Single Nucleotide Polymorphism Genotyping Platforms Research Articles

Rapid one-pot human single nucleotide polymorphism genotyping platform with Cas13a nuclease

Rapid one-pot human single nucleotide polymorphism genotyping platform with Cas13a nuclease

TigerBase: a DNA registration system to enhance enforcement and compliance testing of captive tiger facilities

The illegal trade in tigers (Panthera tigris) and their derivatives, such as bones, teeth and pelts, is a major threat to the species’ long-term persistence. As wild tiger populations have dwindled, a large proportion of trafficked tiger products now derive from captive breeding facilities found throughout Asia. Moreover, wild tigers have been poached and laundered into captive facilities, then falsely designated as captive-bred. The establishment of a DNA registration system is recognized as a key tool to monitor compliance of captive facilities, support tiger trade investigations and improve prosecution outcomes. Here, we present a standardised wildlife forensic DNA profiling system for captive tigers called TigerBase. TigerBase has been developed in four South-East Asia countries with captive tiger facilities: Malaysia, Vietnam, Thailand and Lao PDR. TigerBase DNA profile data is based on 60 single nucleotide polymorphism (SNP) markers, genotyped using two different TaqMan®-based approaches: OpenArray® chip (capable of genotyping 60 SNPs for 48 samples in a single chip), and singleplex TaqMan® assays (capable of genotyping one SNP for one sample per reaction). Of the 60 SNPs, 53 are autosomal nuclear markers, suitable for individualisation and parentage applications, two are sex-linked markers, suitable for sexing, and five are mtDNA markers, suitable for maternal subspecies identification. We conducted a series of validation experiments to investigate the reliability and limitations of these SNP genotyping platforms. We found that the OpenArray® chip platform is more suitable for generating reference data given its greater throughput, while the singleplex TaqMan® assays are more appropriate for genotyping lower quality casework samples, given their higher sensitivity and throughput flexibility. Only 19 autosomal nuclear markers were validated as singleplex TaqMan® assays, which generally provides ample power for individualisation analysis (probability of identity among siblings was <6.9 ×10-4), but may lack power for specific parentage questions, such as determining parentage of an offspring when one of the parent’s genotypes is missing. Further, we have developed pipelines to support standardised SNP calling and decrease the chance of genotyping errors through the use of analytical workflows and synthetic positive controls. We expect the implementation of TigerBase will enhance enforcement of tiger trafficking cases and encourage compliance among captive tiger facilities, together contributing to combatting the illegal tiger trade.

Genetic overlap between psoriatic arthritis and ankylosing spondylitis in a Chinese population.

Previous studies reveal that psoriatic arthritis (PsA) and ankylosing spondylitis (AS) share susceptibility genes, such as HLA-B27, demonstrating a degree of genetic overlap between these diseases. Recent studies have identified a number of novel AS and PsA genetic susceptibility loci, but data on these loci in Chinese PsA patients are limited. To identify candidate genes that confer susceptibility to PsA in Chinese patients with PsA, psoriasis vulgaris (PsV), and healthy controls. Sixteen susceptibility loci, reported in a genome-wide association study of AS, and nine susceptibility loci, reported in candidate gene studies of PsA, were examined. Single-nucleotide polymorphisms (SNPs) were genotyped in 503 patients with PsA, 496 patients with PsV, and 979 healthy controls using the SNPscanTM multiplex SNP genotyping platform. PLINK software and logistic regression analysis were used to estimate the statistical significance of associations. PPP2R3C (rs8006884) was shown to significantly associate with PsA+PsV (p = 1.92×10-3, OR = 1.28) and was suggested to associate with PsV (p = 0.03, OR = 1.19). A suggestive association was also observed between IL-23R (rs12141575) and PsA as well as with axial PsA based on subtype analysis, KIF3A (rs2897442) and PsV, and ERN1 (rs196941) or IFIH1 (rs984971) and axial PsA. Our results suggest that PPP2R3C confers susceptibility to PsA and PsV, and that this gene may be related to the pathogenesis of psoriatic lesions and arthritis. Moreover, our results indicate a possible association between IL-23R, ERN1, or IFIH1 and subtypes of PsA, and between KIF3A and PsV.

