FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

Background  

Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the r ² LD statistic have gained popularity because r ² is directly related to statistical power to detect disease associations. Most of existing r ² based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.     

Genetic analysis of prolactin gene in Pakistani cattle

Prolactin (PRL) is a polypeptide hormone, secreted mainly by the anterior pituitary gland. It is involved in many endocrine activities. The key functions of PRL are related to reproduction and lactation in mammals. To ascertain the presence of polymorphisms in the bovine PRL gene (bPRL), the bPRL gene was sequenced. Five mutations were identified in exonic region and eleven in associated intronic regions in 100 cattle from four Pakistani cattle breeds. Haplotype of predicted amino acid changes represent a common alteration at codon 222 from R-Arginine into K-Lysine in all four breeds. Significant statistical variations were observed in the distribution of single nucleotide polymorphism (SNP) in various cattle populations. However, on basis of present study, an association of these SNPs with milk performance traits in four Pakistani cow breeds cannot be truly replicated but at least can be effective DNA markers for some of the breeds studied. Linkage analysis between these SNPs on larger populations can be useful for the association with milk production traits. Furthermore, present study may be used for marker-assisted selection and management in cattle breeding program in local cattle breeds.     

A high density SNP array for the domestic horse and extant Perissodactyla: utility for association mapping, genetic diversity, and phylogeny studies

An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species. More than 54,000 polymorphic SNPs provided an average inter-SNP spacing of ～43 kb. The mean minor allele frequency across domestic horse breeds was 0.23, and the number of polymorphic SNPs within breeds ranged from 43,287 to 52,085. Genome-wide linkage disequilibrium (LD) in most breeds declined rapidly over the first 50-100 kb and reached background levels within 1-2 Mb. The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse. Multidimensional scaling (MDS) analyses demonstrated the tight grouping of individuals within most breeds, close proximity of related breeds, and less tight grouping in admixed breeds. The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS. Genotyping of other Perissodactyla (zebras, asses, tapirs, and rhinoceros) was variably successful, with call rates and the number of polymorphic loci varying across taxa. Parsimony analysis placed the modern horse as sister taxa to Equus przewalski. The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus (MC1R) and defining a conserved haplotype of ～750 kb across all breeds. These results demonstrate the high quality of this SNP genotyping resource, its usefulness in diverse genome analyses of the horse, and potential use in related species.     

Genetic determinants of hair and eye colours in the Scottish and Danish populations

Background

The Bovine HapMap Consortium has generated assay panels to genotype ~30,000 single nucleotide polymorphisms (SNPs) from 501 animals sampled from 19 worldwide taurine and indicine breeds, plus two outgroup species (Anoa and Water Buffalo). Within the larger set of SNPs we targeted 101 high density regions spanning up to 7.6 Mb with an average density of approximately one SNP per 4 kb, and characterized the linkage disequilibrium (LD) and haplotype block structure within individual breeds and groups of breeds in relation to their geographic origin and use.

Results

From the 101 targeted high-density regions on bovine chromosomes 6, 14, and 25, between 57 and 95% of the SNPs were informative in the individual breeds. The regions of high LD extend up to ~100 kb and the size of haplotype blocks ranges between 30 bases and 75 kb (10.3 kb average). On the scale from 1–100 kb the extent of LD and haplotype block structure in cattle has high similarity to humans. The estimation of effective population sizes over the previous 10,000 generations conforms to two main events in cattle history: the initiation of cattle domestication (~12,000 years ago), and the intensification of population isolation and current population bottleneck that breeds have experienced worldwide within the last ~700 years. Haplotype block density correlation, block boundary discordances, and haplotype sharing analyses were consistent in revealing unexpected similarities between some beef and dairy breeds, making them non-differentiable. Clustering techniques permitted grouping of breeds into different clades given their similarities and dissimilarities in genetic structure.

