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Development under extreme conditions: forensic bioinformatics in the wake of the World Trade Center disaster.

The terrorist attacks of September 11, 2001 resulted in death and devastation in three locations, and extraordinary efforts have been exerted to identify the remains of all victims. As mass fatalities go, this one has been unusual at a policy level because the goal has been not merely to identify remains for every decedent, but to identify every bit of remains found so that even small pieces of tissue can be returned to families for burial. While the human impact at the Pentagon and Shanksville, PA was horrific, the World Trade Center site presented a particularly complex challenge for forensic DNA matching and data handling. A complete and definitive list of all those killed is still elusive, and human remains were crushed and co-mingled by the falling towers. Software tools had never been considered for a problem of this scale and scope. New data handling systems had to be created under extreme software development conditions characterized by incomplete requirements specifications, chaotically changing priorities, truly impossible deadlines and rapidly rolling production releases. Partly because of the company's experience with mtDNA tools built for the Armed Forces DNA Identification Lab starting in 1997, the New York City Office of Chief Medical Examiner [OCME] contacted Gene Codes Corporation in late September as existing data-handling tools began to fail. We began work on the project in mid-October, 2001. Our approach to the problem included: Extreme Programming [XP] methodology for functional software development, On-site time and motion analysis at the OCME for user interface design, Evidentiary references between STR, SNP and mtDNA analysis results, and Separate data Quality Control [QC] and software Quality Assurance [QA] initiatives. A substantial software suite was developed called M-FISys, an acronym for Mass-Fatality Identification System.

Computational Biology↗

The relationship between 5-fluorouracil sensitivity and single nucleotide polymorphisms of the orotate phosphoribosyl transferase gene in colorectal cancer.

Orotate phosphoribosyl transferase (OPRT) is an enzyme playing an important role in exertion of the effect of 5-fluorouracil (5-FU). A type of gene polymorphism, single nucleotide polymorphism (SNP), is considered to be a factor affecting individual differences in exertion of drug effects, and its analysis has recently made progress. We investigated the correlation between SNP of OPRT and 5-FU sensitivity in colon and rectal cancers. The subjects were 31 patients with colorectal cancer who underwent surgical excision between December 2003 and July 2004 at our department. Of SNP of OPRT, 638G/C, 1050T/A, and 1336A/G located in the coding region were analyzed by invader assay. The growth inhibition rate (% IR) of colorectal cancer by 5-FU was obtained by the CDDST method, and 5-FU sensitivity was compared among strains (wild-, homo-, and hetero-types) of each polymorphism. There was no relationship between the strains and 5-FU sensitivity in any of the SNPs. The investigated SNPs of OPRT may have no major influence on 5-FU sensitivity. However, there are many unknown factors in the relationship between SNP of OPRT and 5-FU sensitivity, and SNP analysis of other regions is necessary.

Aged↗

SNPdetector: a software tool for sensitive and accurate SNP detection.

Identification of single nucleotide polymorphisms (SNPs) and mutations is important for the discovery of genetic predisposition to complex diseases. PCR resequencing is the method of choice for de novo SNP discovery. However, manual curation of putative SNPs has been a major bottleneck in the application of this method to high-throughput screening. Therefore it is critical to develop a more sensitive and accurate computational method for automated SNP detection. We developed a software tool, SNPdetector, for automated identification of SNPs and mutations in fluorescence-based resequencing reads. SNPdetector was designed to model the process of human visual inspection and has a very low false positive and false negative rate. We demonstrate the superior performance of SNPdetector in SNP and mutation analysis by comparing its results with those derived by human inspection, PolyPhred (a popular SNP detection tool), and independent genotype assays in three large-scale investigations. The first study identified and validated inter- and intra-subspecies variations in 4,650 traces of 25 inbred mouse strains that belong to either the Mus musculus species or the M. spretus species. Unexpected heterozygosity in CAST/Ei strain was observed in two out of 1,167 mouse SNPs. The second study identified 11,241 candidate SNPs in five ENCODE regions of the human genome covering 2.5 Mb of genomic sequence. Approximately 50% of the candidate SNPs were selected for experimental genotyping; the validation rate exceeded 95%. The third study detected ENU-induced mutations (at 0.04% allele frequency) in 64,896 traces of 1,236 zebra fish. Our analysis of three large and diverse test datasets demonstrated that SNPdetector is an effective tool for genome-scale research and for large-sample clinical studies. SNPdetector runs on Unix/Linux platform and is available publicly (http://lpg.nci.nih.gov).

