High-resolution melting analysis for SNP genotyping and mapping in tetraploid alfalfa (Medicago sativa L.)

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic polymorphism in plant genomes. SNP markers are valuable tools for genetic analysis of complex traits of agronomic importance, linkage and association mapping, genome-wide selection, map-based cloning, and marker-assisted selection. Current challenges for SNP genotyping in polyploid outcrossing species include multiple alleles per loci and lack of high-throughput methods suitable for variant detection. In this study, we report on a high-resolution melting (HRM) analysis system for SNP genotyping and mapping in outcrossing tetraploid genotypes. The sensitivity and utility of this technology is demonstrated by identification of the parental genotypes and segregating progeny in six alfalfa populations based on unique melting curve profiles due to differences in allelic composition at one or multiple loci. HRM using a 384-well format is a fast, consistent, and efficient approach for SNP discovery and genotyping, useful in polyploid species with uncharacterized genomes. Possible applications of this method include variation discovery, analysis of candidate genes, genotyping for comparative and association mapping, and integration of genome-wide selection in breeding programs.     

A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome

SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations - IBM (B73×Mo17) and LHRF (F2×F252) - were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.     

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.     

Evaluation of SNP Data from the Malus Infinium Array Identifies Challenges for Genetic Analysis of Complex Genomes of Polyploid Origin

High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the ‘Golden Delicious’ genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies.     

Construction of a SNP and SSR linkage map in autotetraploid blueberry using genotyping by sequencing

The construction of the first genetic map in autotetraploid blueberry has been made possible by the development of new SNP markers developed using genotyping by sequencing in a mapping population created from a cross between two key highbush blueberry cultivars, Draper × Jewel (Vaccinium corymbosum). The novel SNP markers were supplemented with existing SSR markers to enable the alignment of parental maps.  In total, 1794 single nucleotide polymorphic (SNP) markers and 233 simple sequence repeat (SSR) markers exhibited segregation patterns consistent with a random chromosomal segregation model for meiosis in an autotetraploid. Of these, 700 SNPs and 85 SSRs were utilized for construction of the ‘Draper’ genetic map, and 450 SNPs and 86 SSRs for the ‘Jewel’ map.  The ‘Draper’ map comprises 12  linkage groups (LG), associated with the haploid chromosome number for blueberry, and totals 1621 cM while the ‘Jewel’ map comprises 20 linkage groups totalling 1610 cM. Tentative alignments of the two parental maps have been made on the basis of shared SSR alleles and linkages to double-simplex markers segregating in both parents. Tentative alignments of the two parental maps have been made on the basis of shared SSR alleles and linkages to double-simplex markers segregating in both parents.     

Genotypic and phenotypic characterization of a large,diverse population of maize near‐isogenic lines

Genome‐wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near‐isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping‐by‐sequencing. Across traits, broad‐sense heritability (0.4–0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping‐by‐sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies.     

SNP Discovery and Linkage Map Construction in Cultivated Tomato

Few intraspecific genetic linkage maps have been reported for cultivated tomato, mainly because genetic diversity within Solanum lycopersicum is much less than that between tomato species. Single nucleotide polymorphisms (SNPs), the most abundant source of genomic variation, are the most promising source of polymorphisms for the construction of linkage maps for closely related intraspecific lines. In this study, we developed SNP markers based on expressed sequence tags for the construction of intraspecific linkage maps in tomato. Out of the 5607 SNP positions detected through in silico analysis, 1536 were selected for high-throughput genotyping of two mapping populations derived from crosses between ‘Micro-Tom’ and either ‘Ailsa Craig’ or ‘M82’. A total of 1137 markers, including 793 out of the 1338 successfully genotyped SNPs, along with 344 simple sequence repeat and intronic polymorphism markers, were mapped onto two linkage maps, which covered 1467.8 and 1422.7 cM, respectively. The SNP markers developed were then screened against cultivated tomato lines in order to estimate the transferability of these SNPs to other breeding materials. The molecular markers and linkage maps represent a milestone in the genomics and genetics, and are the first step toward molecular breeding of cultivated tomato. Information on the DNA markers, linkage maps, and SNP genotypes for these tomato lines is available at http://www.kazusa.or.jp/tomato/.     

