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CRISPR-RT: A web service for designing CRISPR-C2c2 crRNA with improved target specificity
Houxiang Zhu1, Emily Richmond2, Chun Liang1, 2*
1Department of Biology, Miami University, Oxford, United States; 2Department of Software
Engineering, Miami University, Oxford, United States
*For correspondence: [email protected]
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Abstract CRISPR-Cas systems have been successfully applied in genome editing. Recently,
the CRISPR-C2c2 system has been reported as a tool for RNA editing. Here we describe
CRISPR-RT (CRISPR RNA-Targeting), the first web service to help biologists design the
crRNA with improved target specificity for the CRISPR-C2c2 system. CRISPR-RT allows users
to set up a wide range of parameters, making it highly flexible for current and future research in
CRISPR-based RNA editing. CRISPR-RT covers major model organisms and can be easily
extended to cover other species. CRISPR-RT will empower researchers in RNA editing. It is
available at http://bioinfolab.miamioh.edu/CRISPR-RT.
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Introduction
The CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-
associated) system is an adaptive immune system of prokaryotes, which is used to resist foreign
genetic elements in bacteria and archaea (Marraffini and Sontheimer, 2010; Barrangou and
Marraffini, 2014). During the past several years, CRISPR-Cas systems have been successfully
applied in genome editing (Hwang et al., 2013; Jiang et al., 2013; Cho et al., 2013; Cong et al.,
2013; Bikard et al., 2014; Wan et al., 2015), but no systems have been reported for RNA editing.
Therefore, new CRISPR-Cas systems that regulate RNA activities are necessary for studying the
roles of RNA molecules. Recently, the CRISPR-C2c2 system has been demonstrated as a tool for
RNA targeting (Abudayyeh et al., 2016).
CRISPR-C2c2 was discovered in 21 bacterial genomes and belongs to the type VI of
Class 2 CRISPR systems (Shmakov et al., 2015). Researchers have characterized the CRISPR-
C2c2 system from the bacteria Leptotrichia shahii (Abudayyeh et al., 2016). The L. shahii C2c2
locus is simply organized, including C2c2, Cas1, Cas2 and a CRISPR array (Figure 1). Cas1
and Cas2 play an important role in spacer acquisition (Nuñez et al., 2015; Heler et al., 2015;
Nuñez et al., 2014; Díez-Villaseñor et al., 2013; Yosef et al., 2012; Datsenko et al., 2012). C2c2,
which contains two higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domains,
mainly functions as a sole effector protein mediating single-strand RNA cleavage (Abudayyeh et
al., 2016). The CRISPR array consists of many short palindromic repeat elements and spacer
sequences. Similar to other Class 2 systems, the CRISPR array of CRISPR-C2c2 is first
transcribed into pre-crRNA (Shmakov et al., 2015). Differently, the pre-crRNA is processed by
C2c2 into mature crRNAs without attaching to trans-activating crRNAs (East-Seletsky et al.,
2016). The mature crRNA binds to C2c2 and guides it to target a specific single-strand RNA.
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Then, in the target site, the HEPN domains of C2c2 mediate cleavage of the single-strand RNA
(Abudayyeh et al., 2016). The crRNA stem-loop structure is also required for cleavage. Thus, the
palindromic repeat length of crRNA needs to be longer than 24 nt to maintain the stem loop
(Abudayyeh et al., 2016). In addition, C2c2 combined with a 22-28 length of the target
complementarity region of crRNA would effectively mediate cleavage (Abudayyeh et al., 2016).
The seed region is located in the center of the crRNA-target duplex, where is more sensitive to
mismatches than the non-seed region (Abudayyeh et al., 2016). Single mismatch can be fully
tolerated by C2c2, but if double mismatches are located in the seed region, C2c2 is unable to
cleave the single-strand RNA (Abudayyeh et al., 2016). C2c2 can even tolerate 3 consecutive
mismatches in the non-seed region (Abudayyeh et al., 2016). Currently, there is no research
about gaps (insertions or deletions) tolerated by C2c2, which may be explored in the near future.