Pathogenic/likely pathogenic mutations identified in Vietnamese children diagnosed with autism spectrum disorder using high-resolution SNP genotyping platform

Among the most prevalent neurodevelopmental disorders, Autism Spectrum Disorder (ASD) is highly diverse showing a broad phenotypic spectrum. ASD also couples with a broad range of mutations, both de novo and inherited. In this study, we used a proprietary SNP genotyping chip to analyze the genomic DNA of 250 Vietnamese children diagnosed with ASD. Our Single Nucleotide Polymorphism (SNP) genotyping chip directly targets more than 800 thousand SNPs in the genome. Our primary focus was to identify pathogenic/likely pathogenic mutations that are potentially linked to more severe symptoms of autism. We identified and validated 23 pathogenic/likely pathogenic mutations in this initial study. The data shows that these mutations were detected in several cases spanning multiple biological pathways. Among the confirmed SNPs, mutations were identified in genes previously known to be strongly associated with ASD such as SLCO1B1, ACADSB, TCF4, HCP5, MOCOS, SRD5A2, MCCC2, DCC, and PRKN while several other mutations are known to associate with autistic traits or other neurodevelopmental disorders. Some mutations were found in multiple patients and some patients carried multiple pathogenic/likely pathogenic mutations. These findings contribute to the identification of potential targets for therapeutic solutions in what is considered a genetically heterogeneous neurodevelopmental disorder.

Multiplex genotyping of SNPs in genomic DNA via hydrogel-based assay mediated with MutS and polyethylene glycol

The simultaneous genotyping of multiple single nucleotide polymorphisms (SNPs) in genomic DNA derived from organisms holds significant potential for applications such as precision medicine and food product authentication. However, conventional assay technologies including qPCR-based techniques, microarrays, and hydrogel-based assays face limitations in efficient multiplexing of SNPs, particularly for large-size DNA beyond kilobase scales, due to constraints in multiplex capability, specificity, or sensitivity. In this study, a hydrogel-based multiplex SNP genotyping platform specifically designed for genomic DNA is presented. This platform integrates the ligation detection reaction (LDR) and rolling circle amplification (RCA) techniques within a hydrogel-based multiplex sensing system, enabling adaptable and sensitive SNP genotyping for genomic DNA. To enhance the specificity of the assay, MutS protein and polyethylene glycol are introduced into the protocol, reducing the non-specific ligation and RCA reactions synergistically. With significant specificity improvement of over 10-fold, three types of SNPs within an artificially constructed ∼1000 bp double-stranded DNA (dsDNA) are successfully genotyped with double-digit picomolar sensitivity. Furthermore, the practical applicability of the developed process for the origin identification of raw materials is demonstrated by genotyping three types of SNPs within genomic DNA obtained from two closely related plant species, Korean ginseng (Panax ginseng) and American ginseng (Panax quinquefolius), containing ca. 3.5 gigabase genome size. Of notable significance, this study marks the premiere achievement in PCR-free multiplex genotyping of SNPs in genomic DNA using a single fluorophore.

Development of STARP Marker Platform for Flexible SNP Genotyping in Sugarbeet

Single nucleotide polymorphisms (SNPs) have been widely used for gene identification. Allelic discrimination for an individual SNP with high reliability and flexibility is critical for the accurate detection of beneficial genes linked to specific SNP sites. Several SNP genotyping platforms have been developed but most exclusively rely on fluorescence signals for allelic differentiation. Genotyping via a fluorescence signal can have a lower accuracy if strong background signal noise is present, a common challenge associated with crop genetics. The semi-thermal asymmetric reverse PCR (STARP) marker system introduces extra SNPs in its forward primers to ensure specificity of the PCR reaction and adds a 4-nucleotide insertion into one universal primer to create fragment length polymorphism among STARP markers, which makes SNP allelic discrimination possible through either fluorescence signals or traditional gel electrophoresis. The STARP marker system is preferable for SNP genotyping in crops such as sugarbeet (Beta vulgaris ssp. Vulgaris L.) that exhibit strong background signal noise during PCR reactions due to an abundant repetitive sequence and high levels of heterozygosity in the genome. In this study, SNPs among sugarbeet lines were detected through genotype-by-sequencing (GBS) and confirmed by sequencing PCR products containing SNP sites. STARP primers were designed, and they generated STARP markers clearly discriminated by SNP alleles among sugarbeet plants either through a fluorescence signal or fragment length polymorphism. In addition, by prolonging 5-nucleotide in an allele-specific forward primer F2 that increased fragment length polymorphism of STARP markers from 4-bp to 9-bp, genotyping individual SNPs can be performed using user-friendly agarose gels. This research resulted in the development of a STARP marker platform for the flexible genotyping of individual SNPs of sugarbeet as well as an improved STARP technique for easy SNP allelic discrimination that also has utilities in other plant species.

