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MuPlex: Multi-objective multiplex PCR assay design

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Abstract

We have developed a web-enabled system called MuPlex that aids researchers in the design of multiplex PCR assays. Multiplex PCR is a key technology for an endless list of applications, including detecting infectious microorganisms, whole-genome sequencing and closure, forensic analysis and for enabling flexible yet low-cost genotyping. However, the design of a multiplex PCR assays is computationally challenging because it involves tradeoffs among competing objectives, and extensive computational analysis is required in order to screen out primer-pair cross interactions. With MuPlex, users specify a set of DNA sequences along with primer selection criteria, interaction parameters and the target multiplexing level. MuPlex designs a set of multiplex PCR assays designed to cover as many of the input sequences as possible. MuPlex provides multiple solution alternatives that reveal tradeoffs among competing objectives. MuPlex is uniquely designed for large-scale multiplex PCR assay design in an automated high-throughput environment, where high coverage of potentially thousands of single nucleotide polymorphisms is required. The server is available at http://genomics14.bu.edu:8080/MuPlex/MuPlex.html.
MuPlex: multi-objective multiplex PCR assay design
John Rachlin
1,
*, Chunming Ding
2
, Charles Cantor
1,3,4,6
and Simon Kasif
1,3,5
1
Bioinformatics Program, Boston University, Boston, MA 02215, USA,
2
Centre for Emerging Infectious Diseases,
The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong Special
Administrative Region, China,
3
Department of Biomedical Engineering,
4
Center for Advanced Biotechnology,
5
Center for Advanced Genomic Technologies, Boston University, Boston, MA 02215, USA and
6
SEQUENOM,
Inc., San Diego, CA 92121-1331, USA
Received February 14, 2005; Revised and Accepted March 8, 2005
ABSTRACT
We have developed a web-enabled system called
MuPlex thataidsresearchersinthedesignofmultiplex
PCR assays. Multiplex PCR is a key technology for an
endless list of applications, including detecting infec-
tious microorganisms, whole-genome sequencing
and closure, forensic analysis and for enabling flex-
ible yet low-cost genotyping. However, the design of
a multiplex PCR assays is computationally challeng-
ing because it involves tradeoffs among competing
objectives, and extensive computational analysis is
required in order to screen out primer-pair cross
interactions. With MuPlex, users specify a set of
DNA sequences along with primer selection criteria,
interaction parameters and the target multiplexing
level. MuPlex designs a set of multiplex PCR assays
designed to cover as many of the input sequen-
ces as possible. MuPlex provides multiple solution
alternatives that reveal tradeoffs among competing
objectives. MuPlex is uniquely designed for large-
scale multiplex PCR assay design in an automated
high-throughput environment, where high coverage
of potentially thousands of single nucleotide poly-
morphisms is required. The server is available at
http://genomics14.bu.edu:8080/MuPlex/MuPlex.html.
INTRODUCTION
MuPlex (http://genomics14.bu.edu:8080/MuPlex/MuPlex.html)
is a web-enabled system for designing multiplex PCR assays.
A multiplex PCR solution specifies a forward and reverse primer
for each single nucleotide polymorphism (SNP) and assigns each
primer pair to one of a finite set of tubes. In partitioning SNP
primers into individual tubes, care must be taken to ensure that
all primers within a tube are mutually compatible, i.e. that they
do not form primer-dimers through cross-hybridization, which
would otherwise reduce target product yield. The multiplex
PCR problem is equivalent to partitioning a graph G(V,E)
into a set of disjoint cliques, where nodes represent SNPs,
edges connect two SNPs whose associated primers are tube-
compatible and resulting cliques constitute valid multiplex
PCR tubes. The problem of partitioning a graph into k<K
disjoint cliques is NP-complete (1). The MuPlex system is
unique in that it provides multiple design alternatives that
reveal inherent tradeoffs with respect to multiple competing
objectives, such as average tube size, tube size uniformity
and overall SNP coverage.
Multiplex PCR is a core enabling technology for high-
throughput SNP genotyping, serving as a foundation for
applications in forensic analysis, including human identifica-
tion and paternity testing (2), the diagnosis of infectious
diseases (3,4), whole-genome sequencing (5), and pharmaco-
genomic studies aimed at understanding the connection
between individual genetic traits, drug response and disease
susceptibility (6).
For example, in the hME assay (7), genomic sequences
containing the SNPs of interest are first amplified by PCR.
