Background We have developed an oligonucleotide microarray (genosensor) utilizing a double tandem hybridization technique to search for 9 point mutations located in the most frequently altered codons of the  TP53  gene. Isolated and multiplexed PCR products, 108 and 92 bp long, from exons 7 and 8, respectively, were obtained from 24 different samples. Single-stranded target DNA was then prepared from isolated or multiplexed PCR products, through cyclic DNA synthesis. Independent ssDNA's were annealed with the corresponding pairs of labeled stacking oligonucleotides to create partially duplex DNA having a 7-nt gap, which contains the sequence that will be interrogated by the capture probes forming double tandem hybridization. In the case of multiplexed ssPCR products, only two stacking oligonucleotides were added per target, therefore the gap for the PCR products having two consecutive codons to be interrogated in exon 7 was 12 nt long, so only single tandem hybridization was produced with these respective probes.
Background
We have developed an oligonucleotide microarray (genosensor) utilizing a double tandem hybridization technique to search for 9 point mutations located in the most frequently altered codons of the  TP53  gene. Isolated and multiplexed PCR products, 108 and 92 bp long, from exons 7 and 8, respectively, were obtained from 24 different samples. Single-stranded target DNA was then prepared from isolated or multiplexed PCR products, through cyclic DNA synthesis. Independent ssDNA's were annealed with the corresponding pairs of labeled stacking oligonucleotides to create partially duplex DNA having a 7-nt gap, which contains the sequence that will be interrogated by the capture probes forming double tandem hybridization. In the case of multiplexed ssPCR products, only two stacking oligonucleotides were added per target, therefore the gap for the PCR products having two consecutive codons to be interrogated in exon 7 was 12 nt long, so only single tandem hybridization was produced with these respective probes.TP53Results 18 codon substitutions were found by DNA sequencing. In 13 of them a perfect correlation with the pattern of hybridization was seen (In 5 no signal was seen with the wt probe while a new signal was seen with the appropriate mutant probe, and in 8 more, as expected, no signal was seen with any probe due to the absence of the corresponding probe in the array). In 3 other cases a mutation was falsely suggested by the combination of the absence of the wild type signal along with a false signal in the other probe. In the other 2 cases the presence of the mutation was not detected due to the production of a false hybridization signal with the wild type probe. In both cases (false mutation or no mutation detected) relatively stable mismatched target/probe duplexes should be formed. These problems could be avoided by the addition of probes to improve the performance of the array.
Results
18 codon substitutions were found by DNA sequencing. In 13 of them a perfect correlation with the pattern of hybridization was seen (In 5 no signal was seen with the wt probe while a new signal was seen with the appropriate mutant probe, and in 8 more, as expected, no signal was seen with any probe due to the absence of the corresponding probe in the array). In 3 other cases a mutation was falsely suggested by the combination of the absence of the wild type signal along with a false signal in the other probe. In the other 2 cases the presence of the mutation was not detected due to the production of a false hybridization signal with the wild type probe. In both cases (false mutation or no mutation detected) relatively stable mismatched target/probe duplexes should be formed. These problems could be avoided by the addition of probes to improve the performance of the array.Conclusion Our results demonstrate that a simple  TP53  microarray employing short (7-mer) probes, used in combination with single or double tandem hybridization approach and a simple or multiplex target preparation method, can identify common  TP53  missense mutations from a variety of DNA sources with good specificity.
Conclusion
Our results demonstrate that a simple  TP53  microarray employing short (7-mer) probes, used in combination with single or double tandem hybridization approach and a simple or multiplex target preparation method, can identify common  TP53  missense mutations from a variety of DNA sources with good specificity.TP53TP53

Background Cancer is a group of diseases characterized by uncontrolled cell growth. According to The World Cancer Report, cancer rates could further increase by 50% to 15 million new cases in the year 2020 [ 1 ]. The chances of surviving the onset of some common cancers depend largely on how early they are detected in addition to how well they are treated. The progression of mammalian cells towards malignancy is an evolutionary process that involves an accumulation of mutations at the molecular and chromosomal level. A candidate for involvement in this process is the tumor suppressor gene  TP53  (MIM # 191170) which encodes a transcription factor (p53 protein) with cancer inhibiting properties. This gene is the most frequently mutated gene in human cancer. Between 30% and 70% of cancers of almost every organ and histological subtype have a point mutation in one of the two  TP53  gene copies together with loss of the other copy [ 2 - 4 ]. In many cancers the distribution of mutations along the  TP53  gene is tumor-specific, clustered between exons 5, 7 and 8. This region is highly conserved throughout evolution [ 3 ]. In this domain, six mutational "hotspots" have been identified at codons 175, 245, 248, 249, 273, and 282. The mutational profile of the  TP53  gene is different between cancers, for example, codons 157, 158, 248, 249, and 273 have been designated as  TP53  mutational hotspots in lung cancer [ 5 , 6 ], while in breast cancer the mutational hotspots are in codons, 175, 245, 248, 249 and 273 [ 7 ]. On the contrary, in cervical cancer the frequency of the p53 mutations is very low. [ 8 ]. Because mutations in the  TP53  gene are so common in human tumors and have been widely reported in the literature, extensive mutational databases exist, such as that maintained by IARC [ 9 ]. Walker et al. [ 10 ], have utilized the IARC TP53 mutation database to define 73 "hotspots" for mutation in  TP53  related to changes in protein structure and function. Martin et al. [ 11 ] performed a systematic automated analysis of the effects of TP53 mutations on the structure of the core domain of the p53 protein to functionally classify the various types of p53 mutants according to predicted effects on protein folding or DNA-protein interactions. Most mutations are currently identified by conventional methods of polymorphism detection and DNA sequencing [ 12 ]. A growing number of nucleic acid hybridization techniques have recently been applied to biomedical problems, including development of DNA probe arrays for detection of  TP53  mutations [ 13 - 15 ]. In many applications, DNA chips containing surface-bound oligonucleotides (probes) are used to interrogate sample (target) sequence information through complementary recognition (hybridization) in a highly parallel fashion [ 16 ]. Major applications of DNA microarrays include gene expression profiling [ 17 , 18 ] and gene mutation analysis [ 19 , 20 ]. These techniques allow parallel analysis of multiple DNA samples. Mutation studies with DNA microarrays are still at an early stage and are in continuous development [ 21 , 22 ]. Although the field of microarray assays is still in a relatively early stage, it is generally anticipated that microarray assays will offer decreased cost and faster results, compared with the traditional, more labor intensive dideoxy sequencing approach. We recently reported a novel tandem hybridization strategy and its application for identification of mutations. Reliable discrimination of point mutations has been achieved by double tandem hybridization with a set of seven-mer probes [ 23 , 24 ]. In the present work we designed a novel small format DNA chip (genosensor array) to search for nine point mutations in codons 248, 249 and 273 of the  TP53  gene.
Background
Cancer is a group of diseases characterized by uncontrolled cell growth. According to The World Cancer Report, cancer rates could further increase by 50% to 15 million new cases in the year 2020 [ 1 ]. The chances of surviving the onset of some common cancers depend largely on how early they are detected in addition to how well they are treated.The progression of mammalian cells towards malignancy is an evolutionary process that involves an accumulation of mutations at the molecular and chromosomal level. A candidate for involvement in this process is the tumor suppressor gene  TP53  (MIM # 191170) which encodes a transcription factor (p53 protein) with cancer inhibiting properties. This gene is the most frequently mutated gene in human cancer. Between 30% and 70% of cancers of almost every organ and histological subtype have a point mutation in one of the two  TP53  gene copies together with loss of the other copy [ 2 - 4 ]. In many cancers the distribution of mutations along the  TP53  gene is tumor-specific, clustered between exons 5, 7 and 8. This region is highly conserved throughout evolution [ 3 ]. In this domain, six mutational "hotspots" have been identified at codons 175, 245, 248, 249, 273, and 282. The mutational profile of the  TP53  gene is different between cancers, for example, codons 157, 158, 248, 249, and 273 have been designated as  TP53  mutational hotspots in lung cancer [ 5 , 6 ], while in breast cancer the mutational hotspots are in codons, 175, 245, 248, 249 and 273 [ 7 ]. On the contrary, in cervical cancer the frequency of the p53 mutations is very low. [ 8 ].TP53TP53TP53TP53TP53Because mutations in the  TP53  gene are so common in human tumors and have been widely reported in the literature, extensive mutational databases exist, such as that maintained by IARC [ 9 ]. Walker et al. [ 10 ], have utilized the IARC TP53 mutation database to define 73 "hotspots" for mutation in  TP53  related to changes in protein structure and function. Martin et al. [ 11 ] performed a systematic automated analysis of the effects of TP53 mutations on the structure of the core domain of the p53 protein to functionally classify the various types of p53 mutants according to predicted effects on protein folding or DNA-protein interactions. Most mutations are currently identified by conventional methods of polymorphism detection and DNA sequencing [ 12 ]. A growing number of nucleic acid hybridization techniques have recently been applied to biomedical problems, including development of DNA probe arrays for detection of  TP53  mutations [ 13 - 15 ]. In many applications, DNA chips containing surface-bound oligonucleotides (probes) are used to interrogate sample (target) sequence information through complementary recognition (hybridization) in a highly parallel fashion [ 16 ]. Major applications of DNA microarrays include gene expression profiling [ 17 , 18 ] and gene mutation analysis [ 19 , 20 ]. These techniques allow parallel analysis of multiple DNA samples. Mutation studies with DNA microarrays are still at an early stage and are in continuous development [ 21 , 22 ]. Although the field of microarray assays is still in a relatively early stage, it is generally anticipated that microarray assays will offer decreased cost and faster results, compared with the traditional, more labor intensive dideoxy sequencing approach. We recently reported a novel tandem hybridization strategy and its application for identification of mutations. Reliable discrimination of point mutations has been achieved by double tandem hybridization with a set of seven-mer probes [ 23 , 24 ]. In the present work we designed a novel small format DNA chip (genosensor array) to search for nine point mutations in codons 248, 249 and 273 of the  TP53  gene.TP53TP53TP53TP53Results PCR products and reference hybridization patterns PCR products from exon 7 (codons 248 and 249) and exon 8 (codon 273) were obtained from each type of DNA sources listed in Materials and Methods. Figure  2A  shows gel electrophoretic analysis of the fragments of 108 and 92 bp corresponding to exons 7 and 8, respectively. To prepare ssDNA targets PCR products were used as templates for cycle synthesis of a target strand, using the reverse PCR primer in single or multiplexed reactions cycled 25 times. The production of single-stranded target DNA's was assessed by its change in electrophoretic mobility in 4% agarose gels (Figure  2B ). The reference hybridization patterns produced using synthetic DNA targets are shown in Figures.  3A  and  3B . As expected, all the synthetic targets, including those of the negative controls, yielded hybridization signals with their respective ("perfect-match") probes. Pairs of wild-type with each mutant synthetic target sequences (1:1 mixtures) were also hybridized to reproduce heterozygous conditions. All gave the expected signals, (Figure  3B ). Hybridization of DNA targets Hybridization of individual or multiplexed ssDNA targets prepared from the 24 DNA samples (that correspond to 72 codons in 24 samples) was performed with similar results. Base substitutions were seen in 11 out of the 24 samples tested (Table  3 ). One, two or three codons were altered in 5 (P6, L1, L2, B3 and B6), 5 (P1, L4, L7, L9 and L10) and 1 (L8) samples, respectively. In the cases of the samples having two or three codons affected, at least one of the base substitutions was silent. In the other 13 samples only WT sequences were identified (data not shown). Representative hybridization patterns are shown in Figure.  4A  and the overall results are summarized in Table  3 . The DNA samples hybridized with one or two probes from each codon, corresponding to the homozygous or heterozygous condition, respectively. Among the 24 different samples multiplexed or individually tested in the microarray, six single base susbstitutions in codon 248 were found by sequencing the PCR product. All of them corresponded to base substitutions keeping the original aminoacid (Arginine). The same number of point mutations were also seen in codon 249 by DNA sequencing. However, no probes to search for these base substitutions were placed in the DNA microarray. Six point mutations in codon 273 were obtained. All of them, except the CGT→CCT change observed in plasmid P6, were searched with the set of probes contained in the DNA microarray. In this codon all the base substitutions are producers of aminoacid substitution.
