SNP ID-info: SNP ID Searching and Visualization Platform

The virulence factor α-toxin (hla) is needed by Staphylococcus aureus in order to cause infections in both animals and humans. Although the complicated regulation of hla expression has been well studied in human S. aureus isolates, the mechanisms of of hla regulation in bovine S. aureus isolates remain undefined. In this study, we found that many bovine S. aureus isolates, including the RF122 strain, generate dramatic amounts of α-toxin in vitro compared with human clinical S. aureus isolates, including MRSA WCUH29 and MRSA USA300. To elucidate potential regulatory mechanisms, we analyzed the hla promoter regions and identified predominant single nucleotide polymorphisms (SNPs) at positions −376, −483, and −484 from the start codon in α-toxin hyper-producing isolates. Using site-directed mutagenesis and hla promoter-gfp-luxABCDE dual reporter approaches, we demonstrated that the SNPs contribute to the differential control of hla expression among bovine and human S. aureus isolates. Using a DNA affinity assay, gel-shift assays and a null mutant, we identified and revealed that an hla positive regulator, SarZ, contributes to the involvement of the SNPs in mediating hla expression. In addition, we found that the bovine S. aureus isolate RF122 exhibits higher transcription levels of hla positive regulators, including agrA, saeR, arlR and sarZ, but a lower expression level of hla repressor rot compared to the human S. aureus isolate WCUH29. Our results indicate α-toxin hyperproduction in bovine S. aureus is a multifactorial process, influenced at both the genomic and transcriptional levels. Moreover, the identification of predominant SNPs in the hla promoter region may provide a novel method for genotyping the S. aureus isolates.

BackgroundSingle nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay.ResultsA total of 892,536 bi-allelic SNPs were discovered throughout the B. napus genome. A total of 36,458 putative amino acid variants were located in 13,552 protein-coding genes, which were predicted to have enriched binding and catalytic activity as a result. Using the GoldenGate genotyping platform, 94 of 96 SNPs sampled could effectively distinguish genotypes of 130 lines from two mapping populations, with an average call rate of 92%.ConclusionsDespite the polyploid nature of B. napus, nearly 900,000 simple SNPs were identified by whole genome resequencing. These SNPs were predicted to be effective in high-throughput genotyping assays (51% polymorphic SNPs, 92% average call rate using the GoldenGate assay, leading to an estimated >450 000 useful SNPs). Hence, the development of a much larger genotyping array of informative SNPs is feasible. SNPs identified in this study to cause non-synonymous amino acid substitutions can also be utilized to directly identify causal genes in association studies.

