水稻单核苷酸多态性及其应用现状

单核苷酸多态性（single nucleotide polymorphisms, SNPs）在水稻中数量多,分布密度高,遗传稳定性高。水稻SNPs的发现方法主要有对样本DNA的PCR产物直接测序、从SSR区段检测SNPs和从基因组序列直接搜索等。目前已有多种基因分型技术运用到了水稻SNPs检测,SNPs检测的高度自动化使水稻SNPs基因分型非常方便。单核苷酸多态性在水稻遗传图谱的构建、基因克隆和功能基因组学研究、标记辅助选择育种、遗传资源分类及物种进化等方面的应用具有巨大潜力。     

Analysis of genetic variation in the GenomEUtwin project.

Multiallelic short tandem repeat polymorphisms, or microsatellites, are useful markers in genome wide scans to identify chromosomal regions containing genes underlying disease loci. The biallelic single nucleotide polymorphism (SNP) can be used to fine map previously identified large candidate regions or to test functional candidate genes by association analysis. In the GenomEUtwin project the population based impact of susceptibility genes for six multifactorial traits will be studied. A genome wide panel of informative human microsatellite markers will be analyzed by fluorescent capillary electrophoresis in well characterized twin and population samples. Contrary to microsatellites, selection of the most informative panels of SNPs is hampered by imperfect data on the allele frequencies and population distribution of SNPs markers in the databases. Therefore, selection of SNPs requires a substantial amount of bioinformatics, and, the SNPs need to be validated experimentally in the relevant populations prior to genotyping large sample sets. In the GenomEUtwin project, large scale genotyping of SNPs will be performed using the SNPstreamUHT and MassARRAY genotyping systems that are based on the primer extension reaction principle combined with fluorescent and mass spectrometric detection, respectively. Production of the genotyping data will be a joint effort by GenomEUtwin partners at the University of Helsinki, the National Public Health Institute in Helsinki, Finland and Uppsala University, Sweden. All genotyping data will be stored in a common database established specifically for the GenomEUtwin project, from where it can be accessed by the twin research centres that provided the samples for genotyping.     

Discovery, characterization and validation of single nucleotide polymorphisms within 206 bovine genes that may be considered as candidate genes for beef production and quality

A large number of putative single nucleotide polymorphisms (SNPs) have been identified from the bovine genome-sequencing project. However, few of these have been validated and many will turn out to be sequencing artefacts or have low minor allele frequencies. In addition, there is little information available on SNPs within coding regions, which are likely to be responsible for phenotypic variation. Therefore, additional SNP discovery is necessary to identify and validate polymorphisms both in specific genes and genome-wide. Sequence-tagged sites within 286 genes were resequenced from a panel of animals representing a wide range of European cattle breeds. For 80 genes, no polymorphisms were identified, and 672 putative SNPs were identified within 206 genes. Fifteen European cattle breeds (436 individuals plus available parents) were genotyped with these putative SNPs, and 389 SNPs were confirmed to have minor allele frequencies above 10%. The genes containing SNPs were localized on chromosomes by radiation hybrid mapping and on the bovine genome sequence by Blast . Flanking microsatellite loci were identified, to facilitate the alignment of the genes containing the SNPs in relation to mapped quantitative trait loci. Of the 672 putative SNPs discovered in this work, only 11 were found among the validated SNPs and 100 were found among the approximately 2.3 million putative SNPs currently in dbSNP. The genes studied in this work could be considered as candidates for traits associated with beef production and the SNPs reported will help to assess the role of the genes in the genetic control of muscle development and meat quality. The allele frequency data presented allows the general utility of the SNPs to be assessed.     

