Random mutagenesis-PCR to introduce ... - Wiley Online Library

210

NICKERSON ET AL.

HUMAN MUTATION 17:210219 (2001)

METHODS

Random Mutagenesis-PCR to Introduce Alterations Into Defined DNA Sequences for Validation of SNP and Mutation Detection Methods Michael L. Nickerson,1* Michelle B. Warren,2 Berton Zbar,1 and Laura S. Schmidt2 1

Laboratory of Immunobiology, National Cancer Institute-Frederick Cancer Research and Development Center, Frederick, Maryland 2 Intramural Research Support Program, SAIC Frederick, National Cancer Institute-Frederick Cancer Research and Development Center, Frederick, Maryland Communicated by Graham Taylor

Sensitive and high throughput techniques are required for the detection of DNA sequence variants such as single nucleotide polymorphisms (SNPs) and mutations. One problem, common to all methods of SNP and mutation detection, is that experimental conditions required for detection of DNA sequence variants depend on the specific DNA sequence to be analyzed. Although algorithms and other calculations have been developed to predict the experimental conditions required to detect DNA sequence variation in a specific DNA sequence, these algorithms do not always provide reliable information and experimental conditions for SNP and mutation detection must be devised empirically. Determination of experimental conditions for detection of DNA sequence variation is difficult when samples containing only wild type sequence are available. When patient derived positive controls are used, increasingly there are valid concerns about commercial ownership and patient privacy. This report presents a rapid and efficient method, employing random mutagenesis-PCR (RM-PCR) using low fidelity DNA polymerase, to randomly introduce single and multiple base substitutions and deletions into DNA sequences of interest. Clones with sequence changes were used to validate denaturing HPLC (DHPLC) algorithm predictions, optimize conditions for mutation detection in exon 15 of the tyrosine kinase domain of the MET proto-oncogene, and to confirm the association between specific DNA sequence changes and unique DHPLC chromatographic profiles (signatures). Finally, DNA from 33 papillary renal carcinoma (PRC) patients was screened for mutations in exon 15 of MET using “validated” DHPLC conditions as a proof of principle application of RM-PCR. Use of RM-PCR for DHPLC and other SNP/mutation detection methods is discussed along with challenges associated with detecting sequence alterations in mixed tumor/normal tissue, pooled samples, and from regions of the genome that have been amplified during tumorigenesis or duplicated during evolution. Hum Mutat 17:210–219, 2001. Published 2001 Wiley-Liss, Inc.† KEY WORDS:

mutation detection; single nucleotide polymorphism; SNP; DHPLC; MET proto-oncogene; random mutagenesis; PCR; signature; sequencing

DATABASES:

MET – OMIM:164860; GDB:120178; GenBank: AC002080; HGMD:MET; http://web.ncifcrf.gov/ research/kidney/ (NCI Kidney Cancer Page); http://insertion.stanford.edu/melt.html (Stanford DHPLC Melt Program) Received 3 October 2000; accepted revised manuscript 15 December 2000. *Correspondence to: Michael L. Nickerson, NCI-FCRDC, Bldg. 560, Rm. 12-69. Frederick, MD 21702. E-mail: [email protected] PUBLISHED 2001 WILEY-LISS, INC.

Contract grant sponsor: National Cancer Institute, National Institutes of Health; Contract grant number: NO1-CO-56000. † This article is a US Government work and, as such, is in the public domain in the United States of America.

RM-PCR FOR SNP AND MUTATION DETECTION

INTRODUCTION Studies of sequence variation are an important next step in genome research now that the human genome has been partially sequenced and a finished version is forthcoming. Analysis of variability in DNA, mutations, and SNPs may provide insight into gene biology [Brookes, 1999; Lee et al., 1999; Nickerson et al., 1998], multigenic traits and pharmacogenomics [Cargill et al., 1999; Syvånen et al., 1999], epidemiology [Collins et al., 1999], population genetics [Xiong and Jin, 1999], and comparative genomics [O’Brien et al., 1999]. Accurate detection and characterization of SNPs and mutations requires sensitive, highthroughput, and flexible techniques if data from large-scale efforts [Brown, 1999; Collins et al., 1998] are to be utilized effectively to establish correlations between specific DNA sequence variants and behavior of biological systems. A number of methods have been described and/or compared [Landegren et al., 1998; Cotton, 1997], including direct sequencing and sequence analysis [Buetow et al., 1999; Nickerson et al., 1997], primer extension [www.orchid.com], single stranded conformation polymorphism (SSCP) [Larsen et al., 1999; Förnzler et al., 1998], and chip arrays [Gilles et al., 1999]. Recently, a mutation detection method that can both detect and characterize sequence variation has been developed [O’Donovan et al., 1998; Oefner and Underhill, 1998]. Denaturing High-Performance Liquid Chromatography (DHPLC) detects substitutions and small insertions or deletions by separation of heteroduplexes composed of wild type and mutant strands from homoduplexes using ion-paired, reverse phase chromatography [Liu et al., 1998; Kuklin et al., 1997/98]. Heteroduplexes formed between wild type and mutant PCR-amplified DNA strands from a heterozygous individual will have different retention times from perfectly matched homoduplexes under conditions of partial thermal denaturation. To date, DHPLC has been successfully applied to a number of biological studies requiring high-throughput mutation detection [Nickerson et al., 2000; Giordano et al., 1999; Gross et al., 1999; Wagner et al., 1999]