Results
PCR products and reference hybridization patterns PCR products from exon 7 (codons 248 and 249) and exon 8 (codon 273) were obtained from each type of DNA sources listed in Materials and Methods. Figure  2A  shows gel electrophoretic analysis of the fragments of 108 and 92 bp corresponding to exons 7 and 8, respectively. To prepare ssDNA targets PCR products were used as templates for cycle synthesis of a target strand, using the reverse PCR primer in single or multiplexed reactions cycled 25 times. The production of single-stranded target DNA's was assessed by its change in electrophoretic mobility in 4% agarose gels (Figure  2B ). The reference hybridization patterns produced using synthetic DNA targets are shown in Figures.  3A  and  3B . As expected, all the synthetic targets, including those of the negative controls, yielded hybridization signals with their respective ("perfect-match") probes. Pairs of wild-type with each mutant synthetic target sequences (1:1 mixtures) were also hybridized to reproduce heterozygous conditions. All gave the expected signals, (Figure  3B ).
PCR products and reference hybridization patterns
PCR products from exon 7 (codons 248 and 249) and exon 8 (codon 273) were obtained from each type of DNA sources listed in Materials and Methods. Figure  2A  shows gel electrophoretic analysis of the fragments of 108 and 92 bp corresponding to exons 7 and 8, respectively. To prepare ssDNA targets PCR products were used as templates for cycle synthesis of a target strand, using the reverse PCR primer in single or multiplexed reactions cycled 25 times. The production of single-stranded target DNA's was assessed by its change in electrophoretic mobility in 4% agarose gels (Figure  2B ).The reference hybridization patterns produced using synthetic DNA targets are shown in Figures.  3A  and  3B . As expected, all the synthetic targets, including those of the negative controls, yielded hybridization signals with their respective ("perfect-match") probes. Pairs of wild-type with each mutant synthetic target sequences (1:1 mixtures) were also hybridized to reproduce heterozygous conditions. All gave the expected signals, (Figure  3B ).Hybridization of DNA targets Hybridization of individual or multiplexed ssDNA targets prepared from the 24 DNA samples (that correspond to 72 codons in 24 samples) was performed with similar results. Base substitutions were seen in 11 out of the 24 samples tested (Table  3 ). One, two or three codons were altered in 5 (P6, L1, L2, B3 and B6), 5 (P1, L4, L7, L9 and L10) and 1 (L8) samples, respectively. In the cases of the samples having two or three codons affected, at least one of the base substitutions was silent. In the other 13 samples only WT sequences were identified (data not shown). Representative hybridization patterns are shown in Figure.  4A  and the overall results are summarized in Table  3 . The DNA samples hybridized with one or two probes from each codon, corresponding to the homozygous or heterozygous condition, respectively. Among the 24 different samples multiplexed or individually tested in the microarray, six single base susbstitutions in codon 248 were found by sequencing the PCR product. All of them corresponded to base substitutions keeping the original aminoacid (Arginine). The same number of point mutations were also seen in codon 249 by DNA sequencing. However, no probes to search for these base substitutions were placed in the DNA microarray. Six point mutations in codon 273 were obtained. All of them, except the CGT→CCT change observed in plasmid P6, were searched with the set of probes contained in the DNA microarray. In this codon all the base substitutions are producers of aminoacid substitution.
Hybridization of DNA targets
Hybridization of individual or multiplexed ssDNA targets prepared from the 24 DNA samples (that correspond to 72 codons in 24 samples) was performed with similar results. Base substitutions were seen in 11 out of the 24 samples tested (Table  3 ). One, two or three codons were altered in 5 (P6, L1, L2, B3 and B6), 5 (P1, L4, L7, L9 and L10) and 1 (L8) samples, respectively. In the cases of the samples having two or three codons affected, at least one of the base substitutions was silent. In the other 13 samples only WT sequences were identified (data not shown). Representative hybridization patterns are shown in Figure.  4A  and the overall results are summarized in Table  3 . The DNA samples hybridized with one or two probes from each codon, corresponding to the homozygous or heterozygous condition, respectively. Among the 24 different samples multiplexed or individually tested in the microarray, six single base susbstitutions in codon 248 were found by sequencing the PCR product. All of them corresponded to base substitutions keeping the original aminoacid (Arginine). The same number of point mutations were also seen in codon 249 by DNA sequencing. However, no probes to search for these base substitutions were placed in the DNA microarray. Six point mutations in codon 273 were obtained. All of them, except the CGT→CCT change observed in plasmid P6, were searched with the set of probes contained in the DNA microarray. In this codon all the base substitutions are producers of aminoacid substitution.Discussion The  TP53  tumor suppressor gene has proven to be one of the cellular genes most often mutated in human neoplasias. Analysis of the mutational events that target the  TP53  gene has revealed evidence for both exogenous and endogenous mutational mechanisms. This gene mutational spectrum suggests evidence for a direct causal effect of tobacco smoke in lung cancer [ 26 , 27 ], aflatoxin B1 in liver cancer [ 28 ]. Therefore, identification of mutations in the  TP53  gene may play an important role in the diagnosis, staging, and management of the cancer patients. More than 70% of the molecular studies have focused on the central region of the  TP53  gene, more specifically on exons 5 through 8 which encode the DNA binding domain [ 3 ]. Thus, missense mutations in this region can cause a modification that may alter DNA binding. It is therefore essential that clinical trials aim to accurately establish the effect of  TP53  mutations on all clinical parameters. One approach is the p53 GeneChip of Affymetrix used to identify mutations in this gene [ 13 , 14 ]. However, this technology is expensive and poorly available to many clinicians, which makes it necessary to develop new mutation detection methods [ 29 , 30 ]. The updated IARC TP53 mutation database [ 38 ] shows that more than 1700 different point mutations, which are associated to cancers, are distributed along the  TP53  gene.  TP53  somatic mutations are found in most types of sporadic human cancers at various frequencies (from 20% to 60%) [ 13 , 14 ]. The database also shows that approximately 20% of all mutations are located in the five codons (hotspots) in the core domain: 175, 245, 248, 249 and 273. Therefore a primary screen of these codons would be attractive. Most SNP diagnostic arrays use probes varying from 15 to 20 nt in length with similar Tm values [ 31 ]. However, under this circumstance some of the mutant sequences are difficult to discriminate, due to the relatively small destabilizing effect of certain single mismatches in the probe/target duplex [ 32 ]. The tandem hybridization method described here offers several advantages over the traditional oligonucleotide array configuration in which each interrogated target sequence is represented by a single surface-tethered probe. Because the long stacking probe targets the analysis to a single unique site within a nucleic acid, direct hybridization analysis of nucleic acid samples of high genetic complexity using short capture probes may be enabled [ 24 ]. Recently, we successfully used a double tandem hybridization strategy in the genesensor chip system to discriminate point mutations in codon 634 of RET oncogene in individuals affected by medullary thyroid carcinoma [ 23 ]. This DNA chip format involves a target sequence which is annealed with a pair of labeled oligonucleotides (stabilizing oligonucleotides) prior to hybridization to the array of capture probes, forming a single-stranded gap between the stabilizing oligonucleotides and corresponding to the length of the capture probes. The partially duplex product contains the sequences interrogated by the capture probes, and when the sequences between the target DNA and the capture probe (attached to slide) are perfectly complementary, the stability of the hybridization is enhanced due to coaxial stacking of bases between the contiguous ends of the probe and the stabilizing oligonucleotides. The energy involved varies with the identity of the base pairs and the coaxial stacking [ 22 ]. Tandem hybridization uses shorter capture probes than traditional oligonucleotide array hybridization, which may contribute to increased discrimination of point mutations because the single base mismatch acts on a less stable duplex formed between the target DNA and the shorter probe. Two additional attractive features inherent to tandem hybridization are that, i) the probability that formation of secondary structure within the single stranded DNA [ 25 ] will block accessibility of the target sequence is reduced, and ii) the label needed to reveal the hybridization can be introduced into the two stabilizing oligonucleotides, avoiding the extra step of labeling individual target strands [ 33 , 34 ]. The goal of the present work was to develop a simple format array able to perform a primary screening of the mutations occurring in the most frequently affected codons of the  TP53  gene. It has been recently reported that detection of mutations yields variable results depending on the type of DNA sample [ 35 , 36 ]. Is clear that, the sensitivity to detect mutations in TP53, may also differ depending on the method used. In the current study the double tandem hybridization assay was applied to genomic DNA samples extracted from a variety of sources, including blood cells, cell lines and plasmids. There were not any differences in the ability of our system to detect mutations with respect to the different DNA sources. In the experiments employing synthetic DNA targets hybridized with arrays of mutant and WT probes the expected hybridization signals were seen both in homozygous and heterozygous conditions (Figure.  3 ). This result indicates that the probes are working properly. The hybridization of natural targets was done both with isolated and multiplexed PCR products with similar results. Multiplexing was applied in all (PCR reaction ssDNA target preparation, annealing of target with stacking oligonucleotides and hybridization) the steps. So these results are suggesting that multiplexing can be confidently employed for this analysis. Base changes were found in 11 DNA samples. Two were from plasmid, seven from cell lines and two from blood samples. In 5 of these samples a single codon was affected, in other 5 samples two codons were altered, and in the other sample three codons were affected. Therefore a total of 18 codon alterations were detected. In five of the 18 codon alterations (Samples L2 codon 273, L7 codon 273, L8 codon 273, B3 codon 273 and B6 codon 273) both the absence of hybridization signal with the wild type probe and the production of signal with the appropriated probe was seen. In eight cases (Samples P1 codon 248, P6 codon 273, L8 codons 248 and 249, L9 L8 codons 248 and 249 and L8 codons 248 and 249 and, L10 codons 248 and 249) no hybridization signal was seen even with the wild type sequence. This was due to the absence of the corresponding mutant probe in the array. In three cases (P1 codon 249, L4 codon 249 and L7 codon 249) having either homozygous (sample P1) or heterozygous (samples L4 and L7) genotypes (wtAGG→mutAGA) no hybridization signal with the wild type probe and, an additional false hybridization signal with the probe corresponding to the substitution of guanine for thymine in codon 249 (p-249 G 2 →T) was seen, which could be relatively stable under the conditions tested. Therefore an additional probe, searching by the AGA sequence, should be added in the future array to discriminate between the two alternative silent (AGA) and missense (AGT) genotypes. In the other two codons affected (L1 codon 248 and L4 codon 248) the presence of signal with the wild type probe was seen even when the sequencing was showing a base change (wtCGG→mutCGT in sample L1 or 248 wtCGG→mutCGK in sample L4). In both cases a G:N mismatch is formed which, according to SantaLucia [ 37 ], is relatively stable. So, as in the previous two cases the incorporation of additional probes in the array should help to improve performance of the DNA microarray to confidently identify the genotypes. The base substitution observed in B3 and B6 blood samples is a mutation that substitutes Arginine by Leucine. The presence of this mutation in blood suggests that it could be from germinal origin. In all the mutations (silent and missense) observed an Arginine was involved, which can be expected because it is coded by 6 codons and it frequently produces non conservative aminoacid substitutions. The array is able to confidently detect most of the mutations searched, however, additional probes should be added to improve its performance.