Selecting SNPs for association studies based on population frequencies: a novel interactive tool and its application to polygenic diseases

Common complex polygenic diseases as autoimmune diseases have not been completely understood on a molecular level. While many genes are known to be involved in the pathways responsible for the phenotype, explicit causes for the susceptibility of the disease remain to be elucidated. The susceptibility to disease is thought to be the result of genetic epistatic interactions between common polymorphic genes. This polymorphism is mostly caused by single nucleotide polymorphisms (SNPs). Human subpopulations are known to differ in the susceptibility to the diseases and generally in the distribution of single nucleotide polymorphisms. The here presented approach retrieves SNPs with the most divergent frequencies for selected human subpopulations to help defining properties for the experimental verification of SNPs within defined regions. A web-accessible program implementing this approach was evaluated for multiple sclerosis (MS), a common human polygenic disease. A link to a summary of data from "The SNP Consortium" (TSC) with sex-dependencies of SNPs is available. Associations of SNPs to genes, genetic markers and chromosomal loci are retrieved from the Ensembl project. This tool is recommended to be used in conjunction with microarray analyses or marker association studies that link genes or chromosomal loci to particular diseases.     

Gene-centric characteristics of genome-wide association studies

Background

The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches.

Methodology/Principal Findings

In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics.

Conclusions/Significance

This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions.     

Direct inference of SNP heterozygosity rates and resolution of LOH detection

Single nucleotide polymorphisms (SNPs) have been increasingly utilized to investigate somatic genetic abnormalities in premalignancy and cancer. LOH is a common alteration observed during cancer development, and SNP assays have been used to identify LOH at specific chromosomal regions. The design of such studies requires consideration of the resolution for detecting LOH throughout the genome and identification of the number and location of SNPs required to detect genetic alterations in specific genomic regions. Our study evaluated SNP distribution patterns and used probability models, Monte Carlo simulation, and real human subject genotype data to investigate the relationships between the number of SNPs, SNP HET rates, and the sensitivity (resolution) for detecting LOH. We report that variances of SNP heterozygosity rate in dbSNP are high for a large proportion of SNPs. Two statistical methods proposed for directly inferring SNP heterozygosity rates require much smaller sample sizes (intermediate sizes) and are feasible for practical use in SNP selection or verification. Using HapMap data, we showed that a region of LOH greater than 200 kb can be reliably detected, with losses smaller than 50 kb having a substantially lower detection probability when using all SNPs currently in the HapMap database. Higher densities of SNPs may exist in certain local chromosomal regions that provide some opportunities for reliably detecting LOH of segment sizes smaller than 50 kb. These results suggest that the interpretation of the results from genome-wide scans for LOH using commercial arrays need to consider the relationships among inter-SNP distance, detection probability, and sample size for a specific study. New experimental designs for LOH studies would also benefit from considering the power of detection and sample sizes required to accomplish the proposed aims.     

Single nucleotide polymorphism discovery in barley using autoSNPdb

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico , but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing. The SNP detection method autoSNP has been developed to identify SNPs from sequence data for any species. Confidence in the predicted SNPs is based on sequence redundancy, and haplotype co-segregation scores are calculated for a further independent measure of confidence. We have extended the autoSNP method to produce autoSNPdb, which integrates SNP and gene annotation information with a graphical viewer. We have applied this software to public barley expressed sequences, and the resulting database is available over the Internet. SNPs can be viewed and searched by sequence, functional annotation or predicted synteny with a reference genome, in this case rice. The correlation between SNPs and barley cultivar, expressed tissue type and development stage has been collated for ease of exploration. An average of one SNP per 240 bp was identified, with SNPs more prevalent in the 5' regions and simple sequence repeat (SSR) flanking sequences. Overall, autoSNPdb can provide a wealth of genetic polymorphism information for any species for which sequence data are available.     

A Global View of 54,001 Single Nucleotide Polymorphisms (SNPs) on the Illumina BovineSNP50 BeadChip and Their Transferability to Water Buffalo

