SNP genotyping using PCR

SNP genotyping using PCR

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I read this wikipedia article on SNP genotyping and wasn't able to understand this part :

In examining the results, if a genomic sample is homozygous, then the PCR products that result will be from the primer which matches the SNP location to the outer, opposite strand primer as well from the two opposite, outer primers. If the genomic sample is heterozygous, then products will result from the primer of each allele to their respective outer primer counterparts as well as from the two opposite, outer primers.

Can anyone explain this ?

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Detecting SARS-CoV-2 variants with SNP genotyping

¶ . Full list of consortium names and affiliations are available in S1 File .

Roles Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – review & editing

Affiliation School of Biological Sciences, University of Bristol, Bristol, United Kingdom

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Software, Supervision, Writing – original draft, Writing – review & editing

Affiliation School of Biological Sciences, University of Bristol, Bristol, United Kingdom

SNP detection

There are many methods of detecting novel and known SNPs. These include DNA sequencing, mass spectrometry, molecular beacons, SNP microarrays, and PCR-based methods.

SNP detection can be broken down into two sub-groups: SNP discovery and SNP screening. SNP discovery includes SNPs that are not yet known. Researchers are looking for new SNPs in targeted areas and on a genome-wide scale. SNP screening pertains to known SNPs and researchers are typically looking to genotype individuals or determine if a particular SNP is involved in producing a certain characteristic. There are many methods for performing both discovery and screening. For a historical account, see the paper by Kwok and Chen (1).

Materials and Methods

Preparation of Genomic DNA

Genomic DNA was isolated from fresh blood using Wizard Genomic DNA PuriWcation Kit (Promega Corp., Madison, WI) according to the manufacturer's protocol. Briefly, 300 μL of whole blood was transferred to the tube containing 900 μL of Cell Lysis Solution to lyse the red blood cells. Then after centrifuging, the visible white pellet was collected and lysed with 100 μL of Nuclei Lysis Solution. The sample was centrifuged again and the supernatant was transferred to a clean 1.5 mL microcentrifuge tube containing 300 μL of isopropanol. The white thread-like strands of DNA could form a visible mass by gently mixing the solution. Then genomic DNA was washed twice with 70% ethanol and finally rehydrated in 50 μL of DNA Rehydration Solution. The quality and quantity of DNA were determined by gel electrophoresis and using NANODROP 1000 (Thermo Scientific, Rockford, IL).

PCR Primer Design

Students were invited to retrieve gene database from the National Centre Biotechnology Institute and design primers using Primer Premier 5 program. By searching the term “human prdx6” in the gene database, students could easily find the record (http:// By clicking “SNP” on this page, students can view all SNPs of this gene. Then they were asked to find out which SNP could form a restriction site based on its flanking sequence. After analyzing all the SNPs in the database, one SNP (rs4382766) was selected, because SspI restriction site was found spanning this SNP site. A sequence consisting of 500 bp upstream and downstream of this SNP was input for searching primers. The searching parameters included primer length, search region and product length. Finally, a set of primers were chosen for PCR, with forward primer CCAAACTACTCTTCTTTCCCAACT, and reverse primer GACACTGTGCCAGGCCATAC. The full length of the PCR product was 449 bp, which would be divided into 186 and 263 bp after SspI digestion for T allele.

Amplification of Prdx6 Gene by PCR

The specific DNA fragment spanning rs4382766 was amplified using regular PCR, which was conducted in a total volume of 20 μL containing 0.5 μg genomic DNA, 1.0 pmol of each primer and 10 μL of 2× Master Mixture (Tiangen, China). The PCR cycling parameters were 94 °C for 5 minute, followed by 35 cycles of 94 °C for 30 second, 58 °C for 1 minute, and 72 °C for 1 minute, and one additional extension at 72 °C for 5 minute. Then, 5 μL of the PCR product was analyzed on 2% agarose gel.

Purification of PCR Product

The crude PCR product was purified with SanPrep PCR Purification Kit (Sangon Co. Shanghai, China). After adding three volume of Buffer B3 to the crude product, the tube was inverted several times. Then the mixture was loaded onto the center of a Binding Column inside a Wash Tube. After centrifuging for 1 minute, the Binding Column was further washed twice with Wash Buffer. Finally, 25 μL of Elution Buffer was added to the center of the Column, and was centrifuged to elute the purified DNA.

