GBS-SNP-CROP: a reference-optional pipeline for SNP discovery and plant germplasm characterization using variable length, paired-end genotyping-by-sequencing data

Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato

KEY MESSAGE

De novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over 'fixed' SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker-trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm. This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a 'fixed' SNP Infinium array platform and a 'flexible and open' genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker-trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL 'hotspots' for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

Characterisation and mapping of a Globodera pallida resistance derived from the wild potato species Solanum spegazzinii

KEY MESSAGE

A new resistance locus acting against the potato cyst nematode Globodera pallida was mapped to chromosome VI in the diploid wild potato species Solanum spegazzinii CPC 7195. The potato cyst nematodes (PCN) Globodera pallida and Globodera rostochiensis are economically important potato pests in almost all regions where potato is grown. One important management strategy involves deployment through introgression breeding into modern cultivars of new sources of naturally occurring resistance from wild potato species. We describe a new source of resistance to G. pallida from wild potato germplasm. The diploid species Solanum spegazzinii Bitter accession CPC 7195 shows resistance to G. pallida pathotypes Pa1 and Pa2/3. A cross and first backcross of S. spegazzinii with Solanum tuberosum Group Phureja cultivar Mayan Gold were performed, and the level of resistance to G. pallida Pa2/3 was determined in progeny clones. Bulk-segregant analysis (BSA) using generic mapping enrichment sequencing (GenSeq) and genotyping-by-sequencing were performed to identify single-nucleotide polymorphisms (SNPs) that are genetically linked to the resistance, using S. tuberosum Group Phureja clone DM1-3 516 R44 as a reference genome. These SNPs were converted into allele-specific PCR assays, and the resistance was mapped to an interval of roughly 118 kb on chromosome VI. This newly identified resistance, which we call Gpa VIlspg, can be used in future efforts to produce modern cultivars with enhanced and broad-spectrum resistances to the major pests and pathogens of potato.

GBS-DP: a bioinformatics pipeline for processing data coming from genotyping by sequencing

The development of next-generation sequencing technologies has provided new opportunities for genotyping various organisms, including plants. Genotyping by sequencing (GBS) is used to identify genetic variability more rapidly, and is more cost-effective than whole-genome sequencing. GBS has demonstrated its reliability and flexibility for a number of plant species and populations. It has been applied to genetic mapping, molecular marker discovery, genomic selection, genetic diversity studies, variety identification, conservation biology and evolutionary studies. However, reduction in sequencing time and cost has led to the need to develop efficient bioinformatics analyses for an ever-expanding amount of sequenced data. Bioinformatics pipelines for GBS data analysis serve the purpose. Due to the similarity of data processing steps, existing pipelines are mainly characterised by a combination of software packages specifically selected either to process data for certain organisms or to process data from any organisms. However, despite the usage of efficient software packages, these pipelines have some disadvantages. For example, there is a lack of process automation (in some pipelines, each step must be started manually), which significantly reduces the performance of the analysis. In the majority of pipelines, there is no possibility of automatic installation of all necessary software packages; for most of them, it is also impossible to switch off unnecessary or completed steps. In the present work, we have developed a GBS-DP bioinformatics pipeline for GBS data analysis. The pipeline can be applied for various species. The pipeline is implemented using the Snakemake workflow engine. This implementation allows fully automating the process of calculation and installation of the necessary software packages. Our pipeline is able to perform analysis of large datasets (more than 400 samples).

Identification of QTLs for resistance to 10 pathotypes of Plasmodiophora brassicae in Brassica oleracea cultivar ECD11 through genotyping-by-sequencing

KEY MESSAGE

Two major quantitative trait loci (QTLs) and five minor QTLs for 10 pathotypes were identified on chromosomes C01, C03, C04 and C08 through genotyping-by-sequencing from Brassica oleracea. Clubroot caused by Plasmodiophora brassicae is an important disease in brassica crops. Managing clubroot disease of canola on the Canadian prairie is challenging due to the continuous emergence of new pathotypes. Brassica oleracea is considered a major source of quantitative resistance to clubroot. Genotyping-by-sequencing (GBS) was performed in the parental lines; T010000DH3 (susceptible), ECD11 (resistant) and 124 BC1 plants. A total of 4769 high-quality polymorphic SNP loci were obtained and distributed on 9 chromosomes of B. oleracea. Evaluation of 124 BC1S1 lines for resistance to 10 pathotypes: 3A, 2B, 5C, 3D, 5G, 3H, 8J, 5K, 5L and 3O of P. brassicae, was carried out. Seven QTLs, 5 originating from ECD11 and 2 from T010000DH3, were detected. One major QTL designated as Rcr_C03-1 on C03 contributed 16.0-65.6% of phenotypic variation explained (PVE) for 8 pathotypes: 2B, 5C, 5G, 3H, 8J, 5K, 5L and 3O. Another major QTL designated as Rcr_C08-1 on C08 contributed 8.3 and 23.5% PVE for resistance to 8J and 5K, respectively. Five minor QTLs designated as Rcr_C01-1, Rcr_C03-2, Rcr_C03-3, Rcr_C04-1 and Rcr_C08-2 were detected on chromosomes C01, C03, C04 and C08 that contributed 8.3-23.5% PVE for 5 pathotypes each of 3A, 2B, 3D, 8J and 5K. There were 1, 10 and 4 genes encoding TIR-NBS-LRR/CC-NBS-LRR class disease resistance proteins in the Rcr_C01-1, Rcr_C03-1 and Rcr_C08-1 flanking regions. The syntenic regions of the two major QTLs Rcr_C03-1 and Rcr_C08-1 in the B. rapa genome 'Chiifu' were searched.

Habitat-associated Genomic Variation in a Wall Lizard from an Oceanic Island

The lizard Teira dugesii exhibits morphological divergence between beach and inland habitats in the face of gene flow, within the volcanic island of Madeira, Portugal. Here, we analyzed genomic data obtained by genotyping-by-sequencing, which provided 16,378 single nucleotide polymorphisms (SNPs) from 94 individuals sampled from 15 sites across Madeira. Ancient within-island divergence in allopatry appears to have mediated divergence in similar species within other Atlantic islands, but this hypothesis was not supported for T. dugesii. Across all samples, a total of 168 SNPs were classified as statistical outliers using pcadapt and OutFLANK. Redundancy analysis (RDA) revealed that 17 of these outliers were associated with beach/inland habitats. The SNPs were located within 16 sequence tags and 15 of these were homologous with sequences in a 31 Mb region on chromosome 3 of a reference wall lizard genome (the remaining tag could not be associated with any chromosome). We further investigated outliers through contingency analyses of allele frequencies at each of four pairs of adjacent beach-inland sites. The majority of the outliers detected by the RDA were confirmed at two pairs of these matched sites. These analyses also suggested some parallel divergence at different localities. Six other outliers were associated with site elevation, four of which were located on chromosome 5 of the reference genome. Our study lends support to a previous hypothesis that divergent selection between gray shingle beaches and inland regions overcomes gene flow and leads to the observed morphological divergence between populations in these adjacent habitats.

Genomic characterization and gene bank curation of Aegilops: the wild relatives of wheat

Genetic diversity found in crop wild relatives is critical to preserve and utilize for crop improvement to achieve sustainable food production amid climate change and increased demand. We genetically characterized a large collection of 1,041 Aegilops accessions distributed among 23 different species using more than 45K single nucleotide polymorphisms identified by genotyping-by-sequencing. The Wheat Genetics Resource Center (WGRC) Aegilops germplasm collection was curated through the identification of misclassified and redundant accessions. There were 49 misclassified and 28 sets of redundant accessions within the four diploid species. The curated germplasm sets now have improved utility for genetic studies and wheat improvement. We constructed a phylogenetic tree and principal component analysis cluster for all Aegilops species together, giving one of the most comprehensive views of Aegilops. The Sitopsis section and the U genome Aegilops clade were further scrutinized with in-depth population analysis. The genetic relatedness among the pair of Aegilops species provided strong evidence for the species evolution, speciation, and diversification. We inferred genome symbols for two species Ae. neglecta and Ae. columnaris based on the sequence read mapping and the presence of segregating loci on the pertinent genomes as well as genetic clustering. The high genetic diversity observed among Aegilops species indicated that the genus could play an even greater role in providing the critical need for untapped genetic diversity for future wheat breeding and improvement. To fully characterize these Aegilops species, there is an urgent need to generate reference assemblies for these wild wheats, especially for the polyploid Aegilops.