The Illumina BovineSNP50 BeadChip features 54,001 informative single nucleotide polymorphisms (SNPs) that uniformly span the entire bovine genome. Among them, 52,255 SNPs have locations assigned in the current genome assembly (Btau_4.0), including 19,294 (37%) intragenic SNPs (i.e., located within genes) and 32,961 (63%) intergenic SNPs (i.e., located between genes). While the SNPs represented on the Illumina Bovine50K BeadChip are evenly distributed along each bovine chromosome, there are over 14,000 genes that have no SNPs placed on the current BeadChip. Kernel density estimation, a non-parametric method, was used in the present study to identify SNP-poor and SNP-rich regions on each bovine chromosome. With bandwidth = 0.05 Mb, we observed that most regions have SNP densities within 2 standard deviations of the chromosome SNP density mean. The SNP density on chromosome X was the most dynamic, with more than 30 SNP-rich regions and at least 20 regions with no SNPs. Genotyping ten water buffalo using the Illumina BovineSNP50 BeadChip revealed that 41,870 of the 54,001 SNPs are fully scored on all ten water buffalo, but 6,771 SNPs are partially scored on one to nine animals. Both fully scored and partially/no scored SNPs are clearly clustered with various sizes on each chromosome. However, among 43,687 bovine SNPs that were successfully genotyped on nine and ten water buffalo, only 1,159 were polymorphic in the species. These results indicate that the SNPs sites, but not the polymorphisms, are conserved between two species. Overall, our present study provides a solid foundation to further characterize the SNP evolutionary process, thus improving understanding of within- and between-species biodiversity, phylogenetics and adaption to environmental changes.     

A global view of 54,001 single nucleotide polymorphisms (SNPs) on the Illumina BovineSNP50 BeadChip and their transferability to water buffalo

The Illumina BovineSNP50 BeadChip features 54,001 informative single nucleotide polymorphisms (SNPs) that uniformly span the entire bovine genome. Among them, 52,255 SNPs have locations assigned in the current genome assembly (Btau_4.0), including 19,294 (37%) intragenic SNPs (i.e., located within genes) and 32,961 (63%) intergenic SNPs (i.e., located between genes). While the SNPs represented on the Illumina Bovine50K BeadChip are evenly distributed along each bovine chromosome, there are over 14,000 genes that have no SNPs placed on the current BeadChip. Kernel density estimation, a non-parametric method, was used in the present study to identify SNP-poor and SNP-rich regions on each bovine chromosome. With bandwidth = 0.05 Mb, we observed that most regions have SNP densities within 2 standard deviations of the chromosome SNP density mean. The SNP density on chromosome X was the most dynamic, with more than 30 SNP-rich regions and at least 20 regions with no SNPs. Genotyping ten water buffalo using the Illumina BovineSNP50 BeadChip revealed that 41,870 of the 54,001 SNPs are fully scored on all ten water buffalo, but 6,771 SNPs are partially scored on one to nine animals. Both fully scored and partially/no scored SNPs are clearly clustered with various sizes on each chromosome. However, among 43,687 bovine SNPs that were successfully genotyped on nine and ten water buffalo, only 1,159 were polymorphic in the species. These results indicate that the SNPs sites, but not the polymorphisms, are conserved between two species. Overall, our present study provides a solid foundation to further characterize the SNP evolutionary process, thus improving understanding of within- and between-species biodiversity, phylogenetics and adaption to environmental changes.     

Development of PCR-based SNP markers for rice blast resistance genes at the<Emphasis Type="Italic"> Piz</Emphasis> locus

We assessed the utility of single-nucleotide polymorphisms (SNPs) and small insertion/deletion polymorphisms (InDels) as DNA markers in genetic analysis and breeding of rice. Toward this end, we surveyed SNPs and InDels in the chromosomal region containing the Piz and Piz-t rice blast resistance genes and developed PCR-based markers for typing the SNPs. Analysis of sequences from a blast-susceptible Japanese cultivar and two cultivars each containing one of these genes revealed that SNPs are abundant in the Piz and Piz-t regions (on average, one SNP every 248 bp), but the number of InDels was much lower. The dense distribution of SNPs facilitated the generation of SNP markers in the vicinity of the genes. For typing these SNPs, we used a modified allele-specific PCR method. Of the 49 candidate allele-specific markers, 33 unambiguously and reproducibly discriminated between the two alleles. We used the markers for mapping the Piz and Piz-t genes and evaluating the size of DNA segments introgressed from the Piz donor cultivar in Japanese near-isogenic lines containing Piz. Our findings suggest that, because of its ability to generate numerous markers within a target region and its simplicity in assaying genotypes, SNP genotyping with allele-specific PCR is a valuable tool for gene mapping, map-based cloning, and marker-assisted selection in crops, especially rice.Communicated by D.J. Mackill     