Conclusion

This work presents the first high-resolution analysis of haplotype block structure in worldwide cattle samples. Several novel results were obtained. First, cattle and human share a high similarity in LD and haplotype block structure on the scale of 1–100 kb. Second, unexpected similarities in haplotype block structure between dairy and beef breeds make them non-differentiable. Finally, our findings suggest that ~30,000 uniformly distributed SNPs would be necessary to construct a complete genome LD map in Bos taurus breeds, and ~580,000 SNPs would be necessary to characterize the haplotype block structure across the complete cattle genome.     

Extent of linkage disequilibrium in large-breed dogs: chromosomal and breed variation

The aim of this study was to better define the extent of linkage disequilibrium (LD) in populations of large-breed dogs and its variation by breed and chromosomal region. Understanding the extent of LD is a crucial component for successful utilization of genome-wide association studies and allows researchers to better define regions of interest and target candidate genes. Twenty-four Golden Retriever dogs, 28 Rottweiler dogs, and 24 Newfoundland dogs were genotyped for single-nucleotide polymorphism (SNP) data using a high-density SNP array. LD was calculated for all autosomes using Haploview. Decay of the squared correlation coefficient (r ²) was plotted on a per-breed and per-chromosome basis as well as in a genome-wide fashion. The point of 50 % decay of r ² was used to estimate the difference in extent of LD between breeds. Extent of LD was significantly shorter for Newfoundland dogs based upon 50 % decay of r ² data at a mean of 344 kb compared to Golden Retriever and Rottweiler dogs at 715 and 834 kb, respectively (P < 0.0001). Notable differences in LD by chromosome were present within each breed and not strictly related to the length of the corresponding chromosome. Extent of LD is breed and chromosome dependent. To our knowledge, this is the first report of SNP-based LD for Newfoundland dogs, the first report based on genome-wide SNPs for Rottweilers, and an almost tenfold improvement in marker density over previous genome-wide studies of LD in Golden Retrievers.     

The extent of linkage disequilibrium in beef cattle breeds using high-density SNP genotypes

Background

The extent of linkage disequilibrium (LD) between molecular markers impacts genome-wide association studies and implementation of genomic selection. The availability of high-density single nucleotide polymorphism (SNP) genotyping platforms makes it possible to investigate LD at an unprecedented resolution. In this work, we characterised LD decay in breeds of beef cattle of taurine, indicine and composite origins and explored its variation across autosomes and the X chromosome.

Findings

In each breed, LD decayed rapidly and r² was less than 0.2 for marker pairs separated by 50 kb. The LD decay curves clustered into three groups of similar LD decay that distinguished the three main cattle types. At short distances between markers (< 10 kb), taurine breeds showed higher LD (r² = 0.45) than their indicine (r² = 0.25) and composite (r² = 0.32) counterparts. This higher LD in taurine breeds was attributed to a smaller effective population size and a stronger bottleneck during breed formation. Using all SNPs on only the X chromosome, the three cattle types could still be distinguished. However for taurine breeds, the LD decay on the X chromosome was much faster and the background level much lower than for indicine breeds and composite populations. When using only SNPs that were polymorphic in all breeds, the analysis of the X chromosome mimicked that of the autosomes.

Conclusions

The pattern of LD mirrored some aspects of the history of breed populations and showed a sharp decay with increasing physical distance between markers. We conclude that the availability of the HD chip can be used to detect association signals that remained hidden when using lower density genotyping platforms, since LD dropped below 0.2 at distances of 50 kb.     