Phylogenetic Analysis of Allotetraploid Species Using Polarized Genomic Sequences

Phylogenetic analysis of polyploid hybrid species has long posed a formidable challenge as it requires the ability to distinguish between alleles of different ancestral origins in order to disentangle their individual evolutionary history. This problem has been previously addressed by conceiving phylogenies as reticulate networks, using a two-step phasing strategy that first identifies and segregates homoeologous loci and then, during a second phasing step, assigns each gene copy to one of the subgenomes of an allopolyploid species. Here, we propose an alternative approach, one that preserves the core idea behind phasing-to produce separate nucleotide sequences that capture the reticulate evolutionary history of a polyploid-while vastly simplifying its implementation by reducing a complex multistage procedure to a single phasing step. While most current methods used for phylogenetic reconstruction of polyploid species require sequencing reads to be pre-phased using experimental or computational methods-usually an expensive, complex, and/or time-consuming endeavor-phasing executed using our algorithm is performed directly on the multiple-sequence alignment (MSA), a key change that allows for the simultaneous segregation and sorting of gene copies. We introduce the concept of genomic polarization that, when applied to an allopolyploid species, produces nucleotide sequences that capture the fraction of a polyploid genome that deviates from that of a reference sequence, usually one of the other species present in the MSA. We show that if the reference sequence is one of the parental species, the polarized polyploid sequence has a close resemblance (high pairwise sequence identity) to the second parental species. This knowledge is harnessed to build a new heuristic algorithm where, by replacing the allopolyploid genomic sequence in the MSA by its polarized version, it is possible to identify the phylogenetic position of the polyploid's ancestral parents in an iterative process. The proposed methodology can be used with long-read and short-read high-throughput sequencing data and requires only one representative individual for each species to be included in the phylogenetic analysis. In its current form, it can be used in the analysis of phylogenies containing tetraploid and diploid species. We test the newly developed method extensively using simulated data in order to evaluate its accuracy. We show empirically that the use of polarized genomic sequences allows for the correct identification of both parental species of an allotetraploid with up to 97% certainty in phylogenies with moderate levels of incomplete lineage sorting (ILS) and 87% in phylogenies containing high levels of ILS. We then apply the polarization protocol to reconstruct the reticulate histories of Arabidopsis kamchatica and Arabidopsis suecica, two allopolyploids whose ancestry has been well documented. [Allopolyploidy; Arabidopsis; genomic polarization; homoeologs; incomplete lineage sorting; phasing; polyploid phylogenetics; reticulate evolution.].

Diversity analyses in two ornamental and large-genome Ranunculaceae species based on a low-cost Klenow NGS-based protocol

Persian buttercup (Ranunculus asiaticus L.) and poppy anemone (Anemone coronaria L.) are ornamental, outcrossing, perennial species belonging to the Ranunculaceae family, characterized by large and highly repetitive genomes. We applied K-seq protocol in both species to generate high-throughput sequencing data and produce a large number of genetic polymorphisms. The technique entails the application of Klenow polymerase-based PCR using short primers designed by analyzing k-mer sets in the genome sequence. To date the genome sequence of both species has not been released, thus we designed primer sets based on the reference the genome sequence of the related species Aquilegia oxysepala var. kansuensis (Brühl). A whole of 11,542 SNPs were selected for assessing genetic diversity of eighteen commercial varieties of R. asiaticus, while 1,752 SNPs for assessing genetic diversity in six cultivars of A. coronaria. UPGMA dendrograms were constructed and in R. asiaticus integrated in with PCA analysis. This study reports the first molecular fingerprinting within Persian buttercup, while the results obtained in poppy anemone were compared with a previously published SSR-based fingerprinting, proving K-seq to be an efficient protocol for the genotyping of complex genetic backgrounds.

On the usefulness of mock genomes to define heterotic pools, testers, and hybrid predictions in orphan crops

The advances in genomics in recent years have increased the accuracy and efficiency of breeding programs for many crops. Nevertheless, the adoption of genomic enhancement for several other crops essential in developing countries is still limited, especially for those that do not have a reference genome. These crops are more often called orphans. This is the first report to show how the results provided by different platforms, including the use of a simulated genome, called the mock genome, can generate in population structure and genetic diversity studies, especially when the intention is to use this information to support the formation of heterotic groups, choice of testers, and genomic prediction of single crosses. For that, we used a method to assemble a reference genome to perform the single-nucleotide polymorphism (SNP) calling without needing an external genome. Thus, we compared the analysis results using the mock genome with the standard approaches (array and genotyping-by-sequencing (GBS)). The results showed that the GBS-Mock presented similar results to the standard methods of genetic diversity studies, division of heterotic groups, the definition of testers, and genomic prediction. These results showed that a mock genome constructed from the population's intrinsic polymorphisms to perform the SNP calling is an effective alternative for conducting genomic studies of this nature in orphan crops, especially those that do not have a reference genome.

DT-PICS: An Efficient and Cost-Effective SNP Selection Method for the Germplasm Identification of Arabidopsis

Germplasm identification is essential for plant breeding and conservation. In this study, we developed a new method, DT-PICS, for efficient and cost-effective SNP selection in germplasm identification. The method, based on the decision tree concept, could efficiently select the most informative SNPs for germplasm identification by recursively partitioning the dataset based on their overall high PIC values, instead of considering individual SNP features. This method reduces redundancy in SNP selection and enhances the efficiency and automation of the selection process. DT-PICS demonstrated significant advantages in both the training and testing datasets and exhibited good performance on independent prediction, which validates its effectiveness. Thirteen simplified SNP sets were extracted from 749,636 SNPs in 1135 Arabidopsis varieties resequencing datasets, including a total of 769 DT-PICS SNPs, with an average of 59 SNPs per set. Each simplified SNP set could distinguish between the 1135 Arabidopsis varieties. Simulations demonstrated that using a combination of two simplified SNP sets for identification can effectively increase the fault tolerance in independent validation. In the testing dataset, two potentially mislabeled varieties (ICE169 and Star-8) were identified. For 68 same-named varieties, the identification process achieved 94.97% accuracy and only 30 shared markers on average; for 12 different-named varieties, the germplasm to be tested could be effectively distinguished from 1,134 other varieties while grouping extremely similar varieties (Col-0) together, reflecting their actual genetic relatedness. The results suggest that the DT-PICS provides an efficient and accurate approach to SNP selection in germplasm identification and management, offering strong support for future plant breeding and conservation efforts.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India

INTRODUCTION

The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits.

METHODS AND RESULTS

The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Life on a beach leads to phenotypic divergence despite gene flow for an island lizard

Limited spatial separation within small islands suggests that observed population divergence may occur due to habitat differences without interruption to gene flow but strong evidence of this is scarce. The wall lizard Teira dugesii lives in starkly contrasting shingle beach and inland habitats on the island of Madeira. We used a matched pairs sampling design to examine morphological and genomic divergence between four beach and adjacent (<1 km) inland areas. Beach populations are significantly darker than corresponding inland populations. Geometric morphometric analyses reveal divergence in head morphology: beach lizards have generally wider snouts. Genotyping-by-sequencing allows the rejection of the hypothesis that beach populations form a distinct lineage. Bayesian analyses provide strong support for models that incorporate gene flow, relative to those that do not, replicated at all pairs of matched sites. Madeiran lizards show morphological divergence between habitats in the face of gene flow, revealing how divergence may originate within small islands.

Genomic selection for survival under naturally occurring Saprolegnia oomycete infection in farmed European whitefish Coregonus lavaretus

Saprolegnia oomycete infection causes serious economic losses and reduces fish health in aquaculture. Genomic selection based on thousands of DNA markers is a powerful tool to improve fish traits in selective breeding programs. Our goal was to develop a single nucleotide polymorphism (SNP) marker panel and to test its use in genomic selection for improved survival against Saprolegnia infection in European whitefish Coregonus lavaretus, the second most important farmed fish species in Finland. We used a double digest restriction site associated DNA (ddRAD) genotyping by sequencing method to produce a SNP panel, and we tested it analyzing data from a cohort of 1,335 fish, which were measured at different times for mortality to Saprolegnia oomycete infection and weight traits. We calculated the genetic relationship matrix (GRM) from the genome-wide genetic data, integrating it in multivariate mixed models used for the estimation of variance components and genomic breeding values (GEBVs), and to carry out Genome-Wide Association Studies for the presence of quantitative trait loci (QTL) affecting the phenotypes in analysis. We identified one major QTL on chromosome 6 affecting mortality to Saprolegnia infection, explaining 7.7% to 51.3% of genetic variance, and a QTL for weight on chromosome 4, explaining 1.8% to 5.4% of genetic variance. Heritability for mortality was 0.20 to 0.43 on the liability scale, and heritability for weight was 0.44 to 0.53. The QTL for mortality showed an additive allelic effect. We tested whether integrating the QTL for mortality as a fixed factor, together with a new GRM calculated excluding the QTL from the genetic data, would improve the accuracy estimation of GEBVs. This test was done through a cross-validation approach, which indicated that the inclusion of the QTL increased the mean accuracy of the GEBVs by 0.28 points, from 0.33 to 0.61, relative to the use of full GRM only. The area under the curve of the receiver-operator curve for mortality increased from 0.58 to 0.67 when the QTL was included in the model. The inclusion of the QTL as a fixed effect in the model increased the correlation between the GEBVs of early mortality with the late mortality, compared to a model that did not include the QTL. These results validate the usability of the produced SNP panel for genomic selection in European whitefish and highlight the opportunity for modeling QTLs in genomic evaluation of mortality due to Saprolegnia infection.

Management and Utilization of Plant Genetic Resources for a Sustainable Agriculture

Despite the dramatic increase in food production thanks to the Green Revolution, hunger is increasing among human populations around the world, affecting one in nine people. The negative environmental and social consequences of industrial monocrop agriculture is becoming evident, particularly in the contexts of greenhouse gas emissions and the increased frequency and impact of zoonotic disease emergence, including the ongoing COVID-19 pandemic. Human activity has altered 70–75% of the ice-free Earth’s surface, squeezing nature and wildlife into a corner. To prevent, halt, and reverse the degradation of ecosystems worldwide, the UN has launched a Decade of Ecosystem Restoration. In this context, this review describes the origin and diversity of cultivated species, the impact of modern agriculture and other human activities on plant genetic resources, and approaches to conserve and use them to increase food diversity and production with specific examples of the use of crop wild relatives for breeding climate-resilient cultivars that require less chemical and mechanical input. The need to better coordinate in situ conservation efforts with increased funding has been highlighted. We emphasise the need to strengthen the genebank infrastructure, enabling the use of modern biotechnological tools to help in genotyping and characterising accessions plus advanced ex situ conservation methods, identifying gaps in collections, developing core collections, and linking data with international databases. Crop and variety diversification and minimising tillage and other field practices through the development and introduction of herbaceous perennial crops is proposed as an alternative regenerative food system for higher carbon sequestration, sustaining economic benefits for growers, whilst also providing social and environmental benefits.

Genotyping-by-Sequencing and Morphology Revealed the Role of Polyploidization and Hybridization in the Diversification of the Centaurea aspera L. Complex of Section Seridia (Juss.) DC. (Asteraceae)

Hybridization and polyploidy are major drivers of plant evolution. In Centaurea (Asteraceae), both mechanisms are frequent and lead to reticulate evolutions. However, in the Western Mediterranean section, Seridia studies are scarce. In this section, Centaurea aspera forms a complex including four European diploid and one Moroccan autotetraploid subspecies, an allopolyploid, and hybrids among them. Here, we aimed to delimit the different taxa, identify any introgressions, and discuss their evolutionary history. Samples of all taxa were analysed using 1688 SNPs obtained through GBS and were morphologically characterized. Three genetically well-differentiated clusters were observed, corresponding to the allopolyploid C. seridis, the diploid C. aspera and the cryptic autotetraploid C. aspera ssp. gentilii, which is proposed to be considered as a species. Centaurea seridis showed a high isolation by distance, a greater morphological variability, and a lack of interspecific gene flow. Diploid and autotetraploid C. aspera individuals were morphologically similar, and some introgressions were detected in Southern Spain, where new forms may promote diversification. This gene flow might have taken place during the Messinian and before autopolyploidization occurred in Morocco. In the C. aspera complex, current interspecific barriers are strong, while polyploidization may provide a better adaptation to drier environments.

Selection of genome-wide SNPs for pooled allelotyping assays useful for population monitoring

Parasitic worms are serious pests of humans, livestock and crops worldwide. Multiple management strategies are employed in order to reduce their impact, and some of these may affect their genome and population allelic frequency distribution. The evolution of chemical resistance, ecological changes, and pest dispersal have allowed an increasing number of pests to become difficult to control with current management methods. Their lifestyle limits the use of ecological and individual-based management of populations. There is a need to develop rapid, affordable, and simple diagnostics to assess the efficacy of management strategies and delay the evolution of resistance to these strategies. This study presents a multi-locus, equal-representation, whole genome pooled SNPs selection approach as a monitoring tool for the ovine nematode parasite Haemonchus contortus. The SNP selection method used two reference genomes of different quality, then validated these SNPs against a high-quality recent genome assembly. From over 11 million high-quality SNPs identified, 334 SNPs were selected, of which 262 were species-specific, yielded similar allele frequencies when assessed as multiple individuals or as pools of individuals, and suitable to distinguish mixed nematode isolate pools from single isolate pools. As a proof-of-concept, 21 Australian H. contortus populations with various phenotypes and genotypes were screened. This analysis confirmed the overall low-level of genetic differentiation between populations collected from the field, but clearly identifying highly inbred populations, and populations showing genetic signatures associated with chemical resistance. The analysis showed that 66% of the SNPs were necessary for stability in assessing population genetic patterns, and SNP pairs did not show linkage according to allelic frequencies across the 21 populations. This method demonstrates that ongoing monitoring of parasite allelic frequencies and genetic changes can be achieved as a management assessment tool to identify drug-treatment failure, population incursions, and inbreeding signatures due to selection. The SNP selection method could also be applied to other parasite species.

Population dynamics linked to glacial cycles in Cercis chuniana F. P. Metcalf (Fabaceae) endemic to the montane regions of subtropical China

The mountains of subtropical China are an excellent system for investigating the processes driving the geographical distribution of biodiversity and radiation of plant populations in response to Pleistocene climate fluctuations. How the major mountain ranges in subtropical China have affected the evolution of plant species in the subtropical evergreen broadleaved forest is an issue with long-term concern. Here, we focused on Cercis chuniana, a woody species endemic to the southern mountain ranges in subtropical China, to elucidate its population dynamics. We used genotyping by sequencing (GBS) to investigate the spatial pattern of genetic variation among 11 populations. Geographical isolation was detected between the populations located in adjacent mountain ranges, thought to function as geographical barriers due to their complex physiography. Bayesian time estimation revealed that population divergence occurred in the middle Pleistocene, when populations in the Nanling Mts. separated from those to the east. The orientation and physiography of the mountain ranges of subtropical China appear to have contributed to the geographical pattern of genetic variation between the eastern and western populations of C. chuniana. Complex physiography plus long-term stable ecological conditions across glacial cycles facilitated the demographic expansion in the Nanling Mts., from which contemporary migration began. The Nanling Mts. are thus considered as a suitable area for preserving population diversity and large population sizes of C. chuniana compared with other regions. As inferred by ecological niche modeling and coalescent simulations, secondary contact occurred during the warm Lushan-Tali Interglacial period, with intensified East Asia summer monsoon and continuous habitat available for occupation. Our data support the strong influence of both climatic history and topographic characteristics on the high regional phytodiversity of the subtropical evergreen broadleaved forest in subtropical China.

Grass pea natural variation reveals oligogenic resistance to Fusarium oxysporum f. sp. pisi

Grass pea (Lathyrus sativus L.) is an annual legume species, phylogenetically close to pea (Pisum sativum L.), that may be infected by Fusarium oxysporum f. sp. pisi (Fop), the causal agent of fusarium wilt in peas with vast worldwide yield losses. A range of responses varying from high resistance to susceptibility to this pathogen has been reported in grass pea germplasm. Nevertheless, the genetic basis of that diversity of responses is still unknown, hampering its breeding exploitation. To identify genomic regions controlling grass pea resistance to fusarium wilt, a genome-wide association study approach was applied on a grass pea worldwide collection of accessions inoculated with Fop race 2. Disease responses were scored in this collection that was also subjected to high-throughput based single nucleotide polymorphisms (SNP) screening through genotyping-by-sequencing. A total of 5,651 high-quality SNPs were considered for association mapping analysis, performed using mixed linear models accounting for population structure. Because of the absence of a fully assembled grass pea reference genome, SNP markers' genomic positions were retrieved from the pea's reference genome v1a. In total, 17 genomic regions were associated with three fusarium wilt response traits in grass pea, anticipating an oligogenic control. Seven of these regions were located on pea chromosomes 1, 6, and 7. The candidate genes underlying these regions were putatively involved in secondary and amino acid metabolism, RNA (regulation of transcription), transport, and development. This study revealed important fusarium wilt resistance favorable grass pea SNP alleles, allowing the development of molecular tools for precision disease resistance breeding.

Weak coupling among barrier loci and waves of neutral and adaptive introgression across an expanding hybrid zone

Hybridization can serve as an evolutionary stimulus, but we have little understanding of introgression at early stages of hybrid zone formation. We analyze reproductive isolation and introgression between a range‐limited and a widespread species. Reproductive barriers are estimated based on differences in flowering time, ecogeographic distributions, and seed set from crosses. We find an asymmetrical mating barrier due to cytonuclear incompatibility that is consistent with observed clusters of coincident and concordant tension zone clines (barrier loci) for mtDNA haplotypes and nuclear SNPs. These groups of concordant clines are spread across the hybrid zone, resulting in weak coupling among barrier loci and extensive introgression. Neutral clines had nearly equal introgression into both species’ ranges, whereas putative cases of adaptive introgression had exceptionally wide clines with centers shifted toward one species. Analyses of cline shape indicate that secondary contact was initiated within the last 800 generations with the per‐generation dispersal between 200 and 400 m, and provide some of the first estimates of the strength of selection required to account for observed levels of adaptive introgression. The weak species boundary between these species appears to be in early stages of dissolution, and ultimately will precipitate genetic swamping of the range‐limited species.