211

and SNP genotyping and/or discovery [Austin et al., 2000; Oefner, 2000; Schriml et al., 2000; Sévenet et al., 1999]. A current shortcoming in the literature regarding methods, such as DHPLC, SSCP, denaturing gradient gel electrophoresis (DGGE) [Miller et al., 1999], enzymatic mutation detection [Oldenburg and Siebert, 2000; Del Tito et al., 1998], molecular beacons [Tyagi and Kramer, 1996], and others, relates to validation and optimization of methods for detection of SNPs and mutations in new DNA fragments. Primarily, this is due to lack of a quick and efficient method to introduce sequence variation into a DNA sequence of interest. Positive controls consisting of nucleotide substitutions, insertions, or deletions at single or multiple sites in a stretch of DNA would allow experimental examination of methods designed for mutation detection within that region, such as DHPLC gradients and temperatures and resolution of bands in SSCP gel electrophoresis. Our interest in the study of families with inherited papillary renal carcinoma [Schmidt et al., 1999a] has led us to examine the MET protooncogene (MET, MIM# 164860) for mutations and SNPs in patient DNA samples. Previously, a number of disease-associated, activating mutations were found in exons 16–19 of the tyrosine kinase domain of this transmembrane receptor using SSCP, sequencing, and DHPLC [Nickerson et al., 2000; Schmidt et al., 1999b; Schmidt et al., 1998]. Exon 15 of MET is located in the tyrosine kinase domain of the receptor and lies in a strategic position closest to the juxta-membrane domain [Schmidt et al., 1999b; Duh et al., 1997]. It also resides very close to glycine rich ATP binding loop mutations, which were shown to play a role in disease [Olivero et al., 1999; Schmidt et al., 1999b]. To date, the PRCassociated mutations that have been found in exons 16–19 account for most hereditary PRC type I cases but only approximately 13% of sporadic PRC cases. In an effort to achieve highthroughput screening of sporadic renal tumor samples and blood DNA samples from members of families with inherited disease and to discover new mutations associated with PRC in additional

212

NICKERSON ET AL.

MET exons, we have utilized DHPLC for mutation detection. Additionally, we have improved DHPLC mutation detection by using positive controls that contain sequence changes randomly introduced into the DNA fragment. This will insure comprehensive identification of mutations and polymorphisms in new DNA segments. Presented below is a straightforward procedure, which we have termed random mutagenesis-PCR (RM-PCR), to introduce single and multiple base changes, and single base deletions in DNA that is useful for validation and optimization of methods to detect mutations and SNPs. This random mutagenesis approach is rapid, less costly (synthesis of primers to introduce desired base changes is avoided), and produces a large number of mutations compared to site-directed mutagenesis systems. Synthesis of RM-PCR cloned inserts takes advantage of relatively high mismatch incorporation rates of low and moderate fidelity polymerases to introduce sequence changes into a DNA strand during PCR amplification. After rapid (5 min) topoisomerase-mediated cloning [Shuman, 1994] to separate individual amplicons from the population of molecules in the PCR reaction, followed by sequencing, sequence changes in individual fragments were identified. RM-PCR clones were used to validate DHPLC mutation and SNP detection parameters and to confirm that each sequence change is associated with a unique DHPLC signature. Finally, DNA samples from 33 PRC patients were screened for mutations in MET tyrosine kinase domain exon 15 using these “validated” conditions. METHODS Random Mutagenesis-PCR, Cloning, and Sequencing

Exon 15 of the MET proto-oncogene was amplified from three Centre d’Etude Polymorphisme Humain (CEPH) DNA samples using AmpliTaq® DNA polymerase (Perkin-Elmer, Norwalk, CT) according to the manufacturer’s recommendations. Thermal cycling in a PTC100™ (MJ Research, Waltham, MA) consisted of: 95°C for 4 min; then 35 cycles of 95°C for 30 sec, 60°C for 30 sec, and 72°C for 55 sec, and a