The CRISPR-C2c2 system prefers H (A, U, or C) for the 3’ protospacer flanking site (PFS)
sequence of one single base length to mediate single-strand RNA cleavage (Abudayyeh et al.,
2016). CRISPR-C2c2 has been reprogrammed to knockdown the specific mRNA in vivo,
although C2c2 may also cleave collateral RNAs (Abudayyeh et al., 2016). Researchers have
applied the CRISPR-C2c2 system to sensitively detect transcripts in complex mixtures (East-
Seletsky et al., 2016). C2c2 can be easily converted into an inactive RNA-binding protein
(dC2c2) by mutating any of the two HEPN domains (Abudayyeh et al., 2016). Compared to the
wild type C2c2, dC2c2 has more potential applications as an RNA-binding protein (Abudayyeh
et al., 2016). The CRISPR-C2c2 system is opening a new chapter for the programmable CRISPR
tools of RNA editing. However, until now there is no available software for designing crRNAs
of the CRISPR-C2c2 system.
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We have developed CRISPR-RT (CRISPR RNA-Targeting), a web service to help
biologists design the crRNA for the CRISPR-C2c2 system. To maximize the flexibility for
current and future research in CRISPR-based RNA editing, CRISPR-RT allows users to set up a
wide range of parameters, such as length of the target complementarity region of crRNA, length
of the seed region, the PFS, and the number of mismatches or gaps tolerated by off targets. After
setting up the required parameters, CRISPR-RT will find target candidates from the input RNA
sequence and employ rigorous alignment algorithms to search on- and off-target sites for each
target candidate within the reference transcriptome (Langmead and Salzberg, 2012). The results
are displayed in highly interactive graphical interfaces. Users can rank target candidates by the
total number of target sites in the reference transcriptome, which help them choose the target
candidate based on the minimum effect of off targets. In addition, users are able to validate the
on- and off-target sites in the background of annotated genome and transcript features by data
visualization through JBrowse (Skinner et al., 2009).
Results
Graphic Input Interface
Figure 2 shows the home page of CRISPR-RT. If users click “C2c2” on the left side
menu, the setting page of the CRISPR-C2c2 system will be displayed (Figure 3). First, users
input an RNA sequence that they want to target in FASTA format into the text area. Users can
also convert a cDNA sequence to the corresponding RNA sequence by clicking the “cDNA?”
link. After converting, they then copy the converted RNA sequence back into the text area as the
input sequence. If users want to use an example sequence, they can click the “Example Sequence”
button. Second, users select a reference transcriptome. If the transcriptome that users want to
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choose does not show up in the drop-down menu and this transcriptome is available in
ENSEMBL genome annotation (www.ensembl.org), they can click the “others?” link to submit a
requirement so that the transcriptome will be added to the web server manually soon. Third, in
terms of our current understanding of the CRISPR-C2c2 system architecture (Figure 1), users
can set up the PFS sequence and crRNA requirements for the CRISPR-C2c2 system properly.
The on- and off- target PFS sequence can be set respectively, which accepts any single letter or
combination of the international union of pure and applied chemistry (IUPAC) nucleotide codes
except “T” and “Z”. Users then set up the length of the target complementarity region of crRNA
and the length of the seed region. The seed region is located in the center of the crRNA-target
duplex, and its length should not be greater than the length of the target complementarity region
of crRNA. Fourth, users can choose an off-target setting (“Basic settings” or “Specific settings”).
For “Basic settings”, the number of mismatches or gaps tolerated by off targets as well as by the
seed region can be set respectively. The number of consecutive mismatches or gaps in the seed
or non-seed region tolerated by off targets can also be configured. For “Specific settings”, users
can set up more detailed parameters in the seed and non-seed region separately, such as the
number of mismatches in the seed or non-seed region tolerated by off targets. Users can also set
up the search sensitivity of Bowtie2 (Langmead and Salzberg, 2012), which is related to the
alignment options setting of Bowtie2, to search target sites in the reference transcriptome. Higher
sensitivity setting causes alignments to be more sensitive, but it usually results in a slower search
time. CRISPR-RT maximizes flexible and adjustable settings to help biologists conduct current
and future experiments with more in-depth understanding of the CRISPR-C2c2 system. After
setting up all the parameters, users click the “Find targets!” button which will run programs in
the background to get the results. If users want to retrieve a recent job, they can click “Retrieve
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Jobs” on the left side menu to enter the “Job ID”, which is generated in the result page, for
retrieving results in later times. The results will be kept in our server for only one week and will
be deleted automatically afterwards.
