High-throughput single nucleotide polymorphism (SNP) identification and mapping in the sesame (<Emphasis Type="Italic">Sesamum indicum</Emphasis> L.) genome with genotyping by sequencing (GBS) analysis

Sesame (Sesamum indicum L. syn. Sesamum orientale L.) is considered to be the first oil seed crop known to man. Despite its versatile use as an oil seed and a leafy vegetable, sesame is a neglected crop and has not been a subject of molecular genetic research until the last decade. There is thus limited knowledge regarding genome-specific molecular markers that are indispensible for germplasm enhancement, gene identification, and marker-assisted breeding in sesame. In this study, we employed a genotyping by sequencing (GBS) approach to a sesame recombinant inbred line (RIL) population for high-throughput single nucleotide polymorphism (SNP) identification and genotyping. A total of 15,521 SNPs were identified with 14,786 SNPs (95.26 %) located along sesame genome assembly pseudomolecules. By incorporating sesame-specific simple sequence repeat (SSR) markers developed in our previous work, 230.73 megabases (99 %) of sequence from the genome assembly were saturated with markers. This large number of markers will be available for sesame geneticists as a resource for candidate polymorphisms located along the physical chromosomes of sesame. Defining SNP loci in genome assembly sequences provides the flexibility to utilize any genotyping strategy to survey any sesame population. SNPs selected through a high stringency filtering protocol (770 SNPs) for improved map accuracy were used in conjunction with SSR markers (50 SSRs) in linkage analysis, resulting in 13 linkage groups that encompass a total genetic distance of 914 cM with 432 markers (420 SNPs, 12 SSRs). The genetic linkage map constitutes the basis for future work that will involve quantitative trait locus (QTL) analyses of metabolic and agronomic traits in the segregating RIL population.     

Genomic copy number variation and its potential role in lipoprotein and metabolic phenotypes

PURPOSE OF REVIEW: This review examines the role of copy number variation in the human genome as a newly recognized determinant of lipoprotein and metabolic phenotypes. RECENT FINDINGS: Much of the recent progress defining the molecular basis of lipoprotein disorders has been the result of studying genomic DNA at the single nucleotide level, for instance with nucleotide sequence analysis or genotyping to detect single nucleotide polymorphisms. Focus on single nucleotides, however, fails to capture the complete spectrum of potential genetic variability. Recent genome-wide mapping studies have demonstrated the surprising ubiquity of large-scale copy number variations in apparently healthy people, adding to the complexity of the 'normal' genome, but also emphasizing this form of genetic variation as a potential disease mechanism. The application of this understanding to the genetics of lipoprotein disorders has been rapid. For instance, the use of novel techniques to detect copy number variations, such as multiplex ligation-dependent probe amplification, has revealed many additional causative mutations in the low-density lipoprotein receptor gene in patients with familial hypercholesterolemia. SUMMARY: Copy number variations thus represent a new level of genomic variation that is both an important mechanism of monogenic lipoprotein disorders and a potential contributor to common complex lipoprotein and metabolic phenotypes in the general population.     

Recent patents on high-throughput single nucleotide polymorphism (SNP) genotyping methods

Single nucleotide polymorphisms (SNPs) are single-base inheritable variations in a given and defined genetic location that occur in at least 1% of the population. SNPs are useful markers for genetic association studies in disease susceptibility or adverse drug reactions, in evolutionary studies and forensic science. Given the potential impact of SNPs, the biotechnology industry has focused on the development of high-throughput methods for SNP genotyping. Many highthroughput SNP genotyping technologies are currently available and many others are being patented recently. Each offers a unique combination of scale, accuracy, throughput and cost. In this review, we described some of the most important recent SNP genotyping methods and also recent patents associated with it.     

Array-based high-throughput DNA markers for crop improvement

The last two decades have witnessed a remarkable activity in the development and use of molecular markers both in animal and plant systems. This activity started with low-throughput restriction fragment length polymorphisms and culminated in recent years with single nucleotide polymorphisms (SNPs), which are abundant and uniformly distributed. Although the latter became the markers of choice for many, their discovery needed previous sequence information. However, with the availability of microarrays, SNP platforms have been developed, which allow genotyping of thousands of markers in parallel. Besides SNPs, some other novel marker systems, including single feature polymorphisms, diversity array technology and restriction site-associated DNA markers, have also been developed, where array-based assays have been utilized to provide for the desired ultra-high throughput and low cost. These microarray-based markers are the markers of choice for the future and are already being used for construction of high-density maps, quantitative trait loci (QTL) mapping (including expression QTLs) and genetic diversity analysis with a limited expense in terms of time and money. In this study, we briefly describe the characteristics of these array-based marker systems and review the work that has already been done involving development and use of these markers, not only in simple eukaryotes like yeast, but also in a variety of seed plants with simple or complex genomes.     

