Optimizing ddRADseq in Non-Model Species: A Case Study in Eucalyptus dunnii Maiden

Comparison of ddRAD derived genome-wide SSR markers in outbred and inbred Swiss albino mice

Genetic monitoring of inbred laboratory animal populations, developed at any laboratory, is one of the key elements of quality control and their colony management. The present study aimed to mine microsatellite (or SSR) markers from double digest restriction-site associated DNA (ddRAD) sequencing data of outbred foundation stock and F9 inbred generation of Swiss albino mice. Genomic DNA (12 F0 outbred and 12 F9 inbred) was isolated from tail tissue samples of F0 outbred and F9 inbred Swiss albino mice and processed for genotyping by sequencing using ddRAD platform. Double digestion of DNA was done using EcoR1 and Mse1 enzymes, and ddRAD data was subsequently analysed to identify and characterize microsatellite markers at genome-wide level. The analysis involved three key steps: pre-processing of reads, single sequence repeat (SSR) mining, and primer designing using different software i.e., PEAR, stacks and QDD. A total of 508 and 353 SSR motifs were identified in the outbred and inbred groups, respectively. Additionally, 828 and 551 primer sets were designed for the outbred and inbred groups, respectively. Furthermore, SSR loci specific to the outbred and inbred groups were also identified. Among these, eight SSR motifs (three each specific to the outbred and inbred groups, and two common) were validated using PCR amplification and gel electrophoresis. The designed primer sets successfully amplified respective SSR loci and produced reproducible bands on gel electrophoresis. The validated microsatellites were mapped to specific chromosomal locations using NCBI BLASTN with Mus musculus as the reference genome. In conclusion, the present study reports mining of SSR loci in outbred and inbred mice population. SSR loci were found to be more abundant and diverse in outbred population as compared to the inbred population. The unique SSRs identified for outbred and inbred groups will be helpful in checking the strain purity, marker assisted selection, and breeding programs without need for repeating the ddRAD sequencing in other laboratory animal population.

Introgression of dwarfing allele dw1 reduced seed dormancy and increased pre-harvest sprouting susceptibility in grain sorghum converted lines

Grain sorghum (Sorghum bicolor L. moench) stands as a globally significant cereal crop but the adversity of pre-harvest sprouting (PHS) caused by reduced grain dormancy and moist conditions prior to harvest remains unsolved. Here, we identified a dormancy QTL using a Redlan×IS9530 RIL population, where parent lines are low in tannins and early flowering but otherwise contrasting in grain dormancy and plant height. We phenotyped this population in 2 years with informative PHS-related traits (grain germination index, embryo sensitivity to abscisic acid and in one year the actual natural sprouting), revealing a robust dormancy QTL in chromosome 9 (qDOR-9). This signal overlapped with associations found for plant height (caused by the dw1 locus, used for decades in sorghum improvement) and time to flowering. The effect of qDOR-9 was validated with independent near isogenic lines carrying the IS9530 "dormant" allele while maintaining the Redlan dw1 "short" allele. Additional analyses on Yellow Milo, from which the dw1 allele originated, implied that a low dormancy allele close to dw1 was introduced to Redlan-as well as to many other currently productive lines-by breeding efforts aimed at decreasing plant height, thus illustrating a new instance of genome erosion canalised by crop breeding. However, the introgression of qDOR-9 could enhance PHS tolerance in cultivated dw1-carrying backgrounds without affecting plant stature.

Combining Linkage and Association Mapping Approaches to Study the Genetic Architecture of Verticillium Wilt Resistance in Sunflower

Sunflower Verticillium Wilt and Leaf Mottle (SVW), caused by Verticillium dahliae Kleb., is a globally prevalent disease affecting sunflower production. In this study, we identified a major quantitative trait locus (QTL) on chromosome 10 and other genomic regions associated with SVW resistance by integrating biparental and association mapping in sunflower populations from the National Institute of Agricultural Technology. Nine replicated field trials were conducted in highly infested V. dahliae reservoirs to assess disease incidence and severity. Both mapping populations were genotyped using double-digest restriction-site-associated DNA sequencing (ddRADseq). Association mapping with 18,161 SNPs and biparental QTL mapping with 1769 SNPs identified a major QTL on chromosome 10 explaining up to 30% of phenotypic variation for disease incidence at flowering and for the area under the disease progress curve for disease incidence, and which contributes to a lesser extent to disease severity reduction. Additional QTLs on chromosomes 17, 8, 9, 14, 13, and 11 were associated with reduced disease incidence, severity, or both. Candidate genes were identified within these associated regions, 39 of which are in the major QTL on Chromosome 10. These findings demonstrate the value of integrating complementary QTL mapping strategies for validating resistance loci and advancing sunflower breeding for SVW resistance.