Graphic Output Interface
Figure 4A shows all the target candidates and relevant information for the user input
RNA sequence. Users can view the input sequence by clicking the “Input Sequence Viewer”
button. In the sequence viewer, users can search and highlight any subsequence such as the target
candidate sequence (Figure 4B). The “Job ID” can be used to retrieve users’ recent jobs from
CRISPR-RT and all relevant data will be stored for a week in our server. Users can also
download the target candidates file by clicking the “Download” link. In the table, the protospacer
and PFS of each target candidate are labeled by different colors. The corresponding crRNA of
each target candidate can be accessed by clicking “crRNA”; a graph will appear to help users
design their own crRNAs (Figure 5). The table also displays the start position, end position, and
GC content of each target candidate sequence. The last column of the table shows the number of
target sites in the transcriptome for each target candidate. By clicking the “#Targets” header
users are able to rank all the target candidates based on the number of target sites. Target
candidates with fewer number of target sites have higher target specificity in the transcriptome.
If the number of target sites is 1, the corresponding table cell will be highlighted with green
background color to indicate that the target candidate is highly specific in the whole
transcriptome. By clicking the number of target sites users can view the detailed information of
target sites for each target candidate (Figure 4C). Because CRISPR-RT has converted the
transcriptome mapping result to a genome mapping result, the information of target sites are
displayed in genomic context with genomic coordinates and gene annotations, including mapped
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gene, chromosome, strand, start/end position, and transcript isoforms. Users can click the
“transcript ID” link or “gene ID” link of each target site to view the detailed description of
transcript or gene where the target site located. The number of mismatches or gaps in each target
site is also shown in the table. To visualize and manually validate the target sites, users can click
the “JBrowse” link to visualize each target site in the background of genome and transcript
features annotated by ENSEMBL (www.ensembl.org) (Figure 4D).
Discussion
The CRISPR-C2c2 system has been reported as a tool for RNA editing (Abudayyeh et al.,
2016). Additionally, CRISPR-C2c2 has already been successfully used for specific RNA
knockdown in E. coli (Abudayyeh et al., 2016), and it has been applied for RNA detection in
human total RNAs (East-Seletsky et al., 2016). The dC2c2, just like dCas9 (Bikard et al., 2013;
Qi et al., 2013; Gilbert et al., 2013; Piatek et al., 2015; Maeder et al., 2013; Perez-Pinera et al.,
2013; Mali et al., 2013; Cheng et al., 2013; Polstein and Gersbach, 2015; Nihongaki et al., 2015;
Zetsche et al., 2015; Gao et al., 2016), also has many potential applications as an RNA-binding
protein, such as bringing effectors to specific RNAs to regulate their translation and tracking
specific RNAs by fluorescent tag (Abudayyeh et al., 2016). Therefore, the CRISPR-C2c2 system
has been viewed as a powerfully programmable tool for current and future RNA editing
(Abudayyeh et al., 2016; East-Seletsky et al., 2016; Nainar et al., 2016; Wang and Qi, 2016;
Puchta, 2017). However, so far no available software was developed to design crRNAs for the
CRISPR-C2c2 system.
In this project, we studied the architecture and features of CRISPR-C2c2 from the
bacteria L. shahii. By emphasizing the flexible parameters input and the target specificity of
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crRNAs, we developed CRISPR-RT, the first web-based bioinformatics tool to help biologists
design the crRNA for the CRISPR-C2c2 system. Specifically, CRISPT-RT accepts a wide range
of parameters such as the number of mismatches or gaps tolerated by off targets, but maintains a
simple interface, making it highly flexible for current and future research in CRISPR-based RNA
editing and targeting. The powerful alignment tool - Bowtie2 (Langmead and Salzberg, 2012) is
used to search all the target sites within the reference transcriptome for each target candidate.
Researchers are able to choose the target candidate with minimum off-target effect for crRNA
designing. In addition, the on and off-target sites can be validated by data visualization through
JBrowse with proper gene and transcript annotations (Skinner et al., 2009).
CRISPR-RT currently covers 10 model organisms including human and can be easily
extended to cover other species. The availability of CRISPR-RT will help researchers improve
the target specificity of crRNA design for the CRISPR-C2c2 system and empower biologists in
CRISPR-based RNA editing and targeting.