Association between Genetic Polymorphisms in Cav2.3 (R-type) Ca2+ Channels and Fentanyl Sensitivity in Patients Undergoing Painful Cosmetic Surgery

Individual differences in the sensitivity to fentanyl, a widely used opioid analgesic, lead to different proper doses of fentanyl, which can hamper effective pain treatment. Voltage-activated Ca²⁺ channels (VACCs) play a crucial role in the nervous system by controlling membrane excitability and calcium signaling. Ca_v2.3 (R-type) VACCs have been especially thought to play critical roles in pain pathways and the analgesic effects of opioids. However, unknown is whether single-nucleotide polymorphisms (SNPs) of the human CACNA1E (calcium channel, voltage-dependent, R type, alpha 1E subunit) gene that encodes Ca_v2.3 VACCs influence the analgesic effects of opioids. Thus, the present study examined associations between fentanyl sensitivity and SNPs in the human CACNA1E gene in 355 Japanese patients who underwent painful orofacial cosmetic surgery, including bone dissection. We first conducted linkage disequilibrium (LD) analyses of 223 SNPs in a region that contains the CACNA1E gene using genomic samples from 100 patients, and a total of 13 LD blocks with 42 Tag SNPs were observed within and around the CACNA1E gene region. In the preliminary study using the same 100 genomic samples, only the rs3845446 A/G SNP was significantly associated with perioperative fentanyl use among these 42 Tag SNPs. In a confirmatory study using the other 255 genomic samples, this SNP was also significantly associated with perioperative fentanyl use. Thus, we further analyzed associations between genotypes of this SNP and all of the clinical data using a total of 355 samples. The rs3845446 A/G SNP was associated with intraoperative fentanyl use, 24 h postoperative fentanyl requirements, and perioperative fentanyl use. Subjects who carried the minor G allele required significantly less fentanyl for pain control compared with subjects who did not carry this allele. Although further validation is needed, the present findings show the possibility of the involvement of CACNA1E gene polymorphisms in fentanyl sensitivity.     

SNPs detected in the yak MC4R gene and their association with growth traits

MC4R (melanocortin 4 receptor) is expressed in the appetite-regulating areas of the brain and takes part in leptin signaling pathways. Sequencing of the coding region of the MC4R gene for 354 yaks identified the following five single nucleotide polymorphisms (SNPs): SNP1 (273C>T), SNP2 (321 G>T), SNP3 (864 C>A), SNP4 (1069G>C) and SNP5 (1206 G>C). SNP1, SNP2 and SNP3 were synonymous mutations, whereas SNP4 and SNP5 were missense mutations resulting in amino acid substitutions (V286L and R331S). Pairwise linkage disequilibrium (LD) analysis indicated that two pairs of SNPs, SNP2 and SNP5 (r²=0.81027) and SNP4 and SNP5 (r²=0.53816), exhibited higher degrees of LD. CC genotype of SNP4, CGACG and CTCCC haplotypes for all SNPs were associated with increased BW of animals that were 18 months old and with the average daily gain. The secondary structure and transmembrane region prediction of the yak MC4R protein suggested that SNP4 was correlated with influential changes in the seventh transmembrane domain of the MC4R protein and with the functional deterioration or even incapacitation of MC4R, which may contribute to the increased feed intake, BW and average daily gain of the yaks with CC genotypes. The data from this study suggested that 1069G>C SNP of the MC4R gene could be used in marker-assisted selection of growth traits in the Maiwa yak breed.     

Linkage disequilibrium grouping of single nucleotide polymorphisms (SNPs) reflecting haplotype phylogeny for efficient selection of tag SNPs

Single nucleotide polymorphisms (SNPs) have been proposed to be grouped into haplotype blocks harboring a limited number of haplotypes. Within each block, the portion of haplotypes is expected to be tagged by a selected subset of SNPs; however, none of the proposed selection algorithms have been definitive. To address this issue, we developed a tag SNP selection algorithm based on grouping of SNPs by the linkage disequilibrium (LD) coefficient r(2) and examined five genes in three ethnic populations--the Japanese, African Americans, and Caucasians. Additionally, we investigated ethnic diversity by characterizing 979 SNPs distributed throughout the genome. Our algorithm could spare 60% of SNPs required for genotyping and limit the imprecision in allele-frequency estimation of nontag SNPs to 2% on average. We discovered the presence of a mosaic pattern of LD plots within a conventionally inferred haplotype block. This emerged because multiple groups of SNPs with strong intragroup LD were mingled in their physical positions. The pattern of LD plots showed some similarity, but the details of tag SNPs were not entirely concordant among three populations. Consequently, our algorithm utilizing LD grouping allows selection of a more faithful set of tag SNPs than do previous algorithms utilizing haplotype blocks.     