Genome-Wide Diversity in Lowland and Highland Maize Landraces From Southern South America: Population Genetics Insights to Assist Conservation

Maize (Zea mays ssp. mays L.) landraces are traditional American crops with high genetic variability that conform a source of original alleles for conventional maize breeding. Northern Argentina, one the southernmost regions of traditional maize cultivation in the Americas, harbours around 57 races traditionally grown in two regions with contrasting environmental conditions, namely, the Andean mountains in the Northwest and the tropical grasslands and Atlantic Forest in the Northeast. These races encounter diverse threats to their genetic diversity and persistence in their regions of origin, with climate change standing out as one of the major challenges. In this work, we use genome-wide SNPs derived from ddRADseq to study the genetic diversity of individuals representing the five groups previously described for this area. This allowed us to distinguish two clearly differentiated gene pools, the highland northwestern maize (HNWA) and the floury northeastern maize (FNEA). Subsequently, we employed essential biodiversity variables at the genetic level, as proposed by the Group on Earth Observations Biodiversity Observation Network (GEO BON), to evaluate the conservation status of these two groups. This assessment encompassed genetic diversity (Pi), inbreeding coefficient (F) and effective population size (Ne). FNEA showed low Ne values and high F values, while HNWA showed low Ne values and low Pi values, indicating that further genetic erosion is imminent for these landraces. Outlier detection methods allowed identification of putative adaptive genomic regions, consistent with previously reported flowering-time loci and chromosomal regions displaying introgression from the teosinte Zea mays ssp. mexicana. Finally, species distribution models were obtained for two future climate scenarios, showing a notable reduction in the potential planting area of HNWA and a shift in the cultivation areas of FNEA. These results suggest that maize landraces from Northern Argentina may be unable to cope with climate change. Therefore, active conservation policies are advisable.

Comparison of ddRADseq and EUChip60K SNP genotyping systems for population genetics and genomic selection in Eucalyptus dunnii (Maiden)

Eucalyptus dunnii is one of the most important Eucalyptus species for short-fiber pulp production in regions where other species of the genus are affected by poor soil and climatic conditions. In this context, E. dunnii holds promise as a resource to address and adapt to the challenges of climate change. Despite its rapid growth and favorable wood properties for solid wood products, the advancement of its improvement remains in its early stages. In this work, we evaluated the performance of two single nucleotide polymorphism, (SNP), genotyping methods for population genetics analysis and Genomic Selection in E. dunnii. Double digest restriction-site associated DNA sequencing (ddRADseq) was compared with the EUChip60K array in 308 individuals from a provenance-progeny trial. The compared SNP set included 8,011 and 19,008 informative SNPs distributed along the 11 chromosomes, respectively. Although the two datasets differed in the percentage of missing data, genome coverage, minor allele frequency and estimated genetic diversity parameters, they revealed a similar genetic structure, showing two subpopulations with little differentiation between them, and low linkage disequilibrium. GS analyses were performed for eleven traits using Genomic Best Linear Unbiased Prediction (GBLUP) and a conventional pedigree-based model (ABLUP). Regardless of the SNP dataset, the predictive ability (PA) of GBLUP was better than that of ABLUP for six traits (Cellulose content, Total and Ethanolic extractives, Total and Klason lignin content and Syringyl and Guaiacyl lignin monomer ratio). When contrasting the SNP datasets used to estimate PAs, the GBLUP-EUChip60K model gave higher and significant PA values for six traits, meanwhile, the values estimated using ddRADseq gave higher values for three other traits. The PAs correlated positively with narrow sense heritabilities, with the highest correlations shown by the ABLUP and GBLUP-EUChip60K. The two genotyping methods, ddRADseq and EUChip60K, are generally comparable for population genetics and genomic prediction, demonstrating the utility of the former when subjected to rigorous SNP filtering. The results of this study provide a basis for future whole-genome studies using ddRADseq in non-model forest species for which SNP arrays have not yet been developed.

