iBP-seq:An efficient and low-cost multiplex targeted genotyping and epigenotyping system

Inter-and intra-specific variations in phenotype are common and can be associated with genomic mutations as well as epigenomic variation.Profiling both genomic and epigenomic variants is at the core of dissecting phenotypic variation.However,an efficient targeted genotyping and epigenotyping system is lacking.We describe a new multiplex targeted genotyping and epigenotyping system called improved bulked-PCR sequencing(iBP-seq).We employed iBP-seq for the detection of genotypes and methylation levels of dozens of target regions in mixed DNA samples.iBP-seq can be adapted for the construction of linkage maps,fine mapping of quantitative-trait loci,and detection of genome editing mutations at a cost as low as$0.016 per site per sample.We developed an automated bioinformatics pipeline,including primer design,a series of bioinformatic analyses for genotyping and epigenotyping,and visualization of results.iBP-seq and its bioinformatics pipeline,available at http://zeasystemsbio.hzau.edu.cn/tools/ibp/,can be adapted to a wide variety of species.

Development of a target capture sequencing SNP genotyping platform for genetic analysis and genomic breeding in rapeseed

Rapeseed(Brassica napus)is an oil crop grown worldwide,making it a key plant species in molecular breeding research.However,the complexity of its polyploid genome increases sequencing costs and reduces sequencing accuracy.Target capture coupled with high-throughput sequencing is an efficient approach for detecting genetic variation at genomic regions or loci of interest.In this study,588 resequenced accessions of rapeseed were used to develop a target capture sequencing SNP genotyping platform named BnaPan50T.The platform comprised 54,765,with 54,058 resequenced markers from the pan-genome,and 855 variant trait-associated markers for 12 agronomic traits.The capture quality of BnaPan50T was demonstrated well in 12 typical accessions.Compared with a conventional genotyping array,BnaPan50T has a high SNP density and a high proportion of SNPs in unique physical positions and in annotated functional genes,promising wide application.Target capture sequencing and wholegenome resequencing in 90 doubled-haploid lines yielded 60%specificity,78%uniformity within tenfold coverage range,and 93%genotyping accuracy for the platform.BnaPan50T was used to construct a genetic map for quantitative trait loci(QTL)mapping,identify 21 unique QTL,and predict several candidate genes for yield-related traits in multiple environments.A set of 132 core SNP loci was selected from BnaPan50T to construct DNA fingerprints and germplasm identification resources.This study provides genomics resources to support target capture sequencing,genetic analysis and genomic breeding of rapeseed.

The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs

Background:Survival from birth to slaughter is an important economic trait in commercial pig productions.Increasing survival can improve both economic efficiency and animal welfare.The aim of this study is to explore the impact of genotyping strategies and statistical models on the accuracy of genomic prediction for survival in pigs during the total growing period from birth to slaughter.Results:We simulated pig populations with different direct and maternal heritabilities and used a linear mixed model,a logit model,and a probit model to predict genomic breeding values of pig survival based on data of individual survival records with binary outcomes(0,1).The results show that in the case of only alive animals having genotype data,unbiased genomic predictions can be achieved when using variances estimated from pedigreebased model.Models using genomic information achieved up to 59.2%higher accuracy of estimated breeding value compared to pedigree-based model,dependent on genotyping scenarios.The scenario of genotyping all individuals,both dead and alive individuals,obtained the highest accuracy.When an equal number of individuals(80%)were genotyped,random sample of individuals with genotypes achieved higher accuracy than only alive individuals with genotypes.The linear model,logit model and probit model achieved similar accuracy.Conclusions:Our conclusion is that genomic prediction of pig survival is feasible in the situation that only alive pigs have genotypes,but genomic information of dead individuals can increase accuracy of genomic prediction by 2.06%to 6.04%.