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds

Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.     

Analysis of genome-wide structure, diversity and fine mapping of Mendelian traits in traditional and village chickens

Extensive phenotypic variation is a common feature among village chickens found throughout much of the developing world, and in traditional chicken breeds that have been artificially selected for traits such as plumage variety. We present here an assessment of traditional and village chicken populations, for fine mapping of Mendelian traits using genome-wide single-nucleotide polymorphism (SNP) genotyping while providing information on their genetic structure and diversity. Bayesian clustering analysis reveals two main genetic backgrounds in traditional breeds, Kenyan, Ethiopian and Chilean village chickens. Analysis of linkage disequilibrium (LD) reveals useful LD (r(2) ≥ 0.3) in both traditional and village chickens at pairwise marker distances of ~10 Kb; while haplotype block analysis indicates a median block size of 11-12 Kb. Association mapping yielded refined mapping intervals for duplex comb (Gga 2:38.55-38.89 Mb) and rose comb (Gga 7:18.41-22.09 Mb) phenotypes in traditional breeds. Combined mapping information from traditional breeds and Chilean village chicken allows the oocyan phenotype to be fine mapped to two small regions (Gga 1:67.25-67.28 Mb, Gga 1:67.28-67.32 Mb) totalling ~75 Kb. Mapping the unmapped earlobe pigmentation phenotype supports previous findings that the trait is sex-linked and polygenic. A critical assessment of the number of SNPs required to map simple traits indicate that between 90 and 110K SNPs are required for full genome-wide analysis of haplotype block structure/ancestry, and for association mapping in both traditional and village chickens. Our results demonstrate the importance and uniqueness of phenotypic diversity and genetic structure of traditional chicken breeds for fine-scale mapping of Mendelian traits in the species, with village chicken populations providing further opportunities to enhance mapping resolutions.     

Genetic associations of common deletion polymorphisms in families with Avellino corneal dystrophy

Although the locations of many common deletion variants in the human genome are unknown, such deletions may be causative in rare disorders. Deletions can be mapped through the identification of Mendelian inconsistencies in pedigrees. Data for a total of 341,577 SNPs from an ACD family cohort (n = 551) and 341,039 SNPs from a Korean-Vietnamese family cohort (n = 554) were collected for a genome-wide association study using Illumina 370K-Duo Beadchips^®. In the present study, a Mendelian inconsistency analysis of genotype data identified 1029 deletion variants in Korean and Korean-Vietnam family cohorts of 404 trios comprising 1105 individuals. Small-deletion copy number variations adjacent to 10 deletion variants were then validated by the real-time quantitative polymerase chain reaction. The expected copy numbers of each deletion variant were directly matched to its genotype cluster image. Deletion variants were also in strong linkage disequilibrium with nearby SNPs. To determine the overall contribution of the 1029 deletion variants, we analyzed case-control trio associations with the risk for Avellino corneal dystrophy. One SNP marker (rs885945) neighboring the gene encoding major histocompatibility complex class I F (HLA-F) was significantly associated with the risk of Avellino corneal dystrophy (P = 0.0003). rs885945 showed high LD with SNPs within the HLA-F gene. Therefore, HLA-F may be a potential candidate gene for Avellino corneal dystrophy.     

Improved Heritability Estimation from Genome-wide SNPs

Estimation of narrow-sense heritability, h², from genome-wide SNPs genotyped in unrelated individuals has recently attracted interest and offers several advantages over traditional pedigree-based methods. With the use of this approach, it has been estimated that over half the heritability of human height can be attributed to the ∼300,000 SNPs on a genome-wide genotyping array. In comparison, only 5%–10% can be explained by SNPs reaching genome-wide significance. We investigated via simulation the validity of several key assumptions underpinning the mixed-model analysis used in SNP-based h² estimation. Although we found that the method is reasonably robust to violations of four key assumptions, it can be highly sensitive to uneven linkage disequilibrium (LD) between SNPs: contributions to h² are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD. The overall direction of the bias can be up or down depending on the genetic architecture of the trait, but it can be substantial in realistic scenarios. We propose a modified kinship matrix in which SNPs are weighted according to local LD. We show that this correction greatly reduces the bias and increases the precision of h² estimates. We demonstrate the impact of our method on the first seven diseases studied by the Wellcome Trust Case Control Consortium. Our LD adjustment revises downward the h² estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases. To calculate our revised kinship matrix, we developed LDAK, software for computing LD-adjusted kinships.     

Linkage Disequilibrium and Demographic History of Wild and Domestic Canids

Assessing the extent of linkage disequilibrium (LD) in natural populations of a nonmodel species has been difficult due to the lack of available genomic markers. However, with advances in genotyping and genome sequencing, genomic characterization of natural populations has become feasible. Using sequence data and SNP genotypes, we measured LD and modeled the demographic history of wild canid populations and domestic dog breeds. In 11 gray wolf populations and one coyote population, we find that the extent of LD as measured by the distance at which r² = 0.2 extends <10 kb in outbred populations to >1.7 Mb in populations that have experienced significant founder events and bottlenecks. This large range in the extent of LD parallels that observed in 18 dog breeds where the r² value varies from ~20 kb to >5 Mb. Furthermore, in modeling demographic history under a composite-likelihood framework, we find that two of five wild canid populations exhibit evidence of a historical population contraction. Five domestic dog breeds display evidence for a minor population contraction during domestication and a more severe contraction during breed formation. Only a 5% reduction in nucleotide diversity was observed as a result of domestication, whereas the loss of nucleotide diversity with breed formation averaged 35%.     

Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

Background

The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor.

Methods

Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin.

Results

Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies.

Conclusions

The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.     

Genetic variability of myostatin and prolactin genes in popular goat breeds in Egypt

The genetic polymorphisms of two functional genes named: myostatin (MSTN) and prolactin (PRL) were investigated in three goat breeds (Barki, Damascus and Zaraibi) using Sanger nucleotide sequence and restriction fragment length polymorphism (RFLP) methods, in order to differentiate between these breeds. Nucleotide sequencing of 337 bp MSTN gene detected five SNPs in Barki breed, two SNPs in Damascus breed, while the Zaraibi breed did not show any SNPs. Moreover, MSTN-HaeIII/PCR-RFLP gave a single Genotype BB was found in all the studied breeds. Meanwhile, Nucleotide sequencing of 196 bp PRL gene showed two SNPs in Damascus breed, one SNPs in Zaraibi breed, while the Barki breed did not show any SNPs. Moreover, PRL-Eco24I/PCR-RFLP showed three genotypes (AA, AB and BB). The genotype AB showed the maximum frequency in all the studied breeds (0.75, 0.85, and 0.90 for Damascus, Barki and Zaraibi breeds, respectively). Observed heterozygosity (Ho) value was higher than expected heterozygosity (He) value all studied breeds. In addition, the values of both Ho and He were the highest in Zaraibi breed (0.90 and 0.51 respectively). Chi-square (χ²) value revealed a significant variation Hardy-Weinberg equilibrium (P < .05) in the three studied breeds. It is the highest in Zaraibi goats and lowest in Damascus breed. The results demonstrated that the PRL-Eco24I/PCR-RFLP polymorphism may be utilized as effective marker for genetic differentiation between goat breeds, but MSTN-HaeIII/PCR-RFLP revealed no polymorphism or variation, thus it is not recommended in the selection program. Moreover, these results open up interesting prospects for future selection programs, especially marker assisted selection. In addition, the results established that PCR-RFLP method is a suitable tool for calculating genetic variability.     

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.