Discussion
The  TP53  tumor suppressor gene has proven to be one of the cellular genes most often mutated in human neoplasias. Analysis of the mutational events that target the  TP53  gene has revealed evidence for both exogenous and endogenous mutational mechanisms. This gene mutational spectrum suggests evidence for a direct causal effect of tobacco smoke in lung cancer [ 26 , 27 ], aflatoxin B1 in liver cancer [ 28 ]. Therefore, identification of mutations in the  TP53  gene may play an important role in the diagnosis, staging, and management of the cancer patients.TP53TP53TP53More than 70% of the molecular studies have focused on the central region of the  TP53  gene, more specifically on exons 5 through 8 which encode the DNA binding domain [ 3 ]. Thus, missense mutations in this region can cause a modification that may alter DNA binding. It is therefore essential that clinical trials aim to accurately establish the effect of  TP53  mutations on all clinical parameters. One approach is the p53 GeneChip of Affymetrix used to identify mutations in this gene [ 13 , 14 ]. However, this technology is expensive and poorly available to many clinicians, which makes it necessary to develop new mutation detection methods [ 29 , 30 ].TP53TP53The updated IARC TP53 mutation database [ 38 ] shows that more than 1700 different point mutations, which are associated to cancers, are distributed along the  TP53  gene.  TP53  somatic mutations are found in most types of sporadic human cancers at various frequencies (from 20% to 60%) [ 13 , 14 ]. The database also shows that approximately 20% of all mutations are located in the five codons (hotspots) in the core domain: 175, 245, 248, 249 and 273. Therefore a primary screen of these codons would be attractive.TP53TP53Most SNP diagnostic arrays use probes varying from 15 to 20 nt in length with similar Tm values [ 31 ]. However, under this circumstance some of the mutant sequences are difficult to discriminate, due to the relatively small destabilizing effect of certain single mismatches in the probe/target duplex [ 32 ].The tandem hybridization method described here offers several advantages over the traditional oligonucleotide array configuration in which each interrogated target sequence is represented by a single surface-tethered probe. Because the long stacking probe targets the analysis to a single unique site within a nucleic acid, direct hybridization analysis of nucleic acid samples of high genetic complexity using short capture probes may be enabled [ 24 ].Recently, we successfully used a double tandem hybridization strategy in the genesensor chip system to discriminate point mutations in codon 634 of RET oncogene in individuals affected by medullary thyroid carcinoma [ 23 ]. This DNA chip format involves a target sequence which is annealed with a pair of labeled oligonucleotides (stabilizing oligonucleotides) prior to hybridization to the array of capture probes, forming a single-stranded gap between the stabilizing oligonucleotides and corresponding to the length of the capture probes. The partially duplex product contains the sequences interrogated by the capture probes, and when the sequences between the target DNA and the capture probe (attached to slide) are perfectly complementary, the stability of the hybridization is enhanced due to coaxial stacking of bases between the contiguous ends of the probe and the stabilizing oligonucleotides. The energy involved varies with the identity of the base pairs and the coaxial stacking [ 22 ]. Tandem hybridization uses shorter capture probes than traditional oligonucleotide array hybridization, which may contribute to increased discrimination of point mutations because the single base mismatch acts on a less stable duplex formed between the target DNA and the shorter probe. Two additional attractive features inherent to tandem hybridization are that, i) the probability that formation of secondary structure within the single stranded DNA [ 25 ] will block accessibility of the target sequence is reduced, and ii) the label needed to reveal the hybridization can be introduced into the two stabilizing oligonucleotides, avoiding the extra step of labeling individual target strands [ 33 , 34 ].The goal of the present work was to develop a simple format array able to perform a primary screening of the mutations occurring in the most frequently affected codons of the  TP53  gene.TP53It has been recently reported that detection of mutations yields variable results depending on the type of DNA sample [ 35 , 36 ]. Is clear that, the sensitivity to detect mutations in TP53, may also differ depending on the method used. In the current study the double tandem hybridization assay was applied to genomic DNA samples extracted from a variety of sources, including blood cells, cell lines and plasmids. There were not any differences in the ability of our system to detect mutations with respect to the different DNA sources.In the experiments employing synthetic DNA targets hybridized with arrays of mutant and WT probes the expected hybridization signals were seen both in homozygous and heterozygous conditions (Figure.  3 ). This result indicates that the probes are working properly.The hybridization of natural targets was done both with isolated and multiplexed PCR products with similar results. Multiplexing was applied in all (PCR reaction ssDNA target preparation, annealing of target with stacking oligonucleotides and hybridization) the steps. So these results are suggesting that multiplexing can be confidently employed for this analysis.Base changes were found in 11 DNA samples. Two were from plasmid, seven from cell lines and two from blood samples. In 5 of these samples a single codon was affected, in other 5 samples two codons were altered, and in the other sample three codons were affected. Therefore a total of 18 codon alterations were detected. In five of the 18 codon alterations (Samples L2 codon 273, L7 codon 273, L8 codon 273, B3 codon 273 and B6 codon 273) both the absence of hybridization signal with the wild type probe and the production of signal with the appropriated probe was seen. In eight cases (Samples P1 codon 248, P6 codon 273, L8 codons 248 and 249, L9 L8 codons 248 and 249 and L8 codons 248 and 249 and, L10 codons 248 and 249) no hybridization signal was seen even with the wild type sequence. This was due to the absence of the corresponding mutant probe in the array. In three cases (P1 codon 249, L4 codon 249 and L7 codon 249) having either homozygous (sample P1) or heterozygous (samples L4 and L7) genotypes (wtAGG→mutAGA) no hybridization signal with the wild type probe and, an additional false hybridization signal with the probe corresponding to the substitution of guanine for thymine in codon 249 (p-249 G 2 →T) was seen, which could be relatively stable under the conditions tested. Therefore an additional probe, searching by the AGA sequence, should be added in the future array to discriminate between the two alternative silent (AGA) and missense (AGT) genotypes. In the other two codons affected (L1 codon 248 and L4 codon 248) the presence of signal with the wild type probe was seen even when the sequencing was showing a base change (wtCGG→mutCGT in sample L1 or 248 wtCGG→mutCGK in sample L4). In both cases a G:N mismatch is formed which, according to SantaLucia [ 37 ], is relatively stable. So, as in the previous two cases the incorporation of additional probes in the array should help to improve performance of the DNA microarray to confidently identify the genotypes.The base substitution observed in B3 and B6 blood samples is a mutation that substitutes Arginine by Leucine. The presence of this mutation in blood suggests that it could be from germinal origin.In all the mutations (silent and missense) observed an Arginine was involved, which can be expected because it is coded by 6 codons and it frequently produces non conservative aminoacid substitutions.The array is able to confidently detect most of the mutations searched, however, additional probes should be added to improve its performance.Conclusions Our results demonstrate that a simple  TP53  microarray using short (7-mer) probes, used in combination with a double tandem hybridization approach and a simple multiplex fragment preparation method, can identify common  TP53  point mutations from different DNA sources. All the previous data confirms that the tandem hybridization technology, with the appropriated set of probes, is highly specific and can be confidently employed for diagnostic purposes. This system could provide rapid, economical and accurate mutational screening in the  TP53  gene. We are presently improving our system by adding probes for these and other  TP53  mutational hot spots.
