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<p>The first step in any MERFISH experiment is the design of the oligonucleotide probes that will be used to label individual RNA species. In our current implementation of MERFISH, each oligonucleotide encoding probe consists of three basic components as illustrated in Figure 2. The first region is a 30-nt targeting region that is complementary to a portion of the sequence of the RNA to which it is designed to bind. The second region is a set of sequences that are called readout sequences, which were designed to be complementary and hence only bind to MERFISH readout probes and not other nucleic acid in the cell. Finally, the third region is a set of priming regions used in the construction of these probes, which will be discussed in detail in <a href="https://www.protocols.io/view/rna-imaging-with-merfish-probe-construction-meqc3dw" target="_blank">Probe Construction</a>. In addition to the nucleotide sequences for each of these components, a codebook —the specific set of binary barcodes that will be used and their association with different RNA species of interest—must also be designed. In this section, we provide protocols to design these sequences and to build a codebook. Example code to perform these steps can be found at <a href="http://zhuang.harvard.edu/merfish/ " target="_blank">http://zhuang.harvard.edu/merfish/ </a>.</p>
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[GUIDELINES]
<p style="text-align: justify;"><strong>Design of Target Regions</strong></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Functionally, the goal of a target region is to direct the binding of each encoding probe to its target RNA of interest with high binding efficiency and specificity. The central challenge in the design of target regions for MERFISH (and smFISH, in general), is to design a set of target regions where these properties are optimized for all probes under a constant set of hybridization conditions, e.g. incubation temperature. To accomplish this goal target regions are designed to cover a relatively narrow range of GC content and melting temperatures (TM ) with their target. In addition, a good target region should have limited homology to other RNAs in the transcriptome, reducing the probability that it will bind to the wrong RNA. Finally, the typical smFISH measurement does not bind each RNA with a single probe but rather tiles that RNA with multiple probes, each of which targets a different portion of the sequence of the RNA. See Figure 2. For many smFISH measurements, the number of unique probes per RNA is often ~50; however, this number can be lowered with a corresponding reduction in the brightness of the individual RNA spots (Raj et al., 2008). For initial MERFISH work, we recommend having at least 50 encoding probes per RNA.</p>
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<p style="text-align: center;"><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/rwxfw26.png" width="505" height="580" data-src="https://s3.amazonaws.com/pr-journal/rwxfw26.png" data-ofn="Screen Shot 2017-12-29 at 1.44.58 PM.png" /></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">As described by others (Raj et al., 2008), smFISH probes can be designed online using a web interface (<a href="https://www.biosearchtech.com/support/tools/design-software/stellaris-probedesigner" target="_blank">https://www.biosearchtech.com/support/tools/design-software/stellaris-probedesigner</a>). In principle, probes designed with this software should work well as target regions for MERFISH. However, there is no batch processing option for such software and submitting hundreds to thousands of genes individually would be very labor intensive. Thus, we describe the alternative approach that we have used.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">We design our target regions with the software package, OligoArray 2.0, which was developed for the design of microarrays (Rouillard, 2003). This software has been used previously in the design of FISH probes for DNA (Beliveau et al., 2012). In addition to the ability to batch process mRNAs, one advantage of this software is the additional stringency  OligoArray applies to the design of its probes. Specifically, internal secondary structure and off-target binding are assessed not via the number of complementary bases but by the thermodynamic stability of these structures. Of course, these extra calculations come at a computational cost, and calculation of target regions for a large number of genes can take days of computing resources on a desktop computer.</p>
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<p style="text-align: justify;"><strong>Design of Readout Probes</strong></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">There are several important considerations in the design of readout probes. First, to improve the binding efficiency of these probes, it is desirable to select probes that have similar TM and GC content so that their hybridization properties are similar under a given hybridization condition. Second, to limit the number of potential off-target binding sites, potential sequences should be screened for homology to RNAs in the transcriptome of interest. Third, these sequences must be orthogonal, in that they should have limited homology with one another to prevent binding of one readout probe to the wrong readout sequence.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">We have already screened and validated several readout probes for human samples, and we recommend the use of these sequences, which are provided in Table 1. The steps can be taken if new or additional readout probes are required.</p>
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<p style="text-align: center;"><img id="s-mce-img" class="s-mce-img" src="https://s3.amazonaws.com/pr-journal/rxdfw26.png" width="483" height="239" data-src="https://s3.amazonaws.com/pr-journal/rxcfw26.png" data-ofn="Screen Shot 2017-12-29 at 5.52.29 PM.png" /></p>
