SLAF-seq: An Efficient Method of Large-Scale De Novo SNP Discovery and Genotyping Using High-Throughput Sequencing

Large-scale genotyping plays an important role in genetic association studies. It has provided new opportunities for gene discovery, especially when combined with high-throughput sequencing technologies. Here, we report an efficient solution for large-scale genotyping. We call it specific-locus amplified fragment sequencing (SLAF-seq). SLAF-seq technology has several distinguishing characteristics: i) deep sequencing to ensure genotyping accuracy; ii) reduced representation strategy to reduce sequencing costs; iii) pre-designed reduced representation scheme to optimize marker efficiency; and iv) double barcode system for large populations. In this study, we tested the efficiency of SLAF-seq on rice and soybean data. Both sets of results showed strong consistency between predicted and practical SLAFs and considerable genotyping accuracy. We also report the highest density genetic map yet created for any organism without a reference genome sequence, common carp in this case, using SLAF-seq data. We detected 50,530 high-quality SLAFs with 13,291 SNPs genotyped in 211 individual carp. The genetic map contained 5,885 markers with 0.68 cM intervals on average. A comparative genomics study between common carp genetic map and zebrafish genome sequence map showed high-quality SLAF-seq genotyping results. SLAF-seq provides a high-resolution strategy for large-scale genotyping and can be generally applicable to various species and populations.     

单核苷酸多态性检测方法的研究进展

单核苷酸多态性（single nucleotide polymorphism, SNP）的研究已成为人类后基因组时代的主要内容之一。因此建立高度自动化和高通量的SNP检测分析技术十分重要。文章系统地介绍了最新发展的几种SNP检测技术的原理和检测平台,详细阐述了等位基因特异性杂交、内切酶酶切技术、引物延伸法、寡核苷酸连接反应等SNP检测原理,以及平板读数仪、基因芯片、微球阵列技术和质谱仪等检测平台,并对SNP高通量检测技术的发展进行了展望。     

单核苷酸多态性检测方法的研究进展

单核苷酸多态性(single nucleotide polymorphism,SNP)作为第三代遗传标记已经广泛应用于基因作图、疾病相关性分析、群体遗传学及药物研究等领域.因此建立高度自动化和高通量的SNP检测分析技术十分重要.简要介绍了国内外几种主要SNP检测技术的原理和检测分析手段,并对SNP高通量检测技术的发展进行了展望.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Using Mendelian Inheritance To Improve High-Throughput SNP Discovery

Restriction site-associated DNA sequencing or genotyping-by-sequencing (GBS) approaches allow for rapid and cost-effective discovery and genotyping of thousands of single-nucleotide polymorphisms (SNPs) in multiple individuals. However, rigorous quality control practices are needed to avoid high levels of error and bias with these reduced representation methods. We developed a formal statistical framework for filtering spurious loci, using Mendelian inheritance patterns in nuclear families, that accommodates variable-quality genotype calls and missing data—both rampant issues with GBS data—and for identifying sex-linked SNPs. Simulations predict excellent performance of both the Mendelian filter and the sex-linkage assignment under a variety of conditions. We further evaluate our method by applying it to real GBS data and validating a subset of high-quality SNPs. These results demonstrate that our metric of Mendelian inheritance is a powerful quality filter for GBS loci that is complementary to standard coverage and Hardy–Weinberg filters. The described method, implemented in the software MendelChecker, will improve quality control during SNP discovery in nonmodel as well as model organisms.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Grapevine Phenological Quantitative Trait SSR Genotyping Using High-Throughput HRM-PCR Analysis

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.     

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

The development of next generation sequencing (NGS) and high throughput genotyping are important techniques for the QTL mapping and genetic analysis of different crops. High-resolution melting (HRM) is an emerging technology used for detecting single-nucleotide polymorphisms (SNPs) in various species. However, its use is still limited in maize. The HRM analysis was integrated with SNPs to identify three types of populations (NIL population, RIL population and natural population), and the useful tags were screened. The patterns of temperature-shifted 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.     

