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 phen...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.展开更多
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 accu...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.展开更多
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 ...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%.展开更多
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 ...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.展开更多
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...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-DNA<sup>TM</sup> Miniprep Plus kit” https://www.zymoresearch.com/. Molecular HPV detection and genotyping were performed by multiplex RT-PCR with the Seegene Anyplex<sup>TM</sup> 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.展开更多
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,depende...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.展开更多
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.Mi...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.展开更多
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 u...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.展开更多
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 in...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_m)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 R_mand difficulty reaching a stable status;(2) the R_mof 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_m).展开更多
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 var...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.展开更多
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 technolo...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.展开更多
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...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.展开更多
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...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.展开更多
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 approa...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.展开更多
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 cos...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.展开更多
Discrimination among grapevine varieties based on quantitative traits,such as flowering,veraison and ripening dates is crucial for variety selection in the context of climate change and in breeding programs.These trai...Discrimination among grapevine varieties based on quantitative traits,such as flowering,veraison and ripening dates is crucial for variety selection in the context of climate change and in breeding programs.These traits are under complex genetic control for which 6 linked SSR loci(VVS2,VVIn16,VMC7G3,VrZAG29,VMC5G7,and VVIB23)have been identified.Using these markers in HRM-PCR analysis,we assessed genetic diversity among a large collection of 192 grapevine varieties.The grapevine germplasm used encompasses the majority of Greek vineyard with 181 varieties,3 prominent foreign varieties and 11 varieties of Palestinian origin.The SSR markers used were highly polymorphic,displaying unique melting curves for unusually higher number of samples than generally observed in SSR analysis.This prompted us to examine sequence composition for selected samples and found that variation present as SNPs in the flanking sequences of SSR motifs was responsible for the observed polymorphism.Hence,HRM-PCR proved to be a tool of higher analytical power to distinguish genotypes surpassing the discrimination power of conventional gel-based SSR analysis.The study provides a better understanding of genetic variation of SSR marker loci associated to phenological traits in grapevine varieties,signifying an analytical methodology that may be of higher discrimination power in detection of polymorphism for utilization in breeding programs.展开更多
The Tubulin Based Polymorphism (TBP) method was used to genotype olive cultivars of different origin and to produce short-size cultivar-specific molecular probes. Both the first and the second intron of the members of...The Tubulin Based Polymorphism (TBP) method was used to genotype olive cultivars of different origin and to produce short-size cultivar-specific molecular probes. Both the first and the second intron of the members of the olive β-tubulin gene family were exploited as sources of DNA polymorphism. Compared with the data obtained with the use of a set of 11 SSR markers selected from an Olea europea L. database, TBP is shown to provide similar, if not better, information about the polymorphic content of the olive genomes, releasing, at the same time, a simple and discriminatory DNA barcode specific for any of the analyzed cultivars. Such a barcode is the source for the preparation of variety specific molecular probes.展开更多
基金the funding supports from the National Natural Science Foundation of China(32272158)the Major Program of Hubei Hongshan Laboratory(2021hszd008)+1 种基金Hainan Yazhou Bay Seed Lab(B21HJ8102)Huazhong Agricultural University Scientific&Technological Self-innovation Foundation(2021ZKPY001)。
文摘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.
基金supported by the National Natural Science Foundation of China(31871653 to K.L.,31830067 to J.L.)the Talent Project of Chongqing Natural Science Foundation(cstc2021ycjhbgzxm0033 to K.L.)Germplasm Creation Special Program of Southwest University.
文摘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.
基金funded by the"Genetic improvement of pig survival"project from Danish Pig Levy Foundation (Aarhus,Denmark)The China Scholarship Council (CSC)for providing scholarship to the first author。
文摘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%.
基金funded by the Italian Ministry for Agriculture,Food and Forestry Policies in the framework of the“FAO-RGV(FAO-Vegetal Genetic Resources)Project”.
文摘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.