final 72°C extension for 10 min. Intronic PCR primer sequences are 5′ CCA TTA AAT GAG GTT TTA CTG TTG T (sense strand) and 5′ GCA AAG GCC AAA GAT AAA ATG CTT AC (antisense strand). Cloning of PCR products (352 bp wild type) utilized topoisomeraseactivated vector [Shuman, 1994] and One Shot® TOP 10 cells from a TOPO TA® Kit (Invitrogen, Carlsbad, CA). Colonies were re-streaked on ampicillin selective LB plates to isolate individual clones. Amplified inserts were prepared either by colony PCR or by PCR from miniprep DNA prepared from liquid culture using a Wizard ® Miniprep kit (Promega, Madison, WI). For colony PCR, cells were transferred from a colony into a PCR tube with a toothpick, and amplified with Pfu-Turbo™ polymerase (Stratagene, La Jolla, CA) according to the manufacturer’s recommendations with one exception: the reaction buffer concentration was increased from 1x to 1.5x. PCR products were purified using QuickStep™ (Edge BioSystems, Gaithersburg, MD), quantitated in 2% agarose using DNA Quanti-Ladder™ (OriGene, Rockville, MD), and used as template for sequencing with Big Dye™ reagents (PE Applied BioSystems, Foster City, CA). Reactions were cleaned up with Gel Filtration Cartridges (Edge BioSystems, Gaithersburg, MD), dried, and run on a PE-ABI 377 DNA sequencer (Foster City, CA). Clone characterization was accomplished using BLAST [Altschul et al., 1990] to compare the clone sequence to a chromosome 7q31 genomic BAC containing sequence of the MET gene (Genbank Accession # AC002080), using Lasergene (DNAStar, Madison, WI) for sequence alignment and identification of conflicts, and by manually examining chromatogram trace files. MET Exon 15 DHPLC Method Design

The optimal melting temperatures were obtained by analysis of wild type sequence using an annealing algorithm at the Stanford DHPLC web site (http://insertion.stanford.edu/melt. html) [Jones et al., 1999; Oefner and Underhill, 1998]. Additionally, Wavemaker 3.4 (Transgenomic, Omaha, NE) calculated the ratio of Buffers A [0.1 M Triethylammonium acetate


(TEAA), pH7.0, 0.025% acetonitrile (v/v)] and B [0.1 M TEAA, 25 % acetonitrile (v/v), pH 7.0] for an analytical gradient. The method (Table 1) was designed to include an initial analytical gradient (composed of Buffer A and Buffer B), a 75% acetonitrile wash to remove contaminants from the column, a rejuvenating gradient to clear residual acetonitrile, and a final column equilibration [Nickerson et al., 2000]. Signatures Produced by RM-PCR Clones

Pfu-Turbo™ (Stratagene) was used to amplify PCR products from colonies or miniprep DNA. Equal amounts of gel quantitated mutant and wild type alleles were mixed, heteroduplexed, and injected in a WAVE® DNA Fragment Analysis System containing a DNASep® column. Methods utilized cut injections that discarded 1 µl volumes from the front and back of injected aliquots. Each clone was analyzed at temperatures between 52°C and 62°C to determine the optimum temperature for signature visualization. Sporadic PRC Patient DNA Samples and DHPLC Analysis

DNA was extracted from blood [Vogelstein and Gillespie, 1979] and paraffin-embedded tumor blocks [Weirich et al., 1997] obtained through the Urologic Oncology Branch of NIH. As described above, MET exon 15 was amplified, heteroduplexed, and analyzed by DHPLC using conditions presented in Table 1. RESULTS

Our interest focused on analysis of exon 15 of the MET proto-oncogene located in the tyrosine kinase domain of the receptor. As shown TABLE 1.

Time (min) 0.0 0.5 5.0 5.3 5.8 6.9 7.5 10.0 end

213

in Figure 1, 60 clones were characterized after amplification from genomic DNA using low fidelity DNA polymerase, topoisomerase mediated cloning, and transformation. Hundreds of clones were produced from which 60 were randomly picked. After re-streaking on fresh plates to isolate individual clones followed by colony PCR of cloned inserts with a high fidelity polymerase, about half (32) had inserts of the correct size (352 bp) and were sequenced on both strands. Clone mutations are presented in Table 2 and show that one out of three clones (11 clones with sequence changes out of 32 clones with inserts) were useful to test mutation and SNP detection methods, i.e. cloned inserts had base substitutions or deletions. Locations of sequence changes (Fig. 2) were randomly distributed along the entire 5′ to 3′ length of the DNA strand, making the RM-PCR method attractive for synthesis of positive controls used for mutation analysis of new DNA fragments. Randomly-mutagenized clones were used to examine DHPLC parameters, including temperature and analytical gradient, predicted by the Stanford and Wavemaker 3.4 algorithms, respectively. The analytical gradient, D buffer wash, and rejuvenating gradient shown in Table 1 [see also Nickerson et al., 2000] resolved heteroduplexes for 10 out of 11 positive controls examined at temperatures near those predicted for this DNA fragment by the Stanford algorithm, 54°C and 59°C. Experimentally determined temperatures that resolved signatures were between 54°C and 61°C and selected clone signatures are presented in Figure 3. The clones that generated signatures at higher temperatures (60/61°C) all fall in the interior core of the

DHPLC Method for MET Exon 15

% buffer A

% buffer B

% buffer D

Flow rate (ml/min)

50 45 36 0 65 52 50 50

50 55 64 0 35 48 50 50

0 0 0 100 0 0 0 0

0.7 0.7 0.7 0.7 0.9 0.9 0.9 0.9

The DHPLC method for MET exon 15 consisted of a 10-minute run composed of an analytical gradient, column wash, and rejuvenating gradient.

