Journal of Virological Methods, 41 (1993) 157-166 157 0 1993 Elsevier Science Publishers B.V. / All rights reserved / 0166-0934/93/$06.00

VIRMET 01439

A computer program for the design of PCR primers for diagnosis of highly variable genomes

Joaquin Dopazo and Francisco Sobrino

INIA - Sanidad Animal, Madrid (Spain)

(Accepted 1 September 1992)

Summary

PCRDiag (Diagnosis by PCR) is a computer program which allows the localization of pairs of oligonucleotides with optimal thermodynamic requirements for use in a PCR assay. The program is designed for the selection of pairs of primers complementary to sequences present in a group, whose identification is intended, but are absent in other non-specific sequences. The program constitutes a powerful tool, specially in systems which display a high degree of sequence heterogeneity, as is the case of RNA viruses.

The program runs on IBM-PC and compatible computers and has no special software requirements. It does not need the previous alignment of the sequences analyzed.

PCR; Primer selection; Diagnosis; Computer software; Variability; Foot-and-mouth disease virus

Introduction

The use of the polymerase chain reaction (PCR) has allowed a sequence- specific, highly sensitive detection and amplification of genomes (Erlich et al., 1991; Saiki et al., 1988).

PCR has opened new perspectives in the diagnosis of viral infections (Kwok and Sninsky, 1989). Specific detection of DNA viruses has been achieved, among others, for human papilloma viruses (Manos et al., 1989), human hepatitis B (Mack and Sninsky, 1988), human cytomegalovirus (Demmler et

Correspondence to; J. Dopazo, INIA-Sanidad Animal, Embajadores 68, 28012 Madrid, Spain.

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al., 1988). Also RNA viruses such as hantaviruses (Giebel et al., 1990) rotaviruses (Flores et al., 1990), rubella virus (Ho-Terry et al., 1990) picornaviruses (Hyypia et al., 1989; Jansen et al., 1990; Laor et al., 1992; Olive et al., 1990; Rodriguez et al., 1992; Yang et al., 1991) and retroviruses (Kwok et al., 1988; Ou et al., 1988) have been successfully detected by PCR amplification.

The selection of oligonucleotides for use as primers for specific detection by PCR amplification has to take into account the observation of several rules which include adequate C + G content (Rappole, 1990) and the presence of a G:C pair in the 3’ terminal (Linz et al., 1990; Sommer and Tautz, 1989) required for the appropriate primer stability, and the absence of intra- and inter-primer complementarity (Lowe et al., 1990; Rychlik and Rhoads, 1989). Primers used for diagnosis must be absolutely specific for the sequences to be detected. Selection of regions matching these requirements becomes difficult and time consuming, mostly for systems which display high genetic variability, as is the case of RNA viruses (Domingo and Holland, 1988; Holland et al., 1982). Recently, specific algorithms, implemented in computer programs, which face the problem of searching for oligonucleotides common to families of aligned sequences have been suggested (Dopazo et al., 1992; Lukas et al., 1991; Montpetit et al., 1992). This type of software may become an essential tool in the field of diagnosis in the near future.

We describe a computer program, available upon request, specifically developed for the identification of primers common to groups of highly variable genomes. To confirm the efficiency of the program we have used as a model a set of sequences of foot-and-mouth disease virus (FMDV), a picornavirus which shows a considerable genetic variability (Domingo et al., 1990; Dopazo et al., 1988, 1992). These sequences have been used to carry out a search of primers able to amplify specifically 3D FMDV gene.

Material and Methods

PCRDiag runs on IBM-PC or compatible computers under an operating system DOS 3.0 or higher. It needs a minimum of 256 kilobytes (kb) of random access memory (RAM), although, at least 512 kb are recommended. No math coprocessor, graphic card or any other special requirement is necessary to run the program.