Algorithms↗

Growth factor binding to 7,12-dimethylbenz(a)anthracene-induced mammary tumors from rats subject to chronic caloric restriction.

Caloric restriction (CR) inhibits tumorigenesis in rodents. To understand the basis for this effect the binding of insulin, insulin-like growth factor I/somatomedin C (IGF-I/Sm-C), insulin-like growth factor II/multiplication stimulating activity (IGF-II/MSA), and epidermal growth factor were examined to membrane preparations of 7,12-dimethylbenz(a)anthracene-induced mammary adenocarcinomas and several normal tissues from female Sprague-Dawley rats. Animals were fed ad libitum (AL) or 25% and 40% calorically restricted diets. Large, palpable (LP) and small, less than or equal to 100 mg, nonpalpable (SNP) tumors were evaluated. Growth factor binding to tumors was differentially affected by CR. IGF-I/Sm-C binding was comparable for AL-LP, AL-SNP, and 25% CR-LP tumors, but elevated in 25% CR-SNP tumors. Scatchard analysis revealed high and low affinity IGF-I/Sm-C binding sites, with AL-SNP and 25% CR-SNP tumors exhibiting similar levels of high affinity sites and at a greater concentration than AL-LP and 25% CR-LP tumors. Insulin binding to mammary tumors was low, i.e., 8- to 13-fold lower than IGF-I/Sm-C binding. The 25% CR-LP and SNP tumors bound 2- to 5-fold more insulin than corresponding AL-LP and SNP tumors. Binding of IGF-II/MSA to these tumor preparations was high, approximately 11- to 25-fold greater than insulin binding, and was unaffected by CR or tumor size. The binding of epidermal growth factor was not detected in any tumor preparations. Receptor binding studies were confirmed with covalent cross-linking and sodium dodecyl sulfate-polyacrylamide gel electrophoresis analyses. Normal tissues exhibited tissue- and growth factor-specific alterations in binding with host CR. Thus, alterations in growth factor binding were not tumor specific, but were less pronounced than in mammary tumors. These findings suggest alterations in IGF-I/Sm-C and insulin binding properties to tumors in relation to CR and tumor size may contribute, in part, to the inhibitory effects of CR on tumorigenesis.

9,10-Dimethyl-1,2-benzanthracene↗

Resistin SNP-420 determines its monocyte mRNA and serum levels inducing type 2 diabetes.

Resistin, secreted from adipocytes, causes insulin resistance in rodents. Its roles and main source in humans remain unknown. The G/G genotype of resistin single nucleotide polymorphism, SNP-420, induces type 2 diabetes mellitus (T2DM) by increasing promoter activity. We elucidated factors correlated with serum resistin and effects of SNP-420 on monocyte resistin mRNA. In 198 T2DM and 157 controls, fasting serum resistin was higher in T2DM. Multiple regression analysis revealed that SNP-420 genotype was the strongest determinant of serum resistin. In T2DM, 1-year duration of T2DM and 1% HbA1c was also correlated with 0.19 and 0.54 ng/ml serum resistin, respectively. Logistic regression analysis revealed that serum resistin was an independent factor for T2DM. In 23 healthy volunteers, monocyte resistin mRNA was positively correlated with its simultaneous serum levels and was higher in G/G genotype. Thus, SNP-420 determines monocyte mRNA and serum levels of resistin, which could induce T2DM.

Adipocytes↗

Ultrathin-layer gel electrophoresis of biopolymers.

Emerging need for large-scale, high-resolution analysis of biopolymers, such as DNA sequencing polymerase chain reaction, (PCR) product sizing, single nucleotide polymorphism (SNP) hunting and analysis of protein molecules necessitated the development of automated and high-throughput gel electrophoresis based methods enabling rapid, high-performance separations in a wide molecular weight range. Scaling down electric field mediated separation processes supports higher throughput due to the applicability of higher voltages, thus speeding up analysis time. Indeed, efforts in miniaturization resulted in faster, easier, less costly and more convenient analyses, fulfilling the needs of the emerging biotechnology industry for microscale and massively parallel assays. The two primary approaches in miniaturizing electrophoresis dimensions are the capillary and microslab formats. This latter one evolved towards ultrathin-layer gel electrophoresis which is, except from the thickness of the separation platform, slightly in the upper side of the scale, resulting in considerably easier handling. Ultrathin-layer gel electrophoresis combines the advantages of conventional slab-gel electrophoresis (multilane format) and capillary gel electrophoresis (rapid, high-efficiency separations). It is readily automated, automatic versions of it have been extensively used for large-scale DNA sequencing in the Human Genome Project and more recently became popular in high throughput DNA fragment analysis. Ultrathin-layer techniques are the first step towards the wider use of electrophoresis microchips in perfecting a user-friendly interface between the user and the microdevice.