After shrimp alkaline phosphatase digestion of excess dNTPs,
a primer extension reaction is carried out to interrogate the
SNPs. The primer extension products (often oligonucleotides
18 to 25 bases long) are then detected by matrix-assisted
laser desorption ionization time-of-flight (MALDI-TOF) mass
spectrometry. Given the large molecular weight window
(4500–9000 Da) and the high resolution of the mass spectro-
metry, 20 or more SNPs can be easily and simultaneously
genotyped. Thus, the throughput-limiting step is often the
PCR plex level. In a 384-well format with 20-plex PCR,
the per-SNP cost can be reduced to just a few cents while a
single MALDI-TOF mass spectrometry can be used to geno-
type 76 800 SNPs by a single operator in 1 day.
MuPlex features
Given a set of DNA sequences and a SNP location at each, the
system aims at designing (i) a set of pair forward and reverse
*To whom correspondence should be addressed. Tel: +1 617 921 9669; Fax: +1 617 353 4814; Email: rachlin@bu.edu
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W544–W547 Nucleic Acids Research, 2005, Vol. 33, Web Server issue
doi:10.1093/nar/gki377
primers for each sequence; (ii) a placement of these primers
into maximal size tubes such that the coverage (number of
sequences) included in the PCR assay is maximized. Figure 1
presents the MuPlex home page where specific problems may
be submitted. (No user registration or fee is required.) The
user provides a set of SNPs and associated flanking sequences
in the standard FASTA format. These sequences may be
entered manually or uploaded from a file. To improve primer
specificity, users may instruct the MuPlex server to filter res-
ulting primer candidates by aligning them against the human
genome using BLAT (8). In addition to the SNP sequences, the
user specifies primer selection criteria, including length, GC
content, positional constraints, and melting temperature T
m
constraints for individual primer oligos as well as interaction
parameters (maximum local alignment score, 3’ tail DG), and
a maximum T
m
range for all primer pairs within a single
multiplex assay.
MuPlex then solves the dual problem of selecting primer
pairs for amplifying the flanking sequence of each SNP and
partitions these primer pairs into multiplex compatible sets
each corresponding to a single multiplex PCR tube reaction.
As noted above, MuPlex generates multiple solutions altern-
ative each corresponding to a set of multiplex PCR tubes.
Each solution is evaluated with respect to the following
objectives:
(i) Total number of tubes required.
(ii) Minimum, average and maximum tube size (multiplexing
level).
(iii) Number of unique tube sizes.
(iv) Total SNP coverage measured both in terms of the
percentage of SNPs (associated primer pairs) assigned
to maximum-sized tubes, as well as the percentage of
SNPs assigned to tubes of any size.
For example, some solutions may achieve higher overall
multiplexing levels but at the expense of lower coverage,
i.e. by excluding some SNPs from the solution. In addition,
MuPlex tries to minimize the number of unique tube sizes in
order to facilitate automation in a high-throughput genomics
environment. Resulting solutions are emailed to the user. The
email contains a solution summary allowing quick comparison
of each alternative, and details for each solution including the
selected primers, their individual properties and assigned tube.
MuPlex employs a number of heuristic algorithms and
allows new algorithms to be added over time. Solution time
depends on the number of solution alternatives requested, the
number of SNPs and the target multiplexing level. For typical
problems involving <100 SNPs, multiple solutions can often
be generated in 5–10 min.
ARCHITECTURE
MuPlex is written entirely in Java ( j2sdk1.4.2_05) and
employs the Apache Jakarta Tomcat server (http://jakarta.
apache.org/tomcat) connected to a backend mySQL database
(http://www.mysql.com). Individual solvers operate asyn-
chronously on a network of workstations running a customized
distribution of the Linux operating system based on Fedora
Core 3 (http://fedora.redhat.com). These solvers monitor the
MuPlex database for the arrival of new problems. New prob-
lems are assigned to the first available solver. As depicted
Figure 1. The MuPlex homepage. Users specify primer selection criteria and provide a collection of SNPs in the FASTA format. The system emails to the user one or
more solution alternatives revealing key design tradeoffs.
Nucleic Acids Research, 2005, Vol. 33, Web Server issue W545
in Figure 2, the solver maintains a population of candidate
solutions. Each solution is evaluated with respect to a set
of registered objectives. Agents encapsulating specific algo-
rithms either create new solutions from scratch, improve or
modify existing solutions, or remove unpromising solutions
from further consideration. For example, one ‘creator’ algo-
rithm is based on a best-fit methodology that iteratively assigns
SNPs to the largest open compatible tube. When the tube size
reaches the target multiplexing level specified by the user, it is
closed, and no further additions or modifications to that tube
are made. Each unassigned SNP is assigned a new primer pair
candidate and the process repeats. One improver algorithm
eliminates partial tubes in order to reduce the number of
unique tube sizes but while incurring reduced coverage,
while another attempts at reformulating partial tubes in an
effort to identify additional full tubes. Efficiency is enhanced
during the optimization process by periodically culling
unpromising solutions from the population of candidates.