Background: We previously revealed that single nucleotide polymorphisms (SNPs) of CYP19A1, MAP3K1 rs889312, and ABCB1 rs2032582 were associated with overall survival (OS) in early-stage hormone receptor (HR)-positive breast cancer patients. Previous studies also showed that FGFR2 rs1219468 and TOX3 rs8051542 influenced OS in early-stage breast cancer patients. In this study, we assessed whether undiscovered SNPs of CYP19A1, MAP3K1, ABCB1, FGFR2, and TOX3 are associated with clinical outcome of patients with early-stage HR-positive breast cancer. Patients and Methods: We used next-generation sequencing (NGS) methods to explore unidentified SNPs of CYP19A1, MAP3K1, ABCB1, FGFR2, and TOX3 in 80 patients who had HR+, T1 to T2, and N0 to N1 breast cancer and had matched clinicopathological features and clinical outcomes (experimental cohort). The mapping selected SNPs identified from NGS were located in different chromosomes, such as chromosome 5 (MAP3K), 7 (ABCB1), 10 (FGFR2), 15 (CYP19A1), and 16 (TOX3), were analyzed. The multivariate-adjusted hazard ratio (aHR) of OS associated with the individual genotypes of the experimental cohort was assessed after adjusting for age, tumor size, tumor grade, HER2 status, menopausal status, and chemotherapy using Cox regression analyses. We further correlated identified significant novel SNPs with disease-free survival (DFS) and OS in 195 patients with HR-positive, T1-T2, and N0-1 breast cancer (validation cohort) using stepwise selection multiple Cox model analyses. Results: Through target region re-sequencing, we identified 69 novel SNPs, including 18 CYP19A1 SNPs, 16 MAP3K SNPs, 18 ABCB1 SNPs, 12 FGFR2 SNPs, and 5 TOX3 SNPs in the experimental cohort (n = 80). After multivariate-adjusted analyzing, FGFR2 rs2981460(C/C) (p = 0.0115), and MAP3K1 rs3822625 (A/A) (p = 0.0475), rs702689 (G/G) (p = 0.0312), rs832567 (C/C) (p = 0.0312), and rs9687226 (C/C) (p = 0.0475), and ABCB1 rs2032582 (T/T+T/C) (p = 0.0061) were significantly associated with the poorer OS of the experimental cohort. In a validated cohort (n =195) (Table 1), we found that MAP3K1 rs702689 (G/G) was significantly associated with poorer DFS (aHR = 2.3; 95% confidence interval [CI] = 1.1 to 5.1; p = 0.03) and OS (aHR = 4.9; 95% CI = 1.3 to 18.7; p = 0.02). In addition, MAP3K1 rs832567 (C/C) was significantly associated with poorer DFS (aHR = 2.5; 95% CI = 1.1 to 5.5; p = 0.02) and OS (aHR = 5.4; 95% CI = 1.4 to 21.6; p = 0.02). In premenopausal women of validation cohort (n = 108), ABCB1 rs2032582 (T/T+T/C) was significantly associated with a poor OS (aHR = 62.3; 95% CI = 2.0 to 1911.7; p = 0.02). Conclusions: Our results indicate that 3 novel SNPs, MAP3K1 rs702689, MAP3K1 rs832567, and ABCB1 rs2032582, may affect the prognosis of early-stage HR-positive breast cancer. Further validation of these SNPs in a large series of patients with early-stage HR-positive breast cancer who received adjuvant endocrine therapy alone is warranted. Table 1. The Associations of Hormone Receptor-Positive Breast Cancer Patients with Various Genotypes in multiple Cox model (validation cohort)Disease-free survivalOverall survivalGenotypeaHR (95%CI)PaHR (95%CI)PTotal (n = 195)FGFR2_ rs2981460 (C/C vs.C/T+T/T)0.4 (0.1-1.8)0.220.6 (0.1-5.4)0.68MAP3K1_ rs3822625 (A/A vs. G/A+GG)2.0 (0.7-5.3)0.192.7 (0.6-12.9)0.20MAP3K1_ rs702689 (G/G vs. A/A+A/G)2.3 (1.1-5.1)0.034.9 (1.3-18.7)0.02MAP3K1_rs832567 (C/C vs. A/A+A/C)2.5 (1.1-5.5)0.025.4 (1.4-21.6)0.02MAP3K1_rs9687226 (C/C vs. T/T+T/C)2.0 (0.7-5.3)0.192.7 (0.6-12.9)0.20Premenopausal (n=108)ABCB1_rs2032582 (T/T+T/C vs. C/C)2.0 (0.8-5.0)0.1562.3 (2.0-1911.7)0.02aHR: adjusted by age, estrogen receptor and progesterone receptor status, number of lymph nodes, menopausal status, adjuvant chemotherapy, lymphovascular invasion, and tumor size. Citation Format: Sung-Hsin Kuo, Shi-Yi Yang, Po-Han Lin, Chen-Hsin Chen, Hsin-Chou Yang, Chih-Yuan Hsu, Chiun-Sheng Huang. Identification of novel single nucleotide polymorphisms located in MAP3K1 and ABCB1 genes as markers for poor overall survival in early-stage hormone receptor-positive breast cancer using next-generation sequencing [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-06-30.