Mapping freezing tolerance QTL in alfalfa: based on indoor phenotyping

BACKGROUND

Winter freezing temperature impacts alfalfa (Medicago sativa L.) persistence and seasonal yield and can lead to the death of the plant. Understanding the genetic mechanisms of alfalfa freezing tolerance (FT) using high-throughput phenotyping and genotyping is crucial to select suitable germplasm and develop winter-hardy cultivars. Several clones of an alfalfa F1 mapping population (3010 x CW 1010) were tested for FT using a cold chamber. The population was genotyped with SNP markers identified using genotyping-by-sequencing (GBS) and the quantitative trait loci (QTL) associated with FT were mapped on the parent-specific linkage maps. The ultimate goal is to develop non-dormant and winter-hardy alfalfa cultivars that can produce extended growth in the areas where winters are often mild.

RESULTS

Alfalfa FT screening method optimized in this experiment comprises three major steps: clone preparation, acclimation, and freezing test. Twenty clones of each genotype were tested, where 10 samples were treated with freezing temperature, and 10 were used as controls. A moderate positive correlation (r ~ 0.36, P < 0.01) was observed between indoor FT and field-based winter hardiness (WH), suggesting that the indoor FT test is a useful indirect selection method for winter hardiness of alfalfa germplasm. We detected a total of 20 QTL associated with four traits; nine for visual rating-based FT, five for percentage survival (PS), four for treated to control regrowth ratio (RR), and two for treated to control biomass ratio (BR). Some QTL positions overlapped with WH QTL reported previously, suggesting a genetic relationship between FT and WH. Some favorable QTL from the winter-hardy parent (3010) were from the potential genic region for a cold tolerance gene CBF. The BLAST alignment of a CBF sequence of M. truncatula, a close relative of alfalfa, against the alfalfa reference showed that the gene's ortholog resides around 75 Mb on chromosome 6.

CONCLUSIONS

The indoor freezing tolerance selection method reported is useful for alfalfa breeders to accelerate breeding cycles through indirect selection. The QTL and associated markers add to the genomic resources for the research community and can be used in marker-assisted selection (MAS) for alfalfa cold tolerance improvement.

Genomic Variation Shaped by Environmental and Geographical Factors in Prairie Cordgrass Natural Populations Collected across Its Native Range in the USA

Prairie cordgrass (Spartina pectinata Link) is a native perennial warm-season (C4) grass common in North American prairies. With its high biomass yield and abiotic stress tolerance, there is a high potential of developing prairie cordgrass for conservation practices and as a dedicated bioenergy crop for sustainable cellulosic biofuel production. However, as with many other undomesticated grass species, little information is known about the genetic diversity or population structure of prairie cordgrass natural populations as compared to their ecotypic and geographic adaptation in North America. In this study, we sampled and characterized a total of 96 prairie cordgrass natural populations with 9315 high quality SNPs from a genotyping-by-sequencing (GBS) approach. The natural populations were collected from putative remnant prairie sites throughout the Midwest and Eastern USA, which are the major habitats for prairie cordgrass. Partitioning of genetic variance using SNP marker data revealed significant variance among and within populations. Two potential gene pools were identified as being associated with ploidy levels, geographical separation, and climatic separation. Geographical factors such as longitude and altitude, and environmental factors such as annual temperature, annual precipitation, temperature of the warmest month, precipitation of the wettest month, precipitation of Spring, and precipitation of the wettest month are important in affecting the intraspecific distribution of prairie cordgrass. The divergence of prairie cordgrass natural populations also provides opportunities to increase breeding value of prairie cordgrass as a bioenergy and conservation crop.

Genome-wide approaches for the identification of markers and genes associated with sugarcane yellow leaf virus resistance

Sugarcane yellow leaf (SCYL), caused by the sugarcane yellow leaf virus (SCYLV) is a major disease affecting sugarcane, a leading sugar and energy crop. Despite damages caused by SCYLV, the genetic base of resistance to this virus remains largely unknown. Several methodologies have arisen to identify molecular markers associated with SCYLV resistance, which are crucial for marker-assisted selection and understanding response mechanisms to this virus. We investigated the genetic base of SCYLV resistance using dominant and codominant markers and genotypes of interest for sugarcane breeding. A sugarcane panel inoculated with SCYLV was analyzed for SCYL symptoms, and viral titer was estimated by RT-qPCR. This panel was genotyped with 662 dominant markers and 70,888 SNPs and indels with allele proportion information. We used polyploid-adapted genome-wide association analyses and machine-learning algorithms coupled with feature selection methods to establish marker-trait associations. While each approach identified unique marker sets associated with phenotypes, convergences were observed between them and demonstrated their complementarity. Lastly, we annotated these markers, identifying genes encoding emblematic participants in virus resistance mechanisms and previously unreported candidates involved in viral responses. Our approach could accelerate sugarcane breeding targeting SCYLV resistance and facilitate studies on biological processes leading to this trait.

Robust and efficient software for reference-free genomic diversity analysis of genotyping-by-sequencing data on diploid and polyploid species

Genotyping-by-sequencing (GBS) is a widely used and cost-effective technique for obtaining large numbers of genetic markers from populations by sequencing regions adjacent to restriction cut sites. Although a standard reference-based pipeline can be followed to analyse GBS reads, a reference genome is still not available for a large number of species. Hence, reference-free approaches are required to generate the genetic variability information that can be obtained from a GBS experiment. Unfortunately, available tools to perform de novo analysis of GBS reads face issues of usability, accuracy and performance. Furthermore, few available tools are suitable for analysing data sets from polyploid species. In this manuscript, we describe a novel algorithm to perform reference-free variant detection and genotyping from GBS reads. Nonexact searches on a dynamic hash table of consensus sequences allow for efficient read clustering and sorting. This algorithm was integrated in the Next Generation Sequencing Experience Platform (NGSEP) to integrate the state-of-the-art variant detector already implemented in this tool. We performed benchmark experiments with three different empirical data sets of plants and animals with different population structures and ploidies, and sequenced with different GBS protocols at different read depths. These experiments show that NGSEP has comparable and in some cases better accuracy and always better computational efficiency compared to existing solutions. We expect that this new development will be useful for many research groups conducting population genetic studies in a wide variety of species.

Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review

The usefulness of genomic prediction (GP) for many animal and plant breeding programs has been highlighted for many studies in the last 20 years. In maize breeding programs, mostly dedicated to delivering more highly adapted and productive hybrids, this approach has been proved successful for both large- and small-scale breeding programs worldwide. Here, we present some of the strategies developed to improve the accuracy of GP in tropical maize, focusing on its use under low budget and small-scale conditions achieved for most of the hybrid breeding programs in developing countries. We highlight the most important outcomes obtained by the University of São Paulo (USP, Brazil) and how they can improve the accuracy of prediction in tropical maize hybrids. Our roadmap starts with the efforts for germplasm characterization, moving on to the practices for mating design, and the selection of the genotypes that are used to compose the training population in field phenotyping trials. Factors including population structure and the importance of non-additive effects (dominance and epistasis) controlling the desired trait are also outlined. Finally, we explain how the source of the molecular markers, environmental, and the modeling of genotype-environment interaction can affect the accuracy of GP. Results of 7 years of research in a public maize hybrid breeding program under tropical conditions are discussed, and with the great advances that have been made, we find that what is yet to come is exciting. The use of open-source software for the quality control of molecular markers, implementing GP, and envirotyping pipelines may reduce costs in an efficient computational manner. We conclude that exploring new models/tools using high-throughput phenotyping data along with large-scale envirotyping may bring more resolution and realism when predicting genotype performances. Despite the initial costs, mostly for genotyping, the GP platforms in combination with these other data sources can be a cost-effective approach for predicting the performance of maize hybrids for a large set of growing conditions.

Genetics and breeding for climate change in Orphan crops

Climate change is rapidly changing how we live, what we eat and produce, the crops we breed and the target traits. Previously underutilized orphan crops that are climate resilient are receiving much attention from the crops research community, as they are often the only crops left in the field after periods of extreme weather conditions. There are several orphan crops with incredible resilience to biotic and abiotic stresses. Some are nutritious, while others provide good sources of biofuel, medicine and other industrial raw materials. Despite these benefits, orphan crops are still lacking in important genetic and genomic resources that could be used to fast track their improvement and make their production profitable. Progress has been made in generating draft genomes of at least 28 orphan crops over the last decade, thanks to the reducing cost of sequencing. The implementation of a structured breeding program that takes advantage of additional modern crop improvement tools such as genomic selection, speed breeding, genome editing, high throughput phenotyping and breeding digitization would make rapid improvement of these orphan crops possible, but would require coordinated research investment. Other production challenges such as lack of adequate germplasm conservation, poor/non-existent seed systems and agricultural extension services, as well as poor marketing channels will also need to be improved if orphan crops were to be profitable. We review the importance of breeding orphan crops under the increasing effects of climate change, highlight existing gaps that need to be addressed and share some lessons to be learned from major crops.

