High-resolution, high-throughput SNP mapping in Drosophila melanogaster

Single nucleotide polymorphisms (SNPs) are useful markers for genetic mapping experiments in model organisms. Here we report the establishment of a high-density SNP map and high-throughput genotyping assays for Drosophila melanogaster. Our map comprises 27,367 SNPs in common laboratory Drosophila stocks. These SNPs were clustered within 2,238 amplifiable markers at an average density of 1 marker every 50.3 kb, or 6.3 genes. We have also constructed a set of 62 Drosophila stocks, each of which facilitates the generation of recombinants within a defined genetic interval of 1-2 Mb. For flexible, high-throughput SNP genotyping, we used fluorescent tag-array mini-sequencing (TAMS) assays. We designed and validated TAMS assays for 293 SNPs at an average resolution of 391.3 kb, and demonstrated the utility of these tools by rapidly mapping 14 mutations that disrupt embryonic muscle patterning. These resources enable high-resolution high-throughput genetic mapping in Drosophila.     

Single nucleotide polymorphisms (SNPs) that map to gaps in the human SNP map

An international effort is underway to generate a comprehensive haplotype map (HapMap) of the human genome represented by an estimated 300000 to 1 million ‘tag’ single nucleotide polymorphisms (SNPs). Our analysis indicates that the current human SNP map is not sufficiently dense to support the HapMap project. For example, 24.6% of the genome currently lacks SNPs at the minimal density and spacing that would be required to construct even a conservative tag SNP map containing 300 000 SNPs. In an effort to improve the human SNP map, we identified 140 696 additional SNP candidates using a new bioinformatics pipeline. Over 51 000 of these SNPs mapped to the largest gaps in the human SNP map, leading to significant improvements in these regions. Our SNPs will be immediately useful for the HapMap project, and will allow for the inclusion of many additional genomic intervals in the final HapMap. Nevertheless, our results also indicate that additional SNP discovery projects will be required both to define the haplotype architecture of the human genome and to construct comprehensive tag SNP maps that will be useful for genetic linkage studies in humans.     

大规模单核苷酸多态性分析与肿瘤易感性

单核苷酸多态性(SNPs)是人类基因组中最常见的变异形式。作为第三代遗传标记,SNP在基因定位、克隆、遗传多态性方面具有广泛应用,特别是作为基因诊断标记在预防医学中具有十分重要的作用。近年来,随着人类基因组计划的发展,数以百万计的SNP被陆续发现,并可在公共数据库中免费获得。SNP数量的快速增加和SNP检测方法的发展,为其在肿瘤易感性领城的应用提供了可能。在本综述中,我们介绍了几种高通量检测SNP的分析方法,总结了大规模SNP分析技术在肿瘤易感性中的应用,介绍了目前人们对于不同人群中的SNP分析、肿瘤易感基因、个体肿瘤易感性的理解,以及研究SNP标记与肿瘤易感性关系时存在的难点。     

High-Throughput SNP Discovery and Genotyping for Constructing a Saturated Linkage Map of Chickpea (Cicer arietinum L.)

The present study reports the large-scale discovery of genome-wide single-nucleotide polymorphisms (SNPs) in chickpea, identified mainly through the next generation sequencing of two genotypes, i.e. Cicer arietinum ICC4958 and its wild progenitor C. reticulatum PI489777, parents of an inter-specific reference mapping population of chickpea. Development and validation of a high-throughput SNP genotyping assay based on Illumina''s GoldenGate Genotyping Technology and its application in building a high-resolution genetic linkage map of chickpea is described for the first time. In this study, 1022 SNPs were identified, of which 768 high-confidence SNPs were selected for designing the custom Oligo Pool All (CpOPA-I) for genotyping. Of these, 697 SNPs could be successfully used for genotyping, demonstrating a high success rate of 90.75%. Genotyping data of the 697 SNPs were compiled along with those of 368 co-dominant markers mapped in an earlier study, and a saturated genetic linkage map of chickpea was constructed. One thousand and sixty-three markers were mapped onto eight linkage groups spanning 1808.7 cM (centiMorgans) with an average inter-marker distance of 1.70 cM, thereby representing one of the most advanced maps of chickpea. The map was used for the synteny analysis of chickpea, which revealed a higher degree of synteny with the phylogenetically close Medicago than with soybean. The first set of validated SNPs and map resources developed in this study will not only facilitate QTL mapping, genome-wide association analysis and comparative mapping in legumes but also help anchor scaffolds arising out of the whole-genome sequencing of chickpea.     