Genotyping ex situ trees of Abies nebrodensis translocated from the original Sicilian population to enrich the gene pool

As a dynamic ex situ conservation strategy,a clonal seed orchard was started in a nursery in Pomaio(POM)in central Italy in 1993 for an assisted migration experiment of Abies nebrodensis(Lojac.)Mattei.Two artifi cial ex situ populations were planted with this gene pool:a seedling arboretum in Pieve Santo Stefano(PSS)and a small dendrological collection in Papiano(PAP),both originating from the Sicilian relict population.Here,using AFLP markers,we estimated the relatedness among the relocated genotypes of the three collections to check whether the three collections had suffi cient genetic variability to be considered as additional sources of variability to the original gene pool for the assisted migration strategy.High individual genetic variability was found in the collections;each plant had a diff erent genotype and was confi rmed to belong to its population of origin.PAP and PSS trees were shown to be only from the original population of A.nebrodensis species and were derived from a limited set of maternal fertile genotypes.Based on the Sicilian fi r population inventory,nursery production in Sicily,and structure clustering analysis,close genetic relationships among POM,PAP and several PSS trees(1–35)were evident.Similarly,the PSS group(36–78)was genetically close to tree 1 of POM and in a lesser proportion to plants 7 and 9 of POM.The sampling of seedlings used to form batches in the nursery might have infl uenced the structure of the resultant plantations.All genotypes will be useful for enriching the original gene pool.

Molecular Genotyping of Human Papillomavirus (HPV) in Hypopharyngeal Cancer

Background: In recent years, head and neck cancers have become common worldwide, ranking sixth in incidence. In 2007, in France the incidence increased by 14,697 including 11,158 among men, which places them in fourth place. The same year, 32,268 patients were hospitalized for this pathology, but 95% are associated with alcohol and tobacco poisoning. Few data exist on these cancers in Africa and Senegal. In recent years, many studies have hypothesized that about 25% of head and neck cancers are associated with high-risk oncogenic human papillomaviruses (HPV) whose role in cervical cancer was already widely established. Objective: To know the prevalence and genotypes of HPV in head and neck cancers, particularly hypopharyngeal cancer. Material and method: This study was carried out on samples of biopsies of hypopharynx cancerous tissue (ulcerative-budding lesion) and healthy oropharyngeal tissue obtained from the ENT department of the Fann hospital, then sent to the Molecular Biology Unit of the Ouakam military hospital (HMO). The nucleic acids extraction was carried out using the standard method of the Zymo research kit “Quick-DNATM Miniprep Plus kit” https://www.zymoresearch.com/. Molecular HPV detection and genotyping were performed by multiplex RT-PCR with the Seegene AnyplexTM II HPV28 kit Detection on a Biorad CFX96 automaton according to the manufacturer’s protocol for the simultaneous genotyping of 28 types of HPV including 19 at High Risk (HR) and 9 low risk (LR). Results: 156 patients were sampled, 61 Hypopharynx cancer biopsies and 95 healthy tissues. The median age of the general population was 36.5 years [12, 73];the median age of the population with hypopharyngeal cancer of 40 years. Of the general study population 24.36% (38/156) was infected with HPV. In populations with hypopharyngeal cancer, HPV prevalence was 19.67% (12/61), 17.84% (5/28) in men and 21.21% (7/33) in women. HPV6 was the most frequently encountered genotype in the cancer population. Multiple infections have also been noted in cancer patients: HPV6+HPV18, HPV6+HPV56. For patients without hypopharyngeal cancer, the HPV prevalence was 27.36% (26/95), 9.59% (7/73) in women and 89.36% (19/22) in men. Several types of HPV-HR genotypes (HPV18, HPV26, HPV69), and HPV-LR genotypes (HPV42, HPV43, HPV70, HPV6) have been detected in healthy patients but also cases of co-infections (HPV6+HPV69;HPV56+HPV44;HPV58+HPV18). Conclusion: Our results showed a higher prevalence of HPV in non-cancer patients compared to hypopharyngeal cancer patients. The genotypes (HPV 6, 18 and 56) were observed in the study population. Molecular genotyping does not show a significant involvement of HPV in hypopharyngeal cancer.

Microsatellite Genotyping for Four Expected Inbred Mouse Strains from KM Mice

Chinese Kun Ming （KM） mouse, an outbreed strain of laboratory animal, has been widely utilized in related pharmaceutical and genetic studies throughout China. However, the value of KM mice to the research community has been severely limited, partially due to the fact that well-characterized inbred strain of KM mice is not available. Several expected inbred strains from KM mice have been bred, but their genetic purity remains uncertain. In this study, four expected inbred strains of KM mice （A1, T2, N2, and N4） were chosen and their inbred degree were compared with two classical inbred mouse lines （BALB/c and C57BL/6） by analyzing the genotypes of about 30 microsatellite markers. In the four strains, A1 and N4 were homozygous at all genotyped loci, but N2 and T2 were only heterozygous at locus D15Mit16. These results indicate that the level of genetic purity/homozygousity of A1, N4, N2, and T2 inbred line is comparable to those of BALB/c and C57BL/6. This study provided the first and solid evidence for genetic purity of four expected inbred strains of KM mice. These 4 inbred mice strains should be well maintained for further characterization and utilization in genetic studies.