214

NICKERSON ET AL.

Overview of RM-PCR clones. In an analysis of 60 clones, 32 clones had inserts of the correct size as determined by colony PCR. When sequenced, 11 clones contained sequence changes useful for validation of mutation and SNP detection methods.

FIGURE 1.

amplicon (box, Fig. 2) thus differentiating sequence changes in this region from flanking sequences near the 5′ and 3′ amplicon ends. DHPLC resolution of signatures was variable for different cloned inserts, some signatures persisted over a range of temperatures (clone 1: 56-58°C; clone 17: 57–60°C) while others resolved at only a single temperature (clones 5, 8, and 50). Importantly, only two out of six clones whose signatures resolved near the higher temperature (59°C) predicted by the Stanford algorithm were detectable at 59°C (clones 17 and 33, see clone sequence variants presented in Table 2).

TABLE 2.

Clone 1 3 5 8 12 17 21 33 45 48 50 51

Clone Sequence Variants Sequence characterization 16,688C>T WT 16,591T>C 16,613T>C 16,727 ∆A 16,657A>T 16,422A>C 16,690T>C 16,494A>T 16,429T>A 16,437G>A 16,555A>G 16,443 ∆T

16,539C>T 16,483C>T 16,722T>G 16,524T>C 16,446G>T

Thirty-two clones containing inserts of expected size were sequenced and sequence changes were found in eleven clones. Changes consisted of 2 single base deletions, 9 transitions, and 6 transversions.

Unique DHPLC signatures for each clone are presented in Figure 3, confirming the association between DHPLC elution profiles and specific sequence changes [Nickerson et al., 2000; Arnold et al., 1999; Gross et al., 1999]. Signatures were analyzed by shape and peak retention time(s). Characterization by retention time differences or melt profiling [Nickerson et al., 2000] was not needed. As demonstrated here, we extend the association between a specific sequence change and a unique DHPLC signature to one, two, and four nucleotide substitutions, and single base deletions that individually reside at various positions along the length of an amplicon. Two clones, 21 and 45, were found to be heterozygous clones that contained copies of both wild type and mutant alleles as cloned inserts in a single transformed cell line. These are very useful since mixing with wild type amplicon is not required and these clones generate signatures immediately after amplification and heteroduplexing (Fig. 3). Lastly, exon 15 of MET was amplified from 33 DNAs obtained from sporadic PRC patients and analyzed by DHPLC at temperatures critical for mutation detection in this exon. Wild type profiles similar to wild type clone 3 (Fig. 3) were seen in all samples; no shifts of heteroduplexes were observed to indicate the presence of sequence variation.


215

Location of introduced sequence changes. Sequence variants in 11 RM-PCR clones of MET exon 15 are presented by position on genomic BAC sequence 16,349 to 16,746 (Accession #AC002080). MET exon 15 intron/exon boundaries are indicated (arrows) and are located at nucleotides 16,444 to 16,678. Mutations are shown with the sequence change indicated above its location. The dotted line at nucleotide 16,727 indicates that no DHPLC signature was obtained for clone 12. Sequence changes in the amplicon core requiring high temperature (60/61°C) for resolution of a signature are boxed, except for mutation 16,539C>T from clone 17, which possessed two sequence changes and exhibited an optimal signature at 59°C.

FIGURE 2.

DISCUSSION

Signatures of RM-PCR clones and a wild type. Equal quantities of selected clone (clones 5, 8, 33, 48, 50, 51) and wild type DNA (clone 3) were amplified, mixed, heteroduplexed, and screened by DHPLC. Heterozygous clone 45 was amplified, heteroduplexed, and examined by DHPLC without mixing with wild type DNA. Signatures were obtained at the optimum temperatures shown in the upper right of each panel.

FIGURE 3.