An ecologist's guide for studying DNA methylation variation in wild vertebrates

The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.

Phenotypic and genetic characterization of Africanized Apis mellifera colonies with natural tolerance to Varroa destructor and contrasting defensive behavior

Africanized Apis mellifera colonies with promising characteristics for beekeeping have been detected in northern Argentina (subtropical climate) and are considered of interest for breeding programs. Integral evaluation of this feral material revealed high colony strength and resistance/tolerance to brood diseases. However, these Africanized honeybees (AHB) also showed variable negative behavioral traits for beekeeping, such as defensiveness, tendency to swarm and avoidance behavior. We developed a protocol for the selection of AHB stocks based on defensive behavior and characterized contrasting colonies for this trait using NGS technologies. For this purpose, population and behavioral parameters were surveyed throughout a beekeeping season in nine daughter colonies obtained from a mother colony (A1 mitochondrial haplotype) with valuable characteristics (tolerance to the mite Varroa destructor, high colony strength and low defensiveness). A Defensive Behavior Index was developed and tested in the colonies under study. Mother and two daughter colonies displaying contrasting defensive behavior were analyzed by ddRADseq. High-quality DNA samples were obtained from 16 workers of each colony. Six pooled samples, including two replicates of each of the three colonies, were processed. A total of 12,971 SNPs were detected against the reference genome of A. mellifera, 142 of which showed significant differences between colonies. We detected SNPs in coding regions, lncRNA, miRNA, rRNA, tRNA, among others. From the original data set, we also identified 647 SNPs located in protein-coding regions, 128 of which are related to 21 genes previously associated with defensive behavior, such as dop3 and dopR2, CaMKII and ADAR, obp9 and obp10, and members of the 5-HT family. We discuss the obtained results by considering the influence of polyandry and paternal lineages on the defensive behavior in AHB and provide baseline information to use this innovative molecular approach, ddRADseq, to assist in the selection and evaluation of honey bee stocks showing low defensive behavior for commercial uses.

Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq) Technology

Double digest restriction-site associated DNA sequencing (ddRADseq) technology combines genome reduced representation by digestion with two restriction enzymes and next generation sequencing (NGS) to obtain thousands of markers (SNP, SSR, and InDels) and genotype tens to hundreds of samples simultaneously. In this chapter, we describe a 96-plex derived ddRADseq protocol that can be set up to obtain different depth of coverage per locus and can be exploited to model and non-model plant species.

ddRADseq-mediated detection of genetic variants in sugarcane

KEY MESSAGE

The article presents an optimization of the key parameters for the identification of SNPs in sugarcane using a GBS protocol based on two Illumina NextSeq and NovaSeq platforms. Sugarcane (Saccharum sp.), a world-wide known feedstock for sugar production, bioethanol, and energy, has an extremely complex genome, being highly polyploid and aneuploid. A double-digestion restriction site-associated DNA sequencing protocol (ddRADseq) was tested in four commercial sugarcane hybrids and one high-fibre biotype for the detection of single nucleotide polymorphisms (SNPs). In this work we tested two Illumina sequencing platforms, read size (70 vs. 150 bp), different sequencing coverage per individual (medium and high coverage), and single-reads versus paired-end reads. We also explored different variant calling strategies (with and without reference genome) and filtering schemes [combining two minor allele frequencies (MAFs) with three depth of coverage thresholds]. For the discovery of a large number of novel SNPs in sugarcane, we recommend longer size and paired-end reads, medium sequencing coverage per individual and Illumina platform NovaSeq6000 for a cost-effective approach, and filter parameters of lower MAF and higher depth coverages thresholds. Although the de novo analysis retrieved more SNPs, the reference-based method allows downstream characterization of variants. For the two best performing matrices, the number of SNPs per chromosome correlated positively with chromosome length, demonstrating the presence of variants throughout the genome. Multivariate comparisons, with both matrices, showed closer relationships among commercial hybrids than with the high-fibre biotype. Functional analysis of the SNPs demonstrated that more than half of them landed within regulatory regions, whereas the other half affected coding, intergenic and intronic regions. Allelic distances values were lower than 0.07 when analysing two replicated genotypes, confirming the protocol robustness.

Genome-Wide Association Studies in Sunflower: Towards Sclerotinia sclerotiorum and Diaporthe/Phomopsis Resistance Breeding

Diseases caused by necrotrophic fungi, such as the cosmopolitan Sclerotinia sclerotiorum and the Diaporthe/Phomopsis complex, are among the most destructive diseases of sunflower worldwide. The lack of complete resistance combined with the inefficiency of chemical control makes assisted breeding the best strategy for disease control. In this work, we present an integrated genome-wide association (GWA) study investigating the response of a diverse panel of sunflower inbred lines to both pathogens. Phenotypic data for Sclerotinia head rot (SHR) consisted of five disease descriptors (disease incidence, DI; disease severity, DS; area under the disease progress curve for DI, AUDPCI, and DS, AUDPCS; and incubation period, IP). Two disease descriptors (DI and DS) were evaluated for two manifestations of Diaporthe/Phomopsis: Phomopsis stem canker (PSC) and Phomopsis head rot (PHR). In addition, a principal component (PC) analysis was used to derive transformed phenotypes as inputs to a univariate GWA (PC-GWA). Genotypic data comprised a panel of 4269 single nucleotide polymorphisms (SNP), generated via genotyping-by-sequencing. The GWA analysis revealed 24 unique marker-trait associations for SHR, 19 unique marker-trait associations for Diaporthe/Phomopsis diseases, and 7 markers associated with PC1 and PC2. No common markers were found for the response to the two pathogens. Nevertheless, epistatic interactions were identified between markers significantly associated with the response to S. sclerotiorum and Diaporthe/Phomopsis. This suggests that, while the main determinants of resistance may differ for the two pathogens, there could be an underlying common genetic basis. The exploration of regions physically close to the associated markers yielded 364 genes, of which 19 were predicted as putative disease resistance genes. This work presents the first simultaneous evaluation of two manifestations of Diaporthe/Phomopsis in sunflower, and undertakes a comprehensive GWA study by integrating PSC, PHR, and SHR data. The multiple regions identified, and their exploration to identify candidate genes, contribute not only to the understanding of the genetic basis of resistance, but also to the development of tools for assisted breeding.

Heritable Variation of Foliar Spectral Reflectance Enhances Genomic Prediction of Hydrogen Cyanide in a Genetically Structured Population of Eucalyptus

Plants produce a wide diversity of specialized metabolites, which fulfill a wide range of biological functions, helping plants to interact with biotic and abiotic factors. In this study, an integrated approach based on high-throughput plant phenotyping, genome-wide haplotypes, and pedigree information was performed to examine the extent of heritable variation of foliar spectral reflectance and to predict the leaf hydrogen cyanide content in a genetically structured population of a cyanogenic eucalyptus (Eucalyptus cladocalyx F. Muell). In addition, the heritable variation (based on pedigree and genomic data) of more of 100 common spectral reflectance indices was examined. The first profile of heritable variation along the spectral reflectance curve indicated the highest estimate of genomic heritability ( h g 2 =0.41) within the visible region of the spectrum, suggesting that several physiological and biological responses of trees to environmental stimuli (ex., light) are under moderate genetic control. The spectral reflectance index with the highest genomic-based heritability was leaf rust disease severity index 1 ( h g 2 =0.58), followed by the anthocyanin reflectance index and the Browning reflectance index ( h g 2 =0.54). Among the Bayesian prediction models based on spectral reflectance data, Bayes B had a better goodness of fit than the Bayes-C and Bayesian ridge regression models (in terms of the deviance information criterion). All models that included spectral reflectance data outperformed conventional genomic prediction models in their predictive ability and goodness-of-fit measures. Finally, we confirmed the proposed hypothesis that high-throughput phenotyping indirectly capture endophenotypic variants related to specialized metabolites (defense chemistry), and therefore, generally more accurate predictions can be made integrating phenomics and genomics.