Restriction Enzyme Digestion

After verification of the PCR product by electrophoresis, the purified PCR product was digested with SspI enzyme (New England Biolabs Inc.), with a total volume of 20 μL containing 2 μL 10× buffer, 17 μL of the product and 1 μL (10U) of SspI. To avoid incomplete digestion, the mixture was incubated at 37 °C for 2 hour, and then analyzed on 2% agarose gel.

Precautions and Safety

For precaution and time saving, most reagents/solutions were provided using the commercial kits or prepared by the instructor in batches before the experiment. The major hazardous material was the blood samples. Although these samples were taken from healthy subjects, students were informed of the dangers and asked to follow the guidelines of safety rules. They were also informed other hazardous chemicals used in all the experiments, and they were required to wear gloves during all the procedures. To ensure the continuity of this lab course, genomic DNA and its PCR products were prepared by the instructor for those who failed to get any product to guarantee that all the students reach the final step.


Next-generation sequencing technologies such as pyrosequencing sequence less than 250 bases in a read which limits their ability to sequence whole genomes. However, their ability to generate results in real-time and their potential to be massively scaled up makes them a viable option for sequencing small regions to perform SNP genotyping. Compared to other SNP genotyping methods, sequencing is in particular, suited to identifying multiple SNPs in a small region, such as the highly polymorphic Major Histocompatibility Complex region of the genome.

Genotyping - qPCR

Genotyping refers to the process of determining genetic variations among individuals in a population. Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation and by definition are single-base differences at a specific locus that is found in more than 1% of the population. SNPs can be found in both coding and non-coding regions of the genome and can lead to phenotypic variations when found in coding regions. These genotype changes can confer positive or negative phenotypic outcomes, such as more robust stress tolerance in crops or enhance the susceptibility for disease in humans. Hence, SNPs are often useful markers for understanding the biology of organisms.

When found in non-coding regions, SNPs act as markers for evolutionary genomics studies. Related to SNPs are &ldquoInDels&rdquo, short for insertions and deletions of nucleotides of varying length. As with SNPs, InDels in coding regions can change the amino acid sequence of a protein, either by adding or subtracting an amino acid to the sequence if the indel is in multiples of 3, or by creating a frameshift mutation if the indel is not in a multiple of 3.

A third type of genetic variation is copy number variation (CNV), which results from having different numbers of copies of a DNA segment in various genomes. In cases where the copy number variation is for an encoded gene, the variation can lead to susceptibility or resistance to disease. Some phenotypes are also dosage-sensitive, and the copy number is responsible for shades of variability among members of a species.

For both SNP genotyping, many methods exist to determine genotype among individuals. The chosen method generally depends on the throughput needs, which is a function of both the number of individuals being genotyped and the number of genotypes being tested for each individual. The chosen method also depends on the amount of sample material available from each individual or sample, which dictates the required sensitivity of the assay.

Osteoarthritis: Genetic Studies of Monogenic and Complex Forms

3.2.2 Genome-Wide Association Studies

With advances of high-throughput SNP genotyping technology, genome-wide association studies (GWAS) became possible in the past decade. 17 GWAS took advantage of linkage disequilibrium (LD) that is, the fact that in any given chromosomal region in the genome alleles at physically nearby loci segregate together in the population. The markers analyzed need not be functional, but may simply be in LD with the functional variant. 65 However, the large-scale nature of GWAS introduces a multiple testing issue requiring replication of any positive associations. GWAS are nevertheless a powerful approach for unlocking the genetic basis of complex diseases, such as OA. Individual studies may be hampered by sample size limitations, which result in lack of statistical power and metaanalyses based on consortium efforts may help to overcome some of these limitations.

Several GWAS in OA have been published to date and a summary of the findings is presented in Table 24.2 . While they clearly show that there is no definitive and common highly penetrant allele that causes OA, some interesting genes have emerged. The findings better delineate the types of genes and genetic variants that are involved in OA and provide substantial insight for future research.