Genotyping by Sequencing (GBS) for Genome-Wide SNP Identification in Plants.

Marker-assisted selection has played a pivotal role in developing several elite varieties in the past two decades. Molecular markers employed in plant breeding programs have recently shifted from microsatellites or simple sequence repeats (SSRs) to single nucleotide polymorphisms (SNPs) due to the ubiquity of SNP markers in the genome and the availability of various high-throughput SNP genotyping platforms. Rapid advances in sequencing technologies and the reduction in sequencing cost have facilitated SNP discovery in several plant species including non-model organisms with little or no genomic resources. Despite the lower cost of sequencing, genome complexity reduction approaches are still useful for SNP identification because many applications do not require every base of the genome to be sequenced. Genotyping-by-sequencing (GBS) is a quick and affordable reduced representation method that can simultaneously identify and genotype a large number of SNPs that has been successfully applied to a wide range of plant species. This chapter describes a robust two-enzyme GBS method for SNP discovery and genotyping that has been verified in non-model plant species.

Intra- and Interspecies RNA-Seq Based Variants in the Lactation Process of Ruminants.

The RNA-Seq data provides new opportunities for the detection of transcriptome variants' single nucleotide polymorphisms (SNPs) in various species and tissues. Herein, milk samples from two sheep breeds and two cow breeds were utilized to characterize the genetic variation in the coding regions in three stages (before-peak (BP), peak (P), and after-peak (AP)) of the lactation process. In sheep breeds Assaf and Churra, 100,462 and 97,768, 65,996 and 62,161, and 78,656 and 39,245 variants were observed for BP, P, and AP lactation stages, respectively. The number of specific variants was 59,798 and 76,419, 11,483 and 49,210, and 104,033 and 320,817 in cow breeds Jersy and Kashmiri, respectively, for BP, P, and AP stages. Via the transcriptome analysis of variation in regions containing QTL for fat, protein percentages, and milk yield, we detected a number of pathways and genes harboring mutations that could influence milk production attributes. Many SNPs detected here can be regarded as appropriate markers for custom SNP arrays or genotyping platforms to conduct association analyses among commercial populations. The results of this study offer new insights into milk production genetic mechanisms in cow and sheep breeds, which can contribute to designing suitable breeding systems for optimal milk production.

Twelve Years into Genomic Selection in Forest Trees: Climbing the Slope of Enlightenment of Marker Assisted Tree Breeding

Twelve years have passed since the early outlooks of applying genomic selection (GS) to forest tree breeding, initially based on deterministic simulations, soon followed by empirical reports. Given its solid projections for causing a paradigm shift in tree breeding practice in the years to come, GS went from a hot, somewhat hyped, topic to a fast-moving area of applied research and operational implementation worldwide. The hype cycle curve of emerging technologies introduced by Gartner Inc. in 1995, models the path a technology takes in terms of expectations of its value through time. Starting with a sudden and excessively positive “peak of inflated expectations” at its introduction, a technology that survives the “valley of disappointment” moves into maturity to climb the “slope of enlightenment”, to eventually reach the “plateau of productivity”. Following the pioneering steps of GS in animal breeding, we have surpassed the initial phases of the Gartner hype cycle and we are now climbing the slope of enlightenment towards a wide application of GS in forest tree breeding. By merging modern high-throughput DNA typing, time-proven quantitative genetics and mixed-model analysis, GS moved the focus away from the questionable concept of dissecting a complex, polygenic trait in its individual components for breeding advancement. Instead of trying to find the needle in a haystack, i.e., the “magic” gene in the complex and fluid genome, GS more efficiently and humbly “buys the whole haystack” of genomic effects to predict complex phenotypes, similarly to an exchange-traded fund that more efficiently “buys the whole market”. Tens of studies have now been published in forest trees showing that GS matches or surpasses the performance of phenotypic selection for growth and wood properties traits, enhancing the rate of genetic gain per unit time by increasing selection intensity, radically reducing generation interval and improving the accuracy of breeding values. Breeder-friendly and cost-effective SNP (single nucleotide polymorphism) genotyping platforms are now available for all mainstream plantation forest trees, but methods based on low-pass whole genome sequencing with imputation might further reduce genotyping costs. In this perspective, I provide answers to why GS will soon become the most efficient and effective way to carry out advanced tree breeding, and outline a simple pilot demonstration project that tree breeders can propose in their organization. While the fundamental properties of GS in tree breeding are now solidly established, strategic, logistics and financial aspects for the optimized adoption of GS are now the focus of attentions towards the plateau of productivity in the cycle, when this new breeding method will become fully established into routine tree improvement.