文摘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-DNA<sup>TM</sup> Miniprep Plus kit” https://www.zymoresearch.com/. Molecular HPV detection and genotyping were performed by multiplex RT-PCR with the Seegene Anyplex<sup>TM</sup> 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.
基金supported by the Genomic Selection in PlantsAnimals(GenSAP)research project financed by the Danish Council of Strategic Research(Aarhus,Denmark)the scholarship provided by the China Scholarship Council(CSC)
文摘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.
基金This study was funded by the Genomic Selection in Animals and Plants(GenSAP)research project financed by the Danish Council of Strategic Research(Aarhus,Denmark).Xiao Wang received Ph.D.stipends from the Technical University of Denmark(DTU Bioinformatics and DTU Compute),Denmark,and the China Scholarship Council,China.
文摘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.
文摘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.
基金financially supported by Fundamental Research Funds for the Central Universities of China(2572014EA06)National Natural Science Foundation of China(NSFC 31572285)Study on Resource Survey Technology for Tiger and Amur Leopard Population(State Forestry Administration)
文摘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_m)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 R_mand difficulty reaching a stable status;(2) the R_mof 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_m).
基金This study was funded by Agri-Food and Agriculture Canada(Project AAFC J0000–75)
文摘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.
基金This work was supported by the National Natural Science Foundation of China(31371636)Key R&D Project in Shandong Province(2016GNC110018)+3 种基金Applied Basic Research Project of Qingdao(14-2-4-13-jch)“The Innovation Team in Maize”Modern Agricultural System of Shandong Province(SDAIT-02-01)Improved Seed Engineering in Shandong Province(2019LZGC002)National Natural Science Foundation of China(31201218).
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant nos. 41476113,31000963 and 31272333)the Fujian Natural Science Foundation of China (2010Y2007)
文摘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.
文摘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.
基金the grant support from National Natural Science Foundation of China (32130107, 32002446 and 32102778)Project of Sanya Yazhouwan Science and Technology City Management Foundation (SKJC-KJ-2019KY01)+1 种基金China Agriculture Research System of MOF and MARATaishan Scholar Project Fund of Shandong Province of China
文摘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.
文摘Discrimination among grapevine varieties based on quantitative traits,such as flowering,veraison and ripening dates is crucial for variety selection in the context of climate change and in breeding programs.These traits are under complex genetic control for which 6 linked SSR loci(VVS2,VVIn16,VMC7G3,VrZAG29,VMC5G7,and VVIB23)have been identified.Using these markers in HRM-PCR analysis,we assessed genetic diversity among a large collection of 192 grapevine varieties.The grapevine germplasm used encompasses the majority of Greek vineyard with 181 varieties,3 prominent foreign varieties and 11 varieties of Palestinian origin.The SSR markers used were highly polymorphic,displaying unique melting curves for unusually higher number of samples than generally observed in SSR analysis.This prompted us to examine sequence composition for selected samples and found that variation present as SNPs in the flanking sequences of SSR motifs was responsible for the observed polymorphism.Hence,HRM-PCR proved to be a tool of higher analytical power to distinguish genotypes surpassing the discrimination power of conventional gel-based SSR analysis.The study provides a better understanding of genetic variation of SSR marker loci associated to phenological traits in grapevine varieties,signifying an analytical methodology that may be of higher discrimination power in detection of polymorphism for utilization in breeding programs.
文摘The Tubulin Based Polymorphism (TBP) method was used to genotype olive cultivars of different origin and to produce short-size cultivar-specific molecular probes. Both the first and the second intron of the members of the olive β-tubulin gene family were exploited as sources of DNA polymorphism. Compared with the data obtained with the use of a set of 11 SSR markers selected from an Olea europea L. database, TBP is shown to provide similar, if not better, information about the polymorphic content of the olive genomes, releasing, at the same time, a simple and discriminatory DNA barcode specific for any of the analyzed cultivars. Such a barcode is the source for the preparation of variety specific molecular probes.