The first GWAS using over 100,000 markers to be published was, from the United Kingdom, using pooled DNAs from 357 knee OA patients and 285 controls. 66 It identified a signal (rs4140564) between PTGS2 and PLA2G4A. 66 A second GWAS of knee OA, was published by a Japanese group. 54 After screening patients and 658 controls for <80,000 SNPs, a subset of 2,153 SNPs were tested in a second set of 646 knee OA cases and 631 controls. Two variants, in this region were identified as the most strongly associated. The locus was named double von Willebrand factor A (DWVA), and two coding variants, rs11718863 and rs7639618, were confirmed to be strongly associated with the risk of knee OA, in addition to Chinese and Japanese cases and control samples. The two SNPs were found to influence the binding of the DVWA protein to β-tubulin, and the authors hypothesized that tubulins and microtubules might be protective factors in the pathogenesis of OA. 54 Subsequently, however, the two SNPs were found to show no association on knee or hip OA in Caucasian patients. 67 On the other hand, it was later shown bioinformatically that DVWA is a part of the human gene coding for the collagen VI alpha4 chain (COL6A4) 68 ( Table 24.2 ).

Another Japanese study identified two SNPs within a small region of the HLA locus on chromosome 6p to be associated with knee OA, with P < 7 × 10 −8 . 56 However, replication was not achieved in European cohorts and a population of Han Chinese. 69,70

GWAS in European cohorts from the Netherlands (the Rotterdam study) 71 identified a signal (p < 8 × 10 −8 , OR 1.14) in a region on chromosome 7q22 that included a large LD block extending over 500 kb associated with knee and hand OA. Addition of several more cohorts to the original study increased the credibility of this signal. However, the LD block contained six known genes, all of which are equally good candidates for association with OA. These include PRKAR2B (encoding protein kinase-cAMP-dependent-regulatory type II-β), GPR22 (encoding G protein-coupled receptor 22), and COG5 (encoding component of oligomeric golgi complex 5). A subsequent metaanalysis, which included 6,709 patients with knee OA and 44,439 controls, showed conclusively that this signal is associated with genome-wide significance in European-descent samples with OR = 1.17 (95% CI 1.11–1.24), and a p-value of 9.2 × 10 −9 , but not in Asian populations, where the OR was 1.03 (95% CI 0.85–1.25 n.s.) 58 ( Table 24.2 ).

The arcOGEN study is a UK consortium, based around seven collection centers, which reported a discovery cohort of 3177 patients and 4894 population (not phenotypically characterized) controls. 72 Replication of signals involved additional European cohorts, as well as Caucasian North Americans, resulting in an overall metaanalysis sample of 13,768 hip and knee OA patients and 53,286 controls. Although it involved the largest sample size to date, it was unable to identify a signal of genome-wide significance. The strongest signal was rs2277831 (P = 2.3 × 10 −5 ), located within MICAL3. 72

Later, the same group generated 1000 genomes project-based imputation 73 on the same data from the arcoGEN consortium as aforementioned (3177 knee and hip OA patients and 4894 population controls). Imputation methods exploit information on patterns of multimarker correlation (linkage disequilibrium) from publically available databases, such as the International HapMap project or the SeattleSNPs resequencing studies, and more recently the 1000 genomes project, 73 to estimate or “impute” individual patient or control genotypes at untyped SNPs, and assess the estimated genotypes for association with phenotype. The imputed data were then used to detect previously unidentified risk loci. Through large-scale replication, it was possible to establish robust association with SNPs in the MCF.2 cell line derived transforming sequence-like (MCF2L). 59 The top signal rs11842874 reached a combined OR1.17 (95% CI 1.11–1.23), P = 2.1 × 10 −8 across a total of 19,041 OA cases and 24,504 controls of European descent ( Table 24.2 ). MCF2L encodes a rho-specific guanine nucleotide exchange factor, and its role in OA remains unclear.

A GWAS metaanalysis on 78,000 individuals identified a genome wide significant variant (rs6094710) in the NCOA3 gene (OR = 1.28 95% CI 1.18–1.39 P = 7.9 × 10 −9 ). 65 This p-value was improved after combined analysis of the discovery (P = 5.6 × 10 −8 ) and follow-up studies (P = 7.3 × 10 −4 ). Two loci remained suggestively associated: rs5009270 at 7q31 (OR = 1.10 P = 9.9 × 10 −7 ) and rs3757837 (OR = 1.27 P = 2.2 × 10 −6 in a male-specific analysis) 62 ( Table 24.2 ).