Genetic Mapping to Detect Stringent QTLs Using 1k-RiCA SNP Genotyping Platform from the New Landrace Associated with Salt Tolerance at the Seedling Stage in Rice

Rice is the world’s most important food crop, providing the daily calorie intake for more than half of the world’s population. Rice breeding has always been preoccupied with maximizing yield potential. However, numerous abiotic factors, such as salt, cold, drought, and heat, significantly reduce rice productivity. Salinity, one of the major abiotic stresses, reduces rice yield worldwide. This study was conducted to determine new quantitative trait loci (QTLs) that regulate salt tolerance in rice seedlings. One F2:3 mapping population was derived from a cross between BRRI dhan49 (a popular but sensitive rainfed rice variety) and Akundi (a salt-tolerant rice landrace in Bangladesh used as a donor parent). The 1k-Rice Custom Amplicon (1k-RiCA) single-nucleotide polymorphism (SNP) markers were used to genotype this mapping population. After removing segregation distortion and monomorphic markers, 884 SNPs generated a 1526.8 cM-long genetic linkage map with a mean marker density of 1.7 cM for the 12 linkage groups. By exploiting QGene and ICIM-ADD, a sum of 15 QTLs for nine traits was identified in salt stress on seven chromosomes. Four important genomic loci were identified (qSES1, qSL1, qSUR1 and qRL1) on chromosome 1. Out of these 15 QTLs, 14 QTLs are unique, as no other study has mapped in the same chromosomal location. We also detected 15 putative candidate genes and their functions. The ICIM-EPI approach identified 43 significant pairwise epistasis interactions between regions associated with and unassociated with QTLs. Apart from more well-known donors, Akundi serves as an important new donor source for global salt tolerance breeding initiatives, including Bangladesh. The introgression of the novel QTLs identified in this study will accelerate the development of new salt-tolerant varieties that are highly resistant to salt stress using marker-enabled breeding.

Development and application of the Faba_bean_130K targeted next-generation sequencing SNP genotyping platform based on transcriptome sequencing.

Large-scale faba bean transcriptome data are available, and the first genotyping platform based on liquid-phase probe targeted capture technology was developed for genetic and molecular breeding studies. Faba bean (Vicia faba L., 2n = 12) is an important food legume crop that is widely grown for multiple uses worldwide. However, no reference genome is currently available due to its very large genome size (approximately 13Gb) and limited single nucleotide polymorphism (SNP) markers as well as highly efficient genotyping tools have been reported for faba bean. In this study, 16.7 billion clean reads were obtained from transcriptome libraries of flowers and leaves of 102 global faba bean accessions. A total of 243,120 unigenes were de novo assembled and functionally annotated. Moreover, a total of 1,579,411 SNPs were identified and further filtered according to a selection pipeline to develop a high-throughput, flexible, low-cost Faba_bean_130K targeted next-generation sequencing (TNGS) genotyping platform. A set of 69 Chinese faba bean accessions were genotyped with the TNGS genotyping platform, and the average mapping rate of captured reads to reference transcripts was 93.14%, of which 53.23% were located in the targeted regions. The TNGS genotyping results were validated by Sanger sequencing and the average consistency rate reached 93.6%. Comprehensive population genetic analysis was performed on the 69 Chinese faba bean accessions and identified four genetic subgroups correlated with the geographic distribution. This study provides valuable genomic resources and a reliable genotyping tool that could be implemented in genetic and molecular breeding studies to accelerate new cultivar development and improvement in faba bean.