SNPdetector: a software tool for sensitive and accurate SNP detection

Identification of single nucleotide polymorphisms (SNPs) and mutations is important for the discovery of genetic predisposition to complex diseases. PCR resequencing is the method of choice for de novo SNP discovery. However, manual curation of putative SNPs has been a major bottleneck in the application of this method to high-throughput screening. Therefore it is critical to develop a more sensitive and accurate computational method for automated SNP detection. We developed a software tool, SNPdetector, for automated identification of SNPs and mutations in fluorescence-based resequencing reads. SNPdetector was designed to model the process of human visual inspection and has a very low false positive and false negative rate. We demonstrate the superior performance of SNPdetector in SNP and mutation analysis by comparing its results with those derived by human inspection, PolyPhred (a popular SNP detection tool), and independent genotype assays in three large-scale investigations. The first study identified and validated inter- and intra-subspecies variations in 4,650 traces of 25 inbred mouse strains that belong to either the Mus musculus species or the M. spretus species. Unexpected heterozygosity in CAST/Ei strain was observed in two out of 1,167 mouse SNPs. The second study identified 11,241 candidate SNPs in five ENCODE regions of the human genome covering 2.5 Mb of genomic sequence. Approximately 50% of the candidate SNPs were selected for experimental genotyping; the validation rate exceeded 95%. The third study detected ENU-induced mutations (at 0.04% allele frequency) in 64,896 traces of 1,236 zebra fish. Our analysis of three large and diverse test datasets demonstrated that SNPdetector is an effective tool for genome-scale research and for large-sample clinical studies. SNPdetector runs on Unix/Linux platform and is available publicly (http://lpg.nci.nih.gov).     

Genome-wide SNP discovery in walnut with an AGSNP pipeline updated for SNP discovery in allogamous organisms

ABSTRACT: BACKGROUND: A genome-wide set of single nucleotide polymorphisms (SNPs) is a valuable resource in genetic research and breeding and is usually developed by re-sequencing a genome. If a genome sequence is not available, an alternative strategy must be used. We previously reported the development of a pipeline (AGSNP) for genome-wide SNP discovery in coding sequences and other single-copy DNA without a complete genome sequence in self-pollinating (autogamous) plants. Here we updated this pipeline for SNP discovery in outcrossing (allogamous) species and demonstrated its efficacy in SNP discovery in walnut (Juglans regia L.). RESULTS: The first step in the original implementation of the AGSNP pipeline was the construction of a reference sequence and the identification of single-copy sequences in it. To identify single-copy sequences, multiple genome equivalents of short SOLiD reads of another individual were mapped to shallow genome coverage of long Sanger or Roche 454 reads making up the reference sequence. The relative depth of SOLiD reads was used to filter out repeated sequences from single-copy sequences in the reference sequence. The second step was a search for SNPs between SOLiD reads and the reference sequence. Polymorphism within the mapped SOLiD reads would have precluded SNP discovery; hence both individuals had to be homozygous. The AGSNP pipeline was updated here for using SOLiD or other type of short reads of a heterozygous individual for these two principal steps. A total of 32.6X walnut genome equivalents of SOLiD reads of vegetatively propagated walnut scion cultivar 'Chandler' were mapped to 48,661 'Chandler' bacterial artificial chromosome (BAC) end sequences (BESs) produced by Sanger sequencing during the construction of a walnut physical map. A total of 22,799 putative SNPs were initially identified. A total of 6,000 Infinium II type SNPs evenly distributed along the walnut physical map were selected for the construction of an Infinium BeadChip, which was used to genotype a walnut mapping population having 'Chandler' as one of the parents. Genotyping results were used to adjust the filtering parameters of the updated AGSNP pipeline. With the adjusted filtering criteria, 69.6% of SNPs discovered with the updated pipeline were real and could be mapped on the walnut genetic map. A total of 13,439 SNPs were discovered by BES re-sequencing. BESs harboring SNPs were in 677 FPC contigs covering 98% of the physical map of the walnut genome. CONCLUSION: The updated AGSNP pipeline is a versatile SNP discovery tool for a high-throughput, genome-wide SNP discovery in both autogamous and allogamous species. With this pipeline, a large set of SNPs were identified in a single walnut cultivar.     