Genotyping of White Spot Syndrome Virus in Chinese Cultured Shrimp during 1998-1999

Recent studies showed that white spot syndrome virus(WSSV) isolates from different geographic locations share a high genetic similarity except the variable regions in ORF23/24 and ORF14/15,and variable number of tandem repeats(VNTR) within ORF94.In this study,genotyping was performed according to these three variable regions among WSSV isolates collected during 1998/1999 from Southern China.These WSSV isolates contain a deletion of 1168,5657,5898,9316 and 11093 bp,respectively in the variable region ORF23/24 compared with WSSV-TW,and a deletion of 4749 or 5622 bp in the variable region ORF14/15 relative to TH-96-II.Four types of repeat units(RUs)(6,8,9 and 13 RUs) in ORF94 were detected in these isolates,with the shortest 6 RUs as the most prevalent type.Our results provide important information for a better understanding of the spatio-temporal transmission mode and the WSSV genetic evolution lineage.

Improving genomic predictions by correction of genotypes from genotyping by sequencing in livestock populations

Background: Genotyping by sequencing(GBS) is a robust method to genotype markers. Many factors can influence the genotyping quality. One is that heterozygous genotypes could be wrongly genotyped as homozygotes,dependent on the genotyping depths. In this study, a method correcting this type of genotyping error was demonstrated. The efficiency of this correction method and its effect on genomic prediction were assessed using simulated data of livestock populations.Results: Chip array(Chip) and four depths of GBS data was simulated. After quality control(call rate ≥ 0.8 and MAF ≥ 0.01), the remaining number of Chip and GBS SNPs were both approximately 7,000, averaged over 10 replicates. GBS genotypes were corrected with the proposed method. The reliability of genomic prediction was calculated using GBS, corrected GBS(GBSc), true genotypes for the GBS loci(GBSr) and Chip data. The results showed that GBSc had higher rates of correct genotype calls and higher correlations with true genotypes than GBS. For genomic prediction, using Chip data resulted in the highest reliability. As the depth increased to 10, the prediction reliabilities using GBS and GBSc data approached those using true GBS data. The reliabilities of genomic prediction using GBSc data were 0.604, 0.672, 0.684 and 0.704 after genomic correction, with the improved values of 0.013, 0.009, 0.006 and 0.001 at depth = 2, 4, 5 and 10, respectively.Conclusions: The current study showed that a correction method for GBS data increased the genotype accuracies and, consequently, improved genomic predictions. These results suggest that a correction of GBS genotype is necessary, especially for the GBS data with low depths.

Comparisons of improved genomic predictions generated by different imputation methods for genotyping by sequencing data in livestock populations

Background:Genotyping by sequencing(GBS)still has problems with missing genotypes.Imputation is important for using GBS for genomic predictions,especially for low depths,due to the large number of missing genotypes.Minor allele frequency(MAF)is widely used as a marker data editing criteria for genomic predictions.In this study,three imputation methods(Beagle,IMPUTE2 and FImpute software)based on four MAF editing criteria were investigated with regard to imputation accuracy of missing genotypes and accuracy of genomic predictions,based on simulated data of livestock population.Results:Four MAFs(no MAF limit,MAF≥0.001,MAF≥0.01 and MAF≥0.03)were used for editing marker data before imputation.Beagle,IMPUTE2 and FImpute software were applied to impute the original GBS.Additionally,IMPUTE2 also imputed the expected genotype dosage after genotype correction(GcIM).The reliability of genomic predictions was calculated using GBS and imputed GBS data.The results showed that imputation accuracies were the same for the three imputation methods,except for the data of sequencing read depth(depth)=2,where FImpute had a slightly lower imputation accuracy than Beagle and IMPUTE2.GcIM was observed to be the best for all of the imputations at depth=4,5 and 10,but the worst for depth=2.For genomic prediction,retaining more SNPs with no MAF limit resulted in higher reliability.As the depth increased to 10,the prediction reliabilities approached those using true genotypes in the GBS loci.Beagle and IMPUTE2 had the largest increases in prediction reliability of 5 percentage points,and FImpute gained 3 percentage points at depth=2.The best prediction was observed at depth=4,5 and 10 using GcIM,but the worst prediction was also observed using GcIM at depth=2.Conclusions:The current study showed that imputation accuracies were relatively low for GBS with low depths and high for GBS with high depths.Imputation resulted in larger gains in the reliability of genomic predictions for GBS with lower depths.These results suggest that the application of IMPUTE2,based on a corrected GBS(GcIM)to improve genomic predictions for higher depths,and FImpute software could be a good alternative for routine imputation.