Genomic Selection in Tropical Forage Grasses: Current Status and Future Applications

The world population is expected to be larger and wealthier over the next few decades and will require more animal products, such as milk and beef. Tropical regions have great potential to meet this growing global demand, where pasturelands play a major role in supporting increased animal production. Better forage is required in consonance with improved sustainability as the planted area should not increase and larger areas cultivated with one or a few forage species should be avoided. Although, conventional tropical forage breeding has successfully released well-adapted and high-yielding cultivars over the last few decades, genetic gains from these programs have been low in view of the growing food demand worldwide. To guarantee their future impact on livestock production, breeding programs should leverage genotyping, phenotyping, and envirotyping strategies to increase genetic gains. Genomic selection (GS) and genome-wide association studies play a primary role in this process, with the advantage of increasing genetic gain due to greater selection accuracy, reduced cycle time, and increased number of individuals that can be evaluated. This strategy provides solutions to bottlenecks faced by conventional breeding methods, including long breeding cycles and difficulties to evaluate complex traits. Initial results from implementing GS in tropical forage grasses (TFGs) are promising with notable improvements over phenotypic selection alone. However, the practical impact of GS in TFG breeding programs remains unclear. The development of appropriately sized training populations is essential for the evaluation and validation of selection markers based on estimated breeding values. Large panels of single-nucleotide polymorphism markers in different tropical forage species are required for multiple application targets at a reduced cost. In this context, this review highlights the current challenges, achievements, availability, and development of genomic resources and statistical methods for the implementation of GS in TFGs. Additionally, the prediction accuracies from recent experiments and the potential to harness diversity from genebanks are discussed. Although, GS in TFGs is still incipient, the advances in genomic tools and statistical models will speed up its implementation in the foreseeable future. All TFG breeding programs should be prepared for these changes.

A combined BSA-Seq and linkage mapping approach identifies genomic regions associated with Phytophthora root and crown rot resistance in squash

Two QTL mapping approaches were used to identify a total of six QTL associated with Phytophthora root and crown rot resistance in a biparental squash population. Phytophthora root and crown rot, caused by the soilborne oomycete pathogen Phytophthora capsici, leads to severe yield losses in squash (Cucurbita pepo). To identify quantitative trait loci (QTL) involved in resistance to this disease, we crossed a partially resistant squash breeding line with a susceptible zucchini cultivar and evaluated over 13,000 F₂ seedlings in a greenhouse screen. Bulked segregant analysis with whole genome resequencing (BSA-Seq) resulted in the identification of five genomic regions-on chromosomes 4, 5, 8, 12, and 16-featuring significant allele frequency differentiation between susceptible and resistant bulks in each of two independent replicates. In addition, we conducted linkage mapping using a population of 176 F₃ families derived from individually genotyped F₂ individuals. Variation in disease severity among these families was best explained by a four-QTL model, comprising the same loci identified via BSA-Seq on chromosomes 4, 5, and 8 as well as an additional locus on chromosome 19, for a combined total of six QTL identified between both methods. Loci, whether those identified by BSA-Seq or linkage mapping, were of small-to-moderate effect, collectively accounting for 28-35% and individually for 2-10% of the phenotypic variance explained. However, a multiple linear regression model using one marker in each BSA-Seq QTL could predict F_2:3 disease severity with only a slight drop in cross-validation accuracy compared to genomic prediction models using genome-wide markers. These results suggest that marker-assisted selection could be a suitable approach for improving Phytophthora crown and root rot resistance in squash.

Reliable genomic strategies for species classification of plant genetic resources

BACKGROUND

To address the need for easy and reliable species classification in plant genetic resources collections, we assessed the potential of five classifiers (Random Forest, Neighbour-Joining, 1-Nearest Neighbour, a conservative variety of 3-Nearest Neighbours and Naive Bayes) We investigated the effects of the number of accessions per species and misclassification rate on classification success, and validated theirs generic value results with three complete datasets.

RESULTS

We found the conservative variety of 3-Nearest Neighbours to be the most reliable classifier when varying species representation and misclassification rate. Through the analysis of the three complete datasets, this finding showed generic value. Additionally, we present various options for marker selection for classification taks such as these.

CONCLUSIONS

Large-scale genomic data are increasingly being produced for genetic resources collections. These data are useful to address species classification issues regarding crop wild relatives, and improve genebank documentation. Implementation of a classification method that can improve the quality of bad datasets without gold standard training data is considered an innovative and efficient method to improve gene bank documentation.

Genome-wide association studies for agronomical traits in winter rice accessions of Assam

The 297 winter rice accessions of Assam, North East India were genotyped by sequencing (GBS). The 50,985 high-quality SNPs were filtered and assigned to 12 rice chromosomes. The population structure analysis revealed three major subgroups SG1, SG2, and SG3 consisting of 30, 8, and 143 accessions respectively. The remaining 116 accessions were grouped as admixture population. Phenotypic data were recorded on13 agronomical traits for genome-wide association studies (GWAS). The 60 significant marker-trait associations (MTAs) were identified for 11 agronomical traits, which explained 0 to 15% of phenotypic variance (PV). A QTL 'hot spot' was detected near the centromeric region on chromosome 6. The identified QTLs may be validated and utilized in 'genomics assisted breeding' for improvement of existing rice cultivars of Assam and North East India.

Niche specificity influences gene flow across fine-scale habitat mosaics in Succulent Karoo plants

While the tempo of diversification in biodiversity hotspots has received much attention, the spatial scale of diversification has often been overlooked. Addressing this deficiency requires understanding the drivers of population divergence and the spatial scales at which they operate in species-rich clades and ecosystems. South Africa's Succulent Karoo (SK) hotspot provides an excellent system for such research, being both compact (ca. 110,000 km² ) and home to spectacular in-situ radiations, such as the ruschioid Aizoaceae. Here we use GBS to document genetic structure in two co-occurring ruschioid species, at both coarse (>10 km) and fine (<500 m) spatial scales. Where Ruschia burtoniae shows strong between-population genetic differentiation and no gene flow, Conophytum calculus shows weak differentiation, with high levels of admixture suggesting recent or ongoing gene flow. Community analysis and transplant experiments reveal that R. burtoniae occupies a narrow, low-pH edaphic niche, and at scales of a few hundred metres, areas of elevated genetic turnover correspond to patches of edaphically unsuitable habitat. In contrast, C. calculus occupies a broader niche and exhibits isolation-by-distance without a habitat effect. We suggest that edaphic specialisation, coupled with highly restricted seed and pollen dispersal in heterogeneous landscapes, has played a major role in driving rapid diversification at small spatial scales in this system. However, the contrasting patterns in our study species show that these factors do not influence all organisms uniformly, being strongly modulated by lineage-specific traits that influence both the spatial scale of gene flow and habitat specificity.

Analysis and Identification of QTL for Resistance to Sclerotinia sclerotiorum in Pea (Pisum sativum L.)

White mold caused by Sclerotinia sclerotiorum is an important constraint to field pea (Pisum sativum L.) production worldwide. To transfer white mold resistance into an adapted background, and study the genetics of the disease, two recombinant inbred line (RIL) populations (PRIL17 and PRIL19) were developed by crossing two partially resistant plant introductions with two susceptible pea cultivars. PRIL17 (Lifter × PI240515), and PRIL19 (PI169603 × Medora) were evaluated for resistance to white mold by measuring lesion expansion inhibition (LEI) and nodal transmission inhibition (NTI) at 3, 7, and 14 days post inoculation (dpi) under controlled environmental conditions. Lesion expansion inhibition percentage (LEIP), survival rate (SR), and area under disease progress curves (AUDPC) were also calculated accordingly. Because of a positive correlation between LEI and NTI with height, short and long internode individuals of each population were analyzed separately to avoid any confounding effect of height to pathogen response. A total of 22 short genotypes demonstrated partial resistance based on at least two Porter's resistance criteria. Only two pea genotypes with partial resistance to white mold (PRIL19-18 and PRIL19-124) had both semi-leafless (afila) and short internode traits. Both the RIL populations were genotyped using genotyping by sequencing (GBS). For PRIL17 and PRIL19, genetic maps were constructed from a total of 1,967 and 1,196 single nucleotide polymorphism (SNP) and spanned over 1,494 cM and 1,415 cM representing seven and nine linkage groups, respectively. A consensus map constructed using data from both populations, had 1,486 unique SNPs over 2,461 cM belonging to seven linkage groups. Inclusive composite interval mapping (ICIM) identified thirteen quantitative trait loci (QTL) associated with white mold resistance traits in both populations. Three of them were co-located with height genes (a morphological trait that reduces infection risk and acts as disease avoidance) and the other ten QTL were associated with two forms of physiological resistance (seven for LEI and three for NTI) with LOD and r2 ranging from 3.0 to 28.5 and 5.1 to 64.3, respectively. The development of resistance lines, genetic dissection and identification of markers associated will help accelerate breeding efforts for white mold resistance using molecular breeding approaches.