Language and program characteristics

The program was written in Turbo PASCAL (Borland International) version 6.0 and utilized the Turbo Vision library for the user interface. The program is interactive, having a user interface based on pull-down menus in the Borland

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fashion, full mouse support and context-sensitive, hypertext help. Object- oriented facilities provided by the new Borland Pascal compiler have been used extensively in the development of this program. The memory management, which includes dynamic arrays instead of the fixed-size typical PASCAL arrays, is remarkable. The speed of the program was improved by means of the Turbo PROFILER, version 1 .O, tool (Borland International).

File formats

ASCII files in the most frequent formats are identified automatically and read by the program. Recognized formats include: GenBank, EMBL, NBFR/ PIR, FASTA, Intelligenetics and PHYLIP (Felsenstein, 1990) as well as free format. Unlike in other programs (Montpetit et al., 1992), a previous alignment of the sequences is not necessary and, in fact, it will be ignored if done. The four bases (A, G, C, T/U) as well as IUPAC letters for degenerate bases can be read by the program as both upper and lower case. The maximum length for any individual sequence, in the present version of the program, is 65 521 bases.

Output files are ASCII ~American standard code for information interchange) tiles which can be retrieved from any text processor and can be sent directly to the printer.

Primer selection rules

The selection of both sense and antisense primers is carried out under the observation of a set of empirical rules which make reference to their thermodynamic ability to serve as PCR primers. Primer internal stability, which include primer length, C + G content (Rappole, 1990) and presence of a C:G pair in the 3’-end (Lintz et al., 1990; Sonner and Tautz, 1989) is examined first. Subsequently, primers able to anneal to other regions of the genome and analyzed, to itself or to its respective sense or antisense counterparts are discarded (Lowe et al., 1990; Rychlik and Rhoads, 1989). In addition to the above rules, the sequences complementary to the pairs of primers suitable for diagnosis have to be conserved in the group of genomes, whose identification is intended, although this sequence conservation must be sufficiently low when compared with those genomes whose amplification is not desired.

The program can work in three modes depending on the number of rules applied. (I) Primer identification: only a sequence is provided to the program, and it seeks for pairs of primers which full?1 the search conditions. (2) Common primers identification: a group of sequences (target group) is provided to the program, and it seeks for the primers which, in addition to satisfy the search conditions, display an unique match region in each of the sequences of the target group. (3) Extended common primers identi~cation: this case is similar to the previous one but an additional set of sequences (non-specific group, usually composed of these sequences whose amplification may produce a false positive identification) is provided to the program; then the program proceeds

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as in the previous mode but primers potentially able to anneal to any of the sequences of the non-specific group are discarded.

All the parameters and decision constants on which the rules of selection of primers, in all the modes, are based can be easily changed by the user.

Algorithm

The algorithm used is a combined approach which takes into account thermodynamic criteria as well as considerations on the variability of the genomes studied, and involves the sequential application of a set of rules.

The program constructs a list of possible antisense primers within the region to be searched, as described by Lowe et al. (1990). Starting by the 5’ of the specified region the program seeks for G:C pairs in the sequence. Once a G:C pair is found, a putative antisense primer is constructed, including the complementary base of the CC pair and the complementary bases down- stream, until the ma~mum specified length for a primer is reached. If the G + C content of the primer is beyond the specified limits, a base is removed from the 3’-end. This operation is repeated until either an acceptable G + C content is achieved, or the primer becomes shorter than the minimum possible length specified for a primer. In the last case the primer is discarded and the search follows downstream. If the primer is accepted on the basis of its G + C content, then it is checked for inter and intramolecular self-annealing according to the criteria of Rychlich and Rhoads (1989). Finally, if no significant self-annealing is found, the presence of other annealing regions in the sequence is checked. If the primer fits all requirements described, it is included in the list of antisense primers, and the search follows. If the aim is to search for non-overlapping primers (the most common choice), the search continues after the last base included in the primer, if not, it continues in the base downstream, contiguous to the 3’-end of the primer. Once the complete region has been scanned and the list of antisense primers has been constructed, a similar procedure is followed to build the list of sense primers. In this case, the region is scanned from the 5’ to the 3’-end, and similar criteria are applied to the selection of each putative sense primer.