Improved Allele-specific Polymerase Chain Reaction for Single Nucleotide Polymorphism Genotyping

An improved allele-specific PCR（AS-PCR） approach was applied to investigating -55C/T polymorphism in promoter region of the uncoupling protein 3（UCP3）gene. AS-PCR is a competitive PCR method which is based on positioning the 3＇ base of a PCR primer to match one single nucleotide polymorphism（SNP） allele and accurately extend only the correctly matched primer. But it is limited in use because of its poor specificity. In this study, we improved the specificity of AS-PCR by introducing additional mismatch at the penultimate base of 3＇ end of AS-PCR primer in combination with decreasing the level of dNTP in the reaction mixture. Sensitivity, specificity and reliability of this method were assessed for both simple plasmid model and complex human genomic SNP targets. The -55C/T（rs1800849） polymorphisrn of the UCP3 gene was analyzed via this AS-PCR and restriction fragment length polymorphism（RFLP）, the latter was used as a gold standard. The results suggest that the increase in AS-PCR discrimination with this method should facilitate the use of this simple, rapid, and inexpensive technique for SNP genotyping application.

A High-Performing and Cost-Effective SNP Genotyping Method Using rhPCR and Universal Reporters

We have developed a novel dual enzyme chemistry called rhAmp®SNP genotyping based on RNase H2-dependent PCR (rhPCR) that provides high signal and specificity for SNP analysis. rhAmp SNP genotyping combines a unique two-enzyme system with 3’ end blocked DNA-RNA hybrid primers to interrogate SNP loci. Activation of the blocked primers occurs upon hybridization to its perfectly matched target, which eliminates or greatly reduces primer dimers. A thermostable hot-start RNase H2 cleaves the primer immediately 5’ of the ribose sugar, releasing the blocking group and allowing primer extension. PCR specificity is further improved with the use of a mutant Taq DNA polymerase, resulting in improved allelic discrimination. Signal generation is obtained using a universal reporter system which requires only two reporter probes for any bi-allelic SNP. 1000 randomly selected SNPs were chosen to validate the 95% design rate of the design pipeline. A subsampling of 130 human SNP targets was tested and achieved a 98% call rate, and 99% call accuracy. rhAmp SNP genotyping assays are compatible with various qPCR instruments including QuantStudioTM 7 Flex, CFX384TM, IntelliQube®, and Biomark HDTM. In comparison to TaqMan®, rhAmp SNP genotyping assays show higher signal (Rn) and greater cluster separation, resulting in more reliable SNP genotyping performance. The rhAmp SNP genotyping solution is suited for high-throughput SNP genotyping applications in humans and plants.

The GATK joint genotyping workflow is appropriate for calling variants in RNA-seq experiments

The Genome Analysis Toolkit(GATK) is a popular set of programs for discovering and genotyping variants from next-generation sequencing data.The current GATK recommendation for RNA sequencing(RNA-seq) is to perform variant calling from individual samples,with the drawback that only variable positions are reported.Versions 3.0 and above of GATK offer the possibility of calling DNA variants on cohorts of samples using the HaplotypeCaller algorithm in Genomic Variant Call Format(GVCF) mode.Using this approach,variants are called individually on each sample,generating one GVCF file per sample that lists genotype likelihoods and their genome annotations.In a second step,variants are called from the GVCF files through a joint genotyping analysis.This strategy is more flexible and reduces computational challenges in comparison to the traditional joint discovery workflow.Using a GVCF workflow for mining SNP in RNA-seq data provides substantial advantages,including reporting homozygous genotypes for the reference allele as well as missing data.Taking advantage of RNA-seq data derived from primary macrophages isolated from 50 cows,the GATK joint genotyping method for calling variants on RNA-seq data was validated by comparing this approach to a so-called "per-sample" method.In addition,pair-wise comparisons of the two methods were performed to evaluate their respective sensitivity,precision and accuracy using DNA genotypes from a companion study including the same 50 cows genotyped using either genotyping-by-sequencing or with the Bovine SNP50 Beadchip(imputed to the Bovine high density).Results indicate that both approaches are very close in their capacity of detecting reference variants and that the joint genotyping method is more sensitive than the per-sample method.Given that the joint genotyping method is more flexible and technically easier,we recommend this approach for variant calling in RNA-seq experiments.