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<p style="text-align: justify;"><strong>Design of the Codebook</strong></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Before readout sequences and target sequences can be assembled to form the sequence of encoding probes, a codebook must be designed. The first step in codebook design is the choice of an encoding scheme that is appropriate for the experimental goals. We have utilized two different encoding schemes for MERFISH. The first scheme is a constant Hamming Weight code generated by keeping all binary barcodes from an existing HD4 code known as the Extended Hamming Code that contain only four `1' bits. We call this code the Modified Hamming Distance 4 code (MHD4). The 16-bit version of this encoding scheme contains 140 binary barcodes and is capable of identifying all two-bit errors and correcting any individual single-bit error. Alternatively, if the error correcting abilities of this code are not utilized, it can also detect three-bit errors. The advantage of this encoding scheme is the very high calling rate, ~80%, and low misidentification rates that it provides, as discussed in the full manuscript. In the second encoding scheme, we utilized a constant Hamming Weight code generated from all possible combinations of four `1' bits. This code has a minimum HD of 2 between all barcodes, so we refer to it as a Modified HD 2 code (MHD2). The benefit of this encoding scheme is that the reduced HD allows a much higher level of multiplexing for a given number of a bits—a 14-bit code contains 1,001 barcodes. However, the reduced HD produces a lower calling rate and a slight reduction in accuracy. Again, see the attached manuscript. </p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Here we describe algorithms to generate both encoding schemes; however, we would encourage users to consider alternative encoding schemes, e.g. versions of those provided below with fewer or more bits or schemes with different Hamming Weight or HD, in order to find a scheme that best suits their experimental needs. Again, examples of algorithms to generate these codes as well as the barcodes for the published 16-bit MHD4 and 14-bit MHD2 codes are provided at: <a href=" http://zhuang.harvard.edu/merfish/ " target="_blank">http://zhuang.harvard.edu/merfish/</a>.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;"><strong>Generation of the MHD4 Encoding Scheme</strong>—Here we present a method for generating sets of constant-weight-4 HD-4 (MHD4) barcodes for any number of bits. As an interesting aside, we note that the task of creating the optimal constant weight coding scheme — the encoding scheme that has the maximum possible number of barcodes given a specific HD — remains an unsolved problem. Thus, the algorithm that we present here likely does not produce a constant weight HD-4 code with the maximum possible number of barcodes given a specific number of bits. However, comparison of estimates of the upper bound on the number of barcodes possible in such codes (Brouwer and Etzion, 2011) and the number of barcodes generated by this algorithm suggests that it performs fairly well, typically producing ~75% of the possible number of barcodes. The 16-bit MHD4 code that we have produced is the rare exception: It contains 140 barcodes which is the current known upper limit for an MHD4 code of this length (Brouwer and Etzion, 2011).</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Step 1: Generate the Extended Hamming Code that contains the desired number of bits.</p>
<p style="text-align: justify;">Details on how to generate this code are discussed many places online, and software to</p>
<p style="text-align: justify;">perform this calculation is included at <a href="http://zhuang.harvard.edu/merfish/" target="_blank">http://zhuang.harvard.edu/merfish/</a>.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Step 2: Select only barcodes with the desired Hamming Weight.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;"><strong>Generation of the MHD2 Encoding Scheme</strong>—Constant weight HD2 codes are straightforward to generate, and the algorithm that we provide below will produce the optimal code, i.e. the maximum number of barcodes with four `1's and a minimum HD of 2.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Step 1: Generate a barcode of the desired length with only four `1's.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Step 2: Generate all possible permutations of the bits in this barcode.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;"><strong>Barcode Assignment</strong>—Once the desired barcodes have been designed, the codebook is designed by randomly associating each barcode with a specific RNA of interest. We recommend leaving 5-10% of the possible barcodes unassigned. These `blank' or `control' barcodes will serve as internal controls and will provide estimates of the frequency with which barcodes can be generated by background or spurious signals. The specific use of these `blank' measurements in discussed in the attached full manuscript.</p>
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<p style="text-align: justify;"><strong>Assembly and Screening of Encoding Probes</strong></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">Once the target regions, the readout regions, and the barcodes associated with the desired encoding scheme are designed, the sequence of the encoding probes can be assembled. Each encoding probe will contain multiple readout sequences. However, given length restrictions in synthesis of these sequences, it is typically not the case that all of the readout sequences for each RNA will fit into each encoding probe. We use two readout sequences per encoding probe.</p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;"><strong>Design of Priming Regions</strong></p>
<p style="text-align: justify;"> </p>
<p style="text-align: justify;">The protocol that we use to make encoding probes that contain the sequences designed above require the addition of two priming regions to each probe. The optimal regions should have similar TM , no contiguous stretches of the same nucleotide longer than three, and relatively narrow GC content. They should also have limited homology to each other and to non-priming regions of the encoding probes.</p>

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