Methods
CRISPR-RT is essentially composed of many web interfaces and a backend pipeline.
Web interfaces are implemented by PHP and JavaScript code, which are used to accept user
inputs and display the results interactively. The backend pipeline is implemented by Perl code,
which is used to process user input data and generate multiple result files.
After setting up proper parameters and clicking the “Find targets!” button in the
parameter setting page of CRISPR-C2c2 (Figure 3), all of the parameters stored in PHP code are
passed to the main Perl script, which invokes other specific Perl scripts or commands to execute
specific functions. As shown in Figure 6, first, the Perl script for target candidate search is called
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to find target candidates of specified length with the PFS in the input RNA sequence. Second,
Bowtie2 (Langmead and Salzberg, 2012) is used to map each target candidate sequence to the
reference transcriptome, which is extracted from the genome by RSEM (Li and Dewey, 2011)
using Ensembl gene annotation, to search for on- and off-target sites within the transcriptome.
Third, the Perl scripts for result filtration based on the input parameters are invoked to filter out
the off targets that do not meet the requirements set by users. Next, RSEM is used to convert the
transcriptome mapping result to a genome mapping result, which can be displayed properly in
JBrowse (Skinner et al., 2009). Then, the main Perl script separates the file storing target sites of
all target candidates into many single files that store target sites for each target candidate
respectively. The main Perl script also processes the file of target candidates and the files of
target sites for each target candidate to generate Ajax format files, which are required by
DataTables (a table plug-in for jQuery). After getting all of those files, the PHP and JavaScript
code is used to display detailed information of target candidates and corresponding target sites in
DataTables. The on- and off-target sites can be visualized in JBrowse.
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Figure 1. The configuration and architecture of the CRISPR-C2c2 system. The CRISPR array of CRISPR-C2c2 is
first transcribed into pre-crRNA. Then, the pre-crRNA is processed by C2c2 into mature crRNAs without attaching
to trans-activating crRNAs. The mature crRNA binds to C2c2 and guides C2c2 to target a specific single-strand
RNA at a proper target site.
C2c2
5’
Pre-crRNA
5’
Mature crRNA
C2c2
5’ 3’ PFS
Seed
Target RNA
C2c2 Cas1 Cas2 CRISPR array Leptotrichia shahii CRISPR-C2c2 locus
3’
3’
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Figure 2. The home page of CRISPR-RT web service.
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Figure 3. The parameter setting page of CRISPR-C2c2. First, users input an RNA sequence in FASTA format into
the text area. Second, users select a reference transcriptome. Third, users set up the PFS and crRNA requirements
for the CRISPR-C2c2 system. Fourth, users choose an off-target setting (either “Basic settings” or “Specific
settings”).
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Figure 4. The result web interfaces of CRISPR-RT. (A) The detailed information of all the target candidates in the
user input RNA sequence. (B) User input RNA sequence viewer. (C) The detailed information of target sites in the
transcriptome for each target candidate. (D) Visualization of on- and off-targets with gene and transcript annotations
in JBrowse.
B
C
A
D
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Figure 5. The basic process of crRNA design based on the target candidate sequence (protospacer). The target
complementarity sequence of crRNA is labelled in purple color. The stem-loop sequence of crRNA comes from
previous research (Abudayyeh et al., 2016). The designed crRNA binds to C2c2 to form a crRNA-C2c2 complex for
RNA targeting.
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Figure 6. The flowchart of CRISPR-RT backend pipeline that processes user input RNA sequence and displays
results in the interfaces. All of input parameters, including the RNA sequence, are passed to the main Perl script.
The main Perl script invokes other specific Perl scripts or commands to execute specific functions. Finally, the
results will be displayed in DataTables and JBrowse in the web interfaces.
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Acknowledgements
This project is funded by Office for the Advancement of Research and Scholarship (OARS) and
Biology Department, Miami University, Oxford, Ohio, USA.
Authors’ contributions
CL managed and coordinated the whole project. HZ and CL participated in CRISPR-RT design.
HZ implemented the backend pipeline in Perl. HZ, ER, and CL participated in web interfaces
implementation. HZ, ER, and CL prepared the manuscript. All authors have read and approved
the final manuscript.
Competing interests
The authors declare no competing financial interests.
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