<h3>Introduction</h3> Non-alcoholic fatty liver disease (NAFLD) is a complex trait disorder. Genome-wide association studies (GWAS) of MRI hepatic image phenotypes and health records may allow identification of single nucleotide polymorphisms (SNPs) associated with NAFLD. In this study, we have used the UK Biobank to identify potential genetic risk factors for NAFLD. <h3>Method</h3> Using available data (application ID: 53754) for hepatic MRI proton density fat fraction (PDFF) combined with clinical records, we performed GWAS for NAFLD (continuous and categorical traits) using BOLT-LMM, adjusted for age, sex, diabetes, alcohol intake, smoking status and Townsend Index. An exploratory significance threshold (p &lt; 5x10^-6) was used. Clumping, annotation, expression quantitative trait loci (eQTL) analysis with genome tissue expression database and gene-pathway analysis was performed on the Functional Annotation of Genome Wide Association Study Platform. Lastly, phenome wide association study was performed on UK Biobank traits on lead SNPs (r² &lt; 0.1) was searched for on GeneAtlas. Post-GWAS associations were corrected for a FDR &lt; 0.05. <h3>Results</h3> We identified 32 and 24 lead SNPs (r² &lt; 0.1) in continuous and categorical NAFLD trait GWAS, respectively. Independent SNPs (r² &lt; 0.6) within these loci replicated previously published SNPs associated with NAFLD (<i>PNPLA3, TM6SF2, MBOAT-TMC4, APOE, GATA2DA, ZNF101, PBX4</i> and<i> PARVB)</i>. We identified 29 potential new variants in or near genes related to autophagy and inflammation (<i>AMBRA1, SND1</i> and <i>NFATC1</i>), cell cycle and transcriptional/protein regulation (<i>KBTBD12</i>, <i>ADCY8, CSTF3, TOX, RASF2</i>,<i> POU6F, UBAP2</i>, <i>SNORD37</i> and<i> GMIP</i>), the nervous system (<i>RTTN, NLGN1, NFIB, PCDH9</i>, and<i> PPFIBP1)</i>, adipogenesis and metabolism (<i>FAM120B, CPA6, TMPRSS15</i> and<i> FFAR4),</i> sarcomere maintenance (<i>NCKIPSD)</i>, collagen synthesis (<i>COL1A2</i>) and mitochondrial function (<i>NDUFS6</i>, <i>NDUFA12, NDUFA13, TOMM40,</i> and <i>ATP13A1</i>). Co-localised SNPs (r²&gt;0.6, p&lt;0.05) were in genes enriched for breast cancer and lipoprotein metabolism. SNPs in chromosomes 1, 3, 10, 15, 18, 19 and 22 were shown to be cis-eQTL in a number of tissues. Phenome-wide analysis showed <i>NDUF6</i> was associated with Crohn's disease, while <i>NCKIPDS4</i> and <i>TOMM40</i> were associated with lipidaemia, metabolic and liver disease. <h3>Conclusion</h3> Our GWAS of NAFLD replicated known SNPs and identified new potential loci with implications in diverse biological process. Analysis of larger number of individuals with MRI-PDFF will allow further validation of the associations identified and enable prioritisation for functional studies.

Identification of SNPs and candidate genes associated with early growth in orange-spotted grouper (Epinephelus coioides) by a genome-wide association study

The objectives of this study were to develop breed-specific single nucleotide polymorphisms (SNPs) in five pig breeds sequenced with Illumina's Genome Analyzer and to investigate their usefulness for breed assignment purposes. DNA pools were prepared for Duroc, Landrace, Large White, Pietrain and Wild Boar. The total number of animals used for sequencing was 153. SNP discovery was performed by aligning the filtered reads against Build 7 of the pig genome. A total of 313,964 high confidence SNPs were identified and analysed for the presence of breed-specific SNPs (defined in this context as SNPs for which one of the alleles was detected in only one breed). There were 29,146 putative breed-specific SNPs identified, of which 4441 were included in the PorcineSNP60 beadchip. Upon re-examining the genotypes obtained using the beadchip, 193 SNPs were confirmed as being breed specific. These 193 SNPs were subsequently used to assign an additional 490 individuals from the same breeds, using the sequenced individuals as reference populations. In total, four breed assignment tests were performed. Results showed that for all methods tested 99% of the animals were correctly assigned, with an average probability of assignment of at least 99.2%, indicating the high utility of breed-specific markers for breed assignment and traceability. This study provides a blueprint for the way next-generation sequencing technologies can be used for the identification of breed-specific SNPs, as well as evidence that these SNPs may be a powerful tool for breed assignment and traceability of animal products to their breeds of origin.