Establishment of Multiple Locus Variable-number Tandem Repeat Analysis Assay for Genotyping of Borrelia burgdorferi sensu lato Detected in China

Objective Human Lyme Borreliosis （LB）, which is caused by Borrefia burgdorferi sensu lato （B. burgdorferi）, has been identified as a major arthropod-borne infectious disease in China. We aimed to develop a multiple locus variable-number tandem repeat （VNTR） analysis （MLVA） assay for the genotyping of Borrelia burgdorJ：eri strains detected in China. Methods B. garinii PBi complete 904.246 kb chromosome and two plasmids （cp26 and Ip54） were screened by using Tandem Repeats Finder program for getting potential VNTR loci, the potential VNTR loci were analyzed and identified with PCR and the VNTR loci data were analyzed and MLVA clustering tree were constrcted by using the categorical coefficient and the unweighted pair-group method with arithmetic means （UPGMA）. Results We identified 5 new VNTR loci through analyzing 47 potential VNTR loci. We used the MLVA protocol to analyse 101 B. burgdorferi strains detected in China and finally identified 51 unique genotypes in 4 major clusters including B. burgdorferi sensu stricto （B.b.s.s）, B. garinii, B. a[zelii, and B. valaisiana, consistent with the current MLSA phylogeny studies. The allele numbers of VNTR-1, VNTR-2, VNTR-3, VNTR-4, and VNTR-5 were 7, 3, 9, 7, and 6. The Hunter-Gaston index （HGI） of five VNTR loci were 0.79, 0.22, 0.77, 0.71, and 0.67, respectively. The combined HGI of five VNTR loci was 0.96. Clustering of the strains of Xinjiang, Inner Mongolia and Heilongjiang was confirmed, and this situation was consistent with the close geographical distribution of those provinces. Conclusion The MLVA protocol esytablished in this study is easy and can show strains＇ phylogenetic relationships to distinguish the strains of Borrelia species. It is useful for further phylogenetic and epidemiological analyses of Borrelia strains.

Risks involved in fecal DNA-based genotyping of microsatellite loci in the Amur tiger Panthera tigris altaica:a pilot study

In modern wildlife ecological research,feces is the most common non-invasive source of DNA obtained in the field and polymerase chain reaction(PCR) technology based on microsatellite markers is used to mine genetic information contained within.This is especially the case for endangered species.However,there are risks associated with this genotyping method because of the poor quality of fecal DNA.In this study,we assessed genotyping risk across 12 microsatellite loci commonly used in previous tiger studies using blood and fecal DNA from captive Amur tigers(Panthera tigris altaica).To begin,we developed an index termed the accumulated matching rate of genotypes(R)between positive DNA(blood samples) and fecal DNA to explore the correct genotyping probability of a certain microsatellite locus.We found that different microsatelliteloci had different genotyping risks and required different PCR amplification protocols.The genotyping errors we detected altered population genetic parameters and potentially impact subsequent analyses.Based on these findings,we recommend that:(1) four loci(E7,Fca094,Pti007 and Pti010) of 12 loci are not suitable for Amur tiger genetic research because of a low Rand difficulty reaching a stable status;(2) the Rof the 12 microsatellite loci plateaued differently,and considering limited budgets,amplification times of some loci could be increased when using fecal samples; and(3) future genetic analysis of wild Amur tigers should be corrected by genotyping error rates(1-R).