SNP analysis to dissect human traits

The analysis of complex human diseases has been spurred by the number of published genomic sequence variants - many identified in the course of sequencing the human genome. But, to be useful for genetic analysis, variants have to be mapped accurately, their frequencies in various populations determined, and automated high-throughput assay techniques developed. Recently proposed methods address these issues: the use of 'reduced representation shotgun' methods for more efficient detection of single nucleotide polymorphisms (SNPs), the employment of high-throughput genotyping techniques, the development of SNP maps that incorporate information about linkage disequilibrium, and the use of SNPs in identifying susceptibility genes for common illnesses.     

SNP discovery in associating genetic variation with human disease phenotypes

With the completion of the human genome project, attention is now rapidly shifting towards the study of individual genetic variation. The most abundant source of genetic variation in the human genome is represented by single nucleotide polymorphisms (SNPs), which can account for heritable inter-individual differences in complex phenotypes. Identification of SNPs that contribute to susceptibility to common diseases will provide highly accurate diagnostic information that will facilitate early diagnosis, prevention, and treatment of human diseases. Over the past several years, the advancement of increasingly high-throughput and cost-effective methods to discover and measure SNPs has begun to open the door towards this endeavor. Genetic association studies are considered to be an effective approach towards the detection of SNPs with moderate effects, as in most common diseases with complex phenotypes. This requires careful study design, analysis and interpretation. In this review, we discuss genetic association studies and address the prospect for candidate gene association studies, comparing the strengths and weaknesses of indirect and direct study designs. Our focus is on the continuous need for SNP discovery methods and the use of currently available prescreening methods for large-scale genetic epidemiological research until more advanced sequencing methods currently under development will become available.     

Large-Scale SNP Discovery and Genotyping for Constructing a High-Density Genetic Map of Tea Plant Using Specific-Locus Amplified Fragment Sequencing (SLAF-seq)

Genetic maps are important tools in plant genomics and breeding. The present study reports the large-scale discovery of single nucleotide polymorphisms (SNPs) for genetic map construction in tea plant. We developed a total of 6,042 valid SNP markers using specific-locus amplified fragment sequencing (SLAF-seq), and subsequently mapped them into the previous framework map. The final map contained 6,448 molecular markers, distributing on fifteen linkage groups corresponding to the number of tea plant chromosomes. The total map length was 3,965 cM, with an average inter-locus distance of 1.0 cM. This map is the first SNP-based reference map of tea plant, as well as the most saturated one developed to date. The SNP markers and map resources generated in this study provide a wealth of genetic information that can serve as a foundation for downstream genetic analyses, such as the fine mapping of quantitative trait loci (QTL), map-based cloning, marker-assisted selection, and anchoring of scaffolds to facilitate the process of whole genome sequencing projects for tea plant.     

SNP mining porcine ESTs with MAVIANT, a novel tool for SNP evaluation and annotation

MOTIVATION: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators. RESULTS: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies. AVAILABILITY: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

RAD sequencing yields a high success rate for westslope cutthroat and rainbow trout species-diagnostic SNP assays

Hybridization with introduced rainbow trout threatens most native westslope cutthroat trout populations. Understanding the genetic effects of hybridization and introgression requires a large set of high-throughput, diagnostic genetic markers to inform conservation and management. Recently, we identified several thousand candidate single-nucleotide polymorphism (SNP) markers based on RAD sequencing of 11 westslope cutthroat trout and 13 rainbow trout individuals. Here, we used flanking sequence for 56 of these candidate SNP markers to design high-throughput genotyping assays. We validated the assays on a total of 92 individuals from 22 populations and seven hatchery strains. Forty-six assays (82%) amplified consistently and allowed easy identification of westslope cutthroat and rainbow trout alleles as well as heterozygote controls. The 46 SNPs will provide high power for early detection of population admixture and improved identification of hybrid and nonhybridized individuals. This technique shows promise as a very low-cost, reliable and relatively rapid method for developing and testing SNP markers for nonmodel organisms with limited genomic resources.     