A GWAS on hip OA, using data from the Osteoporotic Fractures in Men Study and the study of osteoporotic fractures, was replicated in five independent studies. The rs788748 SNP located near the IGFBP3 gene was genome-wide significant in this analysis and associated with a lower risk of hip OA (OR = 0.71 P = 2.0 × 10 −8 ). Although the association replicated in all five studies, the signal was weakened after replication, suggesting a possible false positive result (OR = 0.92 P = 0.020). Despite this, a role of this variant and gene in OA is suggested by the results of functional validation studies. 63 Further replication is necessary, ideally with larger sample sizes, to make a more confident assertion of this variant’s role in OA 63 ( Table 24.2 ).

A GWAS on cartilage thickness at the hip has been carried out using data from the Rotterdam study. A SNP in the DOT1L gene was strongly associated with mJSW at the hip 74 . After replication in independent UK cohorts, an overall genetic effect size (expressed as the regression coefficient beta) of 0.09 mm/allele was achieved (P = 1.1 × 10 −11 after metaanalysis). 74 The risk allele for lower mJSW at this SNP was later associated with a 10% increased risk of hip OA (P = 8.8 × 10 −8 ). This effect reached genome wide significance in males (OR = 1.17 95% CI 1.11–1.23 P = 7.8 × 10 −9 ), but was only nominally significant in women with a small effect size (OR = 1.05), consistent with the sexual dimorphism seen in some forms of hip OA 66 ( Table 24.2 ).

The first GWAS to report genome-wide significant results for hand OA revealed a SNP (rs3204689) in the ALDH1A2 gene to be significantly associated with an increased risk of hand OA in an Icelandic discovery cohort (OR = 1.51, P = 3.99 × 10 −10 ). This finding was replicated in cohorts from the United Kingdom and the Netherlands, showing an improved association and significantly increased risk of hand OA (OR = 1.46, P = 1.10 × 10 −11 ). In silico replication found a significant association with this variant for knee OA, but not hip OA. Interestingly, this was a protective effect (OR = 0.95, P = 0.044), the opposite of the effect is seen on hand OA. The authors were surprised at this finding as the literature has previously suggested a close relationship between hand and knee OA 67 ( Table 24.2 ).

More affordable and effective noninvasive SNP genotyping using high-throughput amplicon sequencing

Non-invasive genotyping methods have become key elements of wildlife research over the last two decades, but their widespread adoption is limited by high costs, low success rates, and high error rates. The information lost when genotyping success is low may lead to decreased precision in animal population densities which could misguide conservation and management actions. Single nucleotide polymorphisms (SNPs) provide a promising alternative to traditionally used microsatellites as SNPs allow amplification of shorter DNA fragments, are less prone to genotyping errors, and produce results that are easily shared among laboratories. Here, we outline a detailed protocol for cost-effective and accurate noninvasive SNP genotyping using highly multiplexed amplicon sequencing optimized for degraded DNA. We validated this method for individual identification by genotyping 216 scats, 18 hairs and 15 tissues from coyotes (Canis latrans). Our genotyping success rate for scat samples was 93%, and 100% for hair and tissue, representing a substantial increase compared to previous microsatellite-based studies at a cost of under $5 per PCR replicate (excluding labor). The accuracy of the genotypes was further corroborated in that genotypes from scats matching known, GPS-collared coyotes were always located within the territory of the known individual. We also show that different levels of multiplexing produced similar results, but that PCR product cleanup strategies can have substantial effects on genotyping success. By making noninvasive genotyping more affordable, accurate, and efficient, this research may allow for a substantial increase in the use of noninvasive methods to monitor and conserve free-ranging wildlife populations.

An alternative method for human sex-typing

Citation summary: Identifying the sex of a biological sample is conventionally determined via PCR amplification of amelogenin genes. In this study, Maxeiner, et al., investigate the validity of sexing using neuroligin-4, an autism-associated gene, and present an alternative method using the rhAmp SNP Genotyping System.