The Clinical Study and HLA Genotyping of 112 Familial Myasthenia Gravis Patients

Summary: One hundred and twelve cases of familial myasthenia gravis (MG) from 44 families selected from 2100 patients with MG diagnosed since 1983 in the Department of Neurology were studied. The clinical pictures and immunological features of the patients showed a great resemblance to those of sporadic cases. The pedigree analysis disclosed that the hereditary patterns of familial patients were basically Mendellian autosomal inheritance. Many predisposing factors such as fever, infection, use of aminoglycoside or vaccines, played an important role in presenting the phenotype of subclinical cases. The HLA genotyping suggested that the complement polymorphism C4A*4, the complotype S42, and the genes 0901 and 1301 of DRB1 allele, were related to the pathogenesis of MG. It was concluded that the phenotype of MG may be the result of interaction between hereditary defects and environmental factors.

Identification of Polymorphic Markers by High-Resolution Melting(HRM)Assay for High-Throughput SNP Genotyping in Maize

The development of next generation sequencing(NGS)and high throughput genotyping are important techniques for the QTL mapping and genetic analysis of different crops.High-resolution melting(HRM)is an emerging technology used for detecting single-nucleotide polymorphisms(SNPs)in various species.However,its use is still limited in maize.The HRM analysis was integrated with SNPs to identify three types of populations(NIL population,RIL population and natural population),and the useful tags were screened.The patterns of temperatureshifted melting curves were investigated from the HRM analysis,and compared these with the kit.Among all 48 pairs of primers,10 pairs of them were selected:six pairs of primers for the NIL population,three pairs of primers for the RIL population,and one pair of primer for the natural population.The marker for the natural population was developed with a matching rate of 80%for the plant height trait,based on the data of the phenotypic characteristics measured in the field.This study provides an effective method for maize genotyping in the classification of maize germplasm resources,which can be applied to other plants for high-throughput SNP genotyping or further mapping.

Comparison of Blood Group Molecular Genotyping to Traditional Serological Phenotyping in Patients with Chronic or Recent Blood Transfusion

Objectives: Accurately identifying the Antigens (Ags) on recipient red blood cells (RBCs) is critical in prevention of RBC alloimmunization in chronically transfused patients. The goal of this study was to compare RBC molecular genotyping to serological phenotyping in those patients. Methods: Serological phenotyping and molecular genotyping methods were used to study blood samples from 18 healthy blood donors and 16 transfused patients. Reticulocyte harvesting or hypotonic cell separation was added to recheck RBC phenotypes of the patients with discrepancies between phenotyping and genotyping. Results: No discrepancies were found between the two genotyping methods in all the donors and patients. 1 of 9 sickle-cell disease (SCD) patients and all 3 thalassemia patients demonstrated discrepancies in multiple blood groups between phenotyping and genotyping, which were not corrected by reticulocyte harvesting or hypotonic cell separation. Conclusions: These findings suggest that RBC molecular genotyping is superior to serological phenotyping in chronically transfused SCD or thalassemia patients.

Noninvasive and nondestructive sampling for avian microsatellite genotyping: a case study on the vulnerable Chinese Egret (Egretta eulophotes)

Background: Noninvasive and nondestructive DNA sampling techniques are becoming more important in genetic studies because they can provide genetic material from wild animals with less or even without disturbance,which is particularly useful for the study of endangered species,i.e.,birds.However,nondestructively and noninvasively sampled DNA may,in some cases,be inadequate in the amount and quality of the material collected,which can lead to low amplification success rates and high genotyping errors.Methods: In this study,noninvasive(eggshell swab,shed feather and feces),nondestructive(plucked feather and buccal swab) and invasive(blood) DNA samples were collected from the vulnerable Chinese Egret(Egretta eulophotes).DNA concentrations,PCR amplification success and microsatellite genotyping errors of different sample types were evaluated and compared to determine whether noninvasive and nondestructive samples performed as well as invasive samples in our experimental procedures.Results: A total of 159 samples were collected in the field.Among the different sample types,the highest DNA concentrations(154.0–385.5 ng/μL) were obtained from blood.Those extracted from fecal samples were the lowest,ranging from 1.25 to 27.5 ng/μL.Almost all of the DNA samples,i.e.,95.59 %,were successfully amplified for mt DNA(n = 152) and 92.76 % of mt DNA samples were successfully genotyped for at least five of the nine microsatellite loci tested(n = 141).Blood samples and buccal swabs produced reliable genotypes with no genotyping errors,but in feces,allelic dropouts and false alleles occurred in all nine loci,with error rates ranging from 6.67 to 38.10 % for the dropouts and from 6.06 to 15.15 % for the false alleles.Conclusions: These results indicate that both nondestructive and noninvasive samplings are suitable for avian microsatellite genotyping,save for fecal DNA.However,we should remain cautious of the appearance of genotyping errors,especially when using noninvasive material.