Development of a core set of single nucleotide polymorphism markers for genetic diversity analysis and cultivar fingerprinting in cowpea

AbstractCowpea is an important legume crop worldwide. However, the diversity and relationship of current accessions remain unclear due to a lack of robust genetic information. A set of 40,089 single nucleotide polymorphisms (SNPs) adapted to the Kompetitive Allele Specific PCR (KASP) SNP genotyping platform were developed from the existing Illumina Cowpea iSelect Consortium Array for cowpea germplasm genetic diversity assessment and variety identification. Using the genotypic data of 299 cowpea accessions obtained from this SNP assay, a precore pool of 434 SNPs and 50 informative core SNPs was selected and validated for use in future genetic diversity analyses of cowpea germplasm. By further genotyping 75 commercial cultivars using the set of 50 core SNPs, pairwise genotype alignment and dendrogram analysis both showed that each cultivar could be uniquely identified by this core set of markers. The KASP markers developed in this study provide a flexible marker resource for both basic and applied research of cowpea. The precore SNP pool and the core SNP set also provide valuable tools for genetic variation assessment and variety rights protection for cowpea breeders.

Genotyping tools and resources to assess peanut germplasm: smut-resistant landraces as a case study.

Peanut smut caused by Thecaphora frezii is a severe fungal disease currently endemic to Argentina and Brazil. The identification of smut resistant germplasm is crucial in view of the potential risk of a global spread. In a recent study, we reported new sources of smut resistance and demonstrated its introgression into elite peanut cultivars. Here, we revisited one of these sources (line I0322) to verify its presence in the U.S. peanut germplasm collection and to identify single nucleotide polymorphisms (SNPs) potentially associated with resistance. Five accessions of Arachis hypogaea subsp. fastigiata from the U.S. peanut collection, along with the resistant source and derived inbred lines were genotyped with a 48K SNP peanut array. A recently developed SNP genotyping platform called RNase H2 enzyme-based amplification (rhAmp) was further applied to validate selected SNPs in a larger number of individuals per accession. More than 14,000 SNPs and nine rhAmp assays confirmed the presence of a germplasm in the U.S. peanut collection that is 98.6% identical (P < 0.01, bootstrap t-test) to the resistant line I0322. We report this germplasm with accompanying genetic information, genotyping data, and diagnostic SNP markers.

The MIR137 VNTR rs58335419 Is Associated With Cognitive Impairment in Schizophrenia and Altered Cortical Morphology

Genome-wide association studies (GWAS) of schizophrenia have strongly implicated a risk locus in close proximity to the gene for miR-137. While there are candidate single-nucleotide polymorphisms (SNPs) with functional implications for the microRNA’s expression encompassed by the common haplotype tagged by rs1625579, there are likely to be others, such as the variable number tandem repeat (VNTR) variant rs58335419, that have no proxy on the SNP genotyping platforms used in GWAS to date. Using whole-genome sequencing data from schizophrenia patients (n = 299) and healthy controls (n = 131), we observed that the MIR137 4-repeats VNTR (VNTR4) variant was enriched in a cognitive deficit subtype of schizophrenia and associated with altered brain morphology, including thicker left inferior temporal gyrus and deeper right postcentral sulcus. These findings suggest that the MIR137 VNTR4 may impact neuroanatomical development that may, in turn, influence the expression of more severe cognitive symptoms in patients with schizophrenia.

Abstract 3513: Genome-wide scan for novel prostate cancer susceptibility loci with clinical consequence utilizing increased genetic drift of the Finnish population