Determining the sex identification of a sample is an important part of a broad range of research areas. Human forensic analysis, animal genetics research focused on strategic livestock breeding, and labs that use mouse models for all kinds of biological research all benefit from sex identification based on DNA. For decades, sex identification had been based on the presence of the SRY gene found on the Y chromosome using PCR. Unfortunately, the absence of the SRY gene does not guarantee that the sample is female, and these experiments utilizing SRY lack an internal control. Use of the amelogenin genes (AMELX/Y) for sex differentiation appeared to solve this problem, since they are localized on both the X and Y chromosomes. Neuroligin-4 (NLGN4X/Y) has similar properties, appearing on both sex chromosomes, highlighting this genes potential for use in sex identification.

PCR is the conventional method of choice for sex identification. When genes like NLGN4X/Y contain multiple mutations, standard PCR may not be sufficient to distinguish between the 2 gene copies. The rhAmp&trade SNP Genotyping System overcomes the challenge of many polymorphisms by using blocked primers to minimize non-specific amplification. The 3' end of rhAmp primers incorporate a blocking group that prevents extension unless cleavage and de-blocking occur by RNase H2 enzyme. RNase H2 enzyme recognizes this RNA base only if it is hybridized to its perfect complement, initiating primer cleavage and activation (see figure).


Gene sequence information was downloaded from the NCBI database. DNA was extracted from 6 buccal cell samples and 105 human blood samples. PCR primers were used to identify an insertion/deletion (indel) region. SNP genotyping was performed using the rhAmp SNP Genotyping System starting with identifying primers using the rhAmp Genotyping Design Tool


For conventional PCR to distinguish between the sexes, the sequence may not contain ambiguous bases that might inhibit primer annealing, and the 2 alleles, X and Y, must be distinguishable on an agarose gel using electrophoresis. Unlike conventional PCR, the rhAmp SNP Genotyping System allows for variations in sequence.

To test whether NLGN4 could be used for sex identification using conventional PCR, Maxeiner, et al, targeted an indel region immediately upstream of the start codon. Since NLGN4X (381 bp) is almost twice as long as NLGN4Y (187 bp), conventional PCR can be used to distinguish between the 2 alleles using agarose gel electrophoresis.

The researchers focused on single nucleotide polymorphisms (SNPs) when testing NLGN4 using the rhAmp SNP Genotyping System. All 3 of the assays designed by the rhAmp Genotyping Design Tool successfully identified NLGN4X. One assay was able to separate samples into clusters to distinguish between both sex alleles.

This study is the first to investigate rhAmp genotyping as a method of sex identification. The rhAmp SNP Genotyping System was able to identify the samples&rsquo sex at the same rate as the conventional PCR assay but includes the advantage of scaling. The rhAmp SNP Genotyping System can be scaled up to include multiplexing and allow high-throughput screening. The polymorphisms in NLGN4X/Y were valid markers for distinguishing between the sex alleles. These genes could be used in conjunction with, or as an alternative to, other sex-specific gene pairs like AMELX/Y. The rhAmp SNP strategy could be applied to these other sex-specific gene pairs as well.

Is the acquisition of the raw data and its interpretation complicated?

The answer is no. Once the SpectroCHIP array is loaded into the MassARRAY Analyzer, where the analyte crystals are irradiated and ionized in order that the charged molecules accelerate into a detector. Separation occurs by time-of-flight, which is proportional to the mass of the individual molecules.

The entire process takes less than 50 minutes to analyze 384 samples. In this picture, we can show you how looks a complete spectrum for an experiment of 36-plex assay. The highlighted peaks indicate 24 Da separation in heterozygous alleles (B) of the SNP in question compared to the single peak homozygous genotype (C).

Typer software automatically generates reports that identify the SNP alleles (homozygous or heterozygous) in each sample.

Bioline Scholar – Human Genes, Genetics, Genomes (Special ASHG 2012 Edition)

American Society of Human Genetics 2012 Annual Meeting

Bioline was once again an exhibitor (#Booth 1324-1326) at the American Society of Human Genetics (ASHG) annual meeting held in San Francisco in November. The largest human genetics meeting in the world, ASHG 2012 attracted over 7000 delegates to discuss the very latest advances in basic and clinical research.