Rapid genotyping of human rotavirus using SYBR green real-time reverse transcription-polymerase chain reaction with melting curve analysis

AIM: To develop a real-time reverse transcriptionpolymerase chain reaction(RT-PCR) assay to genotype rotavirus(G and P) in Alberta from January 2012 to June 2013. METHODS: We developed and validated a different approach to perform rotavirus G and P genotyping using a two-step SYBR green RT-PCR(rt-g PCR) by selecting genotype-specific primers of published conventional RT nested PCR(cn RT-PCR) assay and optimizing the amplification conditions. c DNA was first synthesized from total RNA with Super Script? Ⅱ reverse transcriptase kit followed by amplication step using monoplex SYBR green real-time PCR. After the PCR reaction, melting curve analysis was used to determine specific genotype. Sixteen samples previously genotyped using cn RT-PCR were tested using the new assay and the genotyping results were compared as sensitivity analysis. Assay specificity was evaluated by testing other gastroenteritis viruses with the new assay. The amplicon size of each available genotype was determined by gelelectrophoresis and DNA sequences were obtained using Sanger-sequencing method. After validation and optimization, the new assay was used to genotype 122 pediatric clinical stool samples previously tested positive for rotavirus using electron microscopy between January2012 and June 2013.RESULTS: The new rt-g PCR assay was validated and optimized. The assay detected G1 to G4, G9, G12 and P[4] and P[8] that were available as positive controls in our laboratory. A single and clear peak of melting curve was generated for each of specific G and P genotypes with a Tm ranging from 80 ℃ to 82 ℃. The sensitivity of rt-g PCR was comparable to cn RT-PCR with 100% correlation of the 16 samples with known G and P genotypes. No cross reaction was found with other gastroenteritis viruses. Using the new rt-g PCR assay, genotypes were obtained for 121 of the 122 pediatric clinical samples tested positive for rotavirus: G1P[8](42.6%), G2P[4](4.9%), G3P[8](10.7%), G9P[8](10.7%), G9P[4](6.6%), G12P[8](23.0%), and unknown GP[8](0.8%). For the first time, G12 rotavirus strains were found in Alberta and G12 was the second most common genotype during the study period. Gel electrophoresis of all the genotypes showed expected amplicon size for each genotype. The sequence data of the two G12 samples along with other genotypes were blasted in NCBI BLAST or analyzed with Rota C Genotyping tool(http://rotac.regatools.be/). All genotyping results were confirmed to be correct.CONCLUSION: rt-g PCR is a useful tool for the genotyping and characterization of rotavirus. Monitoring of rotavirus genotypes is important for the identification of emerging strains and ongoing evaluation of rotavirus vaccination programs.

Targeted Genotyping of a Whole-Gene Repertoire by an Ultrahigh-Multiplex and Flexible HD-Marker Approach

Targeted genotyping is an extremely powerful approach for the detection of known genetic variations that are biologically or clinically important.However,for non-model organisms,large-scale target geno-typing in a cost-effective manner remains a major challenge.To address this issue,we present an ultrahigh-multiplex,in-solution probe array-based high-throughput diverse marker genotyping(HD-Marker)approach that is capable of targeted genotyping of up to 86000 loci,with coverage of the whole gene repertoire,in what is a 27-fold and six-fold multiplex increase in comparison with the conventional Illumina GoldenGate and original HD-Marker assays,respectively.We perform extensive analyses of var-ious ultrahigh-multiplex levels of HD-Marker(30 k-plex,56 k-plex,and 86 k-plex)and show the power and excellent performance of the proposed method with an extremely high capture rate(about 96%)and genotyping accuracy(about 96%).With great advantages in terms of cost(as low as 0.0006 USD per geno-type)and high technical flexibility,HD-Marker is a highly efficient and powerful tool with broad appli-cation potential for genetic,ecological,and evolutionary studies of non-model organisms.