Rapid SNP Discovery and a RAD-Based High-Density Linkage Map in Jujube (Ziziphus Mill.)

Background

Ziziphus Mill. (jujube), the most valued genus of Rhamnaceae, comprises of a number of economically and ecologically important species such as Z. jujuba Mill., Z. acidojujuba Cheng et Liu and Z. mauritiana Lam. Single nucleotide polymorphism (SNP) markers and a high-density genetic map are of great benefit to the improvement of the crop, mapping quantitative trait loci (QTL) and analyzing genome structure. However, such a high-density map is still absent in the genus Ziziphus and even the family Rhamnaceae. The recently developed restriction-site associated DNA (RAD) marker has been proven to be most powerful in genetic map construction. The objective of this study was to construct a high-density linkage map using the RAD tags generated by next generation sequencing.

Results

An interspecific F1 population and their parents (Z. jujuba Mill. ‘JMS2’ × Z. acidojujuba Cheng et Liu ‘Xing 16’) were genotyped using a mapping-by-sequencing approach, to generate RAD-based SNP markers. A total of 42,784 putative high quality SNPs were identified between the parents and 2,872 high-quality RAD markers were grouped in genetic maps. Of the 2,872 RAD markers, 1,307 were linked to the female genetic map, 1,336 to the male map, and 2,748 to the integrated map spanning 913.87 centi-morgans (cM) with an average marker interval of 0.34 cM. The integrated map contained 12 linkage groups (LGs), consistent with the haploid chromosome number of the two parents.

Conclusion

We first generated a high-density genetic linkage map with 2,748 RAD markers for jujube and a large number of SNPs were also developed. It provides a useful tool for both marker-assisted breeding and a variety of genome investigations in jujube, such as sequence assembly, gene localization, QTL detection and genome structure comparison.     

Molecular Mapping of Restriction-Site Associated DNA Markers in Allotetraploid Upland Cotton

Upland cotton (Gossypium hirsutum L., 2n = 52, AADD) is an allotetraploid, therefore the discovery of single nucleotide polymorphism (SNP) markers is difficult. The recent emergence of genome complexity reduction technologies based on the next-generation sequencing (NGS) platform has greatly expedited SNP discovery in crops with highly repetitive and complex genomes. Here we applied restriction-site associated DNA (RAD) sequencing technology for de novo SNP discovery in allotetraploid cotton. We identified 21,109 SNPs between the two parents and used these for genotyping of 161 recombinant inbred lines (RILs). Finally, a high dense linkage map comprising 4,153 loci over 3500-cM was developed based on the previous result. Using this map quantitative trait locus (QTLs) conferring fiber strength and Verticillium Wilt (VW) resistance were mapped to a more accurate region in comparison to the 1576-cM interval determined using the simple sequence repeat (SSR) genetic map. This suggests that the newly constructed map has more power and resolution than the previous SSR map. It will pave the way for the rapid identification of the marker-assisted selection in cotton breeding and cloning of QTL of interest traits.     

A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map.     

Understanding genetic variation and function- the applications of next generation sequencing

Next generation sequencing (NGS) technology has had a transformatory effect upon population-level studies linking genetic variation to gene function. In this review, I briefly describe recent studies that have used top-down genome scanning and population genetic approaches to identify loci under recent selection, as well as some examples of how large NGS datasets can be deployed to detect the total level of deleterious, neutral and advantageous variation present in standing genetic variation. I then explore studies that have used some of these approaches to study gene function along with advances in sequencing populations under selection, QTL mapping techniques and emerging methodologies utilising targeted capture and NGS.     

Sequence‐based SNP genotyping in durum wheat

Marker development for marker‐assisted selection in plant breeding is increasingly based on next‐generation sequencing (NGS). However, marker development in crops with highly repetitive, complex genomes is still challenging. Here we applied sequence‐based genotyping (SBG), which couples AFLP^®‐based complexity reduction to NGS, for de novo single nucleotide polymorphisms (SNP) marker discovery in and genotyping of a biparental durum wheat population. We identified 9983 putative SNPs in 6372 contigs between the two parents and used these SNPs for genotyping 91 recombinant inbred lines (RILs). Excluding redundant information from multiple SNPs per contig, 2606 (41%) markers were used for integration in a pre‐existing framework map, resulting in the integration of 2365 markers over 2607 cM. Of the 2606 markers available for mapping, 91% were integrated in the pre‐existing map, containing 708 SSRs, DArT markers, and SNPs from CRoPS technology, with a map‐size increase of 492 cM (23%). These results demonstrate the high quality of the discovered SNP markers. With this methodology, it was possible to saturate the map at a final marker density of 0.8 cM/marker. Looking at the binned marker distribution (Figure 2), 63 of the 268 10‐cM bins contained only SBG markers, showing that these markers are filling in gaps in the framework map. As to the markers that could not be used for mapping, the main reason was the low sequencing coverage used for genotyping. We conclude that SBG is a valuable tool for efficient, high‐throughput and high‐quality marker discovery and genotyping for complex genomes such as that of durum wheat.     

Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max

Background

Quantitative trait locus (QTL) mapping is an efficient approach to discover the genetic architecture underlying complex quantitative traits. However, the low density of molecular markers in genetic maps has limited the efficiency and accuracy of QTL mapping. In this study, specific length amplified fragment sequencing (SLAF-seq), a new high-throughput strategy for large-scale SNP discovery and genotyping based on next generation sequencing (NGS), was employed to construct a high-density soybean genetic map using recombinant inbred lines (RILs, Luheidou2 × Nanhuizao, F_5:8). With this map, the consistent QTLs for isoflavone content across various environments were identified.

Results

In total, 23 Gb of data containing 87,604,858 pair-end reads were obtained. The average coverage for each SLAF marker was 11.20-fold for the female parent, 12.51-fold for the male parent, and an average of 3.98-fold for individual RILs. Among the 116,216 high-quality SLAFs obtained, 9,948 were polymorphic. The final map consisted of 5,785 SLAFs on 20 linkage groups (LGs) and spanned 2,255.18 cM in genome size with an average distance of 0.43 cM between adjacent markers. Comparative genomic analysis revealed a relatively high collinearity of 20 LGs with the soybean reference genome. Based on this map, 41 QTLs were identified that contributed to the isoflavone content. The high efficiency and accuracy of this map were evidenced by the discovery of genes encoding isoflavone biosynthetic enzymes within these loci. Moreover, 11 of these 41 QTLs (including six novel loci) were associated with isoflavone content across multiple environments. One of them, qIF20-2, contributed to a majority of isoflavone components across various environments and explained a high amount of phenotypic variance (8.7% - 35.3%). This represents a novel major QTL underlying isoflavone content across various environments in soybean.

Conclusions

Herein, we reported a high-density genetic map for soybean. This map exhibited high resolution and accuracy. It will facilitate the identification of genes and QTLs underlying essential agronomic traits in soybean. The novel major QTL for isoflavone content is useful not only for further study on the genetic basis of isoflavone accumulation, but also for marker-assisted selection (MAS) in soybean breeding in the future.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1086) contains supplementary material, which is available to authorized users.     

Estimation of population allele frequencies from next‐generation sequencing data: pool‐versus individual‐based genotyping

Molecular markers produced by next‐generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual‐based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user‐friendly application assessing the accuracy of allele frequency estimation from both pool‐ and individual‐based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site–associated DNA (RAD) sequencing in pool‐ and individual‐based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost‐effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome‐wide patterns of genetic variation for large numbers of individuals in multiple populations.     

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

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

Construction of High-Density Linkage Maps of Populus deltoides × P. simonii Using Restriction-Site Associated DNA Sequencing

Although numerous linkage maps have been constructed in the genus Populus, they are typically sparse and thus have limited applications due to low throughput of traditional molecular markers. Restriction-site associated DNA sequencing (RADSeq) technology allows us to identify a large number of single nucleotide polymorphisms (SNP) across genomes of many individuals in a fast and cost-effective way, and makes it possible to construct high-density genetic linkage maps. We performed RADSeq for 299 progeny and their two parents in an F₁ hybrid population generated by crossing the female Populus deltoides ‘I-69’ and male Populus simonii ‘L3’. A total of 2,545 high quality SNP markers were obtained and two parent-specific linkage maps were constructed. The female genetic map contained 1601 SNPs and 20 linkage groups, spanning 4,249.12 cM of the genome with an average distance of 2.69 cM between adjacent markers, while the male map consisted of 940 SNPs and also 20 linkage groups with a total length of 3,816.24 cM and an average marker interval distance of 4.15 cM. Finally, our analysis revealed that synteny and collinearity are highly conserved between the parental linkage maps and the reference genome of P. trichocarpa. We demonstrated that RAD sequencing is a powerful technique capable of rapidly generating a large number of SNPs for constructing genetic maps in outbred forest trees. The high-quality linkage maps constructed here provided reliable genetic resources to facilitate locating quantitative trait loci (QTLs) that control growth and wood quality traits in the hybrid population.     

Reference-free SNP calling: improved accuracy by preventing incorrect calls from repetitive genomic regions

ABSTRACT: BACKGROUND: Single nucleotide polymorphisms (SNPs) are the most abundant type of genetic variation in eukaryotic genomes and have recently become the marker of choice in a wide variety of ecological and evolutionary studies. The advent of next-generation sequencing (NGS) technologies has made it possible to efficiently genotype a large number of SNPs in the non-model organisms with no or limited genomic resources. Most NGS-based genotyping methods require a reference genome to perform accurate SNP calling. Little effort, however, has yet been devoted to developing or improving algorithms for accurate SNP calling in the absence of a reference genome. RESULTS: Here we describe an improved maximum likelihood (ML) algorithm called iML, which can achieve high genotyping accuracy for SNP calling in the non-model organisms without a reference genome. The iML algorithm incorporates the mixed Poisson/normal model to detect composite read clusters and can efficiently prevent incorrect SNP calls resulting from repetitive genomic regions. Through analysis of simulation and real sequencing datasets, we demonstrate that in comparison with ML or a threshold approach, iML can remarkably improve the accuracy of de novo SNP genotyping and is especially powerful for the reference-free genotyping in diploid genomes with high repeat contents. CONCLUSIONS: The iML algorithm can efficiently prevent incorrect SNP calls resulting from repetitive genomic regions, and thus outperforms the original ML algorithm by achieving much higher genotyping accuracy. Our algorithm is therefore very useful for accurate de novo SNP genotyping in the non-model organisms without a reference genome.     

Extending RAD tag analysis to microbial ecology: a comparison between MultiLocus Sequence Typing and 2b‐RAD to investigate Listeria monocytogenes genetic structure

The advent of next‐generation sequencing (NGS) has dramatically changed bacterial typing technologies, increasing our ability to differentiate bacterial isolates. Despite it is now possible to sequence a bacterial genome in a few days and at reasonable costs, most genetic analyses do not require whole‐genome sequencing, which also remains impractical for large population samples due to the cost of individual library preparation and bioinformatics. More traditional sequencing approaches, however, such as MultiLocus Sequence Typing (mlst ) are quite laborious and time‐consuming, especially for large‐scale analyses. In this study, a genotyping approach based on restriction site‐associated (RAD) tag sequencing, 2b‐RAD, was applied to characterize Listeria monocytogenes strains. To verify the feasibility of the method, an in silico analysis was performed on 30 available complete genomes. For the same set of strains, in silico mlst analysis was conducted as well. Subsequently, 2b‐RAD and mlst analyses were experimentally carried out on 58 isolates collected from food samples or food‐processing sites. The obtained results demonstrate that 2b‐RAD predicts mlst types and often provides more detailed information on population structure than mlst . Moreover, the majority of variants differentiating identical sequence type isolates mapped against accessory fragments, thus providing additional information to characterize strains. Although mlst still represents a reliable typing method, large‐scale studies on molecular epidemiology and public health, as well as bacterial phylogenetics, population genetics and biosafety could benefit of a low cost and fast turnaround time approach such as the 2b‐RAD analysis proposed here.     

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.     

Development of microsatellite genetic markers in Siberian stone pine (<Emphasis Type="Italic">Pinus sibirica</Emphasis> Du Tour) based on the <Emphasis Type="Italic">de novo</Emphasis> whole genome sequencing

Siberian stone pine, Pinus sibirica Du Tour is one of the most economically and environmentally important forest-forming species of conifers in Russia. To study these forests a large number of highly polymorphic molecular genetic markers, such as microsatellite loci, are required. Prior to the new high-throughput next generation sequencing (NGS) methods, discovery of microsatellite loci and development of micro-satellite markers were very time consuming and laborious. The recently developed draft assembly of the Siberian stone pine genome, sequenced using the NGS methods, allowed us to identify a large number of microsatellite loci in the Siberian stone pine genome and to develop species-specific PCR primers for amplification and genotyping of 70 microsatellite loci. The primers were designed using contigs containing short simple sequence tandem repeats from the Siberian stone pine whole genome draft assembly. Based on the testing of primers for 70 microsatellite loci with tri-, tetra- or pentanucleotide repeats, 18 most promising, reliable and polymorphic loci were selected that can be used further as molecular genetic markers in population genetic studies of Siberian stone pine.     

Genotyping by Genome Reducing and Sequencing for Outbred Animals

Next-generation sequencing (NGS) approaches are widely used in genome-wide genetic marker discovery and genotyping. However, current NGS approaches are not easy to apply to general outbred populations (human and some major farm animals) for SNP identification because of the high level of heterogeneity and phase ambiguity in the haplotype. Here, we reported a new method for SNP genotyping, called genotyping by genome reducing and sequencing (GGRS) to genotype outbred species. Through an improved procedure for library preparation and a marker discovery and genotyping pipeline, the GGRS approach can genotype outbred species cost-effectively and high-reproducibly. We also evaluated the efficiency and accuracy of our approach for high-density SNP discovery and genotyping in a large genome pig species (2.8 Gb), for which more than 70,000 single nucleotide polymorphisms (SNPs) can be identified for an expenditure of only $80 (USD)/sample.     

New generation pharmacogenomic tools: a SNP linkage disequilibrium Map,validated SNP assay resource,and high-throughput instrumentation system for large-scale genetic studies

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.     

Enrichment of an intraspecific genetic map of upland cotton by developing markers using parental RAD sequencing

RAD sequencing was performed using DH962 and Jimian5 as upland cotton mapping parents. Sequencing data for DH962 and Jimian5 were assembled into the genome sequences of ≈55.27 and ≈57.06 Mb, respectively. Analysing genome sequences of the two parents, 1,323 SSR, 3,838 insertion/deletion (InDel), and 9,366 single-nucleotide polymorphism (SNP) primer pairs were developed. All of the SSRs, 121 InDels, 441 SNPs, and other 6,747 primer pairs were screened in the two parents, and a total of 535 new polymorphic loci were identified. A genetic map including 1,013 loci was constructed using these results and 506 loci previously published for this population. Twenty-seven new QTLs for yield and fibre quality were identified, indicating that the efficiency of QTL detection was greatly improved by the increase in map density. Comparative genomics showed there to be considerable homology and collinearity between the A_T and A₂ genomes and between the D_T and D₅ genomes, although there were a few exchanges and introgressions among the chromosomes of the A₂ genome. Here, the development of markers using parental RAD sequencing was effective, and a high-density intraspecific genetic map was constructed. This map can be used for molecular marker-assisted selection in cotton.     

Construction of a high-density genetic map of <Emphasis Type="Italic">Ziziphus jujuba</Emphasis> Mill. using genotyping by sequencing technology

The Chinese jujube (Ziziphus jujuba Mill., 2n = 2 × = 24), one of the most popular fruit trees in China, is widely cultivated and utilized in Asia. High-density genetic linkage maps are valuable resources for molecular breeding and functional genomics; however, they are still under-developed for the jujube. The genotyping by sequencing (GBS) strategy could be an efficient and cost-effective tool for single nucleotide polymorphism (SNP) discovery based on the sequenced jujube genome. Here, we report a new high-density genetic map constructed using GBS technology. An F1 population with 145 progenies and their parents (‘Dongzao’ × ‘Zhongningyuanzao’) were sequenced on the Illumina HiSeq 4000 platform. In total, 79.8 Gb of raw data containing 256,708,177 paired-end reads were generated. After data filtering and SNP genotyping, 40,372 polymorphic SNP markers were developed between the parents and 2540 (1756 non-redundant) markers were mapped onto the integrated genetic linkage map. The map spanned 1456.53 cM and was distributed among 12 linkage groups, which is consistent with the haploid chromosome number of the jujube. The average marker interval was 0.88 cM. The genetic map allowed us to anchor 224 Mb (63.7 %) of scaffolds from the sequenced ‘Junzao’ genome, containing 52 newly anchored scaffolds, which extended the genome assembly by 7 Mb. In conclusion, GBS technology was applied efficiently for SNP discovery in this study. The high-density genetic map will serve as a unique tool for molecular-assisted breeding and genomic studies, which will contribute to further research and improvement of the jujube in the near future.     

A Multi-Population Consensus Genetic Map Reveals Inconsistent Marker Order among Maps Likely Attributed to Structural Variations in the Apple Genome

Genetic maps serve as frameworks for determining the genetic architecture of quantitative traits, assessing structure of a genome, as well as aid in pursuing association mapping and comparative genetic studies. In this study, a dense genetic map was constructed using a high-throughput 1,536 EST-derived SNP GoldenGate genotyping platform and a global consensus map established by combining the new genetic map with four existing reliable genetic maps of apple. The consensus map identified markers with both major and minor conflicts in positioning across all five maps. These major inconsistencies among marker positions were attributed either to structural variations within the apple genome, or among mapping populations, or genotyping technical errors. These also highlighted problems in assembly and anchorage of the reference draft apple genome sequence in regions with known segmental duplications. Markers common across all five apple genetic maps resulted in successful positioning of 2875 markers, consisting of 2033 SNPs and 843 SSRs as well as other specific markers, on the global consensus map. These markers were distributed across all 17 linkage groups, with an average of 169±33 marker per linkage group and with an average distance of 0.70±0.14 cM between markers. The total length of the consensus map was 1991.38 cM with an average length of 117.14±24.43 cM per linkage group. A total of 569 SNPs were mapped onto the genetic map, consisting of 140 recombinant individuals, from our recently developed apple Oligonucleotide pool assays (OPA). The new functional SNPs, along with the dense consensus genetic map, will be useful for high resolution QTL mapping of important traits in apple and for pursuing comparative genetic studies in Rosaceae.