The architecture is scaleable in the sense that new algorithms
can be readily plugged-in over time, and it is robust in that
it does not depend on a single algorithm to generate every
viable alternative, and because system load is balanced across
a distributed collection of solvers.
Within a given solution, there is no guarantee that a SNP
will be assigned, and the results depend on the random order in
which SNPs and primers are processed. Resulting coverage
critically depends on the number of SNPs and the
target level of multiplexing desired (J. Rachlin, C. M. Ding,
C. Cantor and S. Kasif, manuscript submitted).
CONCLUSIONS AND FUTURE WORK
The MuPlex server allows scientists to design Multiplex PCR
assays while explicitly considering intrinsic design tradeoffs.
The consideration of competing alternatives has played a key
role in the development of optimization and decision-support
technologies in complex domains such as manufacturing and
transportation logistics (9,10). Here, we have demonstrated the
viability of such approaches to the optimization of multiplex
PCR assays. Future efforts will focus on the development of
new algorithms and on allowing users to impose dynamic
feedback constraints in an effort to further guide the design
optimization process towards solutions that more closely meet
the scientist’s particular design objectives. We also plan to
develop a distributed version that will run on our 128-
processor Linux cluster.
ACKNOWLEDGEMENTS
The authors thank Noga Alon and Richard Beigel for many
profound insights and suggestions. This work is supported
in part by NSF grants DBI-0239435 and ITR-048715 and
NHGRI grant #1R33HG002850-01A1. Funding to pay the
Open Access publication charges for this article was pro-
vided by NHGRI.
Conflict of interest statement. None declared.
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Nucleic Acids Research, 2005, Vol. 33, Web Server issue W547
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... According to the primer constraints for primer evaluation, the existing tools can be divided into single-objective [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] and multiobjective [26][27][28][29] approaches to design feasible and specific primer pairs for particular experimental situations. The single-objective evolutionary algorithms [15][16][17][18][19][20][21] and multiobjective evolutionary algorithms [26][27][28][29] have demonstrated fast computation for primer design. However, summing the fitness functions means that primer constraints cannot be considered individually (concerning the difference between the value of a primer constraint and a user-specified parameter) [27,29]. ...
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Pandemics have a profound impact on our world, causing loss of life, affecting our culture and historically shaping our genetics. The response to a pandemic requires both resilience and imagination. It has been clearly documented that obtaining an accurate estimate and trends of the actual infection rate and mortality risk are very important for policy makers and medical professionals. One cannot estimate mortality rates without an accurate assessment of the number of infected individuals in the population. This need is also aligned with identifying the infected individuals so they can be properly treated, monitored and tracked. However, accurate estimation of the infection rate, locally, geographically and nationally is important independently. These infection rate estimates can guide policy makers at both state, national or world level to achieve a better management of risk to society. The decisions facing policy makers are very different during early stages of an emerging epidemic where the infection rate is low, middle stages where the rate is rapidly climbing, and later stages where the epidemic curve has flattened to a low and relatively sustainable rate. In this paper we provide relatively efficient pooling methods to both estimate infection rates and identify infected individuals for populations with low infection rates. These estimates may provide significant cost reductions for testing in rural communities, third world countries and other situations where the cost of testing is expensive or testing is not widely available. As we prepare for the second wave of the pandemic this line of work may provide new solutions for both the biomedical community and policy makers at all levels.
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The effectiveness of an agent architecture is measured by its successful application to real problems. In this paper, we describe an agent architecture, A-Teams, that we have successfully used to develop real-world optimization and decision support applications. In an A-Team, an asynchronous team of agents shares a population of solutions and evolves an optimized set of solutions. Each agent embodies its own algorithm for creating, improving or eliminating a solution. Through sharing of the population of solutions, cooperative behavior between agents emerges and tends to result in better solutions than any one agent could produce. Since agents in an A-Team are autonomous and asynchronous, the architecture is both scalable and robust. In order to make the architecture easier to use and more widely available, we have developed an A-Team class library that provides a foundation for creating A-Team based decision-support systems.