Quantitative Trait Loci Associated with Gray Leaf Spot Resistance in St. Augustinegrass

Gray leaf spot (GLS), caused by Magnaporthe grisea, is a major fungal disease of St. Augustinegrass (Stenotaphrum secundatum), causing widespread blighting of the foliage under warm, humid conditions. To identify quantitative trait loci (QTL) controlling GLS resistance, an F₁ mapping population consisting of 153 hybrids was developed from crosses between cultivar Raleigh (susceptible parent) and plant introduction PI 410353 (resistant parent). Single-nucleotide polymorphism (SNP) markers generated from genotyping-by-sequencing constituted nine linkage groups for each parental linkage map. The Raleigh map consisted of 2,257 SNP markers and spanned 916.63 centimorgans (cM), while the PI 410353 map comprised 511 SNP markers and covered 804.27 cM. GLS resistance was evaluated under controlled environmental conditions with measurements of final disease incidence and lesion length. Additionally, two derived traits, area under the disease progress curve and area under the lesion expansion curve, were calculated for QTL analysis. Twenty QTL were identified as being associated with these GLS resistance traits, which explained 7.6 to 37.2% of the total phenotypic variation. Three potential GLS QTL "hotspots" were identified on two linkage groups: P2 (106.26 to 110.36 cM and 113.15 to 116.67 cM) and P5 (17.74 to 19.28 cM). The two major effect QTL glsp2.3 and glsp5.2 together reduced 20.2% of disease incidence in this study. Sequence analysis showed that two candidate genes encoding β-1,3-glucanases were found in the intervals of two QTL, which might function in GLS resistance response. These QTL and linked markers can be potentially used to assist the transfer of GLS resistance genes to elite St. Augustinegrass breeding lines.

Fast-GBS v2.0: an analysis toolkit for genotyping-by-sequencing data

Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.

Identification of resistance loci in Chinese and Canadian canola/rapeseed varieties against Leptosphaeria maculans based on genome-wide association studies

Background

The fungal pathogen Leptosphaeria maculans (Lm). causes blackleg disease on canola/rapeseed in many parts of the world. It is important to use resistant cultivars to manage the disease and minimize yield losses. In this study, twenty-two Lm isolates were used to identify resistance genes in a collection of 243 canola/rapeseed (Brassica napus L.) accessions from Canada and China. These Lm isolates carry different compliments of avirulence genes, and the investigation was based on a genome-wide association study (GWAS) and genotype-by-sequencing (GBS).

Results

Using the CROP-SNP pipeline, a total of 81,471 variants, including 78,632 SNPs and 2839 InDels, were identified. The GWAS was performed using TASSEL 5.0 with GLM + Q model. Thirty-two and 13 SNPs were identified from the Canadian and Chinese accessions, respectively, tightly associated with blackleg resistance with P values < 1 × 10^− 4. These SNP loci were distributed on chromosomes A03, A05, A08, A09, C01, C04, C05, and C07, with the majority of them on A08 followed by A09 and A03. The significant SNPs identified on A08 were all located in a 2010-kb region and associated with resistance to 12 of the 22 Lm isolates. Furthermore, 25 resistance gene analogues (RGAs) were identified in these regions, including two nucleotide binding site (NBS) domain proteins, fourteen RLKs, three RLPs and six TM-CCs. These RGAs can be the potential candidate genes for blackleg resistance.

Conclusion

This study provides insights into potentially new genomic regions for discovery of additional blackleg resistance genes. The identified regions associated with blackleg resistance in the germplasm collection may also contribute directly to the development of canola varieties with novel resistance genes against blackleg of canola.

Expanded functionality, increased accuracy, and enhanced speed in the de novo genotyping-by-sequencing pipeline GBS-SNP-CROP

Summary

GBS-SNP-CROP is a bioinformatics pipeline originally developed to support the cost-effective genome-wide characterization of plant genetic resources through paired-end genotyping-by-sequencing (GBS), particularly in the absence of a reference genome. Since its 2016 release, the pipeline’s functionality has greatly expanded, its computational efficiency has improved, and its applicability to a broad set of genomic studies for both plants and animals has been demonstrated. This note details the suite of improvements to date, as realized in GBS-SNP-CROP v.4.0, with specific attention paid to a new integrated metric that facilitates reliable variant identification despite the complications of homologs. Using the new de novo GBS read simulator GBS-Pacecar, also introduced in this note, results show an improvement in overall pipeline accuracy from 66% (v.1.0) to 84% (v.4.0), with a time saving of ∼70%. Both GBS-SNP-CROP versions significantly outperform TASSEL-UNEAK; and v.4.0 resolves the issue of non-overlapping variant calls observed between UNEAK and v.1.0.

Availability and implementation

GBS-SNP-CROP source code and user manual are available at https://github.com/halelab/GBS-SNP-CROP. The GBS read simulator GBS-Pacecar is available at https://github.com/halelab/GBS-Pacecar.

Supplementary information

Supplementary data are available at Bioinformatics online.

A Cost Reduced Variant of Epi-Genotyping by Sequencing for Studying DNA Methylation in Non-model Organisms

Reference-free reduced representation bisulfite sequencing uses enzymatic digestion for reducing genome complexity and allows detection of markers to study DNA methylation of a high number of individuals in natural populations of non-model organisms. Current methods like epiGBS enquire the use of a higher number of methylated DNA oligos with a significant cost (especially for small labs and first pilot studies). In this paper, we present a modification of this epiGBS protocol that requires the use of only one hemimethylated P2 (common) adapter, which is combined with unmethylated barcoded adapters. The unmethylated cytosines of one chain of the barcoded adapter are replaced by methylated cytosines using nick translation with methylated cytosines in dNTP solution. The basic version of our technique uses only one restriction enzyme, and as a result, genomic fragments are integrated into two orientations with respect to the adapter sequences. Comparing the sequences of two chain orientations makes it possible to reconstruct the original sequence before bisulfite treatment with the help of standard software and newly developed software written in C and described here. We provide a proof of concept via data obtained from almond (Prunus dulcis). Example data and a detailed description of the complete software pipeline starting from the raw reads up until the final differentially methylated cytosines are given in Supplementary Material making this technique accessible to non-expert computer users. The adapter design showed in this paper should allow the use of a two restriction enzyme approach with minor changes in software parameters.

Optimization of Genotype by Sequencing data for phylogenetic purposes

• Herein we propose a framework for assembling and analyzing Genotype by Sequencing (GBS) data to better understand evolutionary relationships within a group of closely related species using the mastiff bats (Molossus) as our model system. Many species within this genus have low-levels of genetic variation within and between morphologically distinct species, and the relationships among them remain unresolved using traditional Sanger sequencing methods. Given that both de novo and reference genome pipelines can be used to assemble next generation sequences, and that several tree inference methodologies have been proposed for single nucleotide polymorphism (SNP) data, we test whether different alignments and phylogenetic approaches produce similar results. We also examined how the process of SNP identification and mapping can affect the consistency of the analyses. Different alignments and phylogenetic inferences produced consistent results, supporting the GBS approach for answering evolutionary questions on a macroevolutionary scale when the genetic distance among phenotypically identifiable clades is low. We highlight the importance of exploring the relationships among groups using different assembly assumptions and also distinct phylogenetic inference methods, particularly when addressing phylogenetic questions in genetic and morphologically conservative taxa. • The method uses the comparison of several filter settings, alignments, and tree inference approaches on Genotype by Sequencing data. • Consistent results were found among several approaches. • The methodology successfully recovered well supported species boundaries and phylogenetic relationships among species of mastiff bats not hypothesized by previous methods.

Development of species-specific molecular markers in Vanilla for seedling selection of hybrids

Vanilla planifolia is the primary botanical source of vanilla extract used globally in various foods and beverages. V. planifolia has a global distribution based on a few foundational clones and therefore has limited genetic diversity. Many Vanilla species easily hybridize with V. planifolia and could be a source of valuable genetic traits like increased vanillin content, disease resistance, or early flowering. While breeding Vanilla hybrids may improve plant performance, basic molecular tools for this species are lacking. DNA-based molecular markers are the most efficient method to validate hybrid progeny, detect hybrids in commercial plantings, and identify unknown accessions. This study used publicly available sequence data to develop species-specific, qRT-PCR-based molecular markers for Vanilla. Over 580,000 assembled sequence fragments were filtered for species specificity and twenty-two targets were selected for qRT-PCR screening. Ten targets differentially amplified among V. planifolia, V. pompona, V. phaeantha, and V. palmarum with ΔCT values as high as 17.58 between species. The ten targets were used to validate the parentage of hybrid progeny from controlled crosses with most hybrid progeny showing amplification patterns similar to both parents. The ten targets were also used to screen sixteen Vanilla species for specificity, and supported species assignments for unknown accessions including the detection of putative hybrids. This is the first report using species-specific, qRT-PCR-based molecular markers in Vanilla. These markers are inexpensive, simple to develop, and can rapidly screen large populations. These methods will enable the further development of species-specific molecular markers when creating Vanilla interspecific hybrid populations.