Association studies in candidate genes: strategies to select SNPs to be tested

OBJECTIVE: When numerous single nucleotide polymorphisms (SNPs) have been identified in a candidate gene, a relevant and still unanswered question is to determine how many and which of these SNPs should be optimally tested to detect an association with the disease. Testing them all is expensive and often unnecessary. Alleles at different SNPs may be associated in the population because of the existence of linkage disequilibrium, so that knowing the alleles carried at one SNP could provide exact or partial knowledge of alleles carried at a second SNP. We present here a method to select the most appropriate subset of SNPs in a candidate gene based on the pairwise linkage disequilibrium between the different SNPs. METHOD: The best subset is identified through power computations performed under different genetic models, assuming that one of the SNPs identified is the disease susceptibility variant. RESULTS: We applied the method on two data sets, an empirical study of the APOE gene region and a simulated study concerning one of the major genes (MG1) from the Genetic Analysis Workshop 12. For these two genes, the sets of SNPs selected were compared to the ones obtained using two other methods that need the reconstruction of multilocus haplotypes in order to identify haplotype-tag SNPs (htSNPs). We showed that with both data sets, our method performed better than the other selection methods.     

Discovery of SNPs in soybean genotypes frequently used as the parents of mapping populations in the United States and Korea

Single nucleotide polymorphisms (SNPs) including insertion/deletions (indels) serve as useful and informative genetic markers. The availability of high-throughput and inexpensive SNP typing systems has increased interest in the development of SNP markers. After fragments of genes were amplified with primers derived from 110 soybean GenBank ESTs, sequencing data of PCR products from 15 soybean genotypes from Korea and the United States were analyzed by SeqScape software to find SNPs. Among 35 gene fragments with at least one SNP among the 15 genotypes, SNPs occurred at a frequency of 1 per 2,038 bp in 16,302 bp of coding sequence and 1 per 191 bp in 16,960 bp of noncoding regions. This corresponds to a nucleotide diversity (theta) of 0.00017 and 0.00186, respectively. Of the 97 SNPs discovered, 78 or 80.4% were present in the six North American soybean mapping parents. The addition of "Hwaeomputkong," which originated from Japan, increased the number to 92, or 94.8% of the total number of SNPs present among the 15 genotypes. Thus, Hwaeomputkong and the six North American mapping parents provide a diverse set of soybean genotypes that can be successfully used for SNP discovery in coding DNA and closely associated introns and untranslated regions.     

Three single nucleotide polymorphisms leading to non-synonymous amino acid substitution in the human ribonuclease 2 and angiogenin genes exhibit markedly less genetic heterogeneity in six populations

Angiogenin and ribonuclease 2 (RNase 2) are members of the human RNase superfamily. Although three potential single nucleotide polymorphisms (SNPs) in these genes, which could give rise to an amino acid substitution in the protein, have been identified, relevant population data are not available, and accordingly they have not been applied to clinical-genetic analysis. For this purpose, a novel genotyping method for each SNP using the mismatched PCR-restriction fragment length polymorphism technique has been developed. Using this method, the genotype distribution of each SNP was investigated in six populations: Japanese (n = 167), Korean (n = 90), Mongolian (n = 92), Ovambos (n = 86), Turkish (n = 87), and German (n = 70). In all the populations, only one genotype was found in each SNP. Irrespective of differences in ethnic groups, the angiogenin and RNase 2 genes appear to exhibit markedly less genetic heterogeneity with regard to these SNPs.     

Association analysis between pseudorabies antibody and five single-nucleotide polymorphisms in pigs

