) algorithm for generating a short sequence such that each k-mer appears at least p times with at most one joker character per k-mer. By running our algorithm on a range of parameters and alphabets, we show that JokerCAKE produces near-optimal sequences. Moreover, through comparison with data from hundreds of DNA-protein binding experiments and with new experimental results for both standard and JokerCAKE libraries, we establish that accurate binding scores can be inferred for high-affinity k-mers using JokerCAKE libraries. JokerCAKE libraries allow researchers to search a significantly larger sequence space using the same number of experimental measurements and at the same cost.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Californie</li><li>Massachusetts</li><li>Virginie</li></region></list><tree><country name="États-Unis"><region name="Massachusetts"><name sortKey="Orenstein, Yaron" sort="Orenstein, Yaron" uniqKey="Orenstein Y" first="Yaron" last="Orenstein">Yaron Orenstein</name></region><name sortKey="Berger, Bonnie" sort="Berger, Bonnie" uniqKey="Berger B" first="Bonnie" last="Berger">Bonnie Berger</name><name sortKey="Fordyce, Polly" sort="Fordyce, Polly" uniqKey="Fordyce P" first="Polly" last="Fordyce">Polly Fordyce</name><name sortKey="Kim, Ryan" sort="Kim, Ryan" uniqKey="Kim R" first="Ryan" last="Kim">Ryan Kim</name><name sortKey="Puccinelli, Robert" sort="Puccinelli, Robert" uniqKey="Puccinelli R" first="Robert" last="Puccinelli">Robert Puccinelli</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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