Genome-Wide SNP discovery and genomic characterization in avocado (Persea americana Mill.)

Modern crop breeding is based on the use of genetically and phenotypically diverse plant material and, consequently, a proper understanding of population structure and genetic diversity is essential for the effective development of breeding programs. An example is avocado, a woody perennial fruit crop native to Mesoamerica with an increasing popularity worldwide. Despite its commercial success, there are important gaps in the molecular tools available to support on-going avocado breeding programs. In order to fill this gap, in this study, an avocado 'Hass' draft assembly was developed and used as reference to study 71 avocado accessions which represent the three traditionally recognized avocado horticultural races or subspecies (Mexican, Guatemalan and West Indian). An average of 5.72 M reads per individual and a total of 7,108 single nucleotide polymorphism (SNP) markers were produced for the 71 accessions analyzed. These molecular markers were used in a study of genetic diversity and population structure. The results broadly separate the accessions studied according to their botanical race in four main groups: Mexican, Guatemalan, West Indian and an additional group of Guatemalan × Mexican hybrids. The high number of SNP markers developed in this study will be a useful genomic resource for the avocado community.

Associations between genomic ancestry, genome size and capitula morphology in the invasive meadow knapweed hybrid complex (Centaurea × moncktonii) in eastern North America

Plant invasions are prime opportunities for studying hybridization and the nature of species boundaries, but hybrids also complicate the taxonomic treatment and management of introduced taxa. In this study, we use population genomics to estimate the extent of genomic admixture and test for its association with morphology and genome size in a hybrid complex of knapweeds invasive to North America: meadow knapweed (Centaurea × moncktonii) and its parental species (C. jacea and C. nigra). We sampled 20 populations from New York and Vermont, USA, and used genotyping by sequencing to identify single nucleotide polymorphisms in order to estimate genome-wide ancestry and classify individuals into hybrid genotype classes. We then tested for association between degree of genomic introgression and variation in a subset of traits diagnostic for the parental taxa, namely capitula morphology and monoploid genome size. Genomic clustering revealed two clearly defined lineages, as well as many admixed individuals forming a continuous gradation of introgression. Individual assignments to hybrid genotype classes revealed many advanced generation intercrosses and backcrosses, suggesting introgression has been extensive and unimpeded by strong reproductive barriers between taxa. Variation in capitula traits between the two unadmixed, presumed parental, lineages exhibited continuous, and in some cases transgressive, segregation among introgressed hybrids. Genome size was also divergent between lineages, although advanced generation hybrids had smaller genomes relative to additive expectations. Our study demonstrates deep introgression between the porous genomes of a hybrid invasive species complex. In addition to strong associations among genomic ancestry, genome size and morphology, hybrids expressed more extreme phenotypic values for capitula traits and genome size, indicating transgressive segregation, as well as a bias towards smaller genomes, possibly due to genomic downsizing. Future studies will apply these results to experimentally test how introgression, transgressive segregation and genome size reduction interact to confer invasiveness.

PLANET-SNP pipeline: PLants based ANnotation and Establishment of True SNP pipeline

Acute prediction of SNPs (Single Nucleotide Polymorphisms) from high throughput sequencing data is a challenging problem, having potential to explore possible variation within plants species. For the extraction of profitable information from bulk of data, machine learning (ML) could lead to development of accurate model based on the learning of prior information. We performed state of art, in-depth learning on six different plant species. Comparative evaluation of five different algorithms showed that Random Forest substantially outperformed in selection of potential SNPs, with markedly improved prediction accuracy via 10-fold cross validation technique and integrated in system known as PLANET-SNP. We present the accurate method to extract the potential SNPs with user specific customizable parameters. It will facilitate the identification of efficient and functional SNPs in most easy and intuitive way. PLANET-SNP pipeline is very flexible in terms of data input and output formats. PLANET-SNP Pipeline is available at http://www.ncgd.nbri.res.in/PLANET-SNP-Pipeline.aspx.

Mapping non-host resistance to the stem rust pathogen in an interspecific barberry hybrid

BACKGROUND

Non-host resistance (NHR) presents a compelling long-term plant protection strategy for global food security, yet the genetic basis of NHR remains poorly understood. For many diseases, including stem rust of wheat [causal organism Puccinia graminis (Pg)], NHR is largely unexplored due to the inherent challenge of developing a genetically tractable system within which the resistance segregates. The present study turns to the pathogen's alternate host, barberry (Berberis spp.), to overcome this challenge.

RESULTS

In this study, an interspecific mapping population derived from a cross between Pg-resistant Berberis thunbergii (Bt) and Pg-susceptible B. vulgaris was developed to investigate the Pg-NHR exhibited by Bt. To facilitate QTL analysis and subsequent trait dissection, the first genetic linkage maps for the two parental species were constructed and a chromosome-scale reference genome for Bt was assembled (PacBio + Hi-C). QTL analysis resulted in the identification of a single 13 cM region (~ 5.1 Mbp spanning 13 physical contigs) on the short arm of Bt chromosome 3. Differential gene expression analysis, combined with sequence variation analysis between the two parental species, led to the prioritization of several candidate genes within the QTL region, some of which belong to gene families previously implicated in disease resistance.

CONCLUSIONS

Foundational genetic and genomic resources developed for Berberis spp. enabled the identification and annotation of a QTL associated with Pg-NHR. Although subsequent validation and fine mapping studies are needed, this study demonstrates the feasibility of and lays the groundwork for dissecting Pg-NHR in the alternate host of one of agriculture's most devastating pathogens.

Clonal diversity impacts coral cover in Acropora cervicornisthickets: Potential relationships between density, growth, and polymorphisms

As coral reefs decline, cryptic sources of resistance and resilience to stress may be increasingly important for the persistence of these communities. Among these sources, inter- and intraspecific diversity remain understudied on coral reefs but extensively impact a variety of traits in other ecosystems. We use a combination of field and sequencing data at two sites in Florida and two in the Dominican Republic to examine clonal diversity and genetic differentiation of high- and low-density aggregations of the threatened coral Acropora cervicornisin the Caribbean. We find that high-density aggregations called thickets are composed of up to 30 genotypes at a single site, but 47% of genotypes are also found as isolated, discrete colonies outside these aggregations. Genet-ramet ratios are comparable for thickets (0.636) and isolated colonies after rarefaction (0.569), suggesting the composition of each aggregation is not substantially different and highlighting interactions between colonies as a potential influence on structure. There are no differences in growth rate, but a significant positive correlation between genotypic diversity and coral cover, which may be due to the influence of interactions between colonies on survivorship or fragment retention during asexual reproduction. Many polymorphisms distinguish isolated colonies from thickets despite the shared genotypes found here, including putative nonsynonymous mutations that change amino acid sequence in 25 loci. These results highlight intraspecific diversity as a density-dependent factor that may impact traits important for the structure and function of coral reefs.

'apparent': a simple and flexible R package for accurate SNP-based parentage analysis in the absence of guiding information

Background

The accurate determination of parent-progeny relationships within both in situ natural populations and ex situ genetic resource collections can greatly enhance plant breeding/domestication efforts and support plant genetic resource conservation strategies. Although a range of parentage analysis tools are available, none are designed to infer such relationships using genome-wide single nucleotide polymorphism (SNP) data in the complete absence of guiding information, such as generational groups, partial pedigrees, or genders. The R package (‘apparent’) developed and presented here addresses this gap.

Results

‘apparent’ adopts a novel strategy of parentage analysis based on a test of genetic identity between a theoretically expected progeny (EP_ij), whose genotypic state can be inferred at all homozygous loci for a pair of putative parents (i and j), and all potential offspring (PO_k), represented by the k individuals of a given germplasm collection. Using the Gower Dissimilarity metric (GD), genetic identity between EP_ij and PO_k is taken as evidence that individuals i and j are the true parents of offspring k. Significance of a given triad (parental pair_ij + offspring_k) is evaluated relative to the distribution of all GD_ij|k values for the population. With no guiding information provided, ‘apparent’ correctly identified the parental pairs of 15 lines of known pedigree within a test population of 77 accessions of Actinidia arguta, a performance unmatched by five other commonly used parentage analysis tools. In the case of an inconclusive triad analysis due to the absence of one parent from the test population, ‘apparent’ can perform a subsequent dyad analysis to identify a likely single parent for a given offspring. Average dyad analysis accuracy was 73.3% in the complete absence of pedigree information but increased to 100% when minimal generational information (adults vs. progeny) was provided.

Conclusions

The ‘apparent’ R package is a fast and accurate parentage analysis tool that uses genome-wide SNP data to identify parent-progeny relationships within populations for which no a priori knowledge of family structure exists.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2662-3) contains supplementary material, which is available to authorized users.