Abstract Background: Prostate cancer (PC) is the second most common cancer in men worldwide with a rising prevalence. However, only limited number of clinically actionable variants are known. The objective of this study is to identify novel PC susceptibility loci with potential clinical relevance utilizing the increased genetic drift and reduced selective pressure of the recently bottlenecked powerful resource of the Finnish population. Methods: We meta-analysed &amp;gt;185.000 germline single nucleotide polymorphisms (SNPs) in 2738 PC cases and 2401 controls of Finnish origin in the Collaborative Oncological Gene-Environment Study (COGS) using Illumina iSelect custom SNP genotyping platform. Results: Altogether 160 variants remain significant on GWAS level (p&amp;lt;5 × 10−8) in 18 different gene regions. Out of the 160 identified PC susceptibility hits 78 (49%) are novel variants not reported earlier in association with PC. PC associated signals are in close proximity to one another forming genetic hot-spots on chromosomes 8, 7, 11, 17 and 19. The strength of association varies for 101 PC risk variants (OR 1.24-1.86) and 59 protective SNPs (OR 0.59-0.80). The strongest risk gene is CASC8 (OR=1.86; p=1.214 × 10−11). The most significant signals were found at the 8p21.2 chromosomal region (p&amp;lt;7.6 × 10−16). Functional annotation identified a missense coding SNP at KLK3 gene to be a candidate causal variant. We showed evidence for association both with early-onset PC (OR 1.73; P=0.02), high serum PSA level at diagnosis (OR 1.36; P=0.024) and with aggressive PC (Gleason score ≥8; OR 1.44; P=0.02) at 17q21. Conclusion: The results facilitate risk stratification for screening, clinical studies, treatment choices and functional research of PC Citation Format: Csilla Sipeky, Teuvo L. Tammela, Anssi Auvinen, Johanna Schleutker. Genome-wide scan for novel prostate cancer susceptibility loci with clinical consequence utilizing increased genetic drift of the Finnish population [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3513.

Genomic Analysis Using Bayesian Methods under Different Genotyping Platforms in Korean Duroc Pigs.

Simple SummaryThis study investigated the informative regions and the efficiency of genomic predictions for backfat thickness, days to 90 kg body weight, loin muscle area, and lean percentage in Korean Duroc pigs. The several regions of the genome were identified and a significant marker was found near the MC4R gene for growth and production-related traits. No differences in genomic accuracy were identified on the basis of the Bayesian approaches in these four growth and production-related traits. The genomic accuracy is improved by using deregressed estimated breeding values including parental information as a response variable in Korean Duroc pigs.Genomic evaluation has been widely applied to several species using commercial single nucleotide polymorphism (SNP) genotyping platforms. This study investigated the informative genomic regions and the efficiency of genomic prediction by using two Bayesian approaches (BayesB and BayesC) under two moderate-density SNP genotyping panels in Korean Duroc pigs. Growth and production records of 1026 individuals were genotyped using two medium-density, SNP genotyping platforms: Illumina60K and GeneSeek80K. These platforms consisted of 61,565 and 68,528 SNP markers, respectively. The deregressed estimated breeding values (DEBVs) derived from estimated breeding values (EBVs) and their reliabilities were taken as response variables. Two Bayesian approaches were implemented to perform the genome-wide association study (GWAS) and genomic prediction. Multiple significant regions for days to 90 kg (DAYS), lean muscle area (LMA), and lean percent (PCL) were detected. The most significant SNP marker, located near the MC4R gene, was detected using GeneSeek80K. Accuracy of genomic predictions was higher using the GeneSeek80K SNP panel for DAYS (Δ2%) and LMA (Δ2–3%) with two response variables, with no gains in accuracy by the Bayesian approaches in four growth and production-related traits. Genomic prediction is best derived from DEBVs including parental information as a response variable between two DEBVs regardless of the genotyping platform and the Bayesian method for genomic prediction accuracy in Korean Duroc pig breeding.

Comparison of SNP Calling Pipelines and NGS Platforms to Predict the Genomic Regions Harboring Candidate Genes for Nodulation in Cultivated Peanut.

Cultivated peanut (Arachis hypogaea L.) forms root nodules to enable a symbiotic relationship with rhizobia for biological nitrogen fixation. To understand the genetic factors of peanut nodulation, it is fundamental to genetically map and clone the genes involved in nodulation. For genetic mapping, high throughput genotyping with a large number of polymorphic markers is critical. In this study, two sets of sister recombinant inbred lines (RILs), each containing a nodulating (Nod+) and non-nodulating (Nod-) line, and their Nod+ parental lines were extensively genotyped. Several next generation sequencing (NGS) methods including target enrichment sequencing (TES), RNA-sequencing (RNA-seq), genotyping by sequencing (GBS), and the 48K Axiom Arachis2 SNP array, and various analysis pipelines were applied to identify single nucleotide polymorphisms (SNP) among the two sets of RILs and their parents. TES revealed the largest number of homozygous SNPs (15,947) between the original parental lines, followed by the Axiom Arachis2 SNP array (1,887), RNA-seq (1,633), and GBS (312). Among the five SNP analysis pipelines applied, the alignment to A/B genome followed by HAPLOSWEEP revealed the largest number of homozygous SNPs and highest concordance rate (79%) with the array. A total of 222 and 1,200 homozygous SNPs were polymorphic between the Nod+ and Nod− sister RILs and between their parents, respectively. A graphical genotype map of the sister RILs was constructed with these SNPs, which demonstrated the candidate genomic regions harboring genes controlling nodulation across the whole genome. Results of this study mainly provide the pros and cons of NGS and SNP genotyping platforms for genetic mapping in peanut, and also provide potential genetic resources to narrow down the genomic regions controlling peanut nodulation, which would lay the foundation for gene cloning and improvement of nitrogen fixation in peanut.

Seed Coat Pattern QTL and Development in Cowpea (Vigna unguiculata [L.] Walp.).

The appearance of the seed is an important aspect of consumer preference for cowpea (Vigna unguiculata [L.] Walp.). Seed coat pattern in cowpea has been a subject of study for over a century. This study makes use of newly available resources, including mapping populations, a reference genome and additional genome assemblies, and a high-density single nucleotide polymorphism genotyping platform, to map various seed coat pattern traits to three loci, concurrent with the Color Factor (C), Watson (W), and Holstein (H) factors identified previously. Several gene models encoding proteins involved in regulating the later stages of the flavonoid biosynthesis pathway have been identified as candidate genes, including a basic helix–loop–helix gene (Vigun07g110700) for the C locus, a WD-repeat gene (Vigun09g139900) for the W locus and an E3 ubiquitin ligase gene (Vigun10g163900) for the H locus. A model of seed coat development, consisting of six distinct stages, is described to explain some of the observed pattern phenotypes.

Rapid DNA-genotyping system targeting ten loci for resistance to blast disease in rice.

The fungal pathogen Pyricularia oryzae causes blast, a severe disease of rice (Oryza sativa L.). Improving blast resistance is important in rice breeding programs. Inoculation tests have been used to select for resistance genotypes, with DNA marker-based selection becoming an efficient alternative. No comprehensive DNA marker system for race-specific resistance alleles in the Japanese rice breeding program has been developed because some loci contain multiple resistance alleles. Here, we used the Fluidigm SNP genotyping platform to determine a set of 96 single nucleotide polymorphism (SNP) markers for 10 loci with race-specific resistance. The markers were then used to evaluate the presence or absence of 24 resistance alleles in 369 cultivars; results were 93.5% consistent with reported inoculation test-based genotypes in japonica varieties. The evaluation system was successfully applied to high-yield varieties with indica genetic backgrounds. The system includes polymorphisms that distinguish the resistant alleles at the tightly linked Pita and Pita-2 loci, thereby confirming that all the tested cultivars with Pita-2 allele carry Pita allele. We also developed and validated insertion/deletion (InDel) markers for ten resistance loci. Combining SNP and InDel markers is an accurate and efficient strategy for selection for race-specific resistance to blast in breeding programs.

Kompetitive Allele Specific PCR (KASP): A Singleplex Genotyping Platform and Its Application

Single nucleotide polymorphism (SNP) can be detected by mining sequence databases or by using different singleplex or multiplex SNP genotyping platforms. Development of high-throughput genotyping molecular markers can be instrumental towards maximizing genetic gain. In this review we provide an overview of Kompetitive Allele Specific PCR (KASP) genotyping platform requirements and its application that might be helpful in KASP marker development. This literature further illustrates the possibilities to design KASP primers. Several research institutes routinely using KASP platform, producing in excess of humungous data points yearly for breeding cultivars and as well as for medical and commercial purposes. KASP genotyping technology offers cost effectiveness and high throughput molecular marker development platform. Conventional molecular markers can be converted into more robust and high throughput KASP markers. More than 2000 published references clearly show the popularity of KASP technology among the researchers.