Use of sequence data from rainbow trout and Atlantic salmon for SNP detection in Pacific salmon

Single nucleotide polymorphisms (SNPs) are a class of genetic markers that are well suited to a broad range of research and management applications. Although advances in genotyping chemistries and analysis methods continue to increase the potential advantages of using SNPs to address molecular ecological questions, the scarcity of available DNA sequence data for most species has limited marker development. As the number and diversity of species being targeted for large-scale sequencing has increased, so has the potential for using sequence from sister taxa for marker development in species of interest. We evaluated the use of Oncorhynchus mykiss and Salmo salar sequence data to identify SNPs in three other species (Oncorhynchus tshawytscha, Oncorhynchus nerka and Oncorhynchus keta). Primers designed based on O. mykiss and S. salar alignments were more successful than primers designed based on Oncorhynchus-only alignments for sequencing target species, presumably due to the much larger number of potential targets available from the former alignments and possibly greater sequence conservation in those targets. In sequencing approximately 89 kb we observed a frequency of 4.30 x 10(-3) SNPs per base pair. Approximately half (53/101) of the subsequently designed validation assays resulted in high-throughput SNP genotyping markers. We speculate that this relatively low conversion rate may reflect the duplicated nature of the salmon genome. Our results suggest that a large number of SNPs could be developed for Pacific salmon using sequence data from other species. While the costs of DNA sequencing are still significant, these must be compared to the costs of using other marker classes for a given application.     

Developing genomic resources for the common bottlenose dolphin (Tursiops truncatus): isolation and characterization of 153 single nucleotide polymorphisms and 53 genotyping assays

Although single nucleotide polymorphisms (SNPs) are commonly used in human genetics, they have only recently been incorporated into genetic studies of non‐model organisms, including cetaceans. SNPs have several advantages over other molecular markers for studies of population genetics: they are quicker and more straightforward to score, cross‐laboratory comparisons of data are less complicated, and they can be used successfully with low‐quality DNA. We screened portions of the genome of one of the most abundant cetaceans in U.S. waters, the common bottlenose dolphin (Tursiops truncatus), and identified 153 SNPs resulting in an overall average of one SNP every 463 base pairs. Custom TaqMan^® Assays were designed for 53 of these SNPs, and their performance was tested by genotyping a set of bottlenose dolphin samples, including some with low‐quality DNA. We found that in 19% of the loci examined, the minor allele frequency (MAF) estimated during initial SNP ascertainment using a DNA pool of 10 individuals differed significantly from the final MAF after genotyping over 100 individuals, suggesting caution when making inferences about MAF values based on small data sets. For two assays, we also characterized the basis for unusual clustering patterns to determine whether their data could still be utilized for further genetic studies. Overall results support the use of these SNPs for accurate analysis of both poor and good‐quality DNA. We report the first SNP markers and genotyping assays for use in population and conservation genetic studies of bottlenose dolphins.     

Human DNA polymorphisms and methods of analysis.

The current predominant method of analyzing base substitution polymorphisms, RFLP analysis, is likely to be gradually supplanted by methods based on PCR because of the improved sensitivity and genotyping rate. The most promising PCR methods for analysis appear to be allele-specific PCR and single-stranded conformational analysis. The single-stranded conformation approach has already been applied to the scanning of cystic fibrosis exons for new mutations. Linkage mapping projects that cover large segments of the human genome will probably rely, in the coming years, primarily on tandem repeat polymorphisms, particularly microsatellite polymorphisms. Microsatellite polymorphisms have at least a fourfold advantage over base substitution RFLPs because they are twice as informative and can be typed at at least twice the rate. The facioscapulohumeral muscular dystrophy gene was recently mapped in just 6 weeks using microsatellite polymorphisms. Because of the informativeness handicap, it will be difficult for base substitution polymorphisms to overtake tandem repeat markers for large-scale linkage mapping. Methods that allow base substitution polymorphisms to be typed at two or three times the rate of microsatellite markers would have to be developed. Most of the other applications of DNA polymorphisms described in the introduction are also increasingly likely to rely on highly informative tandem repeat markers in the future. Methods for analysis will probably be based on PCR. It is easy to envisage, for example, an automated method for large-scale DNA fingerprinting of individuals based upon a standard set of highly informative, dependable microsatellite polymorphisms. Methods for analyzing base substitution polymorphisms will continue to be important for the diagnostic detection of disease-gene alleles.(ABSTRACT TRUNCATED AT 250 WORDS)     

Glycosylase mediated polymorphism detection (GMPD)—a novel process for genetic analysis

A process for mutation and polymorphism detection is described here that offers significant advances over current mutation detection systems and that has the potential to significantly enhance molecular genetic analysis of human disease. This novel process is referred to as glycosylase mediated polymorphism detection (GMPD) and exploits the use of highly specific DNA glycosylase enzymes to excise substrate bases incorporated into amplified DNA. Action of the glycosylase leaves the DNA with one or more specific abasic sites which can be cleaved by enzymatic or chemical means. The GMPD process permits detection of polymorphisms and mutations using fragment size analysis or solid phase formats. GMPD is particularly suitable for genotyping of single nucleotide polymorphism (SNP) based markers and also permits efficient scanning of genes for unknown polymorphisms and mutations.     