Figure 4 presents an overview of the random mutagenesis-PCR method to introduce changes into desired DNA sequences for validation and optimization of mutation and SNP discovery and characterization methods. The lower half of the figure depicts how RM-PCR products were synthesized for exon 15 of the MET proto-oncogene and used for DHPLC mutation detection in sporadic PRC samples. No mutations were found in 33 tumor and blood DNA samples and we are highly confident of these results due to application of RM-PCR for validation of mutation detection parameters. Additional exons of MET and other candidate genes will be examined in the future in hopes of increasing our knowledge of the genetic basis of sporadic PRC. Attractive aspects of the RM-PCR procedure are its simplicity, rapidity, and extensive coverage of a defined sequence with introduced nucleotide changes; a variety of clones are produced with one or more changes per clone, including substitutions and deletions; and some of these (two out of 11) carry both alleles for immediate signature generation without mixing (see below). The quickest route to obtain positive controls is amplification of cloned inserts with high fidelity polymerase directly from colonies on the trans-

216

NICKERSON ET AL.

Random mutagenesis-PCR method flow chart. The procedure for developing random mutagenesis clones for validation of mutation/SNP detection methods is presented using MET exon 15 and DHPLC as an example. Inoculation of liquid culture and the high fidelity polymerase amplification of clones were done simultaneously; however, only the clones containing inserts of correct size were minipreped. Clones were sequenced on both strands using either PCR or miniprep DNA as template.

FIGURE 4.

formation plate, plated at low density so that single colonies are isolated. Our protocol utilizes a 1.5x final concentration of reaction buffer to achieve amplification of inserts from colonies, which is a new application for Pfu-Turbo™ polymerase. Colony PCR was not successful using the standard 1x final reaction buffer concentration (M.N., unpublished data). Importantly, amplification of cloned inserts directly from colo-

nies on the transformation plate allows positive controls to be obtained in two days. Interestingly, we observed that a low number of heterozygous clones, i.e., clones that contained copies of wild type and mutant DNA fragments, were generated. Clones were derived from single colonies that had been re-streaked from transformation plates, so it is unlikely that the heterozygosity was due to cross-contamination of wild type and mutant colonies. It seems more likely that DNA strands were heteroduplexed during thermal cycling and were cloned, or that two recombinant plasmids containing wild type and mutant alleles entered the same competent cell. These clones were very useful as controls, since they were amplified, heteroduplexed, and immediately run on DHPLC to produce a mutation-specific signature. Now we have synthesized RM-PCR clones for several exons of the MET gene with equal success (one in three clones sequenced possessed sequence variants, on average) and have found additional options in choices of template and polymerase. Use of paraffin extracted DNA as starting template and, as expected, lower-fidelity polymerases both produced greater number of sequence variants than higher quality genomic DNA and high fidelity polymerases. Thus, these options should provide a range of choices for a variety of specific applications and allow further development of this basic procedure. Application of RM-PCR to SNP and mutation detection methods aimed at discovery of sequence heterozygosity, such as DGGE [Miller et al., 1999], SSCP [Dobson-Stone et al., 2000; Larsen et al., 1999], enzymatic mutation detection [Del Tito et al., 1998; Youil et al., 1995], and DHPLC, will allow effective validation and optimization of experimental design. We show here that current algorithm predictions of DHPLC parameters, temperature and gradient, are useful for MET exon 15 (Table 1 and Fig. 3) but not exact (59°C predicted, 60/ 61°C actual). These predictions were rigorously examined using RM-PCR to introduce sequence changes along the entire length of the amplicon. Significantly, signatures from mixes of wild type with clones 1 (16688C>T), 5 (16591T>C), 8 (16613T>C), and 50 (16555A>G), containing


sequence changes in the center of the amplicon (box, Fig. 2), were not detected at 59°C. A wild type peak was visible at this temperature and the signatures for clones 5, 8, and 50 for example, were only resolved at a single temperature, 61°C. Further, signatures were not evident at 60 and 62°C showing that some mutations may require scanning at every temperature (1°C intervals) for detection. Hopefully, this data will allow improvement of current algorithms or promote development of new ones leading to robust predictions of mutation detection conditions. Use of randomly-mutagenized clones possessing sequence changes along the entire length of the exon (Fig. 2) were used here to ensure a high degree of confidence that new SNPs and mutations, including single base deletions, would be detected. However, limitations in detection are noted due to failure to detect a single base deletion in clone 12 (Table 2, dotted line in Fig. 2). This sequence change was located 19 nucleotides from the 3′ end of the amplicon within the primer sequences of this cloned insert, and apparently did not initiate melting of the fragment sufficient to produce a signature. Lastly, these clones were used to examine comprehensively the prediction that a specific sequence change generates a unique signature. This prediction is supported by the results presented here (Fig. 3) that allowed rapid identification of a sequence change from its DHPLC signature [Nickerson et al., 2000; Arnold et al., 1999; Gross et al., 1999]. Hopefully, this study contributes to methodology allowing absolute detection of mutations in DNA in complex biological situations of carcinogenesis and genomics. In these situations, consideration of factors affecting background or noise is important because various methods may favor detection in different situations so that the signal to noise ratio allows unambiguous determination of sequence heterogeneity. For example, analysis of tumor blocks can be influenced by the residual presence of preservative (paraffin), varying amounts of normal tissue, or changes in the structure of the genome at a particular locus such as loss of heterozygosity [Brauch et al., 1990] or duplication of alleles [Glukhova et al., 2000; Zhuang et al., 1998]. Additionally, as sequencing the human genome