Conclusions
Our results demonstrate that a simple  TP53  microarray using short (7-mer) probes, used in combination with a double tandem hybridization approach and a simple multiplex fragment preparation method, can identify common  TP53  point mutations from different DNA sources. All the previous data confirms that the tandem hybridization technology, with the appropriated set of probes, is highly specific and can be confidently employed for diagnostic purposes. This system could provide rapid, economical and accurate mutational screening in the  TP53  gene. We are presently improving our system by adding probes for these and other  TP53  mutational hot spots.TP53TP53TP53TP53Methods IARC TP53 gene database search The distribution of nucleotidic changes in the  TP53  gene associated with all cancers war retrieved from the IARC  TP53  database [ 38 ]. Then, the single base substitutions occurring in the 3 exons of  TP53  most frequently altered in cancers were obtained. Both wild type (accession # U94788) and mutated  TP53  sequences were used to design the probes, stacking oligonucleotides, PCR primers and synthetic targets. Oligonucleotides Four new PCR primers of 20–25 nt length (Table  1 ) were used to amplify two DNA fragments of 108 bp (exon 7: codons 248 and 249) and 92 bp (exon 8: codon 273) within the  TP53  gene. Six stacking oligonucleotides of 17–21 nt length were annealed with their corresponding target DNA's, in three pairs, to produce partially duplex DNA's having a 7-nt gap which is the sequence interrogated by the capture probes (Figure  1A ). Fourteen capture probes (seven-mer length; Table  1 ) were designed, two of them to search the wild type sequences for codons 157 and 158, which were used as negative controls, three more for the wild type 248, 249 and 273 codon sequences and nine to look for mutant sequences. According to our previous experience, 7-mer oligonucleotides with base changes located at central positions were selected as probes in order to yield good discrimination of point mutations by tandem hybridization at room temperature. The probes, which had a 3'-aminolink (3'-aminopropanol) modification for covalent binding to the glass slide surface [ 24 ], were purchased from Integrated DNA Technologies Inc. (Coralville, IA, USA). Biological samples (DNA targets) Twenty-four DNA samples from different sources were probed, some having known wild type or mutant  TP53  sequences and others with unknown  TP53  genotype. These included eight blood samples (B), two obtained from healthy subjects and six obtained from lung cancer affected patients, and ten established cancer cell lines or recombinant DNA's acquired from the ATCC (L). Two of the cell lines were a generous gift from Dr Mary A Salazar (IIB, UNAM) and one was a gift from Dr José Sullivan (INER, SS, Mexico). The other eight cell lines were provided by the DNA bank from Genomic Oncology Laboratory (CMN S XXI). Finally, six recombinant plasmids (P) harboring  TP53  (wild type or different point mutations), provided by MSc. Irene Correa (CMN S XXI) were employed to standardize the hybridization arrays. The names, identification numbers, source and known genotypes in the 24 samples studied are described in Table  2 Target preparation and PCR assay Genomic DNA was isolated and purified using the Genomic DNA Extraction Kit (Life Technologies Inc., Gaithersburg, MD). DNA concentration was determined by absorbance at 260 nm in a spectrophotometer MBA 2000 (Perkin-Elmer) and by the PicoGreen ®  dsDNA Quantitation Kit (Molecular Probes). Plasmid DNA was prepared from bacterial cultures using the alkaline lysis/SDS minipreparation according to the manufacturer's instructions (Life Technologies). The quality of the DNA preparations was assessed by gel electrophoresis in 1% agarose. All the reagents for PCR reactions were purchased from Promega (Madison WI. USA). The PCR primers are described in Table  1 . Oligonucleotides sequences and fragment sizes for each exon were as follows: PCREX7-F and PCREX7-R for a 108 bp product in exon 7, and PCREX8-F and PCREX8-R for a 92 bp fragment in exon 8. The final reaction mixture contained 0.2 mM each dNTP, 50 mM KCl, 10 mM Tris-HCl (pH 8.4), 1.5 mM MgCl 2 , 0.5 μM each primer, 2.5 U of Taq DNA pol (Promega) and purified DNA (50–100 ng) in a final volume of 100 μL. The PCR profile consisted of an initial heating at 94°C for 5 min, followed by 30 cycles of 94°C for 30 s, 55°C for 30 s and 72°C for 30 s, with a final extension step at 72°C for 7 min. The PCR product was assessed by electrophoresis in 1 % agarose gel stained with ethidium bromide. Single-stranded target DNA was prepared by cycle synthesis as follows. A 30-μL aliquot of PCR product was processed using Ultrafree (Millipore, Bedford, MA) spin filters (30,000 M r  cutoff), and resuspended in the same volume of HPLC-grade water (OMNI SOLV ® , EM Science). A 5-μL aliquot of this solution was added to a 100-μL PCR reaction, along with the primer corresponding to the target strand, then incubated for 27 temperature cycles using the same temperature profiles described above. The formation of each amplicon was assessed by mobility shift in agarose gel electrophoresis. Each one of the six stacking oligonucleotides was 5'-labeled by reaction with T4 polynucleotide kinase (Invitrogen, San Diego, CA) as follows. 5 pmol of each dephosphorylated stacking oligonucleotide; 5X Forward Reaction Buffer (5 μl); T4 Polynucleotide Kinase (10 unit); [γ 32 P]ATP (10 μCi/μl, 3000 Ci/mmol) 2.5 μl (NEN, Boston MA), specific activity 7000 Ci/mmol, diluted in sterile water to 7 μCi/μl, and autoclaved water HPLC-grade to 25 μl. The mix was incubated 10 min at 37°C and the reaction was stopped by adding 5 mM EDTA (2.5 μl). To prepare labeled partially duplex (gapped) target DNA's, each pair of γ 32 P-labeled stacking oligonucleotides was preannealed with the respective synthetic DNA target, single-stranded PCR fragments or multiplexed, single-stranded PCR products to form a 7-nt gap in each target. The annealing mixture contained 50 μL 20X SSC, 10 μL 1 M Tris-HCl (pH 8.0), 3 μL 0.5 M EDTA, 0.2 pmol of each labeled stacking oligonucleotide, 10 μL of target DNA, and HPLC-grade H 2 O to a final volume of 90 μL. The mixture was incubated at 95°C for 5 min, 45°C for 5 min, then 6°C for 5 min. Excess [γ 32 P]ATP was removed by filtration through an Ultrafree spin filter (3,000 M r  cutoff) (Millipore. Bedford, MA), and the retained DNA was dissolved in 20 μL of 1X SSC. In the case of multiplexed targets, only 4 stacking oligonucleotides (SO-248-R, SO-249-L, SO-273R and SO-273-L) were added, one pair for each exon in the study, forming gap sizes of 12 and 7 nt for exons 7 and 8, respectively. Thus, with exon 7 a single tandem hybridization was conducted with the glass-tethered 7-mer capture probes, whereas with exon 8 double tandem hybridization was conducted. DNA probe arrays Glass microscope slides were prepared by soaking in hexane 20 min, then 20 min in absolute ethanol followed by drying 5 h at 90°C. Oligonucleotide probes containing 3'-terminal aminopropanol modification were dissolved in sterile water to a final concentration of 20 μM, and 200 μl droplets of each probe were applied to the glass slides using a model 417 Affymetrix (Santa Clara, CA) arrayer to place submicroliter droplets onto glass slides. Each array contained 14 probes: three wild type sequences and nine mutant sequences corresponding to the  TP53  targets under study, two negative controls consisting of 7-mers targeted to the wild type sequences from codons 157 and 158 of  TP53  gene, plus one blank spot without probe. As depicted in Fig.  1B , each  TP53  capture probe was arrayed in triplicate (to assess the reproducibility of the results) in an upward direction starting from position 1 and the printing was divided into three groups. Positions 1–14 were printed first, then the pattern was repeated twice more across the slide. Position 15 was left empty (nothing at all was applied) and served as a negative glass control. After spotting, each slide was washed with water to remove unbound oligonucleotides, air-dried, then stored in a dessicator at room temperature. This attachment procedure results in a surface density of 10 10 -10 11  molecules mm 2 , which corresponds to intermolecular spacing of about 30–100 Å across the surface [ 25 ]. Hybridization experiments Just prior to hybridization the slides were soaked for 1 h at room temperature with blocking agent (10 mM tripolyphosphate) and then rinsed twice with water and air-dried. The hybridization cocktail contained: 118 μL 5 M tetramethyl-ammonium chloride (TMAC) (Life Technologies), 9 μL 1 M Tris-HCl (pH 8.0) (Life Technologies), 0.72 μL 0.5 M EDTA, 1.8 μL 10% (w/v) sodium dodecyl sulfate, 14.4 μL 40% (w/v) polyethylene glycol, 20 μL labeled target DNA in 1X SSC, and 35.3 μL HPLC-grade water. A 40-μL aliquot of this cocktail was placed onto each array and a cover slip was applied. Slides were incubated in a humid chamber for 3 h at 25°C. After hybridization, the slides were washed by dipping several times in the same hybridization solution without polyethylene glycol and DNA, air-dried, and then wrapped in plastic film and placed against X-ray film (Kodak BioMax) for autoradiography. Detection and quantitation of  32 P-labeled target molecules bound across the hybridization array was performed with a scanner (HP Scanjet 4400 c), and analysis of densitometric images was performed using ScanAnalyze 2 software (Stanford University). To provide confidence in the interpretation of the signals produced by human samples, reference hybridization patterns were prepared using a full set of synthetic targets. For this purpose, thirteen synthetic targets (44–50 nt), representing the wild type and mutant sequences, were used independently and in combination, to represent homozygous and heterozygous conditions. Sequencing of PCR products The PCR products obtained were purified using the QIAEX II kit (QIAGEN Inc. USA). For each PCR product the presence or absence of a mutation in exons 7 and 8 was demonstrated via sequencing using the Big Dye Terminator kit (Perkin-Elmer) and a model 373 automated DNA sequencer (Instruments Core Center of Health Research Council- IMSS).
Methods
IARC TP53 gene database search The distribution of nucleotidic changes in the  TP53  gene associated with all cancers war retrieved from the IARC  TP53  database [ 38 ]. Then, the single base substitutions occurring in the 3 exons of  TP53  most frequently altered in cancers were obtained. Both wild type (accession # U94788) and mutated  TP53  sequences were used to design the probes, stacking oligonucleotides, PCR primers and synthetic targets.