Sessions included topics such as comparative epigenomics, early exome sequencing in complex traits, large-scale identification of regulators of translation and integrated genetic and functional studies of disease-causing variants.

Bioline unveiled its new format exhibition stand at the conference, where our representatives met with scientists and discussed solutions to their molecular biology challenges. Bioline PCR Specialist, Dr. Sven Bocklandt gave a series of well received and thought-provoking talks on some of our latest products, including SensiFAST™, MyFi™ and MyTaq™ DNA polymerases. Exciting results from both published papers and some unpublished experiments from the Bioline scientific community were presented, including results from the Bioline PCR Challenge.

In keeping with ASHG 2012, this month’s Bioline scholar is dedicated to Human Genetics. We are pleased to highlight a selection of recent papers featuring Bioline products, perfectly suited for both small- and large-scale genetic and genomic studies in humans.

BIO-X-ACT™ Long DNA Polymerase

Mutations in MTM1 (myotubularin 1) cause X-linked myotubular myopathy that affects 1 in 50,000 males. In neonates or infants, movement and breathing are severely affected. The authors developed a MTM1-specific database of genetic variants, with 474 identified mutations from 472 patients. Next-Gen sequencing (Illumina HiSeq) and cDNA analysis revealed the presence of a novel MTM1/MAMLD1 fusion transcript in one case.

CDNA synthesis kit

Children with X-linked retinitis pigmentosa (XLRP) often go blind by the second decade of life. A severe form of XLRP, RP23, was previously mapped to a 10.71Mb interval on Xp22.31-22.13, containing 62 genes. Using targeted NGS (Illumina), the authors identified a deep intronic mutation in OFD1 as the most likely cause of RP23. Insertion of a cryptic exon produces an aberrant transcript and reduced levels of correctly spliced transcript. This is predicted to result in a severely truncated protein and decreased levels of normal protein.

BIOTAQ™ DNA Polymerase

The genetic basis for susceptibility to malaria in a Vietnamese population was investigated by SNP genotyping by researchers from Oxford University and the MalariaGen consortium. Data from 65 SNPs in 42 malarial candidate genes in 956 severe malaria cases and 2350 controls from Vietnam was reported. Variants in six genes (ICAM1, IL1A, IL17RC, IL13, LTA and TNF) encoding adhesion and pro-inflammatory molecules were associated with severe malaria.

BioMix™ Red

Facioscapulohumeral muscular dystrophy (FSHD), characterized by muscle weakness and wasting, is associated with a shortened telomeric chr 4q35 due to deletions of the D4Z4 tandem repeat (FSHD1) or DNA methylation changes of D4Z4 (FSHD2). Using exome sequencing (Illumina NGS) the authors identified two known pathogenic mutations in CAPN3, indicating a case of limb-girdle muscular dystrophy type 2A (LGMD2A) rather than FSHD2. The authors conclude that ‘diagnosis by sequencing’ of FSHD may be more commonly adopted in clinical genetics laboratories around the world.

An arrayed human genomic library comprising 115,000 PAC clones was constructed. Functional studies with a p53-containing PAC clone in p53-null human osteosarcoma cells showed the utility of individual library members in human cell culture models. The library can be used to validate candidate genes identified by GWAS and for gene therapy in different recessive disorders.


Charcot-Marie-Tooth disease (CMT) is an inherited disorder of peripheral nerve dysfunction resulting in numbness and weakness. Mutations in four genes encoding an aminoacyl-tRNA synthetase (ARS) have been associated with CMT. This study from the University of Michigan found that the p.Arg329 AARS mutation is a recurrent, loss-of-function mutation that arises due to methylation-mediated deamination of a CpG dinucleotide.

Introducing the Bioline Scholar Publications Database

Bioline Scholar – from Bioline: The PCR Company

If you’re interested in knowing more about the fields and areas of research in which Bioline products have been used to further knowledge, we’ve added a Bioline Scholar page to our web site listing the papers and publications in which our molecular biology reagents are featured.

You can search for publications by author, title, topic and product and the archive contains papers from 1994 through to the present. Currently the Bioline Scholar database lists and provides links to publications where the research was conducted using the following Bioline products:

That’s it for the Bioline blog in 2012—season’s greetings to all our customers and readers alike, from all at Bioline—see you in 2013!

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