The final step implies the construction of a list of pairs of primers from both, sense and antisense lists of selected primers. For each sense primer, all the antisense primers which fit the following conditions are saved: (I) the distance sense-antisense is compatible with the size limits defined for the amplification product and, (2) no significant annealing between sense and antisense primers is found.

A list of pairs of primers obtained as described correspond to the result provided by the program if working in the first mode. When the program is used in the mode for common primer identification, the user has to decide first which sequence, among those of the target group, will be considered as prototype. For this sequence the lists of sense and antisense primers will be constructed, as described. Then, only the primers which anneal to an unique

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site in each of the sequences of the target group will be selected. After that, the list of pairs of primers is constructed as described above.

Finally, if the program is used in the extended common primer identification mode, it proceeds as in the previous mode until the two lists of sense and antisense primers, common to the sequences of the target group, have been constructed. Then, those primers showing an appreciable annealing to any of the sequences of the non specific group are removed from the corresponding list. In this case, the annealing criteria is based on the percentage of sequence conservation.

A ‘pessimistic’ treatment of base indeterminations is made. This means that base indeterminations will always contribute to reduce the probability of accepting a primer, i.e., a base indetermination will be considered as a mismatch with respect to sequences of the target group whereas it will be considered as a match with respect to sequences of the non-specific group.

Results and Discussion

The process of primer selection in the case of highly variable genomes of RNA viruses is complicated. Application of the program to the selection of pairs of primers specific to conserved regions on the 3D gene of FMDV (target group) when compared with those corresponding to other picornaviruses (non- specific group) rendered the pairs of primers shown in Fig. 1. The predicted primers were compared with those designed following a different approach and that were shown to specifically amplify FMDV 3D gene (Rodriguez et al., 1992). Since the program was used with the option non-overlapping (the most convenient choice for a initial scanning), the pair of primers used by Rodriguez et al. (1992) did not appear among those shown in the list. This is because other primers, overlapping the same sequence, were found before during the search process. A new, more detailed search, with the option non-overlapping turned off, found these primers (Fig. 2) and a considerable number of other ones (not shown).

PCR will play a key role in the near future in the diagnosis field. A critical step for the proper use of this technique is the correct selection of specific primers. As more sequences are available, the need for a computer-based approach to the search of specific oligonucleotides common to groups of sequences becomes evident, specially for highly variable genomes for which design of primer by visual inspection is extremely complex. Thus, a growing demand of specialized software to cope with this kind of tasks will occur along the next years.

The algorithm presented here has been designed to deal with the sequences as a polymerase would ‘look’ them. This is achieved through a sequential monitoring of the sequences. Because of that, no previous sequence alignment is needed. In the design of the algorithm, criteria for suitable PCR amplification (Lintz et al., 1990; Lowe et al., 1990; Rychlik and Rhoads,

162

Date: 19-6-1992 Time: 13:1:19 File: 3d-5end.oli -__--------_----------------------

PCS diagnosis. Version 1.0 Last rev. 28-May-92 _______~~_______~________~~_____~~_______~_________~__~~~__~___~~~________

SEARCH CONDITIONS: only non-overlapping oligos Checked for homologies in other regions CC content of the oli90 between 45.0% and 75.0% Oligo size between 18 and 22 nucleotides Size of the amplified fragment between 550 and 10 nucleotides Sense primer searched between sites 1 and 532 Antisense primer searched between sites 18 and 550 Tm calculated as in Sugys et al. (1981)