MALDI mass spectrometry analysis of single nucleotide polymorphisms by photocleavage and charge-tagging

High-throughput procedures are an important requirement for future large-scale genetic studies such as genotyping of single nucleotide polymorphisms (SNPs). Matrix-assisted laser desorption/ ionisation mass spectrometry (MALDI-MS) has revolutionised the analysis of biomolecules and, in particular, provides a very attractive solution for the rapid typing of DNA. The analysis of DNA by MALDI can be significantly facilitated by a procedure termed ‘charge-tagging’. We show here a novel approach for the generation of charge-tagged DNA using a photocleavable linker and its implementation in a molecular biological procedure for SNP genotyping consisting of PCR, primer extension, photocleavage and a chemical reaction prior to MALDI target preparation and analysis. The reaction sequence is amenable to liquid handling automation and requires no stringent purification procedures. We demonstrate this new method on SNPs in two genes involved in complex traits.     

Application of fluorescence-based semi-automated AFLP analysis in barley and wheat

Genetic mapping and the selection of closely linked molecular markers for important agronomic traits require efficient, large-scale genotyping methods. A semi-automated multifluorophore technique was applied for genotyping AFLP marker loci in barley and wheat. In comparison to conventional ³³P-based AFLP analysis the technique showed a higher resolution of amplicons, thus increasing the number of distinguishable fragments. Automated sizing of the same fragment in different lanes or different gels showed high conformity, allowing subsequent unambigous allele-typing. Simultaneous electrophoresis of different AFLP samples in one lane (multimixing), as well as simultaneous amplification of AFLP fragments with different primer combinations in one reaction (multiplexing), displayed consistent results with respect to fragment number, polymorphic peaks and correct size-calling. The accuracy of semi-automated co-dominant analysis for hemizygous AFLP markers in an F₂ population was too low, proposing the use of dominant allele-typing defaults. Nevertheless, the efficiency of genetic mapping, especially of complex plant genomes, will be accelerated by combining the presented genotyping procedures. Received: 10 April 1999 / Accepted: 11 May 1999     

A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation.     

Universal false discovery rate estimation methodology for genome-wide association studies

Genome-wide case-control association studies aim at identifying significant differential markers between sick and healthy populations. With the development of large-scale technologies allowing the genotyping of thousands of single nucleotide polymorphisms (SNPs) comes the multiple testing problem and the practical issue of selecting the most probable set of associated markers. Several False Discovery Rate (FDR) estimation methods have been developed and tuned mainly for differential gene expression studies. However they are based on hypotheses and designs that are not necessarily relevant in genetic association studies. In this article we present a universal methodology to estimate the FDR of genome-wide association results. It uses a single global probability value per SNP and is applicable in practice for any study design, using any statistic. We have benchmarked this algorithm on simulated data and shown that it outperforms previous methods in cases requiring non-parametric estimation. We exemplified the usefulness of the method by applying it to the analysis of experimental genotyping data of three Multiple Sclerosis case-control association studies.     

Genotyping single nucleotide polymorphisms in barley by tetra-primer ARMS-PCR.

Single nucleotide polymorphisms (SNPs) are the most abundant form of DNA polymorphism. These polymorphisms can be used in plants as simple genetic markers for many breeding applications, for population studies, and for germplasm fingerprinting. The great increase in the available DNA sequences in the databases has made it possible to identify SNPs by "database mining", and the single most important factor preventing their widespread use appears to be the genotyping cost. Many genotyping platforms rely on the use of sophisticated, automated equipment coupled to costly chemistry and detection systems. A simple and economical method involving a single PCR is reported here for barley SNP genotyping. Using the tetra-primer ARMS-PCR procedure, we have been able to assay unambiguously five SNPs in a set of 132 varieties of cultivated barley. The results show the reliability of this technique and its potential for use in low- to moderate-throughput situations; the association of agronomically important traits is discussed.     