Pseudorabies has become endemic and represents a widespread problem for pig production in the world, causing great economic losses associated with reproductive failure and neonatal mortality in the pig industry. Most diseases are the results of mutations of functional genes. Single-nucleotide polymorphisms (SNPs) from the coding regions of the mediators of pro-inflammatory responses or other candidate genes in pigs could indicate their potential involvement in susceptibility or resistance to PrV (pseudorabies virus) infection. There have been no previous association studies with candidate host genes that may influence PrV phenotypic traits. In order to perform association studies to identify genes contributing to PrV phenotypes, the genotypes of five SNPs from four genes (IL10, CXCL12, BAT2 and EHMT2) were determined for 178 sow samples using a high throughput microarray-based methodology. PrV antibodies were tested by enzyme-linked immunosorbent assay (ELISA) to determine whether there was an association between antibody levels and particular genotypes. The association between SNP genotypes and the PrV antibody levels were analysed using the Duncan method of one-way ANOVA procedure using the SAS (Statistical Analysis Systems) software package. The results showed that the glycoprotein E-ELISA antibody level of pigs with genotypes 11(AA) and 12(AG) was significantly higher than in pigs with genotype 22(GG) (P < 0.05) of SNP in the gene EHMT2-SNP2. The SNP of EHMT2 may be an effective potential tool to identify susceptible and resistant animals when used in conjunction with traditional selection methods.     

SNPsFinder--a web-based application for genome-wide discovery of single nucleotide polymorphisms in microbial genomes

SUMMARY: Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations in closely related microbial species, strains or isolates. Some SNPs confer selective advantages for microbial pathogens during infection and many others are powerful genetic markers for distinguishing closely related strains or isolates that could not be distinguished otherwise. To facilitate SNP discovery in microbial genomes, we have developed a web-based application, SNPsFinder, for genome-wide identification of SNPs. SNPsFinder takes multiple genome sequences as input to identify SNPs within homologous regions. It can also take contig sequences and sequence quality scores from ongoing sequencing projects for SNP prediction. SNPsFinder will use genome sequence annotation if available and map the predicted SNP regions to known genes or regions to assist further evaluation of the predicted SNPs for their functional significance. SNPsFinder can generate PCR primers for all predicted SNP regions according to user's input parameters to facilitate experimental validation. The results from SNPsFinder analysis are accessible through the World Wide Web. AVAILABILITY: The SNPsFinder program is available at http://snpsfinder.lanl.gov/. SUPPLEMENTARY INFORMATION: The user's manual is available at http://snpsfinder.lanl.gov/UsersManual/     

The number of genes having different alleles between rice cultivars estimated by SNP analysis

Identification of single nucleotide polymorphisms (SNPs) in a large number of genes will enable estimation of the number of genes having different alleles in a population. In the present study, SNPs between 21 rice cultivars including 17 Japanese cultivars, one upland rice, and three indica cultivars were analyzed by PCR–RF–SSCP. PCR–RF–SSCP analysis was found to be a more efficient method for detecting SNPs than mismatch–cleavage analysis, though both PCR–RF–SSCP and mismatch–cleavage are useful for screening SNPs. The number of DNA fragments showing polymorphism between Japanese cultivars was 134 in the 1,036 genes analyzed. In 137 genes, 638 DNA polymorphisms were identified. Out of 52 genes having polymorphisms in the exons, one had a frame-shift mutation, three had polymorphism causing amino acid insertions or deletions, and 16 genes had missense polymorphisms. The number of genes having frame-shift mutations and missense polymorphisms between the 17 Japanese cultivars was estimated to be 41 and 677 on average, respectively, and those between japonica and indica to be 425 and 6,977, respectively. Chromosomal regions of cultivars selected in rice breeding processes were identified by SNP analysis of genes. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Identification of 187 single nucleotide polymorphisms (SNPs) among 41 candidate genes for ischemic heart disease in the Japanese population

To investigate whether common variants in the human genetic background are associated with pathogenesis of ischemic heart diseases, we systematically surveyed 41 possible candidate genes for single-nucleotide polymorphisms (SNPs) by directly sequencing 96 independent alleles at each locus, derived from 48 unrelated Japanese patients with myocardial infarction, including 25.8 kb 5' flanking regions, 56.8 kb exonic and 35.4 kb intronic sequences, and 1.8 kb 3' flanking regions. In this genomic DNA of nearly 120 kb, we identified 187 SNPs: 55 in 5' flanking regions, seven in 5' untranslated regions (UTRs), 52 in coding elements, 64 in introns, eight in 3' UTRs, and one in a 3' flanking region. Among the 52 coding SNPs, 26 were non-synonymous changes. Allelic frequencies of some of the polymorphisms were significantly different from those reported in European populations. For example, the Q506R substitution in the coagulation factor V gene, the so-called "Leiden mutation", has a reported frequency of 2.3% in Europeans, but we detected the Leiden mutation in none of the Japanese genomes that we investigated. The allelic frequencies of the -33A>G SNP in the thrombomodulin gene were also very different; this allele occurred at a 12% frequency in the Japanese patients that we examined, although it had been detected in none of 82 Caucasians reported previously. These data support the hypothesis that some SNPs are specific to particular ethnic groups.     