Development and evaluation of a 9K SNP array for peach by internationally coordinated SNP detection and validation in breeding germplasm

Although a large number of single nucleotide polymorphism (SNP) markers covering the entire genome are needed to enable molecular breeding efforts such as genome wide association studies, fine mapping, genomic selection and marker-assisted selection in peach [Prunus persica (L.) Batsch] and related Prunus species, only a limited number of genetic markers, including simple sequence repeats (SSRs), have been available to date. To address this need, an international consortium (The International Peach SNP Consortium; IPSC) has pursued a coordinated effort to perform genome-scale SNP discovery in peach using next generation sequencing platforms to develop and characterize a high-throughput Illumina Infinium® SNP genotyping array platform. We performed whole genome re-sequencing of 56 peach breeding accessions using the Illumina and Roche/454 sequencing technologies. Polymorphism detection algorithms identified a total of 1,022,354 SNPs. Validation with the Illumina GoldenGate® assay was performed on a subset of the predicted SNPs, verifying ∼75% of genic (exonic and intronic) SNPs, whereas only about a third of intergenic SNPs were verified. Conservative filtering was applied to arrive at a set of 8,144 SNPs that were included on the IPSC peach SNP array v1, distributed over all eight peach chromosomes with an average spacing of 26.7 kb between SNPs. Use of this platform to screen a total of 709 accessions of peach in two separate evaluation panels identified a total of 6,869 (84.3%) polymorphic SNPs.The almost 7,000 SNPs verified as polymorphic through extensive empirical evaluation represent an excellent source of markers for future studies in genetic relatedness, genetic mapping, and dissecting the genetic architecture of complex agricultural traits. The IPSC peach SNP array v1 is commercially available and we expect that it will be used worldwide for genetic studies in peach and related stone fruit and nut species.     

Highly efficient genotyping of rice biparental populations by GoldenGate assays based on parental resequencing

Key message

A new time- and cost-effective strategy was developed for medium-density SNP genotyping of rice biparental populations, using GoldenGate assays based on parental resequencing.

Abstract

Since the advent of molecular markers, crop researchers and breeders have dedicated huge amounts of effort to detecting quantitative trait loci (QTL) in biparental populations for genetic analysis and marker-assisted selection (MAS). In this study, we developed a new time- and cost-effective strategy for genotyping a population of progeny from a rice cross using medium-density single nucleotide polymorphisms (SNPs). Using this strategy, 728,362 “high quality” SNPs were identified by resequencing Teqing and Lemont, the parents of the population. We selected 384 informative SNPs that were evenly distributed across the genome for genotyping the biparental population using the Illumina GoldenGate assay. 335 (87.2 %) validated SNPs were used for further genetic analyses. After removing segregation distortion markers, 321 SNPs were used for linkage map construction and QTL mapping. This strategy generated SNP markers distributed more evenly across the genome than previous SSR assays. Taking the GW5 gene that controls grain shape as an example, our strategy provided higher accuracy (0.8 Mb) and significance (LOD 5.5 and 10.1) in QTL mapping than SSR analysis. Our study thus provides a rapid and efficient strategy for genetic studies and QTL mapping using SNP genotyping assays.     

Multiplexed SNP genotyping using the Qbead™ system: a quantum dot-encoded microsphere-based assay

We have developed a new method using the Qbead™ system for high-throughput genotyping of single nucleotide polymorphisms (SNPs). The Qbead system employs fluorescent Qdot™ semiconductor nanocrystals, also known as quantum dots, to encode microspheres that subsequently can be used as a platform for multiplexed assays. By combining mixtures of quantum dots with distinct emission wavelengths and intensities, unique spectral ‘barcodes’ are created that enable the high levels of multiplexing required for complex genetic analyses. Here, we applied the Qbead system to SNP genotyping by encoding microspheres conjugated to allele-specific oligonucleotides. After hybridization of oligonucleotides to amplicons produced by multiplexed PCR of genomic DNA, individual microspheres are analyzed by flow cytometry and each SNP is distinguished by its unique spectral barcode. Using 10 model SNPs, we validated the Qbead system as an accurate and reliable technique for multiplexed SNP genotyping. By modifying the types of probes conjugated to microspheres, the Qbead system can easily be adapted to other assay chemistries for SNP genotyping as well as to other applications such as analysis of gene expression and protein–protein interactions. With its capability for high-throughput automation, the Qbead system has the potential to be a robust and cost-effective platform for a number of applications.     