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Silicon chips with immobilized target DNAs were used for accurate genotyping by mass spectrometry. Genomic DNAs were amplified with PCR, and the amplified products were covalently attached to chip wells via N-succinimidyl (4-iodoacetyl)aminobenzoate (SIAB) chemistry. Primer annealing, extension, and termination were performed on a 1-microl scale directly in the chip wells in parallel. Diagnostic products thus generated were detected in situ by using matrix-assisted laser desorption ionization mass spectrometry. This miniaturized method has the potential for accurate, high-throughput, low-cost identification of genetic variations.
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PCR has revolutionized the field of infectious disease diagnosis. To overcome the inherent disadvantage of cost and to improve the diagnostic capacity of the test, multiplex PCR, a variant of the test in which more than one target sequence is amplified using more than one pair of primers, has been developed. Multiplex PCRs to detect viral, bacterial, and/or other infectious agents in one reaction tube have been described. Early studies highlighted the obstacles that can jeopardize the production of sensitive and specific multiplex assays, but more recent studies have provided systematic protocols and technical improvements for simple test design. The most useful of these are the empirical choice of oligonucleotide primers and the use of hot start-based PCR methodology. These advances along with others to enhance sensitivity and specificity and to facilitate automation have resulted in the appearance of numerous publications regarding the application of multiplex PCR in the diagnosis of infectious agents, especially those which target viral nucleic acids. This article reviews the principles, optimization, and application of multiplex PCR for the detection of viruses of clinical and epidemiological importance.
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PCR has revolutionized the field of infectious disease diagnosis. To overcome the inherent disadvantage of cost and to improve the diagnostic capacity of the test, multiplex PCR, a variant of the test in which more than one target sequence is amplified using more than one pair of primers, has been developed. Multiplex PCRs to detect viral, bacterial, and/or other infectious agents in one reaction tube have been described. Early studies highlighted the obstacles that can jeopardize the production of sensitive and specific multiplex assays, but more recent studies have provided systematic protocols and technical improvements for simple test design. The most useful of these are the empirical choice of oligonucleotide primers and the use of hot start-based PCR methodology. These advances along with others to enhance sensitivity and specificity and to facilitate automation have resulted in the appearance of numerous publications regarding the application of multiplex PCR in the diagnosis of infectious agents, especially those which target viral nucleic acids. This article reviews the principles, optimization, and application of multiplex PCR for the detection of viruses of clinical and epidemiological importance.
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Pharmacogenomics is an emerging scientific discipline examining the genetic basis for individual variations in response to therapeutics. Genetic polymorphisms are a major cause of individual differences in drug response. Metabolic phenotyping can be accomplished by administering a probe drug or substrate and measuring the metabolites and clinical outcomes. However, this approach tends to be labor intensive and requires repeated sample collection from the individual being tested. Alternatively, genotyping allows determination of individual DNA sequence differences for a particular trait. Commonly used genotyping methods include gel electrophoresis-based techniques, such as polymerase chain reaction (PCR) coupled with restriction fragment length polymorphism analysis, multiplex PCR, and allele-specific amplification. Fluorescent dye-based high-throughput genotyping procedures are increasing in popularity, including oligonucleotide ligation assay, direct heterozygote sequencing, and TaqMan (Perkin Elmer, Foster City, CA) allelic discrimination. High-density chip array and mass spectrometry technologies are the newest advances in the genotyping field, but their wide application is yet to be developed. Novel mutations/polymorphisms also can be identified by conformation-based mutation screening and direct high-throughput heterozygote sequencing. Rapid and accurate detection of genetic polymorphisms has great potential for application to drug development, animal toxicity studies, improvement of human clinical trials, and postmarket monitoring surveillance for drug efficacy and toxicity.
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Analyzing vertebrate genomes requires rapid mRNA/DNA and cross-species protein alignments. A new tool, BLAT, is more accurate and 500 times faster than popular existing tools for mRNA/DNA alignments and 50 times faster for protein alignments at sensitivity settings typically used when comparing vertebrate sequences. BLAT's speed stems from an index of all nonoverlapping K-mers in the genome. This index fits inside the RAM of inexpensive computers, and need only be computed once for each genome assembly. BLAT has several major stages. It uses the index to find regions in the genome likely to be homologous to the query sequence. It performs an alignment between homologous regions. It stitches together these aligned regions (often exons) into larger alignments (typically genes). Finally, BLAT revisits small internal exons possibly missed at the first stage and adjusts large gap boundaries that have canonical splice sites where feasible. This paper describes how BLAT was optimized. Effects on speed and sensitivity are explored for various K-mer sizes, mismatch schemes, and number of required index matches. BLAT is compared with other alignment programs on various test sets and then used in several genome-wide applications. http://genome.ucsc.edu hosts a web-based BLAT server for the human genome.