Genomic regions involved in yield potential detected by genome-wide association analysis in Japanese high-yielding rice cultivars

Background

High-yielding cultivars of rice (Oryza sativa L.) have been developed in Japan from crosses between overseas indica and domestic japonica cultivars. Recently, next-generation sequencing technology and high-throughput genotyping systems have shown many single-nucleotide polymorphisms (SNPs) that are proving useful for detailed analysis of genome composition. These SNPs can be used in genome-wide association studies to detect candidate genome regions associated with economically important traits. In this study, we used a custom SNP set to identify introgressed chromosomal regions in a set of high-yielding Japanese rice cultivars, and we performed an association study to identify genome regions associated with yield.

Results

An informative set of 1152 SNPs was established by screening 14 high-yielding or primary ancestral cultivars for 5760 validated SNPs. Analysis of the population structure of high-yielding cultivars showed three genome types: japonica-type, indica-type and a mixture of the two. SNP allele frequencies showed several regions derived predominantly from one of the two parental genome types. Distinct regions skewed for the presence of parental alleles were observed on chromosomes 1, 2, 7, 8, 11 and 12 (indica) and on chromosomes 1, 2 and 6 (japonica). A possible relationship between these introgressed regions and six yield traits (blast susceptibility, heading date, length of unhusked seeds, number of panicles, surface area of unhusked seeds and 1000-grain weight) was detected in eight genome regions dominated by alleles of one parental origin. Two of these regions were near Ghd7, a heading date locus, and Pi-ta, a blast resistance locus. The allele types (i.e., japonica or indica) of significant SNPs coincided with those previously reported for candidate genes Ghd7 and Pi-ta.

Conclusions

Introgression breeding is an established strategy for the accumulation of QTLs and genes controlling high yield. Our custom SNP set is an effective tool for the identification of introgressed genome regions from a particular genetic background. This study demonstrates that changes in genome structure occurred during artificial selection for high yield, and provides information on several genomic regions associated with yield performance.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-346) contains supplementary material, which is available to authorized users.     

Preselection statistics and Random Forest classification identify population informative single nucleotide polymorphisms in cosmopolitan and autochthonous cattle breeds

Commercial single nucleotide polymorphism (SNP) arrays have been recently developed for several species and can be used to identify informative markers to differentiate breeds or populations for several downstream applications. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this work, we compared several methods of SNPs preselection (Delta, F_st and principal component analyses (PCA)) in addition to Random Forest classifications to analyse SNP data from six dairy cattle breeds, including cosmopolitan (Holstein, Brown and Simmental) and autochthonous Italian breeds raised in two different regions and subjected to limited or no breeding programmes (Cinisara, Modicana, raised only in Sicily and Reggiana, raised only in Emilia Romagna). From these classifications, two panels of 96 and 48 SNPs that contain the most discriminant SNPs were created for each preselection method. These panels were evaluated in terms of the ability to discriminate as a whole and breed-by-breed, as well as linkage disequilibrium within each panel. The obtained results showed that for the 48-SNP panel, the error rate increased mainly for autochthonous breeds, probably as a consequence of their admixed origin lower selection pressure and by ascertaining bias in the construction of the SNP chip. The 96-SNP panels were generally more able to discriminate all breeds. The panel derived by PCA-chrom (obtained by a preselection chromosome by chromosome) could identify informative SNPs that were particularly useful for the assignment of minor breeds that reached the lowest value of Out Of Bag error even in the Cinisara, whose value was quite high in all other panels. Moreover, this panel contained also the lowest number of SNPs in linkage disequilibrium. Several selected SNPs are located nearby genes affecting breed-specific phenotypic traits (coat colour and stature) or associated with production traits. In general, our results demonstrated the usefulness of Random Forest in combination to other reduction techniques to identify population informative SNPs.