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Title: CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites

Abstract

High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several ofmore » the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.« less

Authors:
; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Washington State Univ., Pullman, WA (United States); Michigan State Univ., East Lansing, MI (United States). MSU-DOE Plant Research Laboratory
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES); National Institutes of Health (NIH); Washington State University (WSU)
OSTI Identifier:
1346599
Alternate Identifier(s):
OSTI ID: 1257836
Grant/Contract Number:  
FG02-04ER15559; FG02-91ER20021; 2008 -35300-04676; T32GM008336; IOS 0641232; MCB 1146928
Resource Type:
Published Article
Journal Name:
PLoS ONE
Additional Journal Information:
Journal Name: PLoS ONE Journal Volume: 11 Journal Issue: 4; Journal ID: ISSN 1932-6203
Publisher:
Public Library of Science
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; sequence motif analysis; DNA sequence analysis; sequence analysis; arabidopsis thaliana; expressed sequence tags; sequence databases; plant genomics; genome analysis

Citation Formats

Sharpe, Richard M., Koepke, Tyson, Harper, Artemus, Grimes, John, Galli, Marco, Satoh-Cruz, Mio, Kalyanaraman, Ananth, Evans, Katherine, Kramer, David, Dhingra, Amit, and Prasad, ed., Manoj. CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites. United States: N. p., 2016. Web. https://doi.org/10.1371/journal.pone.0152404.
Sharpe, Richard M., Koepke, Tyson, Harper, Artemus, Grimes, John, Galli, Marco, Satoh-Cruz, Mio, Kalyanaraman, Ananth, Evans, Katherine, Kramer, David, Dhingra, Amit, & Prasad, ed., Manoj. CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites. United States. https://doi.org/10.1371/journal.pone.0152404
Sharpe, Richard M., Koepke, Tyson, Harper, Artemus, Grimes, John, Galli, Marco, Satoh-Cruz, Mio, Kalyanaraman, Ananth, Evans, Katherine, Kramer, David, Dhingra, Amit, and Prasad, ed., Manoj. Tue . "CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites". United States. https://doi.org/10.1371/journal.pone.0152404.
@article{osti_1346599,
title = {CisSERS: Customizable In Silico Sequence Evaluation for Restriction Sites},
author = {Sharpe, Richard M. and Koepke, Tyson and Harper, Artemus and Grimes, John and Galli, Marco and Satoh-Cruz, Mio and Kalyanaraman, Ananth and Evans, Katherine and Kramer, David and Dhingra, Amit and Prasad, ed., Manoj},
abstractNote = {High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Here, data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERSenable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3’UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERSand results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.},
doi = {10.1371/journal.pone.0152404},
journal = {PLoS ONE},
number = 4,
volume = 11,
place = {United States},
year = {2016},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1371/journal.pone.0152404

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