Correcting for ascertainment biases when analyzing SNP data: applications to the estimation of linkage disequilibrium

As large-scale sequencing efforts turn from single genome sequencing to polymorphism discovery, single nucleotide polymorphisms (SNPs) are becoming an increasingly important class of population genetic data. But because of the ascertainment biases introduced by many methods of SNP discovery, most SNP data cannot be analyzed using classical population genetic methods. Statistical methods must instead be developed that can explicitly take into account each method of SNP discovery. Here we review some of the current methods for analyzing SNPs and derive sampling distributions for single SNPs and pairs of SNPs for some common SNP discovery schemes. We also show that the ascertainment scheme has a large effect on the estimation of linkage disequilibrium and recombination, and describe some methods of correcting for ascertainment biases when estimating recombination rates from SNP data.     

KAREBrowser: SNP database of Korea Association REsource Project

The International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information to the public. However, this kind of information is limited because of the small sample size in both databases. A Genome-Wide Association Study has been conducted with 8,842 Korean subjects as a part of the Korea Association Resource (KARE) project. In an effort to build a publicly available browsing system for genome data resulted from large scale KARE GWAS, we developed the KARE browser. This browser provides users with a large amount of single nucleotide polymorphisms (SNPs) information comprising 1.5 million SNPs from population-based cohorts of 8,842 samples. KAREBrowser was based on the generic genome browser (GBrowse), a webbased application tool developed for users to navigate and visualize the genomic features and annotations in an interactive manner. All SNP information and related functions are available at the web site http://ksnp.cdc. go.kr/karebrowser/.     

Using mtDNA Sequences to Estimate SNP Parameters in ESTs

Discovery of single nucleotide polymorphisms (SNPs) requires analysis of redundant sequences such as those available in large public databases. The ability to detect SNPs, especially those of low frequency, is dependent on the depth and scale of the discovery effort. Large numbers of SNPs have been identified by mining large-scale EST surveys and whole genome sequencing projects. These surveys however are subject to ascertainment bias and the inherent errors in large-scale single pass sequencing efforts. For example, the number of steps involved in the construction and sequencing of cDNA libraries make ESTs highly error prone, resulting in an increased frequency of nonvalid SNPs obtained in these surveys. Sequences of mtDNA genes are often incorporated into cDNA libraries as an artifact of the library construction process and are typically either subtracted from cDNA libraries or are considered superfluous when evaluating the information content of EST datasets. Sequences of mtDNA genes provide a unique resource for the analysis of SNP parameters in EST projects. This study uses sequences from four turkey muscle cDNA libraries to demonstrate how mtDNA sequences gleaned from collections of ESTs can be used to estimate SNP parameters and thus help predict the validity of SNPs.     

Using mtDNA sequences to estimate SNP parameters in ESTs

Discovery of single nucleotide polymorphisms (SNPs) requires analysis of redundant sequences such as those available in large public databases. The ability to detect SNPs, especially those of low frequency, is dependent on the depth and scale of the discovery effort. Large numbers of SNPs have been identified by mining large-scale EST surveys and whole genome sequencing projects. These surveys however are subject to ascertainment bias and the inherent errors in large-scale single pass sequencing efforts. For example, the number of steps involved in the construction and sequencing of cDNA libraries make ESTs highly error prone, resulting in an increased frequency of nonvalid SNPs obtained in these surveys. Sequences of mtDNA genes are often incorporated into cDNA libraries as an artifact of the library construction process and are typically either subtracted from cDNA libraries or are considered superfluous when evaluating the information content of EST datasets. Sequences of mtDNA genes provide a unique resource for the analysis of SNP parameters in EST projects. This study uses sequences from four turkey muscle cDNA libraries to demonstrate how mtDNA sequences gleaned from collections of ESTs can be used to estimate SNP parameters and thus help predict the validity of SNPs.