Twins and Q-banded chromosome polymorphisms

Summary Q-banded chromosomal analyses were performed on 24 pairs of twins to determine the stability and heritability of chromosome polymorphisms, and to establish the use of these markers in the determination of twin zygosity. Sixteen twin pairs were determined monozygotic by chromosome polymorphism analysis and confirmed monozygotic by blood group genotyping. No two genetically distinct individuals had the same polymorphic pattern, suggesting the individuality of each morphological karyotype. The frequencies for the various types of chromosome polymorphisms, including stalk length variations, were determined. Analysis of frequency distribution for variant combinations showed random association.     

Investigating the utility of combining Φ29 whole genome amplification and highly multiplexed single nucleotide polymorphism BeadArray™ genotyping

Background

Sustainable DNA resources and reliable high-throughput genotyping methods are required for large-scale, long-term genetic association studies. In the genetic dissection of common disease it is now recognised that thousands of samples and hundreds of thousands of markers, mostly single nucleotide polymorphisms (SNPs), will have to be analysed. In order to achieve these aims, both an ability to boost quantities of archived DNA and to genotype at low costs are highly desirable. We have investigated Φ29 polymerase Multiple Displacement Amplification (MDA)-generated DNA product (MDA product), in combination with highly multiplexed BeadArray? genotyping technology. As part of a large-scale BeadArray genotyping experiment we made a direct comparison of genotyping data generated from MDA product with that from genomic DNA (gDNA) templates.

Results

Eighty-six MDA product and the corresponding 86 gDNA samples were genotyped at 345 SNPs and a concordance rate of 98.8% was achieved. The BeadArray sample exclusion rate, blind to sample type, was 10.5% for MDA product compared to 5.8% for gDNA.

Conclusions

We conclude that the BeadArray technology successfully produces high quality genotyping data from MDA product. The combination of these technologies improves the feasibility and efficiency of mapping common disease susceptibility genes despite limited stocks of gDNA samples.     

Using blocks of linked single nucleotide polymorphisms as highly polymorphic genetic markers for parentage analysis

Single nucleotide polymorphisms (SNPs) are plentiful in most genomes and amenable to high throughput genotyping, but they are not yet popular for parentage or paternity analysis. The markers are bi-allelic, so individually they contain little information about parentage, and in nonmodel organisms the process of identifying large numbers of unlinked SNPs can be daunting. We explore the possibility of using blocks of between three and 26 linked SNPs as highly polymorphic molecular markers for reconstructing male genotypes in polyandrous organisms with moderate (five offspring) to large (25 offspring) clutches of offspring. Haplotypes are inferred for each block of linked SNPs using the programs Haplore and Phase 2.1. Each multi-SNP haplotype is then treated as a separate allele, producing a highly polymorphic, 'microsatellite-like' marker. A simulation study is performed using haplotype frequencies derived from empirical data sets from Drosophila melanogaster and Mus musculus populations. We find that the markers produced are competitive with microsatellite loci in terms of single parent exclusion probabilities, particularly when using six or more linked SNPs to form a haplotype. These markers contain only modest rates of missing data and genotyping or phasing errors and thus should be seriously considered as molecular markers for parentage analysis, particularly when the study is interested in the functional significance of polymorphisms across the genome.     

SNPWave: a flexible multiplexed SNP genotyping technology

Scalable multiplexed amplification technologies are needed for cost-effective large-scale genotyping of genetic markers such as single nucleotide polymorphisms (SNPs). We present SNPWave, a novel SNP genotyping technology to detect various subsets of sequences in a flexible fashion in a fixed detection format. SNPWave is based on highly multiplexed ligation, followed by amplification of up to 20 ligated probes in a single PCR. Depending on the multiplexing level of the ligation reaction, the latter employs selective amplification using the amplified fragment length polymorphism (AFLP) technology. Detection of SNPWave reaction products is based on size separation on a sequencing instrument with multiple fluorescence labels and short run times. The SNPWave technique is illustrated by a 100-plex genotyping assay for Arabidopsis, a 40-plex assay for tomato and a 10-plex assay for Caenorhabditis elegans, detected on the MegaBACE 1000 capillary sequencer.     

单核苷酸多态性检测分析技术

单核苷酸多态性(SNP)作为第三代遗传标记已经广泛用于基因作图、疾病相关性分析、群体遗传学及药物研究等领域。 文中系统地介绍了目前国内外主要的SNP检测技术,任何一种SNP的检测方法都可将之看成由两部分组成,即区分SNP位点的原理方法和数据的检测分析手段,文章对这两部分做了较详细的介绍,并对SNP检测技术的发展进行了展望。 Abstract :As the third generation of genetic markers SNPs（single nucleotide polymorphisms）has been used extentively in gene mapping,disease-correlativity analysis ,population genetics and drug research.Here methods for detection are reviewed.Most SNP genotyping are a combination of method for interrogating SNPs and analysis tecnique.It described both parts and give a outlook for detection.