Development of novel SSR molecular markers using a Next-Generation Sequencing approach (ddRADseq) in Stetsonia coryne (Cactaceae)

The Cactaceae family is native to the American continent with several centers of diversity. In South America, one of these centers is the Central Andes and many species are considered to be threatened or vulnerable according to the International Union for Conservation of Nature (IUCN). Stetsonia coryne is an emblematic giant columnar cacti of the Chaco phytogeographic province. It has an extensive geographical distribution in many countries of the continent. However, to date there are no specific molecular markers for this species, neither reports of population genetic variability studies, such as for many cactus species. The lack of information is fundamentally due to the lack of molecular markers that allow these studies. In this work, by applying a Genotyping by Sequencing (GBS) technique, we developed polymorphic SSR markers for the Stetsonia coryne and evaluated their transferability to phylogenetically close species, in order to account for a robust panel of molecular markers for multispecies-studies within Cactaceae.

Pseudoreplication in genomics-scale datasets

In genomics-scale datasets, loci are closely packed within chromosomes and hence provide correlated information. Averaging across loci as if they were independent creates pseudoreplication, which reduces the effective degrees of freedom (df') compared to the nominal degrees of freedom, df. This issue has been known for some time, but consequences have not been systematically quantified across the entire genome. Here we measured pseudoreplication (quantified by the ratio df'/df) for a common metric of genetic differentiation (F_ST ) and a common measure of linkage disequilibrium between pairs of loci (r² ). Based on data simulated using models (SLiM and msprime) that allow efficient forward-in-time and coalescent simulations while precisely controlling population pedigrees, we estimated df' and df'/df by measuring the rate of decline in the variance of mean F_ST and mean r² as more loci were used. For both indices, df' increases with N_e and genome size, as expected. However, even for large N_e and large genomes, df' for mean r² plateaus after a few thousand loci, and a variance components analysis indicates that the limiting factor is uncertainty associated with sampling individuals rather than genes. Pseudoreplication is less extreme for F_ST , but df'/df ≤0.01 can occur in datasets using tens of thousands of loci. Commonly-used block-jackknife methods consistently overestimated var(F_ST ), producing very conservative confidence intervals. Predicting df' based on our modeling results as a function of N_e , L, S, and genome size provides a robust way to quantify precision associated with genomics-scale datasets.

Genome-wide association study of cyanogenic glycosides, proline, sugars, and pigments in Eucalyptus cladocalyx after 18 consecutive dry summers

Natural variation of cyanogenic glycosides, soluble sugars, proline, and nondestructive optical sensing of pigments (chlorophyll, flavonols, and anthocyanins) was examined in ex situ natural populations of Eucalyptus cladocalyx F. Muell. grown under dry environmental conditions in the southern Atacama Desert, Chile. After 18 consecutive dry seasons, considerable plant-to-plant phenotypic variation for all the traits was observed in the field. For example, leaf hydrogen cyanide (HCN) concentrations varied from 0 (two acyanogenic individuals) to 1.54 mg cyanide g^-1 DW. Subsequent genome-wide association study revealed associations with several genes with a known function in plants. HCN content was associated robustly with genes encoding Cytochrome P450 proteins, and with genes involved in the detoxification mechanism of HCN in cells (β-cyanoalanine synthase and cyanoalanine nitrilase). Another important finding was that sugars, proline, and pigment content were linked to genes involved in transport, biosynthesis, and/or catabolism. Estimates of genomic heritability (based on haplotypes) ranged between 0.46 and 0.84 (HCN and proline content, respectively). Proline and soluble sugars had the highest predictive ability of genomic prediction models (PA = 0.65 and PA = 0.71, respectively). PA values for HCN content and flavonols were relatively moderate, with estimates ranging from 0.44 to 0.50. These findings provide new understanding on the genetic architecture of cyanogenic capacity, and other key complex traits in cyanogenic E. cladocalyx.

Fine-tuning the performance of ddRAD-seq in the peach genome

The advance of Next Generation Sequencing (NGS) technologies allows high-throughput genotyping at a reasonable cost, although, in the case of peach, this technology has been scarcely developed. To date, only a standard Genotyping by Sequencing approach (GBS), based on a single restriction with ApeKI to reduce genome complexity, has been applied in peach. In this work, we assessed the performance of the double-digest RADseq approach (ddRADseq), by testing 6 double restrictions with the restriction profile generated with ApeKI. The enzyme pair PstI/MboI retained the highest number of loci in concordance with the in silico analysis. Under this condition, the analysis of a diverse germplasm collection (191 peach genotypes) yielded 200,759,000 paired-end (2 × 250 bp) reads that allowed the identification of 113,411 SNP, 13,661 InDel and 2133 SSR. We take advantage of a wide sample set to describe technical scope of the platform. The novel platform presented here represents a useful tool for genomic-based breeding for peach.