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.     

Genosnip: SNP Genotyping by MALDI-TOF MS Using Photocleavable Oligonucleotides

Abstract

A photocleavable o-nitrobenzyl CE phosphoramidite building-block was synthesised and incorporated within oligonucleotides. After allele-specific primer extension, desalting was performed using genostrep purification plates. Release of the SNP information containing part through photocleavage created shortened molecules that are easily accessible for MALDI-TOF analysis. Additionally, incorporation of mass modified nucleosides enables flexible design of multiplex genotyping.     

Assessment of two flexible and compatible SNP genotyping platforms: TaqMan SNP Genotyping Assays and the SNPlex Genotyping System

In this review we describe the principles, protocols, and applications of two commercially available SNP genotyping platforms, the TaqMan SNP Genotyping Assays and the SNPlex Genotyping System. Combined, these two technologies meet the requirements of multiple SNP applications in genetics research and pharmacogenetics. We also describe a set of SNP selection tools and validated assay resources which we developed to accelerate the cycle of experimentation on these platforms. Criteria for selecting the more appropriate of these two genotyping technologies are presented: the genetic architecture of the trait of interest, the throughput required, and the number of SNPs and samples needed for a successful study. Overall, the TaqMan assay format is suitable for low- to mid-throughput applications in which a high assay conversion rate, simple assay workflow, and low cost of automation are desirable. The SNPlex Genotyping System, on the other hand, is well suited for SNP applications in which throughput and cost-efficiency are essential, e.g., applications requiring either the testing of large numbers of SNPs and samples, or the flexibility to select various SNP subsets.     

Automatic Scoring and Quality Assessment Using Accuracy Bounds for FP-TDI SNP Genotyping Data

BACKGROUND: Human diversity, namely single nucleotide polymorphisms (SNPs), is becoming a focus of biomedical research. Despite the binary nature of SNP determination, the majority of genotyping assay data need a critical evaluation for genotype calling. We applied statistical models to improve the automated analysis of 2-dimensional SNP data. METHODS: We derived several quantities in the framework of Gaussian mixture models that provide figures of merit to objectively measure the data quality. The accuracy of individual observations is scored as the probability of belonging to a certain genotype cluster, while the assay quality is measured by the overlap between the genotype clusters. RESULTS: The approach was extensively tested with a dataset of 438 nonredundant SNP assays comprising >150,000 datapoints. The performance of our automatic scoring method was compared with manual assignments. The agreement for the overall assay quality is remarkably good, and individual observations were scored differently by man and machine in 2.6% of cases, when applying stringent probability threshold values. CONCLUSION: Our definition of bounds for the accuracy for complete assays in terms of misclassification probabilities goes beyond other proposed analysis methods. We expect the scoring method to minimise human intervention and provide a more objective error estimate in genotype calling.     

Infinium Assay for Large-scale SNP Genotyping Applications

Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina''s panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.     

High-Throughput RAD-SNP Genotyping for Characterization of Sugar Beet Genotypes

High-throughput single-nucleotide polymorphism (SNP) genotyping provides a rapid way of developing resourceful sets of markers for delineating genetic structure and for understanding the basis of the taxonomic discrimination. In this paper, we present a panel of 192 SNPs for effective genotyping in sugar beet using a high-throughput marker array technology, QuantStudio 12K Flex system, coupled with Taqman OpenArray technology. The selected SNPs were evaluated for genetic diversity among a set of 150 individuals representing 15 genotypes (10 individuals each) from five cytoplasmic male steriles (CMSs), five pollinators, and five commercial varieties. We demonstrated that the proposed panel of 192 SNPs effectively differentiated the studied genotypes. A higher degree of polymorphism was observed among the CMSs as compared to pollinators and commercial varieties. PCoA and STRUCTURE analysis revealed that CMSs, pollinators, and varieties clustered into three distinct subpopulations. Our results demonstrate the utility of the identified panel of 192 SNPs coupled with TaqMan OpenArray technology as a wide set of markers for high-throughput SNP genotyping in sugar beet.     