Antisense 105 sense 14

Antisewe 160 sense 116 sen*e 85

Antisense 189 sense 85 sense 14

Antisense 297 sense 14

Antisense 333 sells* 306 sense 136 Sense 116

Antisense 366 Sense 281 sen5e 198 Sense 85

Antisense 468 Sense 402 Senm 366 Sense 306 Sense 281 Sense 198

Antlsense 502 Sense 468 Sense 306 Sense 281 Sense 136 Sense 116 sense 85

3'-CGGACGGCGGAACAGATTGT-5' II,, = 64.0C 5'-ATACCAGAGATGTGGAAGAGCG-3' Tm = 66.OC Size = lllbp

J'-CTTCAGTMGAGGTCCGT-5' Tm = 58.OC 5'-TGTCTAACAAGGACCCACG-3' Rn = 58.OC Size = 64bp 5'-GTGTTCAATCCTGAGTTCGGGC-3' Tm = 68.OC Size = 95bp

3'-GTGTTXTACAGACGCC~-5' Tm = 68.OC 5'-GTGTTCAATCCTGAGTTCGGGC-3' Tm = 68.W size = 126bp 5'-ATACW-3' Tm = 66.OC Size - 197bp

3’-GCTCCGTTAGTTCCCGCAAC-5’ TX, = 64.OC 5'-ATACCA6AGATGTGGAAGAGCG-3' Tm = 66.OC Size = 303bp

3'-CCTCGGTCTGTGGCGTGGAC-5' Tm = 68.OC 5'-CAAGGGCGTTGACGGACTCG-3' Tm = 66.OC Size = 47bp 5'-CTGAACGAAGGTGTTGTCCTCG-3' Ihl = 68.OC Size = 217bp 5'-TGTCTAACAAGGACCCACG-3' RR = 5B.OC Size = 237hp

3'-GGAGGTTCCCTTTGCGGCG-5' T,r, = 64.OC 5'-CCCCACTGAGCATTTACGAGGC-3' Tm = 7O.OC Size = 104bp 5'-GTCTGCGGAGGACMAGCG-3' Tm = 62.OC size = 187bu 5'-GTGTTCMTCCTGAGTTCGGGC-3' Tm = 68.OC Size = 3bObp

3’-CMRCGMCGGTCPGGAAGGAC-5’ Tm = 68.OC 5'-CGAGAACGGCACGGTCGGAC-3' Tin = 68.OC Size = 88bp 5'-CCTCCAAGGGAMCGCCGC-3' Tm = 64.OC Size - 124bp J’-CAAGGGCGTTGACGGACTCG-3’ Tm = 66-W Size = 184bo 5’-CCCCACTGAGCATTTACGAGGC-3’ Tm = 7O.OC Size = 2Obbp 5*-GT-GGAGGACAAAGCG-3' Tm = 62.OC Size = 292bp

3'-GCGGGCTACCTCTTTCAT-5' TI" = 56.OC 5'-GTTTGCTTGCCAGACCTTCCTG-3' 'II" = 68.OC Size * 52bp S'XAAGGGCGTTGACGGACTCG-3' Tm = 66.OC Size = 214bp 5'-CCCCACTGAGCATTTACGAGGC-3v Tm = 7D.OC size = 239bp f'-CTGAACGAAGGTGTTGTCCTCG-3' Tm = 6S.OC Size = 384bo 5'-TGTCTAACAAGGACCCACG-3' Tm = 58.OC Size = 404bp 5'-GTGTTCAATCCTGAGTTCGGGC-3' Tm = 68.OC Size = 435bp

Antisense 525 3'-GCCGTTCTGAGCGTMCAGC-5' Tm = 64L.OC sense 198 5'-GTCTGCGGAGGACA-3' Tat = 62.OC Size - 347bp Sense 85 5'-GTGTTCAATCCTGAGFWXGC-3' Ihi = 68.OC Size = 46Dbp sense 14 5'-ATAC--3' 'I'm - 66.OC Size = 532bp

_________________________________________________________"________________

26 pairs of oligos found.