Animals↗

BDNF gene is a risk factor for schizophrenia in a Scottish population.

Schizophrenia is a severe psychiatric disease with a strong genetic component. Brain-derived neurotrophic factor (BDNF) has been implicated in the pathogenesis of schizophrenia and bipolar (BP) disorders. The present study has examined two polymorphisms in linkage disequilibrium in the BDNF gene, which have been variously reported as associated with schizophrenia and BP. In our study, 321 probands with a primary diagnosis of schizophrenia or schizoaffective disorder, and 263 with a diagnosis of bipolar affective disorder, were examined together with 350 controls drawn from the same geographical region of Scotland. The val66met single-nucleotide polymorphism (SNP) showed significant (P = 0.005) association for valine (allele G) with schizophrenia but not bipolar disorder. Haplotype analysis of val/met SNP and a dinucleotide repeat polymorphism in the putative promoter region revealed highly significant (P < 1 x 10(-8)) under-representation of the methionine or met-1 haplotype in the schizophrenic but not the BP population. We conclude that, although the val66met polymorphism has been reported to alter gene function, the risk may depend upon the haplotypic background on which the val/met variant is carried.

Adult↗

[Single nucleotide polymorphisms of HIV coreceptor CCR5 gene in Chinese Yi ethnic group and its association with HIV infection].

OBJECTIVE: To investigate the single nucleotide polymorphism (SNP) of HIV-1 coreceptor CCR5 gene in Chinese Yi ethnic group and the association between these SNPs and HIV/AIDS. METHODS: Peripheral blood samples of 102 HIV negative persons of Chinese Yi nationality, 87 males amd 15 females, aged 23 (12-37), and 68 HIV carriers, 61 males and 7 females, aged 27 (17-51). The regulatory and structural regions of the HIV coreceptor CCR5 gene were amplified from the genomic DNA by nested PCR, each of the two regions was divided into three gene fragments which were overlapped. High throughput DHPLC was used for screening of unknown mutations in each gene fragment. The PCR products showing different peak traces from wild types in DHPLC were sequenced by forward and reverse primers respectively. The sequences were analyzed with the help of Sequence Navigator software to search for SNP loci. Statistical analysis by SPSS and PPAP softwares were made to study the association between these SNPs and HIV infection. RESULTS: Five SNPs (A77G, G316A, T532C, C921T, and G668A) and a AGA deletion of the 686-688 nucleotides were discovered in the coding region of this gene in Chinese Yi ethnic group. C921T mutation was a nonsense mutation, and the other SNPs (A77G, G316A, T532C, and G668A) are sense mutation, with the amino acid changes of K26R, G106R, C178R, and R223Q. Only the frequency of R223Q allelic gene was high (0.08) but those of the others were low (less than 0.01). There was no significant difference in the allele frequency between the HIV negative and HIV positive groups (all P > 0.05). Five SNP loci (T58934G, G59029A, T59353C, G59402A, and C59653T) were found in the regulatory region of CCR5 gene with high allelic frequencies of 0.1912-0.2941. Between the HIV negative and HIV positive groups, there were no differences in the SNP loc (all P > 0.05). Statistical analysis of the association between the linkage of mutation loci with HIV infection suggested a significant difference in the haplotype frequency of T59353C-G59402A between the HIV negative and HIV positive groups of the Yi population. CONCLUSION: A high throughput screening method of detecting unknown genetic mutation DHPLC can effectively analyze the SNP of CCR5 regulatory and structural regions in Chinese Yi ethnic group.

Acquired Immunodeficiency Syndrome↗

Association of single nucleotide polymorphisms of the insulin gene with chicken early growth and fat deposition.