IARC TP53 gene database search
The distribution of nucleotidic changes in the  TP53  gene associated with all cancers war retrieved from the IARC  TP53  database [ 38 ]. Then, the single base substitutions occurring in the 3 exons of  TP53  most frequently altered in cancers were obtained. Both wild type (accession # U94788) and mutated  TP53  sequences were used to design the probes, stacking oligonucleotides, PCR primers and synthetic targets.TP53TP53TP53TP53Oligonucleotides Four new PCR primers of 20–25 nt length (Table  1 ) were used to amplify two DNA fragments of 108 bp (exon 7: codons 248 and 249) and 92 bp (exon 8: codon 273) within the  TP53  gene. Six stacking oligonucleotides of 17–21 nt length were annealed with their corresponding target DNA's, in three pairs, to produce partially duplex DNA's having a 7-nt gap which is the sequence interrogated by the capture probes (Figure  1A ). Fourteen capture probes (seven-mer length; Table  1 ) were designed, two of them to search the wild type sequences for codons 157 and 158, which were used as negative controls, three more for the wild type 248, 249 and 273 codon sequences and nine to look for mutant sequences. According to our previous experience, 7-mer oligonucleotides with base changes located at central positions were selected as probes in order to yield good discrimination of point mutations by tandem hybridization at room temperature. The probes, which had a 3'-aminolink (3'-aminopropanol) modification for covalent binding to the glass slide surface [ 24 ], were purchased from Integrated DNA Technologies Inc. (Coralville, IA, USA).
Oligonucleotides
Four new PCR primers of 20–25 nt length (Table  1 ) were used to amplify two DNA fragments of 108 bp (exon 7: codons 248 and 249) and 92 bp (exon 8: codon 273) within the  TP53  gene. Six stacking oligonucleotides of 17–21 nt length were annealed with their corresponding target DNA's, in three pairs, to produce partially duplex DNA's having a 7-nt gap which is the sequence interrogated by the capture probes (Figure  1A ). Fourteen capture probes (seven-mer length; Table  1 ) were designed, two of them to search the wild type sequences for codons 157 and 158, which were used as negative controls, three more for the wild type 248, 249 and 273 codon sequences and nine to look for mutant sequences. According to our previous experience, 7-mer oligonucleotides with base changes located at central positions were selected as probes in order to yield good discrimination of point mutations by tandem hybridization at room temperature. The probes, which had a 3'-aminolink (3'-aminopropanol) modification for covalent binding to the glass slide surface [ 24 ], were purchased from Integrated DNA Technologies Inc. (Coralville, IA, USA).TP53Biological samples (DNA targets) Twenty-four DNA samples from different sources were probed, some having known wild type or mutant  TP53  sequences and others with unknown  TP53  genotype. These included eight blood samples (B), two obtained from healthy subjects and six obtained from lung cancer affected patients, and ten established cancer cell lines or recombinant DNA's acquired from the ATCC (L). Two of the cell lines were a generous gift from Dr Mary A Salazar (IIB, UNAM) and one was a gift from Dr José Sullivan (INER, SS, Mexico). The other eight cell lines were provided by the DNA bank from Genomic Oncology Laboratory (CMN S XXI). Finally, six recombinant plasmids (P) harboring  TP53  (wild type or different point mutations), provided by MSc. Irene Correa (CMN S XXI) were employed to standardize the hybridization arrays. The names, identification numbers, source and known genotypes in the 24 samples studied are described in Table  2
Biological samples (DNA targets)
Twenty-four DNA samples from different sources were probed, some having known wild type or mutant  TP53  sequences and others with unknown  TP53  genotype. These included eight blood samples (B), two obtained from healthy subjects and six obtained from lung cancer affected patients, and ten established cancer cell lines or recombinant DNA's acquired from the ATCC (L). Two of the cell lines were a generous gift from Dr Mary A Salazar (IIB, UNAM) and one was a gift from Dr José Sullivan (INER, SS, Mexico). The other eight cell lines were provided by the DNA bank from Genomic Oncology Laboratory (CMN S XXI). Finally, six recombinant plasmids (P) harboring  TP53  (wild type or different point mutations), provided by MSc. Irene Correa (CMN S XXI) were employed to standardize the hybridization arrays. The names, identification numbers, source and known genotypes in the 24 samples studied are described in Table  2TP53TP53TP53Target preparation and PCR assay Genomic DNA was isolated and purified using the Genomic DNA Extraction Kit (Life Technologies Inc., Gaithersburg, MD). DNA concentration was determined by absorbance at 260 nm in a spectrophotometer MBA 2000 (Perkin-Elmer) and by the PicoGreen ®  dsDNA Quantitation Kit (Molecular Probes). Plasmid DNA was prepared from bacterial cultures using the alkaline lysis/SDS minipreparation according to the manufacturer's instructions (Life Technologies). The quality of the DNA preparations was assessed by gel electrophoresis in 1% agarose. All the reagents for PCR reactions were purchased from Promega (Madison WI. USA). The PCR primers are described in Table  1 . Oligonucleotides sequences and fragment sizes for each exon were as follows: PCREX7-F and PCREX7-R for a 108 bp product in exon 7, and PCREX8-F and PCREX8-R for a 92 bp fragment in exon 8. The final reaction mixture contained 0.2 mM each dNTP, 50 mM KCl, 10 mM Tris-HCl (pH 8.4), 1.5 mM MgCl 2 , 0.5 μM each primer, 2.5 U of Taq DNA pol (Promega) and purified DNA (50–100 ng) in a final volume of 100 μL. The PCR profile consisted of an initial heating at 94°C for 5 min, followed by 30 cycles of 94°C for 30 s, 55°C for 30 s and 72°C for 30 s, with a final extension step at 72°C for 7 min. The PCR product was assessed by electrophoresis in 1 % agarose gel stained with ethidium bromide. Single-stranded target DNA was prepared by cycle synthesis as follows. A 30-μL aliquot of PCR product was processed using Ultrafree (Millipore, Bedford, MA) spin filters (30,000 M r  cutoff), and resuspended in the same volume of HPLC-grade water (OMNI SOLV ® , EM Science). A 5-μL aliquot of this solution was added to a 100-μL PCR reaction, along with the primer corresponding to the target strand, then incubated for 27 temperature cycles using the same temperature profiles described above. The formation of each amplicon was assessed by mobility shift in agarose gel electrophoresis. Each one of the six stacking oligonucleotides was 5'-labeled by reaction with T4 polynucleotide kinase (Invitrogen, San Diego, CA) as follows. 5 pmol of each dephosphorylated stacking oligonucleotide; 5X Forward Reaction Buffer (5 μl); T4 Polynucleotide Kinase (10 unit); [γ 32 P]ATP (10 μCi/μl, 3000 Ci/mmol) 2.5 μl (NEN, Boston MA), specific activity 7000 Ci/mmol, diluted in sterile water to 7 μCi/μl, and autoclaved water HPLC-grade to 25 μl. The mix was incubated 10 min at 37°C and the reaction was stopped by adding 5 mM EDTA (2.5 μl). To prepare labeled partially duplex (gapped) target DNA's, each pair of γ 32 P-labeled stacking oligonucleotides was preannealed with the respective synthetic DNA target, single-stranded PCR fragments or multiplexed, single-stranded PCR products to form a 7-nt gap in each target. The annealing mixture contained 50 μL 20X SSC, 10 μL 1 M Tris-HCl (pH 8.0), 3 μL 0.5 M EDTA, 0.2 pmol of each labeled stacking oligonucleotide, 10 μL of target DNA, and HPLC-grade H 2 O to a final volume of 90 μL. The mixture was incubated at 95°C for 5 min, 45°C for 5 min, then 6°C for 5 min. Excess [γ 32 P]ATP was removed by filtration through an Ultrafree spin filter (3,000 M r  cutoff) (Millipore. Bedford, MA), and the retained DNA was dissolved in 20 μL of 1X SSC. In the case of multiplexed targets, only 4 stacking oligonucleotides (SO-248-R, SO-249-L, SO-273R and SO-273-L) were added, one pair for each exon in the study, forming gap sizes of 12 and 7 nt for exons 7 and 8, respectively. Thus, with exon 7 a single tandem hybridization was conducted with the glass-tethered 7-mer capture probes, whereas with exon 8 double tandem hybridization was conducted.
Target preparation and PCR assay
Genomic DNA was isolated and purified using the Genomic DNA Extraction Kit (Life Technologies Inc., Gaithersburg, MD). DNA concentration was determined by absorbance at 260 nm in a spectrophotometer MBA 2000 (Perkin-Elmer) and by the PicoGreen ®  dsDNA Quantitation Kit (Molecular Probes).Plasmid DNA was prepared from bacterial cultures using the alkaline lysis/SDS minipreparation according to the manufacturer's instructions (Life Technologies).The quality of the DNA preparations was assessed by gel electrophoresis in 1% agarose. All the reagents for PCR reactions were purchased from Promega (Madison WI. USA). The PCR primers are described in Table  1 . Oligonucleotides sequences and fragment sizes for each exon were as follows: PCREX7-F and PCREX7-R for a 108 bp product in exon 7, and PCREX8-F and PCREX8-R for a 92 bp fragment in exon 8. The final reaction mixture contained 0.2 mM each dNTP, 50 mM KCl, 10 mM Tris-HCl (pH 8.4), 1.5 mM MgCl 2 , 0.5 μM each primer, 2.5 U of Taq DNA pol (Promega) and purified DNA (50–100 ng) in a final volume of 100 μL. The PCR profile consisted of an initial heating at 94°C for 5 min, followed by 30 cycles of 94°C for 30 s, 55°C for 30 s and 72°C for 30 s, with a final extension step at 72°C for 7 min. The PCR product was assessed by electrophoresis in 1 % agarose gel stained with ethidium bromide.Single-stranded target DNA was prepared by cycle synthesis as follows. A 30-μL aliquot of PCR product was processed using Ultrafree (Millipore, Bedford, MA) spin filters (30,000 M r  cutoff), and resuspended in the same volume of HPLC-grade water (OMNI SOLV ® , EM Science). A 5-μL aliquot of this solution was added to a 100-μL PCR reaction, along with the primer corresponding to the target strand, then incubated for 27 temperature cycles using the same temperature profiles described above. The formation of each amplicon was assessed by mobility shift in agarose gel electrophoresis.Each one of the six stacking oligonucleotides was 5'-labeled by reaction with T4 polynucleotide kinase (Invitrogen, San Diego, CA) as follows. 5 pmol of each dephosphorylated stacking oligonucleotide; 5X Forward Reaction Buffer (5 μl); T4 Polynucleotide Kinase (10 unit); [γ 32 P]ATP (10 μCi/μl, 3000 Ci/mmol) 2.5 μl (NEN, Boston MA), specific activity 7000 Ci/mmol, diluted in sterile water to 7 μCi/μl, and autoclaved water HPLC-grade to 25 μl. The mix was incubated 10 min at 37°C and the reaction was stopped by adding 5 mM EDTA (2.5 μl).To prepare labeled partially duplex (gapped) target DNA's, each pair of γ 32 P-labeled stacking oligonucleotides was preannealed with the respective synthetic DNA target, single-stranded PCR fragments or multiplexed, single-stranded PCR products to form a 7-nt gap in each target. The annealing mixture contained 50 μL 20X SSC, 10 μL 1 M Tris-HCl (pH 8.0), 3 μL 0.5 M EDTA, 0.2 pmol of each labeled stacking oligonucleotide, 10 μL of target DNA, and HPLC-grade H 2 O to a final volume of 90 μL. The mixture was incubated at 95°C for 5 min, 45°C for 5 min, then 6°C for 5 min. Excess [γ 32 P]ATP was removed by filtration through an Ultrafree spin filter (3,000 M r  cutoff) (Millipore. Bedford, MA), and the retained DNA was dissolved in 20 μL of 1X SSC.In the case of multiplexed targets, only 4 stacking oligonucleotides (SO-248-R, SO-249-L, SO-273R and SO-273-L) were added, one pair for each exon in the study, forming gap sizes of 12 and 7 nt for exons 7 and 8, respectively. Thus, with exon 7 a single tandem hybridization was conducted with the glass-tethered 7-mer capture probes, whereas with exon 8 double tandem hybridization was conducted.DNA probe arrays Glass microscope slides were prepared by soaking in hexane 20 min, then 20 min in absolute ethanol followed by drying 5 h at 90°C. Oligonucleotide probes containing 3'-terminal aminopropanol modification were dissolved in sterile water to a final concentration of 20 μM, and 200 μl droplets of each probe were applied to the glass slides using a model 417 Affymetrix (Santa Clara, CA) arrayer to place submicroliter droplets onto glass slides. Each array contained 14 probes: three wild type sequences and nine mutant sequences corresponding to the  TP53  targets under study, two negative controls consisting of 7-mers targeted to the wild type sequences from codons 157 and 158 of  TP53  gene, plus one blank spot without probe. As depicted in Fig.  1B , each  TP53  capture probe was arrayed in triplicate (to assess the reproducibility of the results) in an upward direction starting from position 1 and the printing was divided into three groups. Positions 1–14 were printed first, then the pattern was repeated twice more across the slide. Position 15 was left empty (nothing at all was applied) and served as a negative glass control. After spotting, each slide was washed with water to remove unbound oligonucleotides, air-dried, then stored in a dessicator at room temperature. This attachment procedure results in a surface density of 10 10 -10 11  molecules mm 2 , which corresponds to intermolecular spacing of about 30–100 Å across the surface [ 25 ].