A High-Density SNP Genotyping Array for Rice Biology and Molecular Breeding

A high-density single nucleotide polymorphism （SNP） array is critically important for geneticists and molecu- lar breeders. With the accumulation of huge amounts of genomic re-sequencing data and available technologies for accurate SNP detection, it is possible to design high-density and high-quality rice SNP arrays. Here we report the devel- opment of a high-density rice SNP array and its utility. SNP probes were designed by screening more than 10 000 000 SNP loci extracted from the re-sequencing data of 801 rice varieties and an array named RiceSNP50 was produced on the Illumina Infinium platform. The array contained 51 478 evenly distributed markers, 68% of which were within genic regions. Several hundred rice plants with parent/F1 relationships were used to generate a high-quality cluster file for accurate SNP calling. Application tests showed that this array had high genotyping accuracy, and could be used for dif- ferent objectives. For example, a core collection of elite rice varieties was clustered with fine resolution. Genome-wide association studies （GWAS） analysis correctly identified a characterized QTL. Further, this array was successfully used for variety verification and trait introgression. As an accurate high-throughput genotyping tool, RiceSNP50 will play an important role in both functional genomics studies and molecular breeding.     

Novel SNP Discovery in African Buffalo,Syncerus caffer,Using High-Throughput Sequencing

The African buffalo, Syncerus caffer, is one of the most abundant and ecologically important species of megafauna in the savannah ecosystem. It is an important prey species, as well as a host for a vast array of nematodes, pathogens and infectious diseases, such as bovine tuberculosis and corridor disease. Large-scale SNP discovery in this species would greatly facilitate further research into the area of host genetics and disease susceptibility, as well as provide a wealth of sequence information for other conservation and genomics studies. We sequenced pools of Cape buffalo DNA from a total of 9 animals, on an ABI SOLiD4 sequencer. The resulting short reads were mapped to the UMD3.1 Bos taurus genome assembly using both BWA and Bowtie software packages. A mean depth of 2.7× coverage over the mapped regions was obtained. Btau4 gene annotation was added to all SNPs identified within gene regions. Bowtie and BWA identified a maximum of 2,222,665 and 276,847 SNPs within the buffalo respectively, depending on analysis method. A panel of 173 SNPs was validated by fluorescent genotyping in 87 individuals. 27 SNPs failed to amplify, and of the remaining 146 SNPs, 43–54% of the Bowtie SNPs and 57–58% of the BWA SNPs were confirmed as polymorphic. dN/dS ratios found no evidence of positive selection, and although there were genes that appeared to be under negative selection, these were more likely to be slowly evolving house-keeping genes.     

DNA from Buccal Swabs Suitable for High-Throughput SNP Multiplex Analysis

We sought a convenient and reliable method for collection of genetic material that is inexpensive and noninvasive and suitable for self-collection and mailing and a compatible, commercial DNA extraction protocol to meet quantitative and qualitative requirements for high-throughput single nucleotide polymorphism (SNP) multiplex analysis on an automated platform. Buccal swabs were collected from 34 individuals as part of a pilot study to test commercially available buccal swabs and DNA extraction kits. DNA was quantified on a spectrofluorometer with Picogreen dsDNA prior to testing the DNA integrity with predesigned SNP multiplex assays. Based on the pilot study results, the Catch-All swabs and Isohelix buccal DNA isolation kit were selected for our high-throughput application and extended to a further 1140 samples as part of a large cohort study. The average DNA yield in the pilot study (n=34) was 1.94 μg ± 0.54 with a 94% genotyping pass rate. For the high-throughput application (n=1140), the average DNA yield was 2.44 μg ± 1.74 with a ≥93% genotyping pass rate. The Catch-All buccal swabs are a convenient and cost-effective alternative to blood sampling. Combined with the Isohelix buccal DNA isolation kit, they provided DNA of sufficient quantity and quality for high-throughput SNP multiplex analysis.     