Growth rate, body composition, and fat deposition are important traits in chickens. Insulin plays important roles in hepatic cells, muscle cells, and adipose tissue cells. The purpose of the present study was to analyze association of the insulin (INS) gene with chicken growth and body composition traits. Using a F2 design resource population constructed with the crossing of Chinese native Xinghua chickens and White Recessive Rock chickens, the association of 4 single nucleotide polymorphisms (SNP; A+428G, C+1549T, T+3737C, and A+3971G) of INS gene with 13 growth and body composition traits was studied. The T+3737C genotypes were significantly associated with small intestine length (P = 0.0002), and the A+3971G genotypes were significantly associated with early growth (hatch weight and BW at 28 d of age) (P < 0.0001), breast angle (P = 0.0002), and small intestine length (P < 0.0001). None of the 4 SNP was significantly associated with abdominal fat pad weight (P > 0.05). The haplotypes based on the 4 SNP were also significantly associated with early growth (hatch weight and BW at 28 d of age; P < 0.0001) and breast angle (P < 0.0001) but not with small intestine length (P = 0.0505). These results suggested that variation of the insulin gene was significantly associated with chicken early growth but not with fat deposition. In addition, the data from the present study supported the inference that both the one-SNP-at-a-time and the haplotype-based approaches have their own advantages and disadvantages when association analysis of one SNP and haplotypes with chicken complex traits was conducted.

Animals↗

Association of the OLR1 gene with milk composition in Holstein dairy cattle.

Oxidized low-density lipoprotein receptor (OLR1) is the major protein that binds, internalizes, and degrades oxidized low-density lipoprotein. The role of OLR1 in lipid metabolism and the results of previous whole-genome scan studies prompted the investigation of OLR1 as a candidate gene affecting milk composition traits. Direct cDNA and genomic sequencing of OLR1 revealed 2 single nucleotide polymorphisms (SNP) in exon 4, 5 SNP in intron 4, and 1 in the 3' untranslated region (UTR). Four intragenic haplotypes comprising SNP positions 7,160, 7,161, 7,278, 7,381, 7,409, 7,438, 7,512, and 8,232 were inferred. Haplotype analysis showed that one of the haplotypes was associated with a significant increase in fat yield and fat percentage. Single SNP analysis showed that allele C of SNP 8,232 (in the 3'-UTR) had significant effects on fat yield and fat percentage, whereas SNP 7,160 and 7,161 (in exon 4) had no significant effects. Both single SNP and haplotype analyses indicate that SNP 8,232 in the 3'-UTR is associated with milk fat yield and percentage and it may be in linkage disequilibrium with the functional polymorphism. To provide support for the hypothesis that SNP 8,232 is responsible for OLR1 expression, OLR1 expression levels in individuals bearing different genotypes were assessed. It was found that OLR1 expression was reduced in genotype AA individuals compared with CC and AC individuals, suggesting that A at position 8,232 may be the nucleotide causing decreased OLR1 expression. The 3'-UTR polymorphism found in this study might control translation or stability of OLR1 mRNA.

3' Untranslated Regions↗

Superb nucleotide discrimination by a novel on/off switch for DNA polymerization and its applications.

With the use of polymerases having 3' to 5' exonuclease activity and 3' phosphorothioate-modified allele-specific primers, we recently devised a SNP-operated on/off switch controlling DNA polymerization. One advantage of this novel on/off switch is its adaptability to arrayed primer extension. To further expand its application in genetic analysis, this new on/off switch was evaluated in discrimination of the match/mismatch status of single nucleotides upstream from the primer 3' terminal. A set of seven amplicons was developed with the templates differing from each other by a single nucleotide. Using this set of amplicons, the new on/off switch was shown to be able to efficiently discriminate single nucleotide polymorphisms from the primer 3' terminus to the -6 position from the primer 3' terminus. These data, illustrating the broad single nucleotide discrimination ability of this novel on/off switch, explain why the SNP-operated on/off switch is powerful in SNP analysis, and also indicate useful applications to genetic analysis additional to SNP assay. First, these data broaden the application of the novel on/off switch in the analysis of mutations other than SNPs. Second, it raises a nucleotide-walking algorithm suitable for de novo array-based sequencing analysis.

DNA Mutational Analysis↗

Selection and use of SNP markers for animal identification and paternity analysis in U.S. beef cattle.