217

nears completion many duplicated regions of the genome, including peri-centromeric repeats and pseudogenes, have been observed [Maggert and Karpen, 2000; Huizing et al., 2000; Hut et al., 2000]. Amplification and analysis of a desired sequence may be confounded by co-amplification of closely related sequences that increase the chances of missing a mutation or SNP, or that increase the level of background sequence variability so that an important sequence alteration is lost in the “noise.” Hopefully, RM-PCR will be used to validate mutation and SNP detection methods to provide accurate details about mechanisms of carcinogenesis and predisposition to disease, and insure that reliable information from genetic testing is provided to patients and their families [Yan et al., 2000]. Lastly, the “synthetic” mutations introduced by RM-PCR provide a way to circumvent troubling issues of patient privacy and commercial ownership that are encountered using patient-derived samples for validation of experimental techniques.

ACKNOWLEDGMENTS We thank Dr. Gregor Weirich for important discussion of clone sequence variants, and Lynn Rasmussen and the staff of the Molecular Technology Center, SAIC-Frederick for management of the sequencing facilities. Critical comments from anonymous reviewers are appreciated. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

REFERENCES Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. J Mol Biol 215: 403–410. Arnold N, Gross E, Schwarz-Boeger U, Pfisterer J, Jonat W, Kiechle M. 1999. A highly sensitive, fast and economical technique for mutation analysis in hereditary breast and ovarian cancers. Hum Mutat 14:333–339. Austin J, Hoogendoorn B, Buckland P, Speight G, Cardno A, Bowen T, Williams N, Spurlock G, Sanders R, Jones L, Murphy K, McCarthy G, McGuffin P, Owen MJ, O’Donovan MC. 2000. Comparative sequencing of the proneurotensin gene and association studies in schizophrenia. Mol Psychiatry 5:208–212.

218

NICKERSON ET AL.

Brauch H, Tory K, Kotler F, Gazdar AF, Pettengill OS, Johnson B, Graziano S, Winton T, Buys CHCM, Sorenson GD, Poiesz BJ, Minna JD, Zbar B. 1990. Molecular mapping of deletion sites in the short arm of chromosome 3 in human lung cancer. Genes Chromosomes Cancer 1:240–246. Brookes AJ. 1999. The essence of SNPs. Gene 234:177–186. Brown SM. 1999. Snapping up SNPs. BioTechniques 26: 1090–1093. Buetow KH, Edmonson MN, Cassidy AB. 1999. Reliable identification of large numbers of candidate SNPs from public EST data. Nat Genet 21:323–325. Cargill M, Altshuler D, Ireland J, Sklar P, Ardlie K, Patil N, Lane CR, Lim EP, Kalyanaraman N, Nemesh J, Ziaugra L, Friedland L, Rolfe A, Warrington J, Lipshutz R, Daley GQ, Lander ES. 1999. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nat Genet 22:231–238. Collins A, Lonjou C, Morton NE. 1999. Genetic epidemiology of single-nucleotide polymorphisms. Proc Natl Acad Sci 96:15173–15177. Collins FS, Brooks LD, Chakravarti A. 1998. A DNA polymorphism discovery resource for research on human genetic variation. Genome Res 8:1229–1231. Cotton RGH. 1997. Slowly but surely towards better scanning for mutations. TIG 13:43–46. Del Tito Jr BJ, Poff III HE, Novotny MA, Cartledge DM, Walker II RI, Earl CD, Bailey AL. 1998. Automated fluorescent analysis procedure for enzymatic mutation detection. Clin Chem 44:731–739. Dobson-Stone C, Cox RD, Lonie L, Southam L, Fraser M, Wise C, Bernier F, Hodgson S, Porter DE, Hamish A, Simpson RW, Monaco AP. 2000. Comparison of fluorescent single-strand conformation polymorphism analysis and denaturing high-performance liquid chromatography for detection of EXT1 and EXT2 mutations in hereditary multiple exostoses. Eur J Hum Genet 8:24–32. Duh F-M, Scherer SW, Tsui L-C, Lerman MI, Zbar B, Schmidt L. 1997. Gene structure of the human MET protooncogene. Oncogene 15:1583–1586. Förnzler D, Her H, Knapik EW, Clark M, Lehrach H, Postlethwait JH, Zon LI, Beier DR. 1998. Gene mapping in zebrafish using single-strand conformation polymorphism analysis. Genomics 51:216–222. Gilles PN, Wu DJ, Foster CB, Dillon PJ, Chanock SJ. 1999. Single nucleotide polymorphic discrimination by an electronic dot blot assay on semiconductor microchips. Nat Biotech 17:365–370. Giordano M, Oefner PJ, Underhill PA, Cavalli-Sforza LL, Tosi R, Richiardi M. 1999. Identification by denaturing high-performance liquid chromatography of numerous polymorphisms in a candidate region for multiple sclerosis susceptibility. Genomics 56:247–253.

Glukhova L, Lavialle C, Fauvet D, Chudoba I, Danglot G, Angevin E, Bernheim A, Goguel AF. 2000. Mapping of the 7q31 subregion common to the small chromosome 7 derivatives from two sporadic papillary renal cell carcinomas: increased copy number and overexpression of the MET proto-oncogene. Oncogene 19:754–761. Gross E, Arnold N, Goette J, Schwarz-Boeger U, Kiechle M. 1999. A comparison of BRCA1 mutation analysis by direct sequencing, SSCP, and DHPLC. Hum Genet 105:72–78. Huizing M, Anikster Y, Gahl WA. 2000. Characterization of a partial pseudogene homologous to the HermanskyPudlak syndrome gene HPS-1; relevance for mutation detection. Hum Genet 106:370–373. Hut PHL, Vlies PVD, Jonkman MF, Verlind E, Shimizu H, Buys CHCM, Scheffer H. 2000. Exempting homologous pseudogene sequences from polymerase chain reaction amplification allows genomic keratin 14 hotspot mutation analysis. J Invest Dermatol 114:616–619. Jones AC, Austin J, Hansen N, Hoogendoorn B, Oefner PJ, Cheadle JP, O’Donovan MC. 1999. Optimal temperature selection for mutation detection by denaturing HPLC and comparison to single-stranded conformation polymorphism and heteroduplex analysis. Clin Chem 45:1133–1140. Kuklin A, Munson K, Gjerde D, Haefele R, Taylor P. 1997/ 98. Detection of single-nucleotide polymorphisms with the WAVE DNA fragment analysis system. Genet Test 1:201–206. Landegren U, Nilsson M, Kwok P-Y. 1998. Reading bits of genetic information: methods for single-nucleotide polymorphism analysis. Genome Res 8:769–776. Larsen LA, Andersen PS, Kanters JK, Jacobsen JR, Vuust J, Christiansen M. 1999. A single strand conformation polymorphism/heteroduplex (SSCP/HD) method for detection of mutations in 15 exons of the KVLQT 1 gene, associated with long QT syndrome. Clin Chim Acta 280:113–125. Lee HS, Sambuughin N, Cervenakova L, Chapman J, Pocchiari M, Litvak S, Qi HY, Budka H, del Sur T, Furukawa H, Brown P, Gajdusek DC, Long JC, Korczyn AD, Goldfarb LG. 1999. Ancestral origins and worldwide distribution of the PRNP 200K mutation causing familial CreutzfeldtJakob disease. Am J Hum Genet 64:1063–1070. Liu W, Smith DI, Rechtzigel KJ, Thibodeau SN, James CD. 1998. Denaturing high performance liquid chromatography (DHPLC) used in the detection of germline and somatic mutations. Nucleic Acids Res 26:1396–1400. Maggert KA, Karpen GH. 2000. Acquisition and metastability of centromere identity and function: sequence analysis of a human neocentromere. Genome Res 10:725–728. Miller KM, Ming TJ, Schulze AD, Withler RE. 1999. Denaturing gradient gel electrophoresis (DGGE): a rapid and sensitive technique to screen nucleotide sequence variation in populations. BioTechniques 27:1016–1030.


219

Nickerson DA, Tobe VO, Taylor SL. 1997. PolyPhred: automating the detection and genotyping of single nucleotide substitutions using fluorescence-based resequencing. Nucleic Acids Res 25:2745–2751.

J, Vocke C, Brown JA, Jenkins R, Richard S, Bergerheim U, Gerrard B, Dean M, Linehan WM, Zbar B. 1999b. Novel mutations of the MET proto-oncogene in papillary renal carcinomas. Oncogene 18: 2343–2350.

Nickerson DA, Taylor SL, Weiss KM, Clark AG, Hutchinson RG, Stengård J, Salomaa V, Vartiainen E, Boerwinkle E, Sing CF. 1998. DNA sequence diversity in a 9.7_kb region of the human lipoprotein lipase gene. Nat Genet 19:233–240.

Schriml LM, Peterson RJ, Gerrard B, Dean M. 2000. Use of denaturing HPLC to map human and murine genes and to validate single-nucleotide polymorphisms. BioTechniques 28:740–745.

Nickerson ML, Weirich G, Zbar B, Schmidt LS. 2000. Signature-based analysis of MET proto-oncogene mutations using DHPLC. Hum Mutat 16:68–76. O’Brien SJ, Menotti-Raymond M, Murphy WJ, Nash WG, Wienberg J, Stanyon R, Copeland NG, Jenkins NA, Womack JE, Graves JAM. 1999. The promise of comparative genomics in mammals. Science 286:458–481. O’Donovan M, Oefner PJ, Roberts SC, Austin J, Hoogendoorn B, Guy C, Speight G, Upadhyaya M, Sommer SS, McGuffen P. 1998. Blind analysis of denaturing high-performance liquid chromatography as a tool for mutation detection. Genomics 52:44–49. Oefner PJ, Underhill PA. 1998. DNA mutation detection using denaturing high-performance liquid chromatography (DHPLC). In: Dracopoli NC, Haines JL, Korf BR, Morton CC, Seidman CE, Seidman JG, Moir DT, Smith DR, editors. Current protocols in human genetics, Suppl. 19. New York: John Wiley and Sons. p 7.10.1–7.10.12. Oefner PJ. 2000. Allelic discrimination by denaturing highperformance liquid chromatography. J Chroma B 739:345–355. Oldenburg MC, Siebert M. 2000. New cleavase fragment length polymorphism method improves the mutation detection assay. BioTechniques 28:351–357. Olivero M, Valente G, Bardelli A, Longati P, Ferrero N, Cracco C, Terrone C, Rocca-Rossetti S, Comoglio PM, Di Renzo MF. 1999. Novel mutation in the ATP-binding site of the MET oncogene tyrosine kinase in a HPRCC family. Int J Cancer 82:640–643. Schmidt L, Junker K, Weirich G, Glenn G, Choyke P, Lubensky I, Zhuang Z, Jeffers M, Vande Woude G, Neumann H, Walther M, Linehan WM, Zbar B. 1998. Two North American families with papillary renal carcinoma and identical novel mutations in the MET protooncogene. Cancer Res 58:1719–1722. Schmidt L, Lubensky I, Linehan WM, Zbar B. 1999a. Hereditary papillary renal carcinoma: pathology and pathogenesis. In: Hino O, editor. Kidney cancer: recent results of basic and clinical research. Contrib Nephrol 128:11–27. Schmidt L, Junker K, Nakaigawa N, Kinjerski T, Weirich G, Miller M, Lubensky I, Neumann HPH, Brauch H, Decker

Sévenet N, Lellouch-Tubiana A, Schofield D, Hoang-Xuan K, Gessler M, Birnbaum D, Jeanpierre C, Jouvet A, Delattre O. 1999. Spectrum of hSNF5/INI1 somatic mutations in human cancer and genotype–phenotype correlations. Hum Mol Genet 8:2359–2368. Shuman S. 1994. Novel approach to molecular cloning and polynucleotide synthesis using Vaccinia DNA topoisomerase. J Biol Chem 269:32678–32684. Syvånen A-C, Landegren U, Isaksson A, Gyllensten U, Brookes A. 1999. Enthusiasm mixed with scepticism about single-nucleotide polymorphism markers for dissecting complex disorders. Eur J Hum Genet 7:98–101. Tyagi S, Kramer FR. 1996. Molecular beacons: probes that fluorese upon hybridization. Nat Biotech 14:303–308. Vogelstein B, Gillespie D. 1979. Preparative and analytical purification of DNA from agarose. Proc Natl Acad Sci 76:615–619. Wagner TMU, Hirtenlehner K, Shen P, Moeslinger R, Muhr D, Fleischmann E, Concin H, Doeller W, Haid A, Lang AH, Mayer P, Petru E, Ropp E, Langbauer G, Kubista E, Scheiner O, Underhill P, Mountain J, Stierer M, Zielinski C, Oefner P. 1999. Global sequence diversity of BRCA2: analysis of 71 breast cancer families and 95 control individuals of worldwide populations. Hum Mol Genet 8:413–423. Weirich G, Hornauer MA, Bruning T, Hofler H, Brauch H. 1997. Fixed archival tissue-purify DNA and primers for a good PCR yield. Mol Biotechnol 8:299–301. Xiong M, Jin L. 1999. Comparison of the power and accuracy of biallelic and microsatellite markers in population-based gene-mapping methods. Am J Hum Genet 64:629–640. Yan H, Kinzler KW, Vogelstein B. 2000. Genetic testingpresent and future. Science 289:1890–1892. Youil R, Kemper BW, Cotton RGH. 1995. Screening for mutations by enzyme mismatch cleavage with T4 endonuclease VII. Proc Natl Acad Sci 92:87–91. Zhuang Z, Park W-S, Pack S, Schmidt L, Vortmeyer AO, Pak E, Pham T, Weil RJ, Candidus S, Lubensky IA, Linehan WM, Zbar B, Weirich G. 1998. Trisomy 7-harbouring nonrandom duplication of the mutant MET allele in hereditary papillary renal carcinomas. Nat Genet 20:66–69.