Fig. I. Output obtained, under the search conditions shown in the head. corresponding to the 500 bases in the S-end of the 3D (polymerase) gene of FMDV. The pairs of primers selected to produce specific PCR amplification of FMDV are listed. The sequences included in the target group were: FMDVOIK, FMDVAIZ, FMDVAlO, FMDVClObb and FMDVC-5%. The non-specific group was composed of the 3D sequences of: Coxsackie viruses types Bl, B3 and B4, swine vesicular disease virus, human rhinoviruses types 2, 14 and 89, bovine enterovirus, Enterovirus 70, polio virus types 1, 2 and 3, encephalo-myocarditis virus and Theyler’s virus. All these sequences were obtained from the EMBL sequence database. Each antisense primer is listed together with all the suitable sense primers. Numbering corresponds to that of the prototype sequence, and refers to the 3’-base of antisense primers and the S-base of each sense primers. Also the size of the amplified fragment as well as the predicted melting temperature (7’,,,), calculated as in Sommer and Tautz (1989), are provided. Polarity of sense primers correspond to that of the prototype sequence whereas antisense primers are given in the complementary polarity. Underlined are the fragments which overlap with the primers used in Rodriguez et al. (1992) for the specific amplification of 3D gene.

1990; Sommer and Tautz, 1989) have been combined with criteria to maximize the likelihood of the primers to anneal with all the sequences to be detected (target group) and minimize the likelihood of anneal with the sequences of the

163

1.m ~alr 3~-1 I+) - 30-2 (-1

AntlSenSe 204 3’-CCTCCTGTTTCGCGACAAGGCG-5’ Tm = 72.OC

Sense 18 5’-CAGAGATGTGGAAGAGCGCGTC-3’ m = 7O.Oc Size = 208bp

2.- Pair 3D-1 I+) - 3D-3 (-1

3’-GCACGGCCGTTCTGAGCGTAAC-5’ Tm = 72.OC

5’-CAGAGATGTGGAAGAGCGCGTC-3’ Tut = 7O.OC Size = 524bp

Fig. 2. Primers 3D-1, 3D-2 and 30-3 used by Rodriguez et al. (1992) to s~c~~cai~y amplify FMDV 3D gene. The primers were found by monitoring the regions in which they were located with the non- overlapping option turned off. In addition to these primers, many other overlapping primers were found

(not shown).

non-specific group. Due to the procedure followed for the construction of the list of pairs of

primers, it might be argued that combinations of primers in which only one of them showed specific priming could be admissible to obtain specific amplification of the target sequences. Nevertheless, the sequences of the non- specific group will frequently be those for which the user suspected the possibility of a false positive. Then, the use of a primer which is known to anneal in any of the non-specific sequences constitutes a potential risk for the specificity of the assay. This is specially true since only fragments of sequences, and no entire genomes, are often used as data in the program. Consequently it is not possible to have the complete guarantee that a region complementary to the primer will not exist outside of the scanned area.

The other limiting rule is the ‘pessimistic’ treatment given to base indeterminations, which can be avoided if the user, by means of his/her own criteria, solves the base ambiguities. In this case, the indeterminations have to be solved directly on the sequence files before these are read by the program. This is part of the philosophy of the program, and it has been designed in this way to minimize the selection of improper primers due to the misinte~retation of sequence ambiguities.

We have improved the speed of the program with the aid of Turbo Profiler (Borland International), a specialized software which helps to find bottlenecks in the code of the program and allows the development of faster programs. On the other hand, we paid special attention to the development of a friendly user interface. This has been made with the aid of the Turbo Vision library (Borland International) which allows the construction of interactive environments based on pull-down menus which constitutes a non-graphical alternative to the Windows Microsoft environment (at present, there is a version of the program in development which will run under Windows). This environment makes the use of the program more intuitive and comfortable, even for users who are not familiar with computers.

164

Acknowledgements

We wish to thank E. Martinez-Salas for valuable comments. This work is supported by grant 9022 from INIA.

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