Identification of Genome-Wide Copy Number Variations among Diverse Pig Breeds Using SNP Genotyping Arrays

Copy number variations (CNVs) are important forms of genetic variation complementary to SNPs, and can be considered as promising markers for some phenotypic and economically important traits or diseases susceptibility in domestic animals. In the present study, we performed a genome-wide CNV identification in 14 individuals selected from diverse populations, including six types of Chinese indigenous breeds, one Asian wild boar population, as well as three modern commercial foreign breeds. We identified 63 CNVRs in total, which covered 9.98 Mb of polymorphic sequence and corresponded to 0.36% of the genome sequence. The length of these CNVRs ranged from 3.20 to 827.21 kb, with an average of 158.37 kb and a median of 97.85 kb. Functional annotation revealed these identified CNVR have important molecular function, and may play an important role in exploring the genetic basis of phenotypic variability and disease susceptibility among pigs. Additionally, to confirm these potential CNVRs, we performed qPCR for 12 randomly selected CNVRs and 8 of them (66.67%) were confirmed successfully. CNVs detected in diverse populations herein are essential complementary to the CNV map in the pig genome, which provide an important resource for studies of genomic variation and the association between various economically important traits and CNVs.     

Ice-Cap: A Method for Growing Arabidopsis and Tomato Plants in 96-well Plates for High-Throughput Genotyping

It is becoming common for plant scientists to develop projects that require the genotyping of large numbers of plants. The first step in any genotyping project is to collect a tissue sample from each individual plant. The traditional approach to this task is to sample plants one-at-a-time. If one wishes to genotype hundreds or thousands of individuals, however, using this strategy results in a significant bottleneck in the genotyping pipeline. The Ice-Cap method that we describe here provides a high-throughput solution to this challenge by allowing one scientist to collect tissue from several thousand seedlings in a single day ^1,2. This level of throughput is made possible by the fact that tissue is harvested from plants 96-at-a-time, rather than one-at-a-time.The Ice-Cap method provides an integrated platform for performing seedling growth, tissue harvest, and DNA extraction. The basis for Ice-Cap is the growth of seedlings in a stacked pair of 96-well plates. The wells of the upper plate contain plugs of agar growth media on which individual seedlings germinate. The roots grow down through the agar media, exit the upper plate through a hole, and pass into a lower plate containing water. To harvest tissue for DNA extraction, the water in the lower plate containing root tissue is rapidly frozen while the seedlings in the upper plate remain at room temperature. The upper plate is then peeled away from the lower plate, yielding one plate with 96 root tissue samples frozen in ice and one plate with 96 viable seedlings. The technique is named "Ice-Cap" because it uses ice to capture the root tissue. The 96-well plate containing the seedlings can then wrapped in foil and transferred to low temperature. This process suspends further growth of the seedlings, but does not affect their viability. Once genotype analysis has been completed, seedlings with the desired genotype can be transferred from the 96-well plate to soil for further propagation. We have demonstrated the utility of the Ice-Cap method using Arabidopsis thaliana, tomato, and rice seedlings. We expect that the method should also be applicable to other species of plants with seeds small enough to fit into the wells of 96-well plates.     

A Fully Automated High-Throughput Training System for Rodents

Addressing the neural mechanisms underlying complex learned behaviors requires training animals in well-controlled tasks, an often time-consuming and labor-intensive process that can severely limit the feasibility of such studies. To overcome this constraint, we developed a fully computer-controlled general purpose system for high-throughput training of rodents. By standardizing and automating the implementation of predefined training protocols within the animal’s home-cage our system dramatically reduces the efforts involved in animal training while also removing human errors and biases from the process. We deployed this system to train rats in a variety of sensorimotor tasks, achieving learning rates comparable to existing, but more laborious, methods. By incrementally and systematically increasing the difficulty of the task over weeks of training, rats were able to master motor tasks that, in complexity and structure, resemble ones used in primate studies of motor sequence learning. By enabling fully automated training of rodents in a home-cage setting this low-cost and modular system increases the utility of rodents for studying the neural underpinnings of a variety of complex behaviors.