A high-throughput SNP discovery strategy for RNA-seq data

Background

Single nucleotide polymorphisms (SNP) have been applied as important molecular markers in genetics and breeding studies. The rapid advance of next generation sequencing (NGS) provides a high-throughput means of SNP discovery. However, SNP development is limited by the availability of reliable SNP discovery methods. Especially, the optimum assembler and SNP caller for accurate SNP prediction from next generation sequencing data are not known.

Results

Herein we performed SNP prediction based on RNA-seq data of peach and mandarin peel tissue under a comprehensive comparison of two paired-end read lengths (125 bp and 150 bp), five assemblers (Trinity, IDBA, oases, SOAPdenovo, Trans-abyss) and two SNP callers (GATK and GBS). The predicted SNPs were compared with the authentic SNPs identified via PCR amplification followed by gene cloning and sequencing procedures. A total of 40 and 240 authentic SNPs were presented in five anthocyanin biosynthesis related genes in peach and in nine carotenogenic genes in mandarin. Putative SNPs predicted from the same RNA-seq data with different strategies led to quite divergent results. The rate of false positive SNPs was significantly lower when the paired-end read length was 150 bp compared with 125 bp. Trinity was superior to the other four assemblers and GATK was substantially superior to GBS due to a low rate of missing authentic SNPs. The combination of assembler Trinity, SNP caller GATK, and the paired-end read length 150 bp had the best performance in SNP discovery with 100% accuracy both in peach and in mandarin cases. This strategy was applied to the characterization of SNPs in peach and mandarin transcriptomes.

Conclusions

Through comparison of authentic SNPs obtained by PCR cloning strategy and putative SNPs predicted from different combinations of five assemblers, two SNP callers, and two paired-end read lengths, we provided a reliable and efficient strategy, Trinity-GATK with 150 bp paired-end read length, for SNP discovery from RNA-seq data. This strategy discovered SNP at 100% accuracy in peach and mandarin cases and might be applicable to a wide range of plants and other organisms.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5533-4) contains supplementary material, which is available to authorized users.

Translocation of a parthenogenesis gene candidate to an alternate carrier chromosome in apomictic Brachiaria humidicola

BACKGROUND

The apomictic reproductive mode of Brachiaria (syn. Urochloa) forage species allows breeders to faithfully propagate heterozygous genotypes through seed over multiple generations. In Brachiaria, reproductive mode segregates as single dominant locus, the apospory-specific genomic region (ASGR). The AGSR has been mapped to an area of reduced recombination on Brachiaria decumbens chromosome 5. A primer pair designed within ASGR-BABY BOOM-like (BBML), the candidate gene for the parthenogenesis component of apomixis in Pennisetum squamulatum, was diagnostic for reproductive mode in the closely related species B. ruziziensis, B. brizantha, and B. decumbens. In this study, we used a mapping population of the distantly related commercial species B. humidicola to map the ASGR and test for conservation of ASGR-BBML sequences across Brachiaria species.

RESULTS

Dense genetic maps were constructed for the maternal and paternal genomes of a hexaploid (2n = 6x = 36) B. humidicola F₁ mapping population (n = 102) using genotyping-by-sequencing, simple sequence repeat, amplified fragment length polymorphism, and transcriptome derived single nucleotide polymorphism markers. Comparative genomics with Setaria italica provided confirmation for x = 6 as the base chromosome number of B. humidicola. High resolution molecular karyotyping indicated that the six homologous chromosomes of the sexual female parent paired at random, whereas preferential pairing of subgenomes was observed in the apomictic male parent. Furthermore, evidence for compensated aneuploidy was found in the apomictic parent, with only five homologous linkage groups identified for chromosome 5 and seven homologous linkage groups of chromosome 6. The ASGR mapped to B. humidicola chromosome 1, a region syntenic with chromosomes 1 and 7 of S. italica. The ASGR-BBML specific PCR product cosegregated with the ASGR in the F₁ mapping population, despite its location on a different carrier chromosome than B. decumbens.

CONCLUSIONS

The first dense molecular maps of B. humidicola provide strong support for cytogenetic evidence indicating a base chromosome number of six in this species. Furthermore, these results show conservation of the ASGR across the Paniceae in different chromosomal backgrounds and support postulation of the ASGR-BBML as candidate genes for the parthenogenesis component of apomixis.

Translocation of a parthenogenesis gene candidate to an alternate carrier chromosome in apomictic Brachiaria humidicola

Background

The apomictic reproductive mode of Brachiaria (syn. Urochloa) forage species allows breeders to faithfully propagate heterozygous genotypes through seed over multiple generations. In Brachiaria, reproductive mode segregates as single dominant locus, the apospory-specific genomic region (ASGR). The AGSR has been mapped to an area of reduced recombination on Brachiaria decumbens chromosome 5. A primer pair designed within ASGR-BABY BOOM-like (BBML), the candidate gene for the parthenogenesis component of apomixis in Pennisetum squamulatum, was diagnostic for reproductive mode in the closely related species B. ruziziensis, B. brizantha, and B. decumbens. In this study, we used a mapping population of the distantly related commercial species B. humidicola to map the ASGR and test for conservation of ASGR-BBML sequences across Brachiaria species.

Results

Dense genetic maps were constructed for the maternal and paternal genomes of a hexaploid (2n = 6x = 36) B. humidicola F₁ mapping population (n = 102) using genotyping-by-sequencing, simple sequence repeat, amplified fragment length polymorphism, and transcriptome derived single nucleotide polymorphism markers. Comparative genomics with Setaria italica provided confirmation for x = 6 as the base chromosome number of B. humidicola. High resolution molecular karyotyping indicated that the six homologous chromosomes of the sexual female parent paired at random, whereas preferential pairing of subgenomes was observed in the apomictic male parent. Furthermore, evidence for compensated aneuploidy was found in the apomictic parent, with only five homologous linkage groups identified for chromosome 5 and seven homologous linkage groups of chromosome 6. The ASGR mapped to B. humidicola chromosome 1, a region syntenic with chromosomes 1 and 7 of S. italica. The ASGR-BBML specific PCR product cosegregated with the ASGR in the F₁ mapping population, despite its location on a different carrier chromosome than B. decumbens.

Conclusions

The first dense molecular maps of B. humidicola provide strong support for cytogenetic evidence indicating a base chromosome number of six in this species. Furthermore, these results show conservation of the ASGR across the Paniceae in different chromosomal backgrounds and support postulation of the ASGR-BBML as candidate genes for the parthenogenesis component of apomixis.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5392-4) contains supplementary material, which is available to authorized users.

GBS-derived SNP catalogue unveiled wide genetic variability and geographical relationships of Italian olive cultivars

Information on the distribution of genetic variation is essential to preserve olive germplasm from erosion and to recover alleles lost through selective breeding. In addition, knowledge on population structure and genotype-phenotype associations is crucial to support modern olive breeding programs that must respond to new environmental conditions imposed by climate change and novel biotic/abiotic stressors. To further our understanding of genetic variation in the olive, we performed genotype-by-sequencing on a panel of 94 Italian olive cultivars. A reference-based and a reference-independent SNP calling pipeline generated 22,088 and 8,088 high-quality SNPs, respectively. Both datasets were used to model population structure via parametric and non parametric clustering. Although the two pipelines yielded a 3-fold difference in the number of SNPs, both described wide genetic variability among our study panel and allowed individuals to be grouped based on fruit weight and the geographical area of cultivation. Multidimensional scaling analysis on identity-by-state allele-sharing values as well as inference of population mixtures from genome-wide allele frequency data corroborated the clustering pattern we observed. These findings allowed us to formulate hypotheses about geographical relationships of Italian olive cultivars and to confirm known and uncover novel cases of synonymy.

Surveying the genome and constructing a high-density genetic map of napiergrass (Cenchrus purpureus Schumach)

Napiergrass (Cenchrus purpureus Schumach) is a tropical forage grass and a promising lignocellulosic biofuel feedstock due to its high biomass yield, persistence, and nutritive value. However, its utilization for breeding has lagged behind other crops due to limited genetic and genomic resources. In this study, next-generation sequencing was first used to survey the genome of napiergrass. Napiergrass sequences displayed high synteny to the pearl millet genome and showed expansions in the pearl millet genome along with genomic rearrangements between the two genomes. An average repeat content of 27.5% was observed in napiergrass including 5,339 simple sequence repeats (SSRs). Furthermore, to construct a high-density genetic map of napiergrass, genotyping-by-sequencing (GBS) was employed in a bi-parental population of 185 F₁ hybrids. A total of 512 million high quality reads were generated and 287,093 SNPs were called by using multiple de-novo and reference-based SNP callers. Single dose SNPs were used to construct the first high-density linkage map that resulted in 1,913 SNPs mapped to 14 linkage groups, spanning a length of 1,410 cM and a density of 1 marker per 0.73 cM. This map can be used for many further genetic and genomic studies in napiergrass and related species.