DNA probe arrays
Glass microscope slides were prepared by soaking in hexane 20 min, then 20 min in absolute ethanol followed by drying 5 h at 90°C. Oligonucleotide probes containing 3'-terminal aminopropanol modification were dissolved in sterile water to a final concentration of 20 μM, and 200 μl droplets of each probe were applied to the glass slides using a model 417 Affymetrix (Santa Clara, CA) arrayer to place submicroliter droplets onto glass slides. Each array contained 14 probes: three wild type sequences and nine mutant sequences corresponding to the  TP53  targets under study, two negative controls consisting of 7-mers targeted to the wild type sequences from codons 157 and 158 of  TP53  gene, plus one blank spot without probe. As depicted in Fig.  1B , each  TP53  capture probe was arrayed in triplicate (to assess the reproducibility of the results) in an upward direction starting from position 1 and the printing was divided into three groups. Positions 1–14 were printed first, then the pattern was repeated twice more across the slide. Position 15 was left empty (nothing at all was applied) and served as a negative glass control. After spotting, each slide was washed with water to remove unbound oligonucleotides, air-dried, then stored in a dessicator at room temperature. This attachment procedure results in a surface density of 10 10 -10 11  molecules mm 2 , which corresponds to intermolecular spacing of about 30–100 Å across the surface [ 25 ].TP53TP53TP53Hybridization experiments Just prior to hybridization the slides were soaked for 1 h at room temperature with blocking agent (10 mM tripolyphosphate) and then rinsed twice with water and air-dried. The hybridization cocktail contained: 118 μL 5 M tetramethyl-ammonium chloride (TMAC) (Life Technologies), 9 μL 1 M Tris-HCl (pH 8.0) (Life Technologies), 0.72 μL 0.5 M EDTA, 1.8 μL 10% (w/v) sodium dodecyl sulfate, 14.4 μL 40% (w/v) polyethylene glycol, 20 μL labeled target DNA in 1X SSC, and 35.3 μL HPLC-grade water. A 40-μL aliquot of this cocktail was placed onto each array and a cover slip was applied. Slides were incubated in a humid chamber for 3 h at 25°C. After hybridization, the slides were washed by dipping several times in the same hybridization solution without polyethylene glycol and DNA, air-dried, and then wrapped in plastic film and placed against X-ray film (Kodak BioMax) for autoradiography. Detection and quantitation of  32 P-labeled target molecules bound across the hybridization array was performed with a scanner (HP Scanjet 4400 c), and analysis of densitometric images was performed using ScanAnalyze 2 software (Stanford University). To provide confidence in the interpretation of the signals produced by human samples, reference hybridization patterns were prepared using a full set of synthetic targets. For this purpose, thirteen synthetic targets (44–50 nt), representing the wild type and mutant sequences, were used independently and in combination, to represent homozygous and heterozygous conditions.
Hybridization experiments
Just prior to hybridization the slides were soaked for 1 h at room temperature with blocking agent (10 mM tripolyphosphate) and then rinsed twice with water and air-dried. The hybridization cocktail contained: 118 μL 5 M tetramethyl-ammonium chloride (TMAC) (Life Technologies), 9 μL 1 M Tris-HCl (pH 8.0) (Life Technologies), 0.72 μL 0.5 M EDTA, 1.8 μL 10% (w/v) sodium dodecyl sulfate, 14.4 μL 40% (w/v) polyethylene glycol, 20 μL labeled target DNA in 1X SSC, and 35.3 μL HPLC-grade water. A 40-μL aliquot of this cocktail was placed onto each array and a cover slip was applied. Slides were incubated in a humid chamber for 3 h at 25°C. After hybridization, the slides were washed by dipping several times in the same hybridization solution without polyethylene glycol and DNA, air-dried, and then wrapped in plastic film and placed against X-ray film (Kodak BioMax) for autoradiography. Detection and quantitation of  32 P-labeled target molecules bound across the hybridization array was performed with a scanner (HP Scanjet 4400 c), and analysis of densitometric images was performed using ScanAnalyze 2 software (Stanford University).To provide confidence in the interpretation of the signals produced by human samples, reference hybridization patterns were prepared using a full set of synthetic targets. For this purpose, thirteen synthetic targets (44–50 nt), representing the wild type and mutant sequences, were used independently and in combination, to represent homozygous and heterozygous conditions.Sequencing of PCR products The PCR products obtained were purified using the QIAEX II kit (QIAGEN Inc. USA). For each PCR product the presence or absence of a mutation in exons 7 and 8 was demonstrated via sequencing using the Big Dye Terminator kit (Perkin-Elmer) and a model 373 automated DNA sequencer (Instruments Core Center of Health Research Council- IMSS).
Sequencing of PCR products
The PCR products obtained were purified using the QIAEX II kit (QIAGEN Inc. USA). For each PCR product the presence or absence of a mutation in exons 7 and 8 was demonstrated via sequencing using the Big Dye Terminator kit (Perkin-Elmer) and a model 373 automated DNA sequencer (Instruments Core Center of Health Research Council- IMSS).Authors' contributions ARL performed all molecular assays, data collection and analysis, and drafted the manuscript. RMR conceived and designed the study, coordinated and managed the study, performed data analysis and participated in drafting the manuscript. MSV conceived and designed the study, coordinated and managed the study, performed data analysis and participated in drafting the manuscript. JMEL participated in the design and coordination of the study. AMT designed the oligonucleotide probes, performed bioinformatic analysis of targets, and participated in drafting the manuscript. KLB assisted in coordination of the study, data analysis, and drafting the manuscript. All authors read and approved the final manuscript.
Authors' contributions
ARL performed all molecular assays, data collection and analysis, and drafted the manuscript. RMR conceived and designed the study, coordinated and managed the study, performed data analysis and participated in drafting the manuscript. MSV conceived and designed the study, coordinated and managed the study, performed data analysis and participated in drafting the manuscript. JMEL participated in the design and coordination of the study. AMT designed the oligonucleotide probes, performed bioinformatic analysis of targets, and participated in drafting the manuscript. KLB assisted in coordination of the study, data analysis, and drafting the manuscript. All authors read and approved the final manuscript.


Recombination is a nearly ubituitous feature of genomes; where and when it occurs can provide insights about its evolution and can affect our ability to identify genes that cause disease

Consider a piece of text, either this one that you are now reading or any other. Surely they are all pretty much alike, in so far as they are all run-on strings of characters. In this same sense, we can envision that all DNA strands are alike because all are monotonous polymers with the same general chemical makeup. Indeed, this is how we think of DNA when considering its basic function of inheritance, in which all parts of all chromosomes must be duplicated and then passed from one cell generation to the next. The capacity for inheritance is fundamentally a consequence of DNA's general molecular structure, and not of its sequence per se, as  Watson and Crick (1953) , and indeed  Muller (1922)  long before them, well appreciated. Muller did not know that genes are made of DNA, but he did realize that, whatever genes were made of, they must have a general capacity to replicate, regardless of the information they carry ( Muller 1922 ).But sequence does matter when DNA fulfills its other, more directly functional role. When the DNA that makes up a gene is exposed and expressed, when a gene is serving its individual function, then the detailed sequence means all.So where does recombination ( Box 1 ) fit in? Is recombination something that happens to DNA generally? Or does it happen to particular sequences? Bacteria have their chi (χ) sequence, which is a specific series of eight base pairs in the DNA of the bacterial chromosome that stimulate the action of proteins that bring about recombination ( Eggleston and West 1997 ). Similarly, the immunoglobulin genes of mammals have recombination signal sequences that are involved in V-J joining—a kind of somatic recombination involving the joining of a variable gene segment and a joining segment to form an immunoglobulin gene ( Krangel 2003 ). But does normal meiotic recombination depend on the local DNA sequence? In yeast, as well as mammals (mice and humans), the answer is partly yes, for it is clear that chromosomes have local recombination hotspots where crossing over is much more likely to occur than in other places on the chromosome. Recombination hotspots are local regions of chromosomes, on the order of one or two thousand base pairs of DNA (or less—their length is difficult to measure), in which recombination events tend to be concentrated. Often they are flanked by “coldspots,” regions of lower than average frequency of recombination ( Lichten and Goldman 1995 ).Diverse Implications of Recombination Hotspots: The Study of Meiosis and the Mapping of Human Disease Alleles Recombination hotspots are of strong interest to at least two quite different groups of biologists. For geneticists and cell biologists who study meiosis, the existence of recombination hotspots offers a way to learn what other processes are associated with recombination. This is partly how we know that homologous crossovers in yeast and other eukaryotes are initiated by the cleavage of single chromosomes, called “double-strand breaks” ( Box 1 ). It turns out that because of this causal linkage, the hotspots for doublestrand breaks and the hotspots for recombination are one and the same ( Game et al. 1989 ;  Sun et al. 1989 ;  Keeney et al. 1997 ;  Lopes et al. 1999 ;  Allers and Lichten 2001 ;  Hunter 2003 ). For population geneticists, much of the interest in recombination hotspots comes from their possible effect on the patterns of DNA sequence variation along human chromosomes and from the possibility that these patterns could be used to map the position of alleles that cause disease. When multiple copies of the DNA sequence of a gene, or of a larger region of a chromosome, are aligned, they reveal the location and distribution of variation at individual nucleotide positions—single nucleotide polymorphisms (SNPs). Each particular sequence, or haplotype, will carry a configuration for the SNPs for that region ( Figure 1 ). Investigators have long known that SNPs that are adjacent or near each other tend to be highly correlated in their pattern and to exhibit strong linkage disequilibrium ( Box 1 ). It is this linkage disequilibrium that enables scientists to map the locations of mutations that cause heritable genetic diseases. If alleles that cause a disease have the same kind of linkage disequilibrium with nearby SNPs as SNPs generally have with each other, then one could search for genes with disease alleles by looking for a pattern of SNPs that is found only in people who have the disease. This general method for mapping disease alleles is called “association mapping,” and it is basically a search for linkage disequilibrium between disease alleles and other SNPs. Whether or not association mapping works depends on the actual patterns of linkage that occur among SNPs in human populations, and these patterns depend in turn on how much recombination has occurred in the past (as well as on other demographic and mutation processes). Figure 1 A Hypothetical Example of Eight Aligned Haplotypes for All the SNPs Found in a Region Base positions that are not variable are not shown. Blocks of adjacent SNPs that revealed no evidence of historical recombination are flanked by vertical red bars. Two longer haplotype blocks are indicated in green. The presence of historical recombination was discerned by the four-gamete criterion. In brief, if the haplotypes for two SNPs, each with two bases (e.g., A/G at one SNP and C/T at the second), reveal all four possible combinations (i.e., A-C, A-T, GC, and G-T) then this is evidence that there has been a recombination event between these SNPs in the history of the sample of haplotypes ( Hudson and Kaplan 1985 ). If haplotype blocks are long, then it is possible to represent much of the haplotype diversity using just a small sample of the SNPs found within that region. With the advent of larger human haplotype data sets, it has become clear that there are often fairly long regions with very high linkage disequilibrium ( Daly et al. 2001 ;  Patil et al. 2001 ;  Gabriel et al. 2002 ). This pattern of variation has been characterized as occurring in “haplotype blocks,” which are apparent regions of low recombination (or high linkage disequilibrium).  Figure 1  shows a hypothetical example of haplotype blocks among eight haplotypes for a series of SNPs found over a region of a chromosome. Given diverse evidence of recombination hotspots in humans, a much discussed question is whether recombination hotspots play a large role in the formation of the pattern of haplotype blocks ( Wang et al. 2002 ;  Innan et al. 2003 ;  Phillips et al. 2003 ;  Stumpf and Goldstein 2003 ). The occurrence of haplotype blocks has inspired the HAPMAP project ( http://www.hapmap.org/),  which has the goal of identifying a subset of SNPs that capture most of the relevant linkage information in the human genome ( IHC 2003 ). If one had a subset of all common SNPs, with one or two per haplotype block, then this subset would contain much of the available information for association mapping of disease alleles.
Diverse Implications of Recombination Hotspots: The Study of Meiosis and the Mapping of Human Disease Alleles
Recombination hotspots are of strong interest to at least two quite different groups of biologists. For geneticists and cell biologists who study meiosis, the existence of recombination hotspots offers a way to learn what other processes are associated with recombination. This is partly how we know that homologous crossovers in yeast and other eukaryotes are initiated by the cleavage of single chromosomes, called “double-strand breaks” ( Box 1 ). It turns out that because of this causal linkage, the hotspots for doublestrand breaks and the hotspots for recombination are one and the same ( Game et al. 1989 ;  Sun et al. 1989 ;  Keeney et al. 1997 ;  Lopes et al. 1999 ;  Allers and Lichten 2001 ;  Hunter 2003 ).For population geneticists, much of the interest in recombination hotspots comes from their possible effect on the patterns of DNA sequence variation along human chromosomes and from the possibility that these patterns could be used to map the position of alleles that cause disease. When multiple copies of the DNA sequence of a gene, or of a larger region of a chromosome, are aligned, they reveal the location and distribution of variation at individual nucleotide positions—single nucleotide polymorphisms (SNPs). Each particular sequence, or haplotype, will carry a configuration for the SNPs for that region ( Figure 1 ). Investigators have long known that SNPs that are adjacent or near each other tend to be highly correlated in their pattern and to exhibit strong linkage disequilibrium ( Box 1 ). It is this linkage disequilibrium that enables scientists to map the locations of mutations that cause heritable genetic diseases. If alleles that cause a disease have the same kind of linkage disequilibrium with nearby SNPs as SNPs generally have with each other, then one could search for genes with disease alleles by looking for a pattern of SNPs that is found only in people who have the disease. This general method for mapping disease alleles is called “association mapping,” and it is basically a search for linkage disequilibrium between disease alleles and other SNPs. Whether or not association mapping works depends on the actual patterns of linkage that occur among SNPs in human populations, and these patterns depend in turn on how much recombination has occurred in the past (as well as on other demographic and mutation processes).With the advent of larger human haplotype data sets, it has become clear that there are often fairly long regions with very high linkage disequilibrium ( Daly et al. 2001 ;  Patil et al. 2001 ;  Gabriel et al. 2002 ). This pattern of variation has been characterized as occurring in “haplotype blocks,” which are apparent regions of low recombination (or high linkage disequilibrium).  Figure 1  shows a hypothetical example of haplotype blocks among eight haplotypes for a series of SNPs found over a region of a chromosome. Given diverse evidence of recombination hotspots in humans, a much discussed question is whether recombination hotspots play a large role in the formation of the pattern of haplotype blocks ( Wang et al. 2002 ;  Innan et al. 2003 ;  Phillips et al. 2003 ;  Stumpf and Goldstein 2003 ). The occurrence of haplotype blocks has inspired the HAPMAP project ( http://www.hapmap.org/),  which has the goal of identifying a subset of SNPs that capture most of the relevant linkage information in the human genome ( IHC 2003 ). If one had a subset of all common SNPs, with one or two per haplotype block, then this subset would contain much of the available information for association mapping of disease alleles.The Evolution of Recombination and (Possibly) Recombination Hotspots Recombination is a nearly ubiquitous feature of genomes, and a great many theories have been put forward to explain why it would be evolutionarily advantageous for genes to regularly break with one another to join new genes ( Barton and Charlesworth 1998 ). By and large these theories predict that recombination should occur more often where genes occur in higher concentration and that it should happen less often in areas of the genome where genes are spaced far apart. This expectation is roughly born out in the human genome, where recombination rates are higher in regions of the genome with higher gene density ( Fullerton et al. 2001 ;  Kong et al. 2002 ). To consider the possible evolutionary advantages of individual recombination hotspots, we can draw from theory on the evolution of recombination modifiers. In particular, recent population genetic theory has brought to light some fairly general circumstances for which mutations that raise recombination rates would be favored by natural selection ( Barton 1995 ;  Otto and Barton 1997 ;  Otto and Barton 2001 ;  Otto and Lenormand 2002 ). The basic idea is that linkage disequilibrium can easily occur (for many reasons) between two (or more) polymorphic sites that are under selection. When this occurs, an allele that raises the recombination rate (and decreases the linkage disequilibrium) can cause selection to act more efficiently. If an allele that is under positive or negative selection always occurs with an allele at another locus that is also under selection (i.e., the two loci are in strong linkage disequilibrium), then selection cannot act on one locus independently of the second locus. As new, multilocus configurations of beneficial alleles are generated (by recombination) and increase in frequency by selection, the modifiers of recombination that caused the production of those beneficial configurations increase in frequency with them. A key piece of evidence supporting this kind of theory of the evolution of recombination is directional selection, like that which occurs in artificial selection experiments, which often generates a correlated elevation in recombination rates ( Otto and Lenormand 2002 ). Connecting these ideas about the evolution of recombination modifiers to the question of recombination hotspots, we come to the possibility that individual hotspots may have arisen as a byproduct of linkage disequilibrium between genes on either side of the hotspot that were under selection. This situation would create a kind of selection pressure favoring recombinant haplotypes and thus also favoring those chromosomes that happen to have a high recombination rate between the selected genes. If true, then we might expect local recombination rates (i.e., hotspots and coldspots for recombination) to fluctuate in location and intensity, in ways that would be hard to precisely predict without knowing what genes have been under selection and what patterns of linkage disequilibria there may have been. In this light, the paper by  Ptak et al. (2004)  in this issue of  PLoS Biology  is especially interesting. They report that chimpanzees do not have a recombination hotspot in the TAP2 region where humans have a fairly well characterized recombination hotspot ( Jeffreys and Neumann 2002 ). Ptak et al.'s is a statistical study of linkage disequilibrium in the TAP2 region of chimpanzees and humans, and is less direct than the sperm-typing study of  Jeffreys and Neumann (2002) . However the contrast in linkage patterns between humans and our closest relatives suggests that recombination hotspots can evolve fairly quickly.