Transcriptome sequencing to produce SNP-based genetic maps of onion

We used the Roche-454 platform to sequence from normalized cDNA libraries from each of two inbred lines of onion (OH1 and 5225). From approximately 1.6 million reads from each inbred, 27,065 and 33,254 cDNA contigs were assembled from OH1 and 5225, respectively. In total, 3,364 well supported single nucleotide polymorphisms (SNPs) on 1,716 cDNA contigs were identified between these two inbreds. One SNP on each of 1,256 contigs was randomly selected for genotyping. OH1 and 5225 were crossed and 182 gynogenic haploids extracted from hybrid plants were used for SNP mapping. A total of 597 SNPs segregated in the OH1 × 5225 haploid family and a genetic map of ten linkage groups (LOD ≥8) was constructed. Three hundred and thirty-nine of the newly identified SNPs were also mapped using a previously developed segregating family from BYG15-23 × AC43, and 223 common SNPs were used to join the two maps. Because these new SNPs are in expressed regions of the genome and commonly occur among onion germplasms, they will be useful for genetic mapping, gene tagging, marker-aided selection, quality control of seed lots, and fingerprinting of cultivars.     

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi‐parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre‐breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.     

Comparative LD mapping using single SNPs and haplotypes identifies QTL for plant height and biomass as secondary traits of drought tolerance in maize

Drought often delays developmental events so that plant height and above-ground biomass are reduced, resulting in yield loss due to inadequate photosynthate. In this study, plant height and biomass measured by the Normalized Difference Vegetation Index (NDVI) were used as criteria for drought tolerance. A total of 305 lines representing temperate, tropical and subtropical maize germplasm were genotyped using two single nucleotide polymorphism (SNP) chips each containing 1536 markers, from which 2052 informative SNPs and 386 haplotypes each constructed with two or more SNPs were used for linkage disequilibrium (LD) or association mapping. Single SNP- and haplotype-based LD mapping identified two significant SNPs and three haplotype loci [a total of four quantitative trait loci (QTL)] for plant height under well-watered and water-stressed conditions. For biomass, 32 SNPs and 12 haplotype loci (30 QTL) were identified using NDVIs measured at seven stages under the two water regimes. Some significant SNP and haplotype loci for NDVI were shared by different stages. Comparing significant loci identified by single SNP- and haplotype-based LD mapping, we found that six out of the 14 chromosomal regions defined by haplotype loci each included at least one significant SNP for the same trait. Significant SNP haplotype loci explained much higher phenotypic variation than individual SNPs. Moreover, we found that two significant SNPs (two QTL) and one haplotype locus were shared by plant height and NDVI. The results indicate the power of comparative LD mapping using single SNPs and SNP haplotypes with QTL shared by plant height and biomass as secondary traits for drought tolerance in maize.     

Single nucleotide polymorphism genotyping in polyploid wheat with the Illumina GoldenGate assay

Single nucleotide polymorphisms (SNPs) are indispensable in such applications as association mapping and construction of high-density genetic maps. These applications usually require genotyping of thousands of SNPs in a large number of individuals. Although a number of SNP genotyping assays are available, most of them are designed for SNP genotyping in diploid individuals. Here, we demonstrate that the Illumina GoldenGate assay could be used for SNP genotyping of homozygous tetraploid and hexaploid wheat lines. Genotyping reactions could be carried out directly on genomic DNA without the necessity of preliminary PCR amplification. A total of 53 tetraploid and 38 hexaploid homozygous wheat lines were genotyped at 96 SNP loci. The genotyping error rate estimated after removal of low-quality data was 0 and 1% for tetraploid and hexaploid wheat, respectively. Developed SNP genotyping assays were shown to be useful for genotyping wheat cultivars. This study demonstrated that the GoldenGate assay is a very efficient tool for high-throughput genotyping of polyploid wheat, opening new possibilities for the analysis of genetic variation in wheat and dissection of genetic basis of complex traits using association mapping approach. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

High-throughput genotyping and mapping of single nucleotide polymorphisms in loblolly pine (Pinus taeda L.)