More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics

While the cost of sequencing genomes has decreased dramatically in recent years, this expense often remains nontrivial. Under a fixed budget, scientists face a natural trade-off between quantity and quality: spending resources to sequence a greater number of genomes or spending resources to sequence genomes with increased accuracy. Our goal is to find the optimal allocation of resources between quantity and quality. Optimizing resource allocation promises to reveal as many new variations in the genome as possible. We introduce a Bayesian nonparametric methodology to predict the number of new variants in a follow-up study based on a pilot study. When experimental conditions are kept constant between the pilot and follow-up, we find that our prediction is competitive with the best existing methods. Unlike current methods, though, our new method allows practitioners to change experimental conditions between the pilot and the follow-up. We demonstrate how this distinction allows our method to be used for more realistic predictions and for optimal allocation of a fixed budget between quality and quantity. We validate our method on cancer and human genomics data.

Comparative Analysis of SNP Discovery and Genotyping in Fagus sylvatica L. and Quercus robur L. Using RADseq, GBS, and ddRAD Methods

Next-generation sequencing of reduced representation genomic libraries (RRL) is capable of providing large numbers of genetic markers for population genetic studies at relatively low costs. However, one major concern of these types of markers is the precision of genotyping, which is related to the common problem of missing data, which appears to be particularly important in association and genomic selection studies. We evaluated three RRL approaches (GBS, RADseq, ddRAD) and different SNP identification methods (de novo or based on a reference genome) to find the best solutions for future population genomics studies in two economically and ecologically important broadleaved tree species, namely F. sylvatica and Q. robur. We found that the use of ddRAD method coupled with SNP calling based on reference genomes provided the largest numbers of markers (28 k and 36 k for beech and oak, respectively), given standard filtering criteria. Using technical replicates of samples, we demonstrated that more than 80% of SNP loci should be considered as reliable markers in GBS and ddRAD, but not in RADseq data. According to the reference genomes’ annotations, more than 30% of the identified ddRAD loci appeared to be related to genes. Our findings provide a solid support for using ddRAD-based SNPs for future population genomics studies in beech and oak.

A High-Density SNP Genetic Map Construction Using ddRAD-Seq and Mapping of Capsule Shattering Trait in Sesame

The seed-bearing capsule of sesame shatters at harvest. This wildish trait makes the crop unsuitable for mechanized harvesting and also restricts its commercial potential by limiting the cultivation for countries that have no access to low-cost labor. Therefore, the underlying genetic basis of the capsule shattering trait is highly important in order to develop mechanization-ready varieties for sustainable sesame farming. In the present study, we generated a sesame F₂ population derived from a cross between a capsule shattering cultivar (Muganli-57) and a non-shattering mutant (PI 599446), which was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing. The resulting high-density genetic map contained 782 single-nucleotide polymorphisms (SNPs) and spanned a length of 697.3 cM, with an average marker interval of 0.89 cM. Based on the reference genome, the capsule shattering trait was mapped onto SNP marker S8_5062843 (78.9 cM) near the distal end of LG8 (chromosome 8). In order to reveal genes potentially controlling the shattering trait, the marker region (S8_5062843) was examined, and a candidate gene including six CDSs was identified. Annotation showed that the gene encodes a protein with 440 amino acids, sharing ∼99% homology with transcription repressor KAN1. Compared with the capsule shattering allele, the SNP change and altered splicing in the flanking region of S8_5062843 caused a frameshift mutation in the mRNA, resulting in the loss of function of this gene in the mutant parent and thus in non-shattering capsules and leaf curling. With the use of genomic data, InDel and CAPS markers were developed to differentiate shattering and non-shattering capsule genotypes in marker-assisted selection studies. The obtained results in the study can be beneficial in breeding programs to improve the shattering trait and enhance sesame productivity.

ddRAD sequencing-based genotyping for population structure analysis in cultivated tomato provides new insights into the genomic diversity of Mediterranean 'da serbo' type long shelf-life germplasm

Double digest restriction-site associated sequencing (ddRAD-seq) is a flexible and cost-effective strategy for providing in-depth insights into the genetic architecture of germplasm collections. Using this methodology, we investigated the genomic diversity of a panel of 288 diverse tomato (Solanum lycopersicum L.) accessions enriched in 'da serbo' (called 'de penjar' in Spain) long shelf life (LSL) materials (152 accessions) mostly originating from Italy and Spain. The rest of the materials originate from different countries and include landraces for fresh consumption, elite cultivars, heirlooms, and breeding lines. Apart from their LSL trait, 'da serbo' landraces are of remarkable interest for their resilience. We identified 32,799 high-quality SNPs, which were used for model ancestry population structure and non-parametric hierarchical clustering. Six genetic subgroups were revealed, clearly separating most 'da serbo' landraces, but also the Spanish germplasm, suggesting a subdivision of the population based on type and geographical provenance. Linkage disequilibrium (LD) in the collection decayed very rapidly within <5 kb. We then investigated SNPs showing contrasted minor frequency allele (MAF) in 'da serbo' materials, resulting in the identification of high frequencies in this germplasm of several mutations in genes related to stress tolerance and fruit maturation such as CTR1 and JAR1. Finally, a mini-core collection of 58 accessions encompassing most of the diversity was selected for further exploitation of key traits. Our findings suggest the presence of a genetic footprint of the 'da serbo' germplasm selected in the Mediterranean basin. Moreover, we provide novel insights on LSL 'da serbo' germplasm as a promising source of alleles for tolerance to stresses.

Genetic Diversity, Population Structure and Linkage Disequilibrium Assessment among International Sunflower Breeding Collections

Sunflower germplasm collections are valuable resources for broadening the genetic base of commercial hybrids and ameliorate the risk of climate events. Nowadays, the most studied worldwide sunflower pre-breeding collections belong to INTA (Argentina), INRA (France), and USDA-UBC (United States of America-Canada). In this work, we assess the amount and distribution of genetic diversity (GD) available within and between these collections to estimate the distribution pattern of global diversity. A mixed genotyping strategy was implemented, by combining proprietary genotyping-by-sequencing data with public whole-genome-sequencing data, to generate an integrative 11,834-common single nucleotide polymorphism matrix including the three breeding collections. In general, the GD estimates obtained were moderate. An analysis of molecular variance provided evidence of population structure between breeding collections. However, the optimal number of subpopulations, studied via discriminant analysis of principal components (K = 12), the bayesian STRUCTURE algorithm (K = 6) and distance-based methods (K = 9) remains unclear, since no single unifying characteristic is apparent for any of the inferred groups. Different overall patterns of linkage disequilibrium (LD) were observed across chromosomes, with Chr10, Chr17, Chr5, and Chr2 showing the highest LD. This work represents the largest and most comprehensive inter-breeding collection analysis of genomic diversity for cultivated sunflower conducted to date.

Genomic Predictions Using Low-Density SNP Markers, Pedigree and GWAS Information: A Case Study with the Non-Model Species Eucalyptus cladocalyx

High-throughput genotyping techniques have enabled large-scale genomic analysis to precisely predict complex traits in many plant species. However, not all species can be well represented in commercial SNP (single nucleotide polymorphism) arrays. In this study, a high-density SNP array (60 K) developed for commercial Eucalyptus was used to genotype a breeding population of Eucalyptus cladocalyx, yielding only ~3.9 K informative SNPs. Traditional Bayesian genomic models were investigated to predict flowering, stem quality and growth traits by considering the following effects: (i) polygenic background and all informative markers (GS model) and (ii) polygenic background, QTL-genotype effects (determined by GWAS) and SNP markers that were not associated with any trait (GSq model). The estimates of pedigree-based heritability and genomic heritability varied from 0.08 to 0.34 and 0.002 to 0.5, respectively, whereas the predictive ability varied from 0.19 (GS) and 0.45 (GSq). The GSq approach outperformed GS models in terms of predictive ability when the proportion of the variance explained by the significant marker-trait associations was higher than those explained by the polygenic background and non-significant markers. This approach can be particularly useful for plant/tree species poorly represented in the high-density SNP arrays, developed for economically important species, or when high-density marker panels are not available.