DNA marker technology represents a promising means for determining the genetic identity and kinship of an animal. Compared with other types of DNA markers, single nucleotide polymorphisms (SNPs) are attractive because they are abundant, genetically stable, and amenable to high-throughput automated analysis. In cattle, the challenge has been to identify a minimal set of SNPs with sufficient power for use in a variety of popular breeds and crossbred populations. This report describes a set of 32 highly informative SNP markers distributed among 18 autosomes and both sex chromosomes. Informativity of these SNPs in U.S. beef cattle populations was estimated from the distribution of allele and genotype frequencies in two panels: one consisting of 96 purebred sires representing 17 popular breeds, and another with 154 purebred American Angus from six herds in four Midwestern states. Based on frequency data from these panels, the estimated probability that two randomly selected, unrelated individuals will possess identical genotypes for all 32 loci was 2.0 x 10(-13) for multi-breed composite populations and 1.9 x 10(-10) for purebred Angus populations. The probability that a randomly chosen candidate sire will be excluded from paternity was estimated to be 99.9% and 99.4% for the same respective populations. The DNA immediately surrounding the 32 target SNPs was sequenced in the 96 sires of the multi-breed panel and found to contain an additional 183 polymorphic sites. Knowledge of these additional sites, together with the 32 target SNPs, allows the design of robust, accurate genotype assays on a variety of high-throughput SNP genotyping platforms.

Animals↗

Genome-wide SNP-based genomic diversity and population structure analysis in alpaca populations from Europe and Peru.

This study aimed to analyze the genetic diversity and population structure of alpacas in Germany, Switzerland, and Austria (German-speaking regions, GSR) and to compare with that of the country of origin of the species (Peru). A total of 179 animals from GSR and 151 from Peru were genotyped with a species-specific 76k SNP array. The observed and expected heterozygosity was 0.305 and 0.311 for GSR and 0.310 and 0.312 for Peru. The mean FROH values were 0.029 for GSR and 0.023 for Peru. In general, results show that breeders in both analyzed regions efficiently maintain genetic diversity. Principal component analysis identified the GSR and Peru populations as separate from each other, but the relative proximity of both clusters indicates the shared genetic heritage. FST and XPEHH methods identified genomic regions under selection for traits such as coat color and adaptation. Genome-wide association studies comparing black and brown with white or gray alpacas identified associated genome regions containing the ASIP and KIT genes, respectively. The association of a recently identified keratin locus on chromosome 16 with differences in fleece type in alpacas was confirmed, while the putative causality of a TRPV3 variant was rejected.

Animals↗

Snap: an integrated SNP annotation platform.

Snap (Single Nucleotide Polymorphism Annotation Platform) is a server designed to comprehensively analyze single genes and relationships between genes basing on SNPs in the human genome. The aim of the platform is to facilitate the study of SNP finding and analysis within the framework of medical research. Using a user-friendly web interface, genes can be searched by name, description, position, SNP ID or clone name. Several public databases are integrated, including gene information from Ensembl, protein features from Uniprot/SWISS-PROT, Pfam and DAS-CBS. Gene relationships are fetched from BIND, MINT, KEGG and are integrated with ortholog data from TreeFam to extend the current interaction networks. Integrated tools for primer-design and mis-splicing analysis have been developed to facilitate experimental analysis of individual genes with focus on their variation. Snap is available at http://snap.humgen.au.dk/ and at http://snap.genomics.org.cn/.

Databases, Nucleic Acid↗

[Optical genome mapping analysis of a Chinese pedigree with a complex balanced translocation involving four chromosomes].

OBJECTIVE: To explore the genetic characteristics of a complex balanced translocation involving four non-homologous chromosomes in a Chinese pedigree using optical genomic mapping (OGM). METHODS: A woman with primary infertility and her family members who presented at the Prenatal Diagnosis Center of the Sixth Affiliated Hospital of Sun Yat-sen University in October 2021 were selected as study subjects. Comprehensive analysis and verification of chromosomal abnormalities were conducted through conventional G-band karyotyping analysis, single nucleotide polymorphism microarray (SNP array) and OGM. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: E2022210). RESULTS: G-band karyotyping analysis indicated that the proband, her father, and younger brother have all carried a complex translocation involving four chromosomes. SNP array analysis revealed a duplication of approximately 21.63 Mb in the 9p24.1-p21.1 region in the proband's younger brother, while no abnormality was detected in other family members. OGM confirmed that the complex balanced translocation has involved chromosomes 5, 8, 9, and 10. CONCLUSION: The proband has harbored a complex balanced translocation. OGM has demonstrated certain advantages in characterization of complex chromosomal structural abnormalities.