The development and application of genomic tools to loblolly pine (Pinus taeda L.) offer promising insights into the organization and structure of conifer genomes. The application of a high-throughput genotyping assay across diverse forest tree species, however, is currently limited taxonomically. This is despite the ongoing development of genome-scale projects aiming at the construction of expressed sequence tag (EST) libraries and the resequencing of EST-derived unigenes for a diverse array of forest tree species. In this paper, we report on the application of Illumina’s high-throughput GoldenGate™ SNP genotyping assay to a loblolly pine mapping population. Single nucleotide polymorphisms (SNPs) were identified through resequencing of previously identified wood quality, drought tolerance, and disease resistance candidate genes prior to genotyping. From that effort, a 384 multiplexed SNP assay was developed for high-throughput genotyping. Approximately 67% of the 384 SNPs queried converted into high-quality genotypes for the 48 progeny samples. Of those 257 successfully genotyped SNPs, 70 were segregating within the mapping population. A total of 27 candidate genes were subsequently mapped onto the existing loblolly pine consensus map, which consists of 12 linkage groups spanning a total map distance of 1,227.6 cM. The ability of SNPs to be mapped to the same position as fragment-based markers previously developed within the same candidate genes, as well as the pivotal role that SNPs currently play in the dissection of complex phenotypic traits, illustrate the usefulness of high-throughput SNP genotyping technologies to the continued development of pine genomics. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A high-throughput SNuPE assay for genotyping SNPs in the flanking regions of Zea mays sequence tagged simple sequence repeats

Information on genetic relationships among individuals is of importanceto maize breeders for line and hybrid development. Estimates on the geneticsimilarity of breeding materials is best obtained using DNA markers. SingleNucleotide Polymorphisms and small insertions/deletions are both emerging as anew generation of markers, due to their abundance and amenability to fullyautomated genotyping. Application of SNPs, for example in genetic mappingprojects or breeding programs, involves the analysis of a large number ofsamples, and therefore requires rapid, inexpensive, and highly automatedmethodsto genotype the sequence variants. Towards this, we have applied a highthroughput Single Nucleotide Primer Extension assay to assess 23 polymorphicbase variations at five microsatellite loci in 22 inbred maize lines, as wellasin a mapping population of two of the inbred lines. Using a MegaBACE automatedgenotyper, we are able to assay more than 1248 (96 × 13) samples in asingle 75 minute run. The SNuPE method successfully genotyped the base pairvariations of interest in all maize lines. It was also found that primerscontaining polymorphisms themselves could be used to genotype the samples. Thistechnique allows the rapid production of valuable high throughput informationongenetic relationships among maize varieties. We further demonstrate the utilityof this method, using it to successfully map one of the microsatellite loci.     

Genomewide linkage searches for Mendelian disease loci can be efficiently conducted using high-density SNP genotyping arrays

Genomewide linkage searches aimed at identifying disease susceptibility loci are generally conducted using 300–400 microsatellite markers. Genotyping bi-allelic single nucleotide polymorphisms (SNPs) provides an alternative strategy. The availability of dense SNP maps coupled with recent technological developments in highly paralleled SNP genotyping makes it practical to now consider the use of these markers for whole-genome genetic linkage analyses. Here, we report the findings from three successful genomewide linkage analyses of families segregating autosomal recessively inherited neonatal diabetes, craniosynostosis and dominantly inherited renal dysplasia using the Affymetrix 10K SNP array. A single locus was identified for each disease state, two of which are novel. The performance of the SNP array, both in terms of efficiency and precision, indicates that such platforms will become the dominant technology for performing genomewide linkage searches.     

Construction of dense linkage maps “on the fly” using early generation wheat breeding populations

In plant species, construction of framework linkage maps to facilitate quantitative trait loci mapping and molecular breeding has been confined to experimental mapping populations. However, development and evaluation of these populations is detached from breeding efforts for cultivar development. In this study, we demonstrate that dense and reliable linkage maps can be constructed using extant breeding populations derived from a large number of crosses, thus eliminating the need for extraneous population development. Using 565 segregating F₁ progeny from 28 four-way cross breeding populations, a linkage map of the hexaploid wheat genome consisting of 3,785 single nucleotide polymorphism (SNP) loci and 22 simple sequence repeat loci was developed. Map estimation was facilitated by application of mapping algorithms for general pedigrees implemented in the software package CRI-MAP. The developed linkage maps showed high rank-order concordance with a SNP consensus map developed from seven mapping studies. Therefore, the linkage mapping methodology presented here represents a resource efficient approach for plant breeding programs that enables development of dense linkage maps “on the fly” to support molecular breeding efforts.     

Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (<Emphasis Type="Italic">Elaeis guineensis</Emphasis> Jacq.)

The identification of quantitative trait loci (QTLs) based on anchor markers, especially candidate genes that control a trait of interest, has been noted to increase the power of QTL detection. Since these markers can be scored as co-dominant data, they are also valuable for comparing and integrating the QTL linkage maps from diverse mapping populations. To estimate the position and effects of QTLs linked to oil yield traits in African oil palm, co-dominant microsatellites (SSR) and candidate gene-based sequence polymorphisms were applied to construct a linkage map for a progeny showing large differences in oil yield components. The progeny was genotyped for 97 SSR markers, 93 gene-linked markers, and 12 non-gene-linked SNP markers. From these, 190 segregating loci could be arranged into 31 linkage groups while 12 markers remained unmapped. Using the single marker linkage, interval mapping and multiple QTL methods, 16 putative QTLs on seven linkage groups affecting important oil yield related traits such as fresh fruit bunch yield (FFB), ratio of oil per fruit (OF), oil per bunch (OB), fruit per bunch (FB) and wet mesocarp per fruit (WMF) could be identified in the segregating population with estimated values for explained variance ranging from 12.4 % to 54.5 %. Markers designed from some candidate genes involved in lipid biosynthesis were found to be mapped near significant QTLs for various economic yield traits. Associations between QTLs and potential candidate genes are discussed.     

A Preliminary Genetic Linkage Map of the Pacific Abalone Haliotis discus hannai Ino

Preliminary genetic linkage maps were constructed for the Pacific abalone (Haliotis discus hannai Ino) using amplified fragment length polymorphism (AFLP), randomly amplified polymorphic DNA (RAPD), and microsatellite markers segregating in a F₁ family. Nine microsatellite loci, 41 RAPD, and 2688 AFLP markers were genotyped in the parents and 86 progeny of the mapping family. Among the 2738 markers, 384 (including 365 AFLP markers, 10 RAPD markers, and 9 microsatellite loci) were polymorphic and segregated in one or both parents: 241 in the female and 146 in the male. The majority of these markers, 232 in the female and 134 in the male, segregated according to the expected 1:1 Mendelian ratio (α = 0.05). Two genetic linkage maps were constructed using markers segregating in the female or the male parent. The female framework map consisted of 119 markers in 22 linkage groups, covering 1773.6 cM with an average intermarker space of 18.3 cM. The male framework map contained 94 markers in 19 linkage groups, spanning 1365.9 cM with an average intermarker space of 18.2 cM. The sex determination locus was mapped to the male map but not to the female map, suggesting a XY-male determination mechanism. Distorted markers showing excess of homozygotes were mapped in clusters, probably because of their linkage to a gene that is incompatible between two parental populations.     

Genetic design and statistical power of nested association mapping in maize

We investigated the genetic and statistical properties of the nested association mapping (NAM) design currently being implemented in maize (26 diverse founders and 5000 distinct immortal genotypes) to dissect the genetic basis of complex quantitative traits. The NAM design simultaneously exploits the advantages of both linkage analysis and association mapping. We demonstrated the power of NAM for high-power cost-effective genome scans through computer simulations based on empirical marker data and simulated traits with different complexities. With common-parent-specific (CPS) markers genotyped for the founders and the progenies, the inheritance of chromosome segments nested within two adjacent CPS markers was inferred through linkage. Genotyping the founders with additional high-density markers enabled the projection of genetic information, capturing linkage disequilibrium information, from founders to progenies. With 5000 genotypes, 30-79% of the simulated quantitative trait loci (QTL) were precisely identified. By integrating genetic design, natural diversity, and genomics technologies, this new complex trait dissection strategy should greatly facilitate endeavors to link molecular variation with phenotypic variation for various complex traits.     

Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n?=?222 samples) and lettuce (n?=?87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike.