SNP discovery by amplicon sequencing and multiplex SNP genotyping in the allopolyploid species Brassica napus

Systems biology approach: identification of hub genes, signaling pathways, and molecular docking of COL1A1 gene in cervical insufficiency

The collagen type I alpha 1 (COL1A1, OMIM #120,150) gene, encoding the alpha-1 chain of type I collagen (UniProt #P02452), plays a key role in life-homeostasis due to its remarkable involvement in collagen synthesis. It is a promising candidate gene implicated in the pathogenesis of cervical insufficiency (CI). This study aimed to identify genetic variations within the COL1A1 gene that contribute to the development of CI. Polymerase chain reaction (PCR) and amplicon sequencing were implemented for single nucleotide polymorphisms (SNPs) detection (+ 1245G/T, SP1 rs1800012), which revealed wild-type sequence for targeted SNPs in enrolled proband indicated negative results regarding COL1A1 gene involvement for current form of CI. It allows further investigation of other closely connected genes probed in this study. Computational approaches viz. Protein-protein interaction (PPI), gene ontology (GO), and pathway participation were used to identify the crucial hub genes and signaling pathways for COL1A1 and CI. Using the Yet Another Scientific Artificial Reality Application (YASARA) software, molecular docking, and molecular dynamic (MD) simulation with the oxytocin (CID 439,302), estradiol (CID 129,728,744), progesterone (CID 5994) and hydroxyprogesterone (CID 150,788) were done. Interactive bioinformatics analysis demonstrated that the COL1A1 and more than 10 collagen sister genes had a strong connection with CI. In sum, the findings of this study provide insights into a modus operandi that can be utilized to illuminate the path toward studying sister genes and smooth diagnosis of CI. These findings have implications for understanding the foundational process of the condition and potentially developing screening, diagnostic, and therapeutic interventions.

Graphical Abstract

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.)

BACKGROUND

Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2).

METHODS AND RESULTS

The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait.

CONCLUSION

Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Mining Grapevine Downy Mildew Susceptibility Genes: A Resource for Genomics-Based Breeding and Tailored Gene Editing

Several pathogens continuously threaten viticulture worldwide. Until now, the investigation on resistance loci has been the main trend to understand the interaction between grapevine and the mildew causal agents. Dominantly inherited gene-based resistance has shown to be race-specific in some cases, to confer partial immunity, and to be potentially overcome within a few years since its introgression. Recently, on the footprint of research conducted in Arabidopsis, putative genes associated with downy mildew susceptibility have been discovered also in the grapevine genome. In this work, we deep-sequenced four putative susceptibility genes-namely VvDMR6.1, VvDMR6.2, VvDLO1, VvDLO2-in 190 genetically diverse grapevine genotypes to discover new sources of broad-spectrum and recessively inherited resistance. Identified Single Nucleotide Polymorphisms were screened in a bottleneck analysis from the genetic sequence to their impact on protein structure. Fifty-five genotypes showed at least one impacting mutation in one or more of the scouted genes. Haplotypes were inferred for each gene and two of them at the VvDMR6.2 gene were found significantly more represented in downy mildew resistant genotypes. The current results provide a resource for grapevine and plant genetics and could corroborate genomic-assisted breeding programs as well as tailored gene editing approaches for resistance to biotic stresses.

Risk factors for recurrence of Helicobacter pylori infection after successful eradication in Chinese children: A prospective, nested case-control study

BACKGROUND

Limited research has been published on the recurrence of Helicobacter pylori infection and risk factors in Chinese children. Our study aimed to identify risk factors for Helicobacter pylori infection recurrence after successful eradication in children.

MATERIALS AND METHODS

A prospective, nested case-control study was performed. A cohort of 230 children with successful eradication of Helicobacter pylori in Baoding (China) was selected from January 2018 to February 2019. A standardized questionnaire was used to obtain socioeconomic details. Eradication regimens and Helicobacter pylori antibiotic susceptibility testing results were also recorded. Interleukin-1β level, interferon-γ level, and genetic susceptibility (IFNGR1 and PTPRZ1 gene polymorphisms) were analyzed. All children were followed for 1 year.

RESULTS

Among 218 (94.8%) children who were successfully followed, 41 children (18.8%) had a Helicobacter pylori infection recurrence. The recurrence rate was higher in children ≤10 years old than >10 years old (22.8% vs 7.1%, P = .01). There was no significant difference between the recurrence group and the non-recurrence group in terms of types of therapy and antibiotic sensitivity (P > .05). Multivariable regression results indicated that residence in urban areas, higher household income, and having lunch at home were significantly protective against recurrence (OR 0.155, 0.408, and 0.351 respectively), whereas Helicobacter pylori infection in family members increased the risk of recurrence (OR 2.283). The levels of IL-1β and IFN-γ exhibited no significant difference between the recurrence group and the non-recurrence group. The allele frequency of G in the IFNGR1-56 site, A in the IFNGR1-600 site, and T in the IFNGR1-565 site was significantly higher in the recurrence group when compared to the non-recurrence group (P < .05).

CONCLUSIONS

The Helicobacter pylori infection recurrence rate is high in children in Baoding region and is closely correlated to socioeconomic factors. The IFNGR1 gene polymorphism may be an independent risk factor for Helicobacter pylori infection recurrence.

Insights on SNP types, detection methods and their utilization in Brassica species: Recent progress and future perspectives

The genus Brassica, family Brassicaceae (Cruciferae), comprises many important species of oil crops, vegetables and medicinal plants including B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, B. carinata. Genomic researches in Brassica species is constrained by polyploidization, mainly due to its complicated genomic structure. However, rapid development of methods for detecting single nucleotide polymorphisms (SNP), such as next generation sequencing and SNP microarray, has accelerated release of reference Brassica species genomes as well as discovery of large numbers and genome-wide SNPs, thus intensifying forward genetics in this genus. In this review, we summarize biological characteristics, classification and various methods for detecting SNPs, focusing on high-throughput techniques. Moreover, we describe the pivotal roles of SNPs in genetic diversity, linkage map construction and QTL mapping, comparative genomics, linkage disequilibrium and genome-wide association studies. These insights are expected to deepen our understanding and guide further advancements in Brassica species research.

Assessment of low-coverage nanopore long read sequencing for SNP genotyping in doubled haploid canola (Brassica napus L.)

Despite the high accuracy of short read sequencing (SRS), there are still issues with attaining accurate single nucleotide polymorphism (SNP) genotypes at low sequencing coverage and in highly duplicated genomes due to misalignment. Long read sequencing (LRS) systems, including the Oxford Nanopore Technologies (ONT) minION, have become popular options for de novo genome assembly and structural variant characterisation. The current high error rate often requires substantial post-sequencing correction and would appear to prevent the adoption of this system for SNP genotyping, but nanopore sequencing errors are largely random. Using low coverage ONT minION sequencing for genotyping of pre-validated SNP loci was examined in 9 canola doubled haploids. The minION genotypes were compared to the Illumina sequences to determine the extent and nature of genotype discrepancies between the two systems. The significant increase in read length improved alignment to the genome and the absence of classical SRS biases results in a more even representation of the genome. Sequencing errors are present, primarily in the form of heterozygous genotypes, which can be removed in completely homozygous backgrounds but requires more advanced bioinformatics in heterozygous genomes. Developments in this technology are promising for routine genotyping in the future.

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High-throughput SNP arrays, or 'SNP chips', can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb (http://snpdb.appliedbioinformatics.com.au), a database for SNP array data produced by the Illumina Infinium™ hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop-breeding activities.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

Identification of Polymorphisms Associated with Drought Adaptation QTL in Brassica napus by Resequencing

Brassica napus is a globally important oilseed for which little is known about the genetics of drought adaptation. We previously mapped twelve quantitative trait loci (QTL) underlying drought-related traits in a biparental mapping population created from a cross between winter and spring B. napus cultivars. Here we resequence the genomes of the mapping population parents to identify genetic diversity across the genome and within QTL regions. We sequenced each parental cultivar on the Illumina HiSeq platform to a minimum depth of 23 × and performed a reference based assembly in order to describe the molecular variation differentiating them at the scale of the genome, QTL and gene. Genome-wide patterns of variation were characterized by an overall higher single nucleotide polymorphism (SNP) density in the A genome and a higher ratio of nonsynonymous to synonymous substitutions in the C genome. Nonsynonymous substitutions were used to categorize gene ontology terms differentiating the parent genomes along with a list of putative functional variants contained within each QTL. Marker assays were developed for several of the discovered polymorphisms within a pleiotropic QTL on chromosome A10. QTL analysis with the new, denser map showed the most associated marker to be that developed from an insertion/deletion polymorphism located in the candidate gene Bna.FLC.A10, and it was the only candidate within the QTL interval with observed polymorphism. Together, these results provide a glimpse of genome-wide variation differentiating annual and biennial B. napus ecotypes as well as a better understanding of the genetic basis of root and drought phenotypes.

Allelic Variation of BnaC.TT2.a and Its Association with Seed Coat Color and Fatty Acids in Rapeseed (Brassica napus L.)

Efficient molecular markers for the selection of rapeseed genetic materials with high seed oil content and ideal fatty acid (FA) composition are preferred by rapeseed breeders. Recently, we reported the molecular mechanism of TRANSPARENT TESTA 2 (TT2) in inhibiting seed FA biosynthesis in Arabidopsis. However, evidence showing the association of rapeseed TT2 homologs and seed FA production are still insufficient. In this study, we collected 83 rapeseed (Brassica napus L.) landraces from different geographical backgrounds to conduct association mapping of BnaC.TT2.a in relation to seed coat color and FA biosynthesis. Population background was corrected by 84 pairs of SSR markers that were uniformly distributed among the linkage groups of the Tapidor-Ningyou-7 DH population. A single copy of BnaC.TT2.a for single nucleotide polymorphism (SNP) assay was cloned by a pair of previously reported specific primers. From the analysis of BnaC.TT2.a allelic variations using GLM+Q model, four SNPs on intron 1 of BnaC.TT2.a that were associated with seed FA were discovered. Moreover, an InDel at position 738 on exon 3 of BnaC.TT2.a indicated a change of protein function that was significantly associated with seed coat color, linoleic acid (C18:2), and total FA content. These findings revealed the role of BnaC.TT2.a in regulating the seed color formation and seed FA biosynthesis in rapeseed, thereby suggesting effective molecular markers for rapeseed breeding.

Diversity Arrays Technology (DArT) Marker Platforms for Diversity Analysis and Linkage Mapping in a Complex Crop, the Octoploid Cultivated Strawberry (Fragaria × ananassa)

Cultivated strawberry (Fragaria × ananassa) is a genetically complex allo-octoploid crop with 28 pairs of chromosomes (2n = 8x = 56) for which a genome sequence is not yet available. The diploid Fragaria vesca is considered the donor species of one of the octoploid sub-genomes and its available genome sequence can be used as a reference for genomic studies. A wide number of strawberry cultivars are stored in ex situ germplasm collections world-wide but a number of previous studies have addressed the genetic diversity present within a limited number of these collections. Here, we report the development and application of two platforms based on the implementation of Diversity Array Technology (DArT) markers for high-throughput genotyping in strawberry. The first DArT microarray was used to evaluate the genetic diversity of 62 strawberry cultivars that represent a wide range of variation based on phenotype, geographical and temporal origin and pedigrees. A total of 603 DArT markers were used to evaluate the diversity and structure of the population and their cluster analyses revealed that these markers were highly efficient in classifying the accessions in groups based on historical, geographical and pedigree-based cues. The second DArTseq platform took benefit of the complexity reduction method optimized for strawberry and the development of next generation sequencing technologies. The strawberry DArTseq was used to generate a total of 9,386 SNP markers in the previously developed ‘232’ × ‘1392’ mapping population, of which, 4,242 high quality markers were further selected to saturate this map after several filtering steps. The high-throughput platforms here developed for genotyping strawberry will facilitate genome-wide characterizations of large accessions sets and complement other available options.

A bi-filtering method for processing single nucleotide polymorphism array data improves the quality of genetic map and accuracy of quantitative trait locus mapping in doubled haploid populations of polyploid Brassica napus

Background

Single nucleotide polymorphism (SNP) markers have a wide range of applications in crop genetics and genomics. Due to their polyploidy nature, many important crops, such as wheat, cotton and rapeseed contain a large amount of repeat and homoeologous sequences in their genomes, which imposes a huge challenge in high-throughput genotyping with sequencing and/or array technologies. Allotetraploid Brassica napus (AACC, 2n = 4x = 38) comprises of two highly homoeologous sub-genomes derived from its progenitor species B. rapa (AA, 2n = 2x = 20) and B. oleracea (CC, 2n = 2x = 18), and is an ideal species to exploit methods for reducing the interference of extensive inter-homoeologue polymorphisms (mHemi-SNPs and Pseudo-simple SNPs) between closely related sub-genomes.

Results

Based on a recent B. napus 6K SNP array, we developed a bi-filtering procedure to identify unauthentic lines in a DH population, and mHemi-SNPs and Pseudo-simple SNPs in an array data matrix. The procedure utilized both monomorphic and polymorphic SNPs in the DH population and could effectively distinguish the mHemi-SNPs and Pseudo-simple SNPs that resulted from superposition of the signals from multiple SNPs. Compared with conventional procedure for array data processing, the bi-filtering method could minimize the pseudo linkage relationship caused by the mHemi-SNPs and Pseudo-simple SNPs, thus improving the quality of SNP genetic map. Furthermore, the improved genetic map could increase the accuracies of mapping of QTLs as demonstrated by the ability to eliminate non-real QTLs in the mapping population.

Conclusions

The bi-filtering analysis of the SNP array data represents a novel approach to effectively assigning the multi-loci SNP genotypes in polyploid B. napus and may find wide applications to SNP analyses in polyploid crops.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1559-4) contains supplementary material, which is available to authorized users.

Spiked GBS: a unified, open platform for single marker genotyping and whole-genome profiling

Background

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of these objectives.

Results

We have developed spiked genotyping-by-sequencing (sGBS), which combines targeted amplicon sequencing with reduced representation genotyping-by-sequencing. To minimize the cost of targeted assays, we utilize a small percent of sequencing capacity available in runs of GBS libraries to “spike” amplified targets of a priori alleles tagged with a different set of unique barcodes. This open platform allows multiple, single-target loci to be assayed while simultaneously generating a whole-genome profile. This dual-genotyping approach allows different sets of samples to be evaluated for single markers or whole genome-profiling. Here, we report the application of sGBS on a winter wheat panel that was screened for converted KASP markers and newly-designed markers targeting known polymorphisms in the leaf rust resistance gene Lr34.

Conclusions

The flexibility and low-cost of sGBS will enable a range of applications across genetics research. Specifically in breeding applications, the sGBS approach will allow breeders to obtain a whole-genome profile of important individuals while simultaneously targeting specific genes for a range of selection strategies across the breeding program.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1404-9) contains supplementary material, which is available to authorized users.

Advances in plant genotyping: where the future will take us

Genetic diversity between individuals can be tracked and monitored using a range of molecular markers. These markers can detect variation ranging in scale from a single base pair up to duplications and translocations of entire chromosomal regions. The genotyping of individuals allows the detection of this variation and it has been successfully applied in plant science for many years. The increasing amounts of sequence data able to be generated using next-generation sequencing (NGS) technologies have produced a vast expansion in the rate of discovery of polymorphisms, with single nucleotide polymorphisms (SNPs) predominating as the marker of choice. This increase in polymorphic marker resources through efficient discovery, coupled with the utility of SNPs, has enabled the shift to high-throughput genotyping assays and these methods are reviewed and discussed here, alongside the recent innovations allowing increased throughput.

SNP markers-based map construction and genome-wide linkage analysis in Brassica napus

An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus.

A high-throughput SNP array in the amphidiploid species Brassica napus shows diversity in resistance genes

Single-nucleotide polymorphisms (SNPs)are molecular markers based on nucleotide variation and can be used for genotyping assays across populations and to track genomic inheritance. SNPs offer a comprehensive genotyping alternative to whole-genome sequencing for both agricultural and research purposes including molecular breeding and diagnostics, genome evolution and genetic diversity analyses, genetic mapping, and trait association studies. Here genomic SNPs were discovered between four cultivars of the important amphidiploid oilseed species Brassica napus and used to develop a B. napus Infinium™ array containing 5,306 SNPs randomly dispersed across the genome. Assay success was high, with >94 % of these producing a reproducible, polymorphic genotype in the 1,070 samples screened. Although the assay was designed to B. napus, successful SNP amplification was achieved in the B. napus progenitor species, Brassica rapa and Brassica oleracea, and to a lesser extent in the related species Brassica nigra. Phylogenetic analysis was consistent with the expected relationships between B. napus individuals. This study presents an efficient custom SNP assay development pipeline in the complex polyploid Brassica genome and demonstrates the utility of the array for high-throughput genotyping in a number of related Brassica species. It also demonstrates the utility of this assay in genotyping resistance genes on chromosome A7, which segregate amongst the 1,070 samples.

Intergenomic single nucleotide polymorphisms as a tool for bacterial artificial chromosome contig building of homoeologous Brassica napus regions

BACKGROUND

Homoeologous sequences pose a particular challenge if bacterial artificial chromosome (BAC) contigs shall be established for specific regions of an allopolyploid genome. Single nucleotide polymorphisms (SNPs) differentiating between homoeologous genomes (intergenomic SNPs) may represent a suitable screening tool for such purposes, since they do not only identify homoeologous sequences but also differentiate between them.

RESULTS

Sequence alignments between Brassica rapa (AA) and Brassica oleracea (CC) sequences mapping to corresponding regions on chromosomes A1 and C1, respectively were used to identify single nucleotide polymorphisms between the A and C genomes. A large fraction of these polymorphisms was also present in Brassica napus (AACC), an allopolyploid species that originated from hybridisation of A and C genome species. Intergenomic SNPs mapping throughout homoeologous chromosome segments spanning approximately one Mbp each were included in Illumina's GoldenGate® Genotyping Assay and used to screen multidimensional pools of a Brassica napus bacterial artificial chromosome library with tenfold genome coverage. Based on the results of 50 SNP assays, a BAC contig for the Brassica napus A subgenome was established that spanned the entire region of interest. The C subgenome region was represented in three BAC contigs.

CONCLUSIONS

This proof-of-concept study shows that sequence resources of diploid progenitor genomes can be used to deduce intergenomic SNPs suitable for multiplex polymerase chain reaction (PCR)-based screening of multidimensional BAC pools of a polyploid organism. Owing to their high abundance and ease of identification, intergenomic SNPs represent a versatile tool to establish BAC contigs for homoeologous regions of a polyploid genome.

Genetic diversity and demographic history of Cajanus spp. illustrated from genome-wide SNPs

Understanding genetic structure of Cajanus spp. is essential for achieving genetic improvement by quantitative trait loci (QTL) mapping or association studies and use of selected markers through genomic assisted breeding and genomic selection. After developing a comprehensive set of 1,616 single nucleotide polymorphism (SNPs) and their conversion into cost effective KASPar assays for pigeonpea (Cajanus cajan), we studied levels of genetic variability both within and between diverse set of Cajanus lines including 56 breeding lines, 21 landraces and 107 accessions from 18 wild species. These results revealed a high frequency of polymorphic SNPs and relatively high level of cross-species transferability. Indeed, 75.8% of successful SNP assays revealed polymorphism, and more than 95% of these assays could be successfully transferred to related wild species. To show regional patterns of variation, we used STRUCTURE and Analysis of Molecular Variance (AMOVA) to partition variance among hierarchical sets of landraces and wild species at either the continental scale or within India. STRUCTURE separated most of the domesticated germplasm from wild ecotypes, and separates Australian and Asian wild species as has been found previously. Among Indian regions and states within regions, we found 36% of the variation between regions, and 64% within landraces or wilds within states. The highest level of polymorphism in wild relatives and landraces was found in Madhya Pradesh and Andhra Pradesh provinces of India representing the centre of origin and domestication of pigeonpea respectively.

Applications and challenges of next-generation sequencing in Brassica species

Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.

Identification of genome-wide single nucleotide polymorphisms in allopolyploid crop Brassica napus

Background

Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay.

Results

A total of 892,536 bi-allelic SNPs were discovered throughout the B. napus genome. A total of 36,458 putative amino acid variants were located in 13,552 protein-coding genes, which were predicted to have enriched binding and catalytic activity as a result. Using the GoldenGate genotyping platform, 94 of 96 SNPs sampled could effectively distinguish genotypes of 130 lines from two mapping populations, with an average call rate of 92%.

Conclusions

Despite the polyploid nature of B. napus, nearly 900,000 simple SNPs were identified by whole genome resequencing. These SNPs were predicted to be effective in high-throughput genotyping assays (51% polymorphic SNPs, 92% average call rate using the GoldenGate assay, leading to an estimated >450 000 useful SNPs). Hence, the development of a much larger genotyping array of informative SNPs is feasible. SNPs identified in this study to cause non-synonymous amino acid substitutions can also be utilized to directly identify causal genes in association studies.

Screening of a Brassica napus bacterial artificial chromosome library using highly parallel single nucleotide polymorphism assays

Background

Efficient screening of bacterial artificial chromosome (BAC) libraries with polymerase chain reaction (PCR)-based markers is feasible provided that a multidimensional pooling strategy is implemented. Single nucleotide polymorphisms (SNPs) can be screened in multiplexed format, therefore this marker type lends itself particularly well for medium- to high-throughput applications. Combining the power of multiplex-PCR assays with a multidimensional pooling system may prove to be especially challenging in a polyploid genome. In polyploid genomes two classes of SNPs need to be distinguished, polymorphisms between accessions (intragenomic SNPs) and those differentiating between homoeologous genomes (intergenomic SNPs). We have assessed whether the highly parallel Illumina GoldenGate® Genotyping Assay is suitable for the screening of a BAC library of the polyploid Brassica napus genome.

Results

A multidimensional screening platform was developed for a Brassica napus BAC library which is composed of almost 83,000 clones. Intragenomic and intergenomic SNPs were included in Illumina’s GoldenGate® Genotyping Assay and both SNP classes were used successfully for screening of the multidimensional BAC pools of the Brassica napus library. An optimized scoring method is proposed which is especially valuable for SNP calling of intergenomic SNPs. Validation of the genotyping results by independent methods revealed a success of approximately 80% for the multiplex PCR-based screening regardless of whether intra- or intergenomic SNPs were evaluated.

Conclusions

Illumina’s GoldenGate® Genotyping Assay can be efficiently used for screening of multidimensional Brassica napus BAC pools. SNP calling was specifically tailored for the evaluation of BAC pool screening data. The developed scoring method can be implemented independently of plant reference samples. It is demonstrated that intergenomic SNPs represent a powerful tool for BAC library screening of a polyploid genome.

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.

Detection and genotyping of restriction fragment associated polymorphisms in polyploid crops with a pseudo-reference sequence: a case study in allotetraploid Brassica napus

Background

The presence of homoeologous sequences and absence of a reference genome sequence make discovery and genotyping of single nucleotide polymorphisms (SNPs) more challenging in polyploid crops.

Results

To address this challenge, we constructed reduced representation libraries (RRLs) for two Brassica napus inbred lines and their 91 doubled haploid (DH) progenies using a modified ddRADseq technique. A bioinformatics pipeline termed RFAPtools was developed to discover and genotype SNPs and presence/absence variations (PAVs). Using this pipeline, a pseudo-reference sequence (PRF) containing 180,991 sequence tags was constructed. By aligning sequence reads to the pseudo-reference sequence, allelic SNPs as well as PAVs were identified and genotyped with RFAPtools. Two parallel linkage maps, one SNP bin map containing 8,780 SNP loci and one PAV linkage map containing 12,423 dominant loci, were constructed. By aligning marker sequences to B. rapa sequence scaffolds, whose genome is available, we assigned 44 unassembled sequence scaffolds comprising 8.15 Mb onto the B. rapa chromosomes, and also identified 14 instances of misassembly and eight instances of mis-ordering sequence scaffolds.

Conclusions

These results indicate that the modified ddRADseq approach is a cost-effective and simple method to genotype tens of thousands SNPs and PAV markers in a polyploidy plant species. The results also demonstrated that RFAPtools developed in this study are powerful to mine allelic SNPs from homoeologous sequences in polyploids, therefore they are generally applicable in either diploid or polyploid species with or without a reference genome sequence.

Large SNP arrays for genotyping in crop plants

Genotyping with large numbers of molecular markers is now an indispensable tool within plant genetics and breeding. Especially through the identification of large numbers of single nucleotide polymorphism (SNP) markers using the novel high-throughput sequencing technologies, it is now possible to reliably identify many thousands of SNPs at many different loci in a given plant genome. For a number of important crop plants, SNP markers are now being used to design genotyping arrays containing thousands of markers spread over the entire genome and to analyse large numbers of samples. In this article, we discuss aspects that should be considered during the design of such large genotyping arrays and the analysis of individuals. The fact that crop plants are also often autopolyploid or allopolyploid is given due consideration. Furthermore, we outline some potential applications of large genotyping arrays including high-density genetic mapping, characterization (fingerprinting) of genetic material and breeding-related aspects such as association studies and genomic selection.

High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L

Background

High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern.

Results

We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups.

Conclusions

Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.

Large-scale development of cost-effective single-nucleotide polymorphism marker assays for genetic mapping in pigeonpea and comparative mapping in legumes

Single-nucleotide polymorphisms (SNPs, >2000) were discovered by using RNA-seq and allele-specific sequencing approaches in pigeonpea (Cajanus cajan). For making the SNP genotyping cost-effective, successful competitive allele-specific polymerase chain reaction (KASPar) assays were developed for 1616 SNPs and referred to as PKAMs (pigeonpea KASPar assay markers). Screening of PKAMs on 24 genotypes [23 from cultivated species and 1 wild species (Cajanus scarabaeoides)] defined a set of 1154 polymorphic markers (77.4%) with a polymorphism information content (PIC) value from 0.04 to 0.38. One thousand and ninety-four PKAMs showed polymorphisms between parental lines of the reference mapping population (C. cajan ICP 28 × C. scarabaeoides ICPW 94). By using high-quality marker genotyping data on 167 F₂ lines from the population, a comprehensive genetic map comprising 875 PKAMs with an average inter-marker distance of 1.11 cM was developed. Previously mapped 35 simple sequence repeat markers were integrated into the PKAM map and an integrated genetic map of 996.21 cM was constructed. Mapped PKAMs showed a higher degree of synteny with the genome of Glycine max followed by Medicago truncatula and Lotus japonicus and least with Vigna unguiculata. These PKAMs will be useful for genetics research and breeding applications in pigeonpea and for utilizing genome information from other legume species.

Large-scale development of cost-effective SNP marker assays for diversity assessment and genetic mapping in chickpea and comparative mapping in legumes

A set of 2486 single nucleotide polymorphisms (SNPs) were compiled in chickpea using four approaches, namely (i) Solexa/Illumina sequencing (1409), (ii) amplicon sequencing of tentative orthologous genes (TOGs) (604), (iii) mining of expressed sequence tags (ESTs) (286) and (iv) sequencing of candidate genes (187). Conversion of these SNPs to the cost-effective and flexible throughput Competitive Allele Specific PCR (KASPar) assays generated successful assays for 2005 SNPs. These marker assays have been designated as Chickpea KASPar Assay Markers (CKAMs). Screening of 70 genotypes including 58 diverse chickpea accessions and 12 BC(3) F(2) lines showed 1341 CKAMs as being polymorphic. Genetic analysis of these data clustered chickpea accessions based on geographical origin. Genotyping data generated for 671 CKAMs on the reference mapping population (Cicer arietinum ICC 4958 × Cicer reticulatum PI 489777) were compiled with 317 unpublished TOG-SNPs and 396 published markers for developing the genetic map. As a result, a second-generation genetic map comprising 1328 marker loci including novel 625 CKAMs, 314 TOG-SNPs and 389 published marker loci with an average inter-marker distance of 0.59 cM was constructed. Detailed analyses of 1064 mapped loci of this second-generation chickpea genetic map showed a higher degree of synteny with genome of Medicago truncatula, followed by Glycine max, Lotus japonicus and least with Vigna unguiculata. Development of these cost-effective CKAMs for SNP genotyping will be useful not only for genetics research and breeding applications in chickpea, but also for utilizing genome information from other sequenced or model legumes.

A transcriptome map of perennial ryegrass (Lolium perenne L.)

Background

Single nucleotide polymorphisms (SNPs) are increasingly becoming the DNA marker system of choice due to their prevalence in the genome and their ability to be used in highly multiplexed genotyping assays. Although needed in high numbers for genome-wide marker profiles and genomics-assisted breeding, a surprisingly low number of validated SNPs are currently available for perennial ryegrass.

Results

A perennial ryegrass unigene set representing 9,399 genes was used as a reference for the assembly of 802,156 high quality reads generated by 454 transcriptome sequencing and for in silico SNP discovery. Out of more than 15,433 SNPs in 1,778 unigenes fulfilling highly stringent assembly and detection parameters, a total of 768 SNP markers were selected for GoldenGate genotyping in 184 individuals of the perennial ryegrass mapping population VrnA, a population being previously evaluated for important agronomic traits. A total of 592 (77%) of the SNPs tested were successfully called with a cluster separation above 0.9. Of these, 509 (86%) genic SNP markers segregated in the VrnA mapping population, out of which 495 were assigned to map positions. The genetic linkage map presented here comprises a total of 838 DNA markers (767 gene-derived markers) and spans 750 centi Mogan (cM) with an average marker interval distance of less than 0.9 cM. Moreover, it locates 732 expressed genes involved in a broad range of molecular functions of different biological processes in the perennial ryegrass genome.

Conclusions

Here, we present an efficient approach of using next generation sequencing (NGS) data for SNP discovery, and the successful design of a 768-plex Illumina GoldenGate genotyping assay in a complex genome. The ryegrass SNPs along with the corresponding transcribed sequences represent a milestone in the establishment of genetic and genomics resources available for this species and constitute a further step towards molecular breeding strategies. Moreover, the high density genetic linkage map predominantly based on gene-associated DNA markers provides an important tool for the assignment of candidate genes to quantitative trait loci (QTL), functional genomics and the integration of genetic and physical maps in perennial ryegrass, one of the most important temperate grassland species.

Identification, characterization and interpretation of single-nucleotide sequence variation in allopolyploid crop species

An understanding of nature and extent of nucleotide sequence variation is required for programmes of discovery and characterization of single nucleotide polymorphisms (SNPs), which provide the most versatile class of molecular genetic marker. A majority of higher plant species are polyploids, and allopolyploidy, because of hybrid formation between closely related taxa, is very common. Mutational variation may arise both between allelic (homologous) sequences within individual subgenomes and between homoeologous sequences among subgenomes, in addition to paralogous variation between duplicated gene copies. Successful SNP validation in allopolyploids depends on differentiation of the sequence variation classes. A number of biological factors influence the feasibility of discrimination, including degree of gene family complexity, inbreeding or outbreeding reproductive habit, and the level of knowledge concerning progenitor diploid species. In addition, developments in high-throughput DNA sequencing and associated computational analysis provide general solutions for the genetic analysis of allopolyploids. These issues are explored in the context of experience from a range of allopolyploid species, representing grain (wheat and canola), forage (pasture legumes and grasses), and horticultural (strawberry) crop. Following SNP discovery, detection in routine genotyping applications also presents challenges for allopolyploids. Strategies based on either design of subgenome-specific SNP assays through homoeolocus-targeted polymerase chain reaction (PCR) amplification, or detection of incremental changes in nucleotide variant dosage, are described.

NGS technologies for analyzing germplasm diversity in genebanks

More than 70 years after the first ex situ genebanks have been established, major efforts in this field are still concerned with issues related to further completion of individual collections and securing of their storage. Attempts regarding valorization of ex situ collections for plant breeders have been hampered by the limited availability of phenotypic and genotypic information. With the advent of molecular marker technologies first efforts were made to fingerprint genebank accessions, albeit on a very small scale and mostly based on inadequate DNA marker systems. Advances in DNA sequencing technology and the development of high-throughput systems for multiparallel interrogation of thousands of single nucleotide polymorphisms (SNPs) now provide a suite of technological platforms facilitating the analysis of several hundred of Gigabases per day using state-of-the-art sequencing technology or, at the same time, of thousands of SNPs. The present review summarizes recent developments regarding the deployment of these technologies for the analysis of plant genetic resources, in order to identify patterns of genetic diversity, map quantitative traits and mine novel alleles from the vast amount of genetic resources maintained in genebanks around the world. It also refers to the various shortcomings and bottlenecks that need to be overcome to leverage the full potential of high-throughput DNA analysis for the targeted utilization of plant genetic resources.

A candidate gene-based association study of tocopherol content and composition in rapeseed (Brassica napus)

Rapeseed (Brassica napus L.) is the most important oil crop of temperate climates. Rapeseed oil contains tocopherols, also known as vitamin E, which is an indispensable nutrient for humans and animals due to its antioxidant and radical scavenging abilities. Moreover, tocopherols are also important for the oxidative stability of vegetable oils. Therefore, seed oil with increased tocopherol content or altered tocopherol composition is a target for breeding. We investigated the role of nucleotide variations within candidate genes from the tocopherol biosynthesis pathway. Field trials were carried out with 229 accessions from a worldwide B. napus collection which was divided into two panels of 96 and 133 accessions. Seed tocopherol content and composition were measured by HPLC. High heritabilities were found for both traits, ranging from 0.62 to 0.94. We identified polymorphisms by sequencing selected regions of the tocopherol genes from the 96 accession panel. Subsequently, we determined the population structure (Q) and relative kinship (K) as detected by genotyping with genome-wide distributed SSR markers. Association studies were performed using two models, the structure-based GLM + Q and the PK-mixed model. Between 26 and 12 polymorphisms within two genes (BnaX.VTE3.a, BnaA.PDS1.c) were significantly associated with tocopherol traits. The SNPs explained up to 16.93% of the genetic variance for tocopherol composition and up to 10.48% for total tocopherol content. Based on the sequence information we designed CAPS markers for genotyping the 133 accessions from the second panel. Significant associations with various tocopherol traits confirmed the results from the first experiment. We demonstrate that the polymorphisms within the tocopherol genes clearly impact tocopherol content and composition in B. napus seeds. We suggest that these nucleotide variations may be used as selectable markers for breeding rapeseed with enhanced tocopherol quality.

Diversity array technology markers: genetic diversity analyses and linkage map construction in rapeseed (Brassica napus L.)

We developed Diversity Array Technology (DArT) markers for application in genetic studies of Brassica napus and other Brassica species with A or C genomes. Genomic representation from 107 diverse genotypes of B. napus L. var. oleifera (rapeseed, AACC genomes) and B. rapa (AA genome) was used to develop a DArT array comprising 11 520 clones generated using PstI/BanII and PstI/BstN1 complexity reduction methods. In total, 1547 polymorphic DArT markers of high technical quality were identified and used to assess molecular diversity among 89 accessions of B. napus, B. rapa, B. juncea, and B. carinata collected from different parts of the world. Hierarchical cluster and principal component analyses based on genetic distance matrices identified distinct populations clustering mainly according to their origin/pedigrees. DArT markers were also mapped in a new doubled haploid population comprising 131 lines from a cross between spring rapeseed lines ‘Lynx-037DH’ and ‘Monty-028DH’. Linkage groups were assigned on the basis of previously mapped simple sequence repeat (SSRs), intron polymorphism (IP), and gene-based markers. The map consisted of 437 DArT, 135 SSR, 6 IP, and 6 gene-based markers and spanned 2288 cM. Our results demonstrate that DArT markers are suitable for genetic diversity analysis and linkage map construction in rapeseed.

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.

Genomic diversity in switchgrass (Panicum virgatum): from the continental scale to a dune landscape

Connecting broad-scale patterns of genetic variation and population structure to genetic diversity on a landscape is a key step towards understanding historical processes of migration and adaptation. New genomic approaches can be used to increase the resolution of phylogeographic studies while reducing locus sampling effects and circumventing ascertainment bias. Here, we use a novel approach based on high-throughput sequencing to characterize genetic diversity in complete chloroplast genomes and >10,000 nuclear loci in switchgrass, at continental and landscape scales. Switchgrass is a North American tallgrass species, which is widely used in conservation and perennial biomass production, and shows strong ecotypic adaptation and population structure across the continental range. We sequenced 40.9 billion base pairs from 24 individuals from across the species' range and 20 individuals from the Indiana Dunes. Analysis of plastome sequence revealed 203 variable SNP sites that define eight haplogroups, which are differentiated by 4-127 SNPs and confirmed by patterns of indel variation. These include three deeply divergent haplogroups, which correspond to the previously described lowland-upland ecotypic split and a novel upland haplogroup split that dates to the mid-Pleistocene. Most of the plastome haplogroup diversity present in the northern switchgrass range, including in the Indiana Dunes, originated in the mid- or upper Pleistocene prior to the most recent postglacial recolonization. Furthermore, a recently colonized landscape feature (approximately 150 ya) in the Indiana Dunes contains several deeply divergent upland haplogroups. Nuclear markers also support a deep lowland-upland split, followed by limited gene flow, and show extensive gene flow in the local population of the Indiana Dunes.