Humans↗

Exploring SNP-SNP interactions and colon cancer risk using polymorphism interaction analysis.

Several single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with colon cancer risk; however, few studies have examined SNP-SNP interactions concurrently. We explored the association between colon cancer and 94 SNPs, using a novel approach, polymorphism interaction analysis (PIA). We developed PIA to examine all possible SNP combinations, based on the 94 SNPs studied in 216 male colon cancer cases and 255 male controls, employing 2 separate functions that cross-validate and minimize false-positive results in the evaluation of SNP combinations to predict colon cancer risk. PIA identified previously described null polymorphisms in glutathione-S-transferase T1 (GSTT1) as the best predictor of colon cancer among the studied SNPs, and also identified novel polymorphisms in the inflammation and hormone metabolism pathways that singly or jointly predict cancer risk. PIA identified SNPs that may interact with the GSTT1 polymorphism, including coding polymorphisms in TP53 (Arg72Pro in p53) and CASP8 (Asp302His in caspase 8), which may modify the association between this polymorphism and colon cancer. This was confirmed by logistic regression, as the GSTT1 null polymorphism in combination with either the TP53 or the CASP8 polymorphism significantly alter colon cancer risk (p(interaction) < 0.02 for both). GSTT1 prevents DNA damage by detoxifying mutagenic compounds, while the p53 protein facilitates repair of DNA damage and induces apoptosis, and caspase 8 is activated in p53-mediated apoptosis. Our results suggest that PIA is a valid method for suggesting SNP-SNP interactions that may be validated in future studies, using more traditional statistical methods on different datasets.

Aged↗

Association analysis of the dopamine receptor D2 (DRD2) SNP rs1076560 in alcoholic patients.

The dopamine system plays a well-established role in alcoholism. In this study, we examined the association between the single-nucleotide polymorphism (SNP) rs1076560 of the dopamine receptor D2 (DRD2) gene and susceptibility to alcoholism. SNP rs1076560 (C/A) is located in intron 6 of DRD2, where it is 1.4 kb downstream from alternative exon 6 and 83 bp upstream from exon 7. A total of 248 alcoholic patients and 322 healthy controls, all Japanese males, were genotyped for rs1076560 polymorphism by direct sequencing and allele-specific PCR. Data were analyzed using standard chi(2) statistics and a backwards logistic regression approach to adjust for the contribution of aldehyde dehydrogenase-2 (ALDH2) genotype status. The DRD2 risk allele A was more prevalent in the alcoholic patients (40.1%) than in the healthy controls (34.0%) (P=0.034, odds ratio=1.300, 95% confidence interval=1.020-1.657). These data identify SNP rs1076560 as a potentially important variable in the development of alcoholism.

Alcoholism↗

Comparison of microsatellites, single-nucleotide polymorphisms (SNPs) and composite markers derived from SNPs in linkage analysis.

There is growing evidence that a map of dense single-nucleotide polymorphisms (SNPs) can outperform a map of sparse microsatellites for linkage analysis. There is also argument as to whether a clustered SNP map can outperform an evenly spaced SNP map. Using Genetic Analysis Workshop 14 simulated data, we compared for linkage analysis microsatellites, SNPs, and composite markers derived from SNPs. We encoded the composite markers in a two-step approach, in which the maximum identity length contrast method was employed to allow for recombination between loci. A SNP map 2.3 times as dense as a microsatellite map (approximately 2.9 cM compared to approximately 6.7 cM apart) provided slightly less information content (approximately 0.83 compared to approximately 0.89). Most inheritance information could be extracted when the SNPs were spaced < 1 cM apart. Comparing the linkage results on using SNPs or composite markers derived from them based on both 3 cM and 0.3 cM resolution maps, we showed that the inter-SNP distance should be kept small (< 1 cM), and that for multipoint linkage analysis the original markers and the derived composite markers had similar power; but for single point linkage analysis the resulting composite markers lead to more power. Considering all factors, such as information content, flexibility of analysis method, map errors, and genotyping errors, a map of clustered SNPs can be an efficient design for a genome-wide linkage scan.

Chromosome Mapping↗