SNP discovery in associating genetic variation with human disease phenotypes

The detection of single nucleotide polymorphisms (SNPs) is of great significance in the early diagnosis of diseases and the rational use of drugs. Thus, a novel biosensor based on the quenching effect of fluorescence-embedded SYBR Green I (SG) dye and graphene oxide (GO) was introduced in this study. The probe DNA forms a double helix structure with perfectly complementary DNA (pcDNA) and 15 single-base mismatch DNA (smDNA) respectively. SG is highly intercalated with perfectly complementary dsDNA (pc-dsDNA) and exhibits strong fluorescence emission. Single-base mismatch dsDNA (SNPs) has a loose double-stranded structure and exhibits poor SG intercalation and low fluorescence sensing. At this time, the sensor still showed poor SNP discrimination. GO has a strong effect on single-stranded DNA (ssDNA), which can reduce the fluorescence response of probe DNA and eliminate background interference. And competitively combined with ssDNA in SNPs, quenching the fluorescence of SG/SNP, while the fluorescence value of pc-dsDNA was retained, increasing the signal-to-noise ratio. At this time, the sensor has obtained excellent SNP resolution. Different SNPs detect different intensities of fluorescence in the near-infrared region to evaluate the sensor's identification of SNPs. The experimental parameters such as incubation time, incubation temperature and salt concentration were optimized. Under optimal conditions, 1 nM DNA with 0–10 nM linear range and differentiate 5% SNP were achieved. The detection method does not require labeling, is low cost, simple in operation, exhibits high SNP discrimination and can be distinguished by SNP at room temperature.

Introduction: Commercial tomato (Solanum lycopersicum L.), one of the most widely grown vegetable crops worldwide, belongs to the Solanaceae family. The marketability of the commercial tomato mostly depends on the fruit quality. Tomato fruit quality is determined mainly by color, texture, shape and flavor. Fruit shape, one of the important traits affecting the quality of tomato fruit, is controlled by multiple minor genes and quantitatively inherited. Two important genes, involved in fruit shape, are SUN and OVATE genes. The SUN gene, which is a member of the IQD (IQ-domain) gene family and the Calmodulin binding protein, controls fruit length. The more expression of both SUN and OVATE genes leads to increased fruit length. Moreover, the increased expression of OVATE gene reduces the size of flower and leaf components. Due to the important role of these genes in tomato fruit shape, identification of single nucleotide polymorphisms (SNPs) as a new generation of robust, frequent and reliable bi-allelic markers, in the coding regions of these genes might be necessary for generating functional markers associated with fruit shape. Materials and Methods: Seeds of 96 tomato genotypes from 12 populations were grown in the research greenhouse of Faculty of Agriculture and Natural Resources of Urmia University. The genotypes had been collected from different regions of West Azerbaijan of Iran and Turkey (Igdir). The young and green plant leaves were used for genomic DNA extraction. The quality and quantity of the extracted DNA was assessed using spectrophotometry and agarose gel electrophoresis. To identify SNPs in SUN and OVATE genes, specific primers were designed by using FastPCR and Gene Runner software for amplifying fragments from coding regions of these genes in 96 tomato genotypes. Then, the amplified fragments of both genes were digested by using restriction enzymes TruI and PstI. Due to the lack of polymorphism in the digested patterns obtained by the used enzymes, four individuals from populations with close geographical distance were selected and amplified. The amplified bands were then purified by a purification kit (Kiagen, USA) and sequenced (Bioneer, South Korea). Sequencing was performed from both ends of the PCR fragments using both the forward and reverse primers used in the PCR reactions. The exon and intron regions of the sequenced fragments were identified by Softberry software. Following the retrieval of the sequenced fragments of each gene using FastPCR and Softberry software, multiple sequence alignment using Clustal Omega was used to identify SNPs in the exon and intron of the genes. Results and Discussion: Digestion of the amplified fragments of the genes using TruI and PstI restriction enzymes produced no polymorphism in the studied genotypes. Thus, four individuals were selected from geographically different populations and gene fragments were amplified, purified and sequenced in these genotypes. Sequencing of the amplified fragment of SUN gene revealed an intron region with a size of 369 bp. Out of the 10 SNPs detected in the SUN gene, four was found in the exon region, while the number of SNPs in intron was six. Of the total SNPs found in the SUN gene, the percentage of transition and transversion substitutions was 80 (50% T/C and 30% A/G) and 20 (T/G), respectively. In the OVATE gene, five SNPs were identified. The percentage of transition (40% G/A and 40% C/T) and transversion (20% G/T) substitutions in this genes were the same as SUN. The ratio of transition to transversion substitutions was 1:4 for both genes. The average number of SNPs in a 100 bp fragment in exonic and itronic region of SUN was 0.9 and 1.62, respectively, while it was 0.5 for exonic region of OVATE gene. Conclusion: The results of the current study revealed low polymorphisms and point mutations in the exon regions of SUN and OVATE genes, suggesting that the coding regions of these genes were conserved during the tomato evolution. Also, the number of SNPs in intron was more than those of exon. Considering the important role of fruit quality, especially fruit shape, in tomato market, the SNPs found in the current study may be used in genetic diversity studies, genetic map preparation, and saturation and identification of the functional markers associated with tomato fruit shape. These markers could accelerate tomato breeding programs aimed fruit shape improvement.

Castration resistant prostate cancer (CRPC) involves the upregulation of androgen receptor variants (AR-Vs), of which AR-V7 is clinically the most relevant. By lacking the ligand-binding domain, AR-V7 is constitutively active and may therefore bypass AR signaling inhibitors. Treating CRPC involves improved AR signaling inhibitors or taxane-based chemotherapy. However, the optimal treating sequence may differ from patient to patient. The presence of AR-V7 in the nucleus of circulating PCa cells, which is associated with AR targeted therapy resistance, is used as a therapy-guiding biomarker. This stratification has a high predictive power and specificity, but its sensitivity is unsatisfying and can only be done by highly specialized laboratories. A PCR/sequencing based test would improve the sensitivity of this biomarker, but it requires a better understanding of AR-V7’s functional regulation. Therefore, we aim here to analyze single nucleotide polymorphisms (SNPs) in the 3’ untranslated region (UTR) of AR-V7 that might have an impact on AR-V7’s expression and/or functional activity. The LD trait tool of NIH was used to search for trait association with AR cryptic exon (CE3) SNPs. Four RNA binding motif databases (oRNAment, ATtRACT, RBP map, and RBPDB) and SpliceAid v2 were used for evaluating SNPs in their capacity to alter motifs. By CRISPR/CAS9 mediated non-homologous end joining (NHEJ) these predictions were assessed experimentally using qPCR and Westen Blot. SNP rs5918762 was selected as it is in linkage disequilibrium with several PCa tagSNPs (rs5919393, rs5919432). rs5918762T/C is characterized by an unequal minor allele frequency (MAF) distribution among different populations. Using an in silico approach, this SNP is predicted to destroy/create a binding site for the splicing machinery involved protein SRSF9. Disrupting this SNP region via NHEJ resulted respectively in an increased and decreased expression of AR-FL and AR-V7 mRNA in 22RV1 cells (C allele). Additionally, analysis of the SU2C dataset (CRPC patients) correlated SRSF9 expression with AR-V7 expression. Subsequently, SRSF9 knock out (KO) resulted in reduced AR-V7 mRNA expression. Our data suggests that SNP rs5918762T/C is located in a region important for CE3 inclusion during AR splicing, which might involve SRSF9. Further validation of these results is in need and encompasses splicing assays by an AR-V7 mini-gene assay, protein-RNA interaction assays and an analysis of a lack of effect in cell lines expressing the T allele. Citation Format: Jasper Van Goubergen, Florian Handle, Marcus V. Cronauer, Frédéric R. Santer. Identification of functional single nucleotide polymorphisms in cryptic exon 3 of the androgen receptor gene [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2692.

Background: Prolactin is a physiological candidate gene which has significant effects on egg production in poultry. Also, it plays a major role on incubation behaviour (broodiness) in birds. The main objective of the present study was identification of single nucleotide polymorphism (SNP) C-2161G in the promoter region of prolactin gene and its association with egg production in Tellicherry native chicken population. Methods: A total of 200 blood samples were collected from the randomly selected birds of Tellicherry native chicken in All India Co-ordinated Research Project on Poultry improvement (AICRP) farm, Mannuthy, Thrissur, Kerala. Isolation of Genomic DNA was done and the isolated samples were subjected to polymerase chain reaction (PCR) followed by restriction fragment length polymorphism (RFLP) analysis to identify the SNP C-2161G of prolactin gene. Result: On the basis of RFLP patterns, birds were designated with three different genotypes namely CC, CG and GG. The allelic and genotypic frequency was calculated. The observed genotypic frequency at the SNP site C-2161G was CC (0.61), CG (0.160) and GG (0.23) and the frequency of allele was 0.69 for C and 0.31 for G. The egg production was shown to be statistically similar for the genotypes of SNP C-2161G.

The regulation of residual feed intake (RFI) in beef cattle involves brain-gut mechanisms due to the interaction between neural signals in the brain and hunger or satiety in the gut. RNA-Seq data contain an extensive resource of untapped SNPs. Therefore, hypothalamic and duodenal tissues from ten extreme RFI individuals were collected, and transcriptome sequenced in this study. All the alignment data were combined according to RFI, and the SNPs in the same group were identified. A total of 270,410 SNPs were found in the high RFI group, and 255,120 SNPs were found in the low RFI group. Most SNPs were detected in the intronic region, followed by the intergenic region, and the exon region accounts for 1.11% and 1.38% in the high and low RFI groups, respectively. Prediction of high-impact SNPs and annotation of the genes in which they are located yielded 83 and 97 genes in the high-RFI and low-RFI groups, respectively. GO enrichment analysis of these genes revealed multiple NADH/NADPH-related pathways, with ND4, ND5, and ND6 significantly enriched as core subunits of NADH dehydrogenase (complex I), and is closely related to mitochondrial function. KEGG enrichment analysis of ND4, ND5, and ND6 genes was enriched in the thermogenic pathway. Multiple genes, such as ATP1A2, SLC9A4, and PLA2G5, were reported to be associated with RFI energy metabolism in the concurrent enrichment analysis. Protein-protein interaction analysis identified multiple potential candidate genes related to energy metabolism that were hypothesized to be potentially associated with the RFI phenotype. The results of this study will help to increase our understanding of identifying SNPs with significant genetic effects and their potential biological functions.

SNP identification in FBXO32 gene and their associations with growth traits in cattle

In recent years, several association analysis methods for case-control studies have been developed. However, as we turn towards the identification of single nucleotide polymorphisms (SNPs) for prognosis, there is a need to develop methods for the identification of SNPs in high dimensional data with survival outcomes. Traditional methods for the identification of SNPs have some drawbacks. First, the majority of the approaches for case-control studies are based on single SNPs. Second, SNPs that are identified without incorporating biological knowledge are more difficult to interpret. Random forests has been found to perform well in gene expression analysis with survival outcomes. In this paper we present the first pathway-based method to correlate SNP with survival outcomes using a machine learning algorithm. We illustrate the application of pathway-based analysis of SNPs predictive of survival with a data set of 192 multiple myeloma patients genotyped for 500,000 SNPs. We also present simulation studies that show that the random forests technique with log-rank score split criterion outperforms several other machine learning algorithms. Thus, pathway-based survival analysis using machine learning tools represents a promising approach for the identification of biologically meaningful SNPs associated with disease.

Single nucleotide polymorphisms (SNPs) are single nucleotide variations which comprise the most wide spread source of genetic diversity in the genome. Currently, SNPs serve as markers for genetic predispositions, clinically evident disorders and diverse drug responses. Present SNP diagnostics are primarily based on enzymatic reactions in different formats including sequencing, polymerase-chain reaction (PCR) and microarrays. In these assays, the enzymes are applied to address the required sensitivity and specificity when detecting SNP. On the other hand, the development of enzyme-free, simple and robust SNP sensing methods is in a constant focus in research and industry as such assays allow rapid and reproducible SNP diagnostics without the need for expensive equipment and reagents. An ideal method for detection of SNP would entail mixing a DNA or RNA target with a probe to directly obtain a signal. Current assays are still not fulfilling these requirements, although remarkable progress has been achieved in recent years. In this review, current SNP sensing approaches are described with a main focus on recently introduced direct, enzyme-free and ultrasensitive SNP sensing by optical methods.