The Evolution of Recombination and (Possibly) Recombination Hotspots
Recombination is a nearly ubiquitous feature of genomes, and a great many theories have been put forward to explain why it would be evolutionarily advantageous for genes to regularly break with one another to join new genes ( Barton and Charlesworth 1998 ). By and large these theories predict that recombination should occur more often where genes occur in higher concentration and that it should happen less often in areas of the genome where genes are spaced far apart. This expectation is roughly born out in the human genome, where recombination rates are higher in regions of the genome with higher gene density ( Fullerton et al. 2001 ;  Kong et al. 2002 ).To consider the possible evolutionary advantages of individual recombination hotspots, we can draw from theory on the evolution of recombination modifiers. In particular, recent population genetic theory has brought to light some fairly general circumstances for which mutations that raise recombination rates would be favored by natural selection ( Barton 1995 ;  Otto and Barton 1997 ;  Otto and Barton 2001 ;  Otto and Lenormand 2002 ). The basic idea is that linkage disequilibrium can easily occur (for many reasons) between two (or more) polymorphic sites that are under selection. When this occurs, an allele that raises the recombination rate (and decreases the linkage disequilibrium) can cause selection to act more efficiently. If an allele that is under positive or negative selection always occurs with an allele at another locus that is also under selection (i.e., the two loci are in strong linkage disequilibrium), then selection cannot act on one locus independently of the second locus. As new, multilocus configurations of beneficial alleles are generated (by recombination) and increase in frequency by selection, the modifiers of recombination that caused the production of those beneficial configurations increase in frequency with them. A key piece of evidence supporting this kind of theory of the evolution of recombination is directional selection, like that which occurs in artificial selection experiments, which often generates a correlated elevation in recombination rates ( Otto and Lenormand 2002 ).Connecting these ideas about the evolution of recombination modifiers to the question of recombination hotspots, we come to the possibility that individual hotspots may have arisen as a byproduct of linkage disequilibrium between genes on either side of the hotspot that were under selection. This situation would create a kind of selection pressure favoring recombinant haplotypes and thus also favoring those chromosomes that happen to have a high recombination rate between the selected genes. If true, then we might expect local recombination rates (i.e., hotspots and coldspots for recombination) to fluctuate in location and intensity, in ways that would be hard to precisely predict without knowing what genes have been under selection and what patterns of linkage disequilibria there may have been.In this light, the paper by  Ptak et al. (2004)  in this issue of  PLoS Biology  is especially interesting. They report that chimpanzees do not have a recombination hotspot in the TAP2 region where humans have a fairly well characterized recombination hotspot ( Jeffreys and Neumann 2002 ). Ptak et al.'s is a statistical study of linkage disequilibrium in the TAP2 region of chimpanzees and humans, and is less direct than the sperm-typing study of  Jeffreys and Neumann (2002) . However the contrast in linkage patterns between humans and our closest relatives suggests that recombination hotspots can evolve fairly quickly.PLoS BiologyFunctional Constraints on Recombination Hotspots As appealing as the recombination modifier theory of recombination hotspots may be, there is circumstantial evidence that argues against it and that suggests that recombination hotspots are not directly the byproduct of selection on alleles in linkage disequilibrium. Particularly important in this regard is that some wellstudied organisms (notably the worm  Caenorhabditis elegans  and the fruitfly  Drosophila melanogaster ) have not shown evidence of recombination hotspots. If we compare these organisms with yeast and mammals, which do show hotspots, we gain some more insight into the factors affecting the evolution of hotspots. Recall that double-strand breaks are the sites where recombination is initiated during meiosis, and that this is true regardless of the presence of hotspots for both phenomena. Apparently it is the case in yeast and mammals that both recombination and double-strand breaks are also prerequisites for the proper formation of the synaptonemal complex (SC) ( Figure 2 ) and thus for proper orientation of the spindle apparatus and accurate segregation of chromosomes during meiosis ( Paques and Haber 1999 ;  Lichten 2001 ;  Hunter 2003 ;  Page and Hawley 2003 ). In contrast, neither double-strand breaks nor recombination appear to be required for the formation of the SC in  D. melanogaster  or  C. elegans  ( Zickler and Kleckner 1999 ;  MacQueen et al. 2002 ;  McKim et al. 2002 ;  Hunter 2003 ;  Page and Hawley 2003 ). Double-strand breaks and recombination do indeed co-occur in these model organisms, and are required for proper chromosome segregation, but they occur after the formation of the SC. Both of these species have broad chromosomal regions where crossing over occurs at higher rates than others, but there have been no reports of local recombination hotspots. Figure 2 The Synaptonemal Complex (A) Model of the SC. Lateral elements (light blue rods) of homologous chromosomes align and synapse together via a meshwork of transverse filaments (black lines) and longitudinal filaments (dark blue rods). The longitudinal filaments are collectively referred to as the “central element” of the SC. Ellipsoidal structures called recombination nodules (gray ellipsoid) are constructed on the central region of the SC. As their name implies, recombination nodules are believed to be involved in facilitating meiotic recombination (crossing over). The chromatin (red loops) of each homologue is attached to its corresponding lateral element. Because there are two “sister chromatids” in each homologue, two loops are shown extending laterally from each point along a lateral element. (B) Top: Set of tomato SCs. Chromatin “sheaths” are visible around each SC. Bottom: Two tomato SCs. The chromatin has been stripped from the SCs, allowing the details of the SC to be observed. Each SC has a kinetochore (“ball-like” structure) at its centromere. Recombination nodules, ellipsoidal structures found on the central regions of SCs, mark the sites of crossover events (see inset). Images and legend courtesy of Daniel G. Peterson, Mississippi Genome Exploration Laboratory, Mississippi State University, Mississippi State, Mississippi, United States ( http://www.msstate.edu/research/mgel/index.htm) . Recombination during meiosis seems to be required for proper chromosome segregation; however, in those organisms where recombination and double-strand-break hotspots occur, these phenomena are also required for proper formation of the SC. It is as if the recombination machinery has been partly co-opted for chromosome alignment in some eukaryotes more so than in others. The implication of these findings is that recombination hotspots are byproducts of other functional constraints associated with the recombination process. This does not rule out the evolutionary theory of recombination modifiers, or that the location and intensity of recombination hotspots may evolve rapidly, but it does suggest that we may not need to invoke the evolutionary modifier theory to explain the existence of recombination hotspots.
Functional Constraints on Recombination Hotspots
As appealing as the recombination modifier theory of recombination hotspots may be, there is circumstantial evidence that argues against it and that suggests that recombination hotspots are not directly the byproduct of selection on alleles in linkage disequilibrium. Particularly important in this regard is that some wellstudied organisms (notably the worm  Caenorhabditis elegans  and the fruitfly  Drosophila melanogaster ) have not shown evidence of recombination hotspots. If we compare these organisms with yeast and mammals, which do show hotspots, we gain some more insight into the factors affecting the evolution of hotspots.Recall that double-strand breaks are the sites where recombination is initiated during meiosis, and that this is true regardless of the presence of hotspots for both phenomena. Apparently it is the case in yeast and mammals that both recombination and double-strand breaks are also prerequisites for the proper formation of the synaptonemal complex (SC) ( Figure 2 ) and thus for proper orientation of the spindle apparatus and accurate segregation of chromosomes during meiosis ( Paques and Haber 1999 ;  Lichten 2001 ;  Hunter 2003 ;  Page and Hawley 2003 ). In contrast, neither double-strand breaks nor recombination appear to be required for the formation of the SC in  D. melanogaster  or  C. elegans  ( Zickler and Kleckner 1999 ;  MacQueen et al. 2002 ;  McKim et al. 2002 ;  Hunter 2003 ;  Page and Hawley 2003 ). Double-strand breaks and recombination do indeed co-occur in these model organisms, and are required for proper chromosome segregation, but they occur after the formation of the SC. Both of these species have broad chromosomal regions where crossing over occurs at higher rates than others, but there have been no reports of local recombination hotspots.Recombination during meiosis seems to be required for proper chromosome segregation; however, in those organisms where recombination and double-strand-break hotspots occur, these phenomena are also required for proper formation of the SC. It is as if the recombination machinery has been partly co-opted for chromosome alignment in some eukaryotes more so than in others. The implication of these findings is that recombination hotspots are byproducts of other functional constraints associated with the recombination process. This does not rule out the evolutionary theory of recombination modifiers, or that the location and intensity of recombination hotspots may evolve rapidly, but it does suggest that we may not need to invoke the evolutionary modifier theory to explain the existence of recombination hotspots.Conclusions Recombination hotspots co-occur with double-strand-break hotspots in some eukaryotes, and together these phenomena appear to play an important role in the formation of the SC in those organisms. Given the limited phylogenetic occurrence of recombination hotspots (i.e., their occurrence in some, but not all, species), general theories for the evolution of recombination may not be very helpful for understanding the existence of recombination hotspots. However, in those species where they do occur, it is quite possible that recombination hotspots do evolve in location and intensity. Furthermore, the presence of recombination hotspots in humans may have large effects on the length of local patterns of linkage disequilibrium (haplotype blocks) and thus on our ability to map disease alleles by their association with other markers.
Conclusions
Recombination hotspots co-occur with double-strand-break hotspots in some eukaryotes, and together these phenomena appear to play an important role in the formation of the SC in those organisms. Given the limited phylogenetic occurrence of recombination hotspots (i.e., their occurrence in some, but not all, species), general theories for the evolution of recombination may not be very helpful for understanding the existence of recombination hotspots. However, in those species where they do occur, it is quite possible that recombination hotspots do evolve in location and intensity. Furthermore, the presence of recombination hotspots in humans may have large effects on the length of local patterns of linkage disequilibrium (haplotype blocks) and thus on our ability to map disease alleles by their association with other markers.Box 1. Glossary
 Double-strand break:  A break in both strands of a DNA molecule, as distinguished from a break in just one strand.
 Linkage disequilibrium:  A pattern of association between two SNPs or two loci that each have multiple alleles, such that pairs of particular SNPs or alleles, one from each locus, tend to co-occur within individuals or genomes more often than would be expected if the loci are sorting independently of each other.
 Recombination:  The process of one double-stranded DNA molecule joining with another; specifically in the context of meiosis, the process of two homologous chromosomes exchanging large portions of their DNA (this is also called “crossing over”).

Box 1. Glossary
Double-strand break:  A break in both strands of a DNA molecule, as distinguished from a break in just one strand.Double-strand break:Linkage disequilibrium:  A pattern of association between two SNPs or two loci that each have multiple alleles, such that pairs of particular SNPs or alleles, one from each locus, tend to co-occur within individuals or genomes more often than would be expected if the loci are sorting independently of each other.Linkage disequilibrium:Recombination:  The process of one double-stranded DNA molecule joining with another; specifically in the context of meiosis, the process of two homologous chromosomes exchanging large portions of their DNA (this is also called “crossing over”).Recombination: