Application of genotyping by sequencing technology to a variety of crop breeding programs

Genomic prediction in Brassica napus: evaluating the benefit of imputed whole-genome sequencing data

Advances in sequencing technology allow whole plant genomes to be sequenced with high quality. Combining genotypic and phenotypic data in genomic prediction helps breeders to select crossing partners in partially phenotyped populations. In plant breeding programs, the cost of sequencing entire breeding populations still exceeds available genotyping budgets. Hence, the method for genotyping is still mainly single nucleotide polymorphism (SNP) arrays; however, arrays are unable to assess the entire genome- and population-wide diversity. A compromise involves genotyping the entire population using an SNP array and a subset of the population with whole-genome sequencing. Both datasets can then be used to impute markers from whole-genome sequencing onto the entire population. Here, we evaluate whether imputation of whole-genome sequencing data enhances genomic predictions, using data from a nested association mapping population of rapeseed (Brassica napus). Employing two cross-validation schemes that mimic scenarios for the prediction of close and distant relatives, we show that imputed marker data do not significantly improve prediction accuracy, likely due to redundancy in relationship estimates and imputation errors. In simulation studies, only small improvements were observed, further corroborating the findings. We conclude that SNP arrays are already equipped with the information that is added by imputation through relationship and linkage disequilibrium.

Genomic characterisation and dissection of the onset of resistance to acetyl CoA carboxylase-inhibiting herbicides in a large collection of Digitaria insularis from Brazil

An in-depth genotypic characterisation of a diverse collection of Digitaria insularis was undertaken to explore the neutral genetic variation across the natural expansion range of this weed species in Brazil. With the exception of Minas Gerais, populations from all other states showed high estimates of expected heterozygosity (HE > 0.60) and genetic diversity. There was a lack of population structure based on geographic origin and a low population differentiation between populations across the landscape as evidenced by average Fst value of 0.02. On combining haloxyfop [acetyl CoA carboxylase (ACCase)-inhibiting herbicide] efficacy data with neutral genetic variation, we found evidence of presence of two scenarios of resistance evolution in this weed species. Whilst populations originating from north-eastern region demonstrated an active role of gene flow, populations from the mid-western region displayed multiple, independent resistance evolution as the major evolutionary mechanism. A target-site mutation (Trp2027Cys) in the ACCase gene, observed in less than 1% of resistant populations, could not explain the reduced sensitivity of 15% of the populations to haloxyfop. The genetic architecture of resistance to ACCase-inhibiting herbicides was dissected using a genome wide association study (GWAS) approach. GWAS revealed association of three SNPs with reduced sensitivity to haloxyfop and clethodim. In silico analysis of these SNPs revealed important non-target site genes belonging to families involved in herbicide detoxification, including UDPGT91C1 and GT2, and genes involved in vacuolar sequestration-based degradation pathway. Exploration of five genomic prediction models revealed that the highest prediction power (≥0.80) was achieved with the models Bayes A and RKHS, incorporating SNPs with additive effects and epistatic interactions, respectively.

Impact of genotype-calling methodologies on genome-wide association and genomic prediction in polyploids

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

A comprehensive lettuce variation map reveals the impact of structural variations in agronomic traits

BACKGROUND

As an important vegetable crop, cultivated lettuce is grown worldwide and a great variety of agronomic traits have been preserved within germplasm collections. The mechanisms underlying these phenotypic variations remain to be elucidated in association with sequence variations. Compared with single nucleotide polymorphisms, structural variations (SVs) that have more impacts on gene functions remain largely uncharacterized in the lettuce genome.

RESULTS

Here, we produced a comprehensive SV set for 333 wild and cultivated lettuce accessions. Comparison of SV frequencies showed that the SVs prevalent in L. sativa affected the genes enriched in carbohydrate derivative catabolic and secondary metabolic processes. Genome-wide association analysis of seven agronomic traits uncovered potentially causal SVs associated with seed coat color and leaf anthocyanin content.

CONCLUSION

Our work characterized a great abundance of SVs in the lettuce genome, and provides a valuable genomic resource for future lettuce breeding.

Accurate prediction of quantitative traits with failed SNP calls in canola and maize

In modern plant breeding, genomic selection is becoming the gold standard to select superior genotypes in large breeding populations that are only partially phenotyped. Many breeding programs commonly rely on single-nucleotide polymorphism (SNP) markers to capture genome-wide data for selection candidates. For this purpose, SNP arrays with moderate to high marker density represent a robust and cost-effective tool to generate reproducible, easy-to-handle, high-throughput genotype data from large-scale breeding populations. However, SNP arrays are prone to technical errors that lead to failed allele calls. To overcome this problem, failed calls are often imputed, based on the assumption that failed SNP calls are purely technical. However, this ignores the biological causes for failed calls-for example: deletions-and there is increasing evidence that gene presence-absence and other kinds of genome structural variants can play a role in phenotypic expression. Because deletions are frequently not in linkage disequilibrium with their flanking SNPs, permutation of missing SNP calls can potentially obscure valuable marker-trait associations. In this study, we analyze published datasets for canola and maize using four parametric and two machine learning models and demonstrate that failed allele calls in genomic prediction are highly predictive for important agronomic traits. We present two statistical pipelines, based on population structure and linkage disequilibrium, that enable the filtering of failed SNP calls that are likely caused by biological reasons. For the population and trait examined, prediction accuracy based on these filtered failed allele calls was competitive to standard SNP-based prediction, underlying the potential value of missing data in genomic prediction approaches. The combination of SNPs with all failed allele calls or the filtered allele calls did not outperform predictions with only SNP-based prediction due to redundancy in genomic relationship estimates.

Development and application of Single Primer Enrichment Technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce

Single primer enrichment technology (SPET) is a novel high-throughput genotyping method based on short-read sequencing of specific genomic regions harboring polymorphisms. SPET provides an efficient and reproducible method for genotyping target loci, overcoming the limits associated with other reduced representation library sequencing methods that are based on a random sampling of genomic loci. The possibility to sequence regions surrounding a target SNP allows the discovery of thousands of closely linked, novel SNPs. In this work, we report the design and application of the first SPET panel in lettuce, consisting of 41,547 probes spanning the whole genome and designed to target both coding (~96%) and intergenic (~4%) regions. A total of 81,531 SNPs were surveyed in 160 lettuce accessions originating from a total of 10 countries in Europe, America, and Asia and representing 10 horticultural types. Model ancestry population structure clearly separated the cultivated accessions (Lactuca sativa) from accessions of its presumed wild progenitor (L. serriola), revealing a total of six genetic subgroups that reflected a differentiation based on cultivar typology. Phylogenetic relationships and principal component analysis revealed a clustering of butterhead types and a general differentiation between germplasm originating from Western and Eastern Europe. To determine the potentiality of SPET for gene discovery, we performed genome-wide association analysis for main agricultural traits in L. sativa using six models (GLM naive, MLM, MLMM, CMLM, FarmCPU, and BLINK) to compare their strength and power for association detection. Robust associations were detected for seed color on chromosome 7 at 50 Mbp. Colocalization of association signals was found for outer leaf color and leaf anthocyanin content on chromosome 9 at 152 Mbp and on chromosome 5 at 86 Mbp. The association for bolting time was detected with the GLM, BLINK, and FarmCPU models on chromosome 7 at 164 Mbp. Associations were detected in chromosomal regions previously reported to harbor candidate genes for these traits, thus confirming the effectiveness of SPET for GWAS. Our findings illustrated the strength of SPET for discovering thousands of variable sites toward the dissection of the genomic diversity of germplasm collections, thus allowing a better characterization of lettuce collections.

Genetic diversity and population structure of bermudagrass (Cynodon spp.) revealed by genotyping-by-sequencing

Bermudagrass (Cynodon spp.) breeding and cultivar development is hampered by limited information regarding its genetic and phenotypic diversity. To explore diversity in bermudagrass, a total of 206 Cynodon accessions consisting of 193 common bermudagrass (C. dactylon var. dactylon) and 13 African bermudagrass (C. transvaalensis) accessions of worldwide origin were assembled for genetic characterization. Genotyping-by-sequencing (GBS) was employed for genetic marker development. With a minor allele frequency of 0.05 and a minimum call rate of 0.5, a total of 37,496 raw single nucleotide polymorphisms (SNPs) were called de novo and were used in the genetic diversity characterization. Population structure analysis using ADMIXTURE revealed four subpopulations in this germplasm panel, which was consistent with principal component analysis (PCA) and phylogenetic analysis results. The first three principal components explained 15.6%, 10.1%, and 3.8% of the variance in the germplasm panel, respectively. The first subpopulation consisted of C. dactylon accessions from various continents; the second subpopulation was comprised mainly of C. transvaalensis accessions; the third subpopulation contained C. dactylon accessions primarily of African origin; and the fourth subpopulation represented C. dactylon accessions obtained from the Oklahoma State University bermudagrass breeding program. Genetic diversity parameters including Nei's genetic distance, inbreeding coefficient, and Fst statistic revealed substantial genetic variation in the Cynodon accessions, demonstrating the potential of this germplasm panel for further genetic studies and cultivar development in breeding programs.

Population Genetic Analysis in Persimmons (Diospyros kaki Thunb.) Based on Genome-Wide Single-Nucleotide Polymorphisms

This study investigated the genetic diversity and population structure of a persimmon (Diospyros kaki Thunb., 2n = 6x = 90) collection in South Korea by evaluating 9751 genome-wide single-nucleotide polymorphisms (SNPs) detected using genotyping-by-sequencing in 93 cultivars. The results of neighbor-joining clustering, principal component analysis, and STRUCTURE analysis based on SNPs indicated clear separation between cultivar groups (pollination-constant nonastringent (PCNA, 40 cultivars), pollination-constant astringent (PCA, 19), pollination-variant nonastringent (PVNA, 23), and the pollination-variant astringent type (PVA, 9)) based on the astringency types, while separation between PVA and PVNA-type cultivars was unclear. Population genetic diversity based on SNPs showed that the proportions of polymorphic SNPs within each group ranged from 99.01% (PVNA) to 94.08% (PVA), and the PVNA group exhibited the highest genetic diversity (He = 3.86 and uHe = 0.397). F (fixation index) values were low ranging from -0.024 (PVA) to 0.176 (PCA) with an average of 0.089, indicating a deficiency of heterozygosity. Analysis of molecular variance (AMOVA) and Fst among cultivar groups indicated that variation within individuals was higher than that among the groups. Pairwise Fst values among the groups ranged from 0.01566 (between PVA and PVNA) to 0.09416 (between PCA and PCNA), indicating a low level of cultivar type differentiation. These findings highlight the potential application of biallelic SNPs in population genetics studies of allopolyploids species and provide valuable insights that may have significant implications for breeding and cultivar identification in persimmon.

Genomic Dynamics and Functional Insights under Salt Stress in Gossypium hirsutum L

The changing climate is intensifying salt stress globally. Salt stress is a menace to cotton crop quality and yield. The seedling, germination, and emergence phases are more prone to the effects of salt stress than other stages. Higher levels of salt can lead to delayed flowering, a reduced number of fruiting positions, shedding of fruits, decreased boll weight, and yellowing of fiber, all of which have an adverse effect on the yield and quality of the seed cotton. However, sensitivity toward salt stress is dependent on the salt type, cotton growth phase, and genotype. As the threat of salt stress continues to grow, it is crucial to gain a comprehensive understanding of the mechanisms underlying salt tolerance in plants and to identify potential avenues for enhancing the salt tolerance of cotton. The emergence of marker-assisted selection, in conjunction with next-generation sequencing technologies, has streamlined cotton breeding efforts. This review begins by providing an overview of the causes of salt stress in cotton, as well as the underlying theory of salt tolerance. Subsequently, it summarizes the breeding methods that utilize marker-assisted selection, genomic selection, and techniques for identifying elite salt-tolerant markers in wild species or mutated materials. Finally, novel cotton breeding possibilities based on the approaches stated above are presented and debated.

Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding

Sorghum is emerging as a model crop for functional genetics and genomics of tropical grasses with abundant uses, including food, feed, and fuel, among others. It is currently the fifth most significant primary cereal crop. Crops are subjected to various biotic and abiotic stresses, which negatively impact on agricultural production. Developing high-yielding, disease-resistant, and climate-resilient cultivars can be achieved through marker-assisted breeding. Such selection has considerably reduced the time to market new crop varieties adapted to challenging conditions. In the recent years, extensive knowledge was gained about genetic markers. We are providing an overview of current advances in sorghum breeding initiatives, with a special focus on early breeders who may not be familiar with DNA markers. Advancements in molecular plant breeding, genetics, genomics selection, and genome editing have contributed to a thorough understanding of DNA markers, provided various proofs of the genetic variety accessible in crop plants, and have substantially enhanced plant breeding technologies. Marker-assisted selection has accelerated and precised the plant breeding process, empowering plant breeders all around the world.

Pangenomic genotyping with the marker array

We present a new method and software tool called rowbowt that applies a pangenome index to the problem of inferring genotypes from short-read sequencing data. The method uses a novel indexing structure called the marker array. Using the marker array, we can genotype variants with respect from large panels like the 1000 Genomes Project while reducing the reference bias that results when aligning to a single linear reference. rowbowt can infer accurate genotypes in less time and memory compared to existing graph-based methods. The method is implemented in the open source software tool rowbowt available at https://github.com/alshai/rowbowt .

Mapping of quantitative trait loci for the nutritional value of fresh market tomato

The incidence of many diseases, such as cancer, cardiovascular diseases, and diabetes, is associated with malnutrition and an unbalanced daily diet. Vegetables are an important source of vitamins and essential compounds for human health. As a result, such metabolites have increasingly become the focus of breeding programs. Tomato is one of the most popular components of our daily diet. Therefore, the improvement of tomato's nutritional quality is an important goal. In the present study, we performed targeted metabolic profiling of an interspecific Solanum pimpinellifolium × S. lycopersicum inbred backcross line (IBL) population and identified quantitative trait loci responsible for the nutritional value of tomato. Transgressive segregation was apparent for many of the nutritional compounds such that some IBLs had extremely high levels of various amino acids and vitamins compared to their parents. A total of 117 QTLs for nutritional traits including 62 QTLs for amino acids, 18 QTLs for fatty acids, 12 QTLs for water-soluble vitamins, and 25 QTLs for fat-soluble vitamins were identified. Moreover, almost 24% of identified QTLs were confirmed in previous studies, and 40 possible gene candidates were found for 18 identified QTLs. These findings can help breeders to improve the nutritional value of tomato.

Comparative transmission genetics of introgressed chromatin in reciprocal advanced backcross populations in Gossypium (cotton) polyploids

Introgression is a potential source of valuable genetic variation and interspecific introgression lines are important resources for plant breeders to access novel alleles. Experimental advanced-generation backcross populations contain individuals with genomic compositions similar to those resulting from natural interspecific hybridization and provide opportunities to study the nature and transmission pattern of donor chromatin in recipient genomes. Here, we analyze transmission of donor chromatin in reciprocal backcrosses between G. hirsutum and G. barbadense. Across the genome, recurrent backcrossing in both backgrounds yielded donor chromatin at slightly higher frequencies than the Mendelian expectation in BC5F1 plants, while the average frequency of donor alleles in BC5F2 segregating families was less than expected. In the two subgenomes of polyploid cotton, the rate of donor chromatin introgression was similar. Although donor chromatin was tolerated over much of the recipient genomes, 21 regions recalcitrant to donor alleles were identified. Only limited correspondence is observed between the recalcitrant regions in the two backgrounds, suggesting the effect of species background on introgression of donor segments. Genetic breakdown was progressive, with floral abscission and seed inviability ongoing during backcrossing cycles. Regions of either high or low introgression tended to be in terminal chromosomal regions that are generally rich in both genes and crossover events, with long stretches around the centromere having limited crossover activity resulting in relatively constant low introgression frequencies. Constraints on fixation and selection of donor alleles highlights the challenges of utilizing introgression breeding in crop improvement.

Trait Mapping of Phenolic Acids in an Interspecific (Vaccinium corymbosum var. caesariense × V. darrowii) Diploid Blueberry Population

Blueberries (Vaccinium sect. Cyanococcus) are a dietary source of phenolic acids, including chlorogenic acid (CGA) and related compounds such as acetylated caffeoylquinic acid (ACQA) and caffeoylarbutin (CA). These compounds are known to be potent antioxidants with potential health benefits. While the chemistry of these compounds has been extensively studied, the genetic analysis has lagged behind. Understanding the genetic basis for traits with potential health implications may be of great use in plant breeding. By characterizing genetic variation related to fruit chemistry, breeders can make more efficient use of plant diversity to develop new cultivars with higher concentrations of these potentially beneficial compounds. Using a large interspecific F1 population, developed from a cross between the temperate V. corymbosum var. ceasariense and the subtropical V. darrowii, with 1025 individuals genotyped using genotype-by-sequencing methods, of which 289 were phenotyped for phenolic acid content, with data collected across 2019 and 2020, we have identified loci associated with phenolic acid content. Loci for the compounds clustered on the proximal arm of Vc02, suggesting that a single gene or several closely associated genes are responsible for the biosynthesis of all four tested compounds. Within this region are multiple gene models similar to hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyltransferase (HCT) and UDP glucose:cinnamate glucosyl transferase (UGCT), genes known to be involved in the CGA biosynthesis pathway. Additional loci on Vc07 and Vc12 were associated with caffeoylarbutin content, suggesting a more complicated biosynthesis of that compound.

Pipeline to Design Inbred Lines and F1 Hybrids of Leaf Chicory (Radicchio) Using Male Sterility and Genotyping-by-Sequencing

Chicory, a horticultural crop cultivated worldwide, presents many botanical varieties and local biotypes. Among these, cultivars of the Italian radicchio group of the pure species Cichorium intybus L. and its interspecific hybrids with Cichorium endivia L.-as the "Red of Chioggia" biotype-includes several phenotypes. This study uses a pipeline to address the marker-assisted breeding of F1 hybrids: it presents the genotyping-by-sequencing results of four elite inbred lines using a RADseq approach and an original molecular assay based on CAPS markers for screening mutants with nuclear male sterility in the radicchio of Chioggia. A total of 2953 SNP-carrying RADtags were identified and used to compute the actual estimates of homozygosity and overall genetic similarity and uniformity of the populations, as well as to determine their genetic distinctiveness and differentiation. Molecular data were further used to investigate the genomic distribution of the RADtags among the two Cichorium species, allowing their mapping in 1131 and 1071 coding sequences in chicory and endive, respectively. Paralleling this, an assay to screen the genotype at the male sterility locus Cims-1 was developed to discriminate wild-type and mutant alleles of the causative gene myb80-like. Moreover, a RADtag mapped close to this genomic region proved the potential application of this method for future marker-assisted selection tools. Finally, after combining the genotype information of the core collection, the best 10 individuals from each inbred line were selected to compute the observed genetic similarity as a measure of uniformity as well as the expected homozygosity and heterozygosity estimates scorable by the putative progenies derived from selfing (pollen parent) and full-sibling (seed parent) or pair-wise crossing (F1 hybrids). This predictive approach was conducted as a pilot study to understand the potential application of RADseq in the fine tuning of molecular marker-assisted breeding strategies aimed at the development of inbred lines and F1 hybrids in leaf chicory.

Population structure and genetic diversity characterization of soybean for seed longevity

Seed longevity is an important trait in the context of germplasm conservation and economics of seed production. The identification of populations with high level of genetic variability for seed longevity and associated traits will become a valuable resource for superior alleles for seed longevity. In this study, Genotyping-by-sequencing (GBS)-single nucleotide polymorphism (SNP) approach, simple sequence repeats (SSR) markers and agro-morphological traits have been explored to investigate the diversity and population structure of assembled 96 genotypes. The GBS technique performed on 96 genotypes of soybean (Glycine max (L.) Merrill) resulted in 37,897 SNPs on sequences aligned to the reference genome sequence. The average genome coverage was 6.81X with a mapping rate of 99.56% covering the entire genome. Totally, 29,955 high quality SNPs were identified after stringent filtering and most of them were detected in non-coding regions. The 96 genotypes were phenotyped for eight quantitative and ten qualitative traits by growing in field by following augmented design. The STRUCTURE (Bayesian-model based algorithm), UPGMA (Un-weighed Pair Group Method with Arithmetic mean) and principal component analysis (PCA) approaches using SSR, SNP as well as quantitative and qualitative traits revealed population structure and diversity in assembled population. The Bayesian-model based STRUCTURE using SNP markers could effectively identify clusters with higher seed longevity associated with seed coat colour and size which were subsequently validated by UPGMA and PCA based on SSR and agro-morphological traits. The results of STRUCTURE, PCA and UPGMA cluster analysis showed high degree of similarity and provided complementary data that helped to identify genotypes with higher longevity. Six black colour genotypes, viz., Local black soybean, Kalitur, ACC Nos. 39, 109, 101 and 37 showed higher seed longevity during accelerated ageing. Higher coefficient of variability observed for plant height, number of pods per plant, seed yield per plant, 100 seed weight and seed longevity confirms the diversity in assembled population and its suitability for quantitative trait loci (QTL) mapping.

Genotyping-by-sequencing (GBS) as a tool for interspecies hybrid detection

Genotyping-by-sequencing (GBS) is an extremely useful, modern and relatively inexpensive approach to discovering high-quality single-nucleotide polymorphisms (SNPs), which seem to be the most promising markers for identifying hybrid individuals between different species, especially those that can create backcrosses. In addition, GBS could become an invaluable tool in finding backcrosses, even several generations back. Its potential for the use of restriction enzymes and species is almost unlimited. It can also be successfully applied to species for which a reference genome is not established. In this paper, we describe the GBS technique, its main advantages and disadvantages, and the research carried out using this method concerning interspecies hybridisation and the identification of fertile hybrids. We also present future approaches that could be of interest in the context of the GBS method.

Identification of a novel major QTL from Chinese wheat cultivar Ji5265 for Fusarium head blight resistance in greenhouse

A novel major QTL for FHB resistance was mapped to a 6.8 Mb region on chromosome 2D in a Chinese wheat cultivar Ji5265, and diagnostic KASP markers were developed for detecting it in a worldwide wheat collection. Fusarium head blight (FHB) is a serious disease in wheat (Triticum aestivum L.) and causes significant reductions in grain yield and quality worldwide. Breeding for FHB resistance is the most effective strategy to minimize the losses caused by FHB; therefore, identification of major quantitative trait loci (QTLs) conferring FHB resistance and development of diagnostic markers for the QTLs are prerequisites for marker-assisted selection (MAS). Ji5265 is a Chinese wheat cultivar resistant to FHB in multiple environments. An F₆ population of 179 recombinant inbred lines (RILs) was developed from Ji5265 × Wheaton. The population was genotyped by genotyping-by-sequencing (GBS) and phenotyped for FHB Type II resistance in greenhouses. A major QTL, designated as QFhb-2DL, was mapped in a 6.8 Mb region between the markers GBS10238 and GBS12056 on the long arm of chromosome 2D in Ji5265 and explained ~ 30% of the phenotypic variation for FHB resistance. The effect of QFhb-2DL on FHB resistance was validated using near-isogenic lines (NILs) derived from residual heterozygotes from an F₆ RIL of Ji5265 × Wheaton. The two flanking markers were converted into Kompetitive allele-specific PCR (KASP) markers (KASP10238 and KASP12056) and validated to be diagnostic in a collection of 2,065 wheat accessions. These results indicate that QFhb-2DL is a novel major QTL for resistance to FHB spread within a spike (Type II) and the two KASP markers can be used for MAS to improve wheat FHB resistance in wheat breeding programs.

Recent status of Genotyping by Sequencing (GBS) Technology in cucumber (Cucumis sativus L.): a review

Current and advanced breeding tools are being used to improve economically important horticultural crops to meet the consumers' needs and preferences. Genotyping-by-sequencing (GBS) is an extremely useful tool in the investigation and analysis of the genetic diversity of different cultivars. Based on a broad range of genetic backgrounds like single nucleotide polymorphism (SNPs), GBS is known as a novel technique to facilitate the detection of quantitative trait loci (QTL) regions robustly linked with interested traits compared to genome-wide association study (GWAS) and QTL. GBS has gained popularity among breeders in recent years and it is also employed in cucumber breeding programs. Cucumbers (C. sativus L.) are monoecious, gynoecious and some of them are parthenocarpic species. Cucumber is one of the most economical and essential crops in the Cucurbitaceae family. For time immemorial, cucumber has been produced and consumed all over the world like other cucurbits. To a large extent, cultivated cucurbits are beneficial to human health for providing necessary minerals and fibers.Therefore, this review portrays the current status of advances made by using GBS and its combination with other tools in various studies of cucumber such as the use of GBS and single nucleotide polymorphism (SNP) markers, GBS and GWAS, also with QTL and marker-assisted selection (MAS) are applied to display and detect explicit genetic architecture complex traits in crops and chromosome rearrangements.Cucumber breeding programs have undoubtedly benefited from genotyping-by-sequencing. Using the GBS method, research discovered lots of new candidate genes that control various traits including spine color, fruit stalk-end color, and disease resistance in cucumber lines.

Whole-genome resequencing of Sorghum bicolor and S. bicolor × S. halepense lines provides new insights for improving plant agroecological characteristics

Sorghum (Sorghum bicolor L. (Moench)) is the world's fifth economically most important cereal and is a staple particularly in the semi-arid tropics of Africa and Asia. Genetic gains in this crop can benefit from wild relatives such as Sorghum halepense. Genome sequences including those from this wild species can boost the study of genome-wide and intraspecific variation for dissecting the genetic basis and improving important traits in sorghum. The whole-genome resequencing carried out in this work on a panel of 172 populations of S. bicolor and S. bicolor × S. halepense (SbxSh) advanced lines generated a total of 567,046,841 SNPs, 91,825,474 indels, 1,532,171 SVs, and 4,973,961 CNVs. Clearly, SbxSh accumulated more variants and mutations with powerful effects on genetic differentiation. A total of 5,548 genes private to SbxSh mapped to biological process GO enrichment terms; 34 of these genes mapped to root system development (GO: 0022622). Two of the root specific genes i.e., ROOT PRIMORDIUM DEFECTIVE 1 (RPD1; GeneID: 8054879) and RETARDED ROOT GROWTH (RRG, GeneID: 8072111), were found to exert direct effect on root growth and development. This is the first report on whole-genome resequencing of a sorghum panel that includes S. halepense genome. Mining the private variants and genes of this wild species can provide insights capable of boosting sorghum genetic improvement, particularly the perenniality trait that is compliant with agroecological practices, sustainable agriculture, and climate change resilience.

Benchmarking small-variant genotyping in polyploids

Genotyping from sequencing is the basis of emerging strategies in the molecular breeding of polyploid plants. However, compared with the situation for diploids, in which genotyping accuracies are confidently determined with comprehensive benchmarks, polyploids have been neglected; there are no benchmarks measuring genotyping error rates for small variants using real sequencing reads. We previously introduced a variant calling method, Octopus, that accurately calls germline variants in diploids and somatic mutations in tumors. Here, we evaluate Octopus and other popular tools on whole-genome tetraploid and hexaploid data sets created using in silico mixtures of diploid Genome in a Bottle (GIAB) samples. We find that genotyping errors are abundant for typical sequencing depths but that Octopus makes 25% fewer errors than other methods on average. We supplement our benchmarks with concordance analysis in real autotriploid banana data sets.

Characterization and Mapping of retr04, retr05 and retr06 Broad-Spectrum Resistances to Turnip Mosaic Virus in Brassica juncea, and the Development of Robust Methods for Utilizing Recalcitrant Genotyping Data

Turnip mosaic virus (TuMV) induces disease in susceptible hosts, notably impacting cultivation of important crop species of the Brassica genus. Few effective plant viral disease management strategies exist with the majority of current approaches aiming to mitigate the virus indirectly through control of aphid vector species. Multiple sources of genetic resistance to TuMV have been identified previously, although the majority are strain-specific and have not been exploited commercially. Here, two Brassica juncea lines (TWBJ14 and TWBJ20) with resistance against important TuMV isolates (UK 1, vVIR24, CDN 1, and GBR 6) representing the most prevalent pathotypes of TuMV (1, 3, 4, and 4, respectively) and known to overcome other sources of resistance, have been identified and characterized. Genetic inheritance of both resistances was determined to be based on a recessive two-gene model. Using both single nucleotide polymorphism (SNP) array and genotyping by sequencing (GBS) methods, quantitative trait loci (QTL) analyses were performed using first backcross (BC₁) genetic mapping populations segregating for TuMV resistance. Pairs of statistically significant TuMV resistance-associated QTLs with additive interactive effects were identified on chromosomes A03 and A06 for both TWBJ14 and TWBJ20 material. Complementation testing between these B. juncea lines indicated that one resistance-linked locus was shared. Following established resistance gene nomenclature for recessive TuMV resistance genes, these new resistance-associated loci have been termed retr04 (chromosome A06, TWBJ14, and TWBJ20), retr05 (A03, TWBJ14), and retr06 (A03, TWBJ20). Genotyping by sequencing data investigated in parallel to robust SNP array data was highly suboptimal, with informative data not established for key BC₁ parental samples. This necessitated careful consideration and the development of new methods for processing compromised data. Using reductive screening of potential markers according to allelic variation and the recombination observed across BC₁ samples genotyped, compromised GBS data was rendered functional with near-equivalent QTL outputs to the SNP array data. The reductive screening strategy employed here offers an alternative to methods relying upon imputation or artificial correction of genotypic data and may prove effective for similar biparental QTL mapping studies.

A novel insight into transcriptional and epigenetic regulation underlying sex expression and flower development in melon (Cucumis melo L.)

Melon (Cucumis melo L.) is an important cucurbit and has been considered as a model plant for studying sex determination. The four most common sexual morphotypes in melon are monoecious (A-G-M), gynoecious (--ggM-), andromonoecious (A-G-mm), and hermaphrodite (--ggmm). Sex expression in melons is complex, as the genes and associated networks that govern the sex expression are not fully explored. Recently, RNA-seq transcriptomic profiling, ChIP-qPCR analysis integrated with gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathways predicted the differentially expressed genes including sex-specific ACS and ACO genes, in regulating the sex-expression, phytohormonal cross-talk, signal transduction, and secondary metabolism in melons. Integration of transcriptional control through genetic interaction in between the ACS7, ACS11, and WIP1 in epistatic or hypostatic manner, along with the recruitment of H3K9ac and H3K27me3, epigenetically, overall determine sex expression. Alignment of protein sequences for establishing phylogenetic evolution, motif comparison, and protein-protein interaction supported the structural conservation while presence of the conserved hydrophilic and charged residues across the diverged evolutionary group predicted the functional conservation of the ACS protein. Presence of the putative cis-binding elements or DNA motifs, and its further comparison with DAP-seq-based cistrome and epicistrome of Arabidopsis, unraveled strong ancestry of melons with Arabidopsis. Motif comparison analysis also characterized putative genes and transcription factors involved in ethylene biosynthesis, signal transduction, and hormonal cross-talk related to sex expression. Overall, we have comprehensively reviewed research findings for a deeper insight into transcriptional and epigenetic regulation of sex expression and flower development in melons.

Sequence coverage required for accurate genotyping by sequencing in polyploid species

Polyploidy plays an important role in the evolution of eukaryotes, especially for flowering plants. Many of ecologically or agronomically important plant or crop species are polyploids, including sycamore maple (tetraploid), the world second and third largest food crops wheat (hexaploid) and potato (tetraploid) as well as economically important aquaculture animals such as Atlantic salmon and trout. The next generation sequencing data enables to allocate genotype at a sequence variant site, known as genotyping by sequencing (GBS). GBS has stimulated enormous interests in population based genomics studies in almost all diploid and many polyploid organisms. DNA sequence polymorphisms are codominant and thus fully informative about the underlying genotype at the polymorphic site, making GBS a straightforward task in diploids. However, sequence data may usually be uninformative in polyploid species, making GBS a far more challenging task in polyploids. This paper presents novel and rigorous statistical methods for predicting the number of sequence reads needed to ensure accurate GBS at a polymorphic site bared by the reads in polyploids and shows that a dozen of reads can ensure a probability of 95% to recover all constituent alleles of any tetraploid genotype but several hundreds of reads are needed to accurately uncover the genotype with probability confidence of 90%, subverting the proposition of GBS using low coverage sequence data in the literature. The theoretical prediction was tested by use of RAD-seq data from tetraploid potato cultivars. The paper provides polyploid experimentalists with theoretical guides and methods for designing and conducting their sequence-based studies.

Genotyping-By-Sequencing diversity analysis of international Vanilla collections uncovers hidden diversity and enables plant improvement

Genomics-based diversity analysis of natural vanilla populations is important in order to guide conservation efforts and genetic improvement through plant breeding. Vanilla is a cultivated, undomesticated spice that originated in Mesoamerica prior to spreading globally through vegetative cuttings. Vanilla extract from the commercial species, mainly V. planifolia and V. × tahitensis, is used around the world as an ingredient in foods, beverages, cosmetics, and pharmaceuticals. The global reliance on descendants of a few foundational clones in commercial production has resulted in an industry at heightened risk of catastrophic failure due to extremely narrow genetic diversity. Conversely, national and institutional collections including those near the center of cultivation contain previously undiscovered diversity that could bolster the genetic improvement of vanilla and guide conservation efforts. Towards this goal, an international vanilla genotyping effort generated and analyzed 431,204 single nucleotide polymorphisms among 412 accessions and 27 species from eight collections. Phylogenetic and STRUCTURE analysis sorted vanilla by species and identified hybrid accessions. Principal Component Analysis and the Fixation Index (FST) were used to refine relationships among accessions and showed differentiation among species. Analysis of the commercial species split V. planifolia into three types with all V. × tahitensis accessions being most similar to V. planifolia type 2. Finally, an in-depth analysis of V. × tahitensis identified seven V. planifolia and six V. odorata accessions as most similar to the estimated parental genotypes providing additional data in support of the current hybrid theory. The prevalence of probable V. × tahitensis parental accessions from Belize suggests that V. × tahitensis could have originated from this area and highlights the need for vanilla conservation throughout Central and South America. The genetic groupings among accessions, particularly for V. planifolia, can now be used to focus breeding efforts on fewer accessions that capture the greatest diversity.

Genome-Wide Scanning Enabled SNP Discovery, Linkage Disequilibrium Patterns and Population Structure in a Panel of Fonio (Digitaria exilis [Kippist] Stapf) Germplasm

White fonio (Digitaria exilis) is a staple food for millions of people in arid and semi-arid areas of West Africa. Knowledge about nutritional and health benefits, insights into morphological diversity, and the recent development of genomic resources call for a better understanding of the genetic structure of the extant germplasm gathered throughout the region in order to set up a robust breeding program. We assessed the genetic diversity and population structure of 259 fonio individuals collected from six countries from West Africa (Nigeria, Benin, Guinea, Mali, Burkina Faso and Niger) in this study using 688 putative out of 21,324 DArTseq-derived SNP markers. Due to the inbreeding and small population size, the results revealed a substantial level of genetic variability. Furthermore, two clusters were found irrespective of the geographic origins of accessions. Moreover, the high level of linkage disequilibrium (LD) between loci observed resulted from the mating system of the crop, which is often associated with a low recombination rate. These findings fill the gaps about the molecular diversity and genetic structure of the white fonio germplasm in West Africa. This was required for the application of genomic tools that can potentially speed up the genetic gain in fonio millet breeding for complex traits such as yield, and other nutrient contents.

Measurement of Transgene Copy Number in Plants Using Droplet Digital PCR

Transgenic plants are produced both to investigate gene function and to confer desirable traits into crops. Transgene copy number is known to influence expression levels, and consequently, phenotypes. Similarly, knowledge of transgene zygosity is desirable for making quantitative assessments of phenotype and tracking the inheritance of transgenes in progeny generations. Since the first transgenic plants were produced, several methods for determining copy number have been applied, including Southern blotting, quantitative real-time PCR, and more recently, sequencing methods; however, each method has specific disadvantages, compromising throughput, accuracy, or expense. Digital PCR (dPCR) divides reactions into partitions, converting the exponential, analogue nature of PCR into a linear, digital signal that allows the frequency of occurrence of specific sequences to be accurately estimated. Confidence increases with the number of partitions; therefore, the availability of emulsion technologies that enable reactions to be divided into tens of thousands of nanodroplets allows accurate determination of copy number in what has become known as digital droplet PCR (ddPCR). ddPCR offers similar benefits of low costs and scalability as other PCR techniques but with superior accuracy and reliability. Graphic abstract: Digital PCR (dPCR) divides reactions into partitions, converting the exponential, analogue nature of PCR into a linear, digital signal that allows the frequency of transgene copy number to be accurately assessed.

Detection of Single Nucleotide Polymorphisms by Fluorescence Embedded Dye SYBR Green I Based on Graphene Oxide

The detection of single nucleotide polymorphisms (SNPs) is of great significance in the early diagnosis of diseases and the rational use of drugs. Thus, a novel biosensor based on the quenching effect of fluorescence-embedded SYBR Green I (SG) dye and graphene oxide (GO) was introduced in this study. The probe DNA forms a double helix structure with perfectly complementary DNA (pcDNA) and 15 single-base mismatch DNA (smDNA) respectively. SG is highly intercalated with perfectly complementary dsDNA (pc-dsDNA) and exhibits strong fluorescence emission. Single-base mismatch dsDNA (SNPs) has a loose double-stranded structure and exhibits poor SG intercalation and low fluorescence sensing. At this time, the sensor still showed poor SNP discrimination. GO has a strong effect on single-stranded DNA (ssDNA), which can reduce the fluorescence response of probe DNA and eliminate background interference. And competitively combined with ssDNA in SNPs, quenching the fluorescence of SG/SNP, while the fluorescence value of pc-dsDNA was retained, increasing the signal-to-noise ratio. At this time, the sensor has obtained excellent SNP resolution. Different SNPs detect different intensities of fluorescence in the near-infrared region to evaluate the sensor's identification of SNPs. The experimental parameters such as incubation time, incubation temperature and salt concentration were optimized. Under optimal conditions, 1 nM DNA with 0–10 nM linear range and differentiate 5% SNP were achieved. The detection method does not require labeling, is low cost, simple in operation, exhibits high SNP discrimination and can be distinguished by SNP at room temperature.

Application of Genomics to Understand Salt Tolerance in Lentil

Soil salinity is a major abiotic stress, limiting lentil productivity worldwide. Understanding the genetic basis of salt tolerance is vital to develop tolerant varieties. A diversity panel consisting of 276 lentil accessions was screened in a previous study through traditional and image-based approaches to quantify growth under salt stress. Genotyping was performed using two contrasting methods, targeted (tGBS) and transcriptome (GBS-t) genotyping-by-sequencing, to evaluate the most appropriate methodology. tGBS revealed the highest number of single-base variants (SNPs) (c. 56,349), and markers were more evenly distributed across the genome compared to GBS-t. A genome-wide association study (GWAS) was conducted using a mixed linear model. Significant marker-trait associations were observed on Chromosome 2 as well as Chromosome 4, and a range of candidate genes was identified from the reference genome, the most plausible being potassium transporters, which are known to be involved in salt tolerance in related species. Detailed mineral composition performed on salt-treated and control plant tissues revealed the salt tolerance mechanism in lentil, in which tolerant accessions do not transport Na⁺ ions around the plant instead localize within the root tissues. The pedigree analysis identified two parental accessions that could have been the key sources of tolerance in this dataset.

Construction of a High-Density Genetic Map of Acca sellowiana (Berg.) Burret, an Outcrossing Species, Based on Two Connected Mapping Populations

Acca sellowiana, known as feijoa or pineapple guava, is a diploid, (2n = 2x = 22) outcrossing fruit tree species native to Uruguay and Brazil. The species stands out for its highly aromatic fruits, with nutraceutical and therapeutic value. Despite its promising agronomical value, genetic studies on this species are limited. Linkage genetic maps are valuable tools for genetic and genomic studies, and constitute essential tools in breeding programs to support the development of molecular breeding strategies. A high-density composite genetic linkage map of A. sellowiana was constructed using two genetically connected populations: H5 (TCO × BR, N = 160) and H6 (TCO × DP, N = 184). Genotyping by sequencing (GBS) approach was successfully applied for developing single nucleotide polymorphism (SNP) markers. A total of 4,921 SNP markers were identified using the reference genome of the closely related species Eucalyptus grandis, whereas other 4,656 SNPs were discovered using a de novo pipeline. The individual H5 and H6 maps comprised 1,236 and 1,302 markers distributed over the expected 11 linkage groups, respectively. These two maps spanned a map length of 1,593 and 1,572 cM, with an average inter-marker distance of 1.29 and 1.21 cM, respectively. A large proportion of markers were common to both maps and showed a high degree of collinearity. The composite map consisted of 1,897 SNPs markers with a total map length of 1,314 cM and an average inter-marker distance of 0.69. A novel approach for the construction of composite maps where the meiosis information of individuals of two connected populations is captured in a single estimator is described. A high-density, accurate composite map based on a consensus ordering of markers provides a valuable contribution for future genetic research and breeding efforts in A. sellowiana. A novel mapping approach based on an estimation of multipopulation recombination fraction described here may be applied in the construction of dense composite genetic maps for any other outcrossing diploid species.

An Integrated Approach of QTL Mapping and Genome-Wide Association Analysis Identifies Candidate Genes for Phytophthora Blight Resistance in Sesame (Sesamum indicum L.)

Phytophthora blight (PB) caused by Phytophthora nicotianae is a highly destructive disease in sesame (Sesamum indicum L.). In this study, we used linkage mapping and genome-wide association study (GWAS) to identify quantitative trait loci (QTL) and candidate genes associated with PB resistance. The QTL mapping in 90 RILs of the Goenbaek × Osan cross using genotyping-by-sequencing detected significant QTLs for PB resistance on chromosome 10, explaining 12.79%-13.34% of phenotypic variation. Association of this locus to PB resistance was also revealed through bulked segregant analysis in second RIL population (Goenbaek × Milsung cross) comprising 188 RILs. The GWAS of 87 sesame accessions evaluated against three P. nicotianae isolates identified 29 SNPs on chromosome 10 significantly associated with PB resistance. These SNPs were located within a 0.79 Mb region, which co-located with the QTL intervals identified in RIL populations, and hence scanned for identifying candidate genes. This region contained several defense-related candidate R genes, five of which were selected for quantitative expression analysis. One of these genes, SIN_1019016 was found to show significantly higher expression in the resistant parent compared to that in the susceptible parents and selected RILs. Paired-end sequencing of the gene SIN_1019016 in parental cultivars revealed two synonymous SNPs between Goenbaek and Osan in exon 2 of coding DNA sequence. These results suggested SIN_1019016 as one of the candidate gene conferring PB resistance in sesame. The findings from this study will be useful in the marker-assisted selection as well as the functional analysis of PB resistance candidate gene(s) in sesame.

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.

On genetic diversity in caraway: Genotyping of a large germplasm collection

Caraway (Carum carvi) is a widespread and frequently used spice and medicinal plant with a long history of cultivation. However, due to ongoing climatic changes, the cultivation is becoming increasingly risky. To secure caraway cultivation in future, timely breeding efforts to develop adapted material are necessary. Analysis of genetic diversity can accompany this process, for instance, by revealing untapped gene pools. Here, we analyzed 137 accessions using genotyping by sequencing (GBS). Hence, we can report a broad overview of population structure and genetic diversity of caraway. Population structure was determined using a principal coordinate analysis, a Bayesian clustering analysis, phylogenetic trees and a neighbor network based on 13,155 SNPs. Genotypic data indicate a clear separation of accessions into two subpopulations, which correlates with the flowering type (annual vs. biennial). Four winter-annual accessions were closer related to biennial accessions. In an analysis of molecular variance, genetic variation between the two subpopulations was 7.84%. In addition, we estimated the genome size for 35 accessions by flow cytometry. An average genome size of 4.282 pg/2C (± 0.0096 S.E.) was estimated. Therefore, we suggest a significantly smaller genome size than stated in literature.

Application of Genomic Big Data in Plant Breeding:Past, Present, and Future

Plant breeding has a long history of developing new varieties that have ensured the food security of the human population. During this long journey together with humanity, plant breeders have successfully integrated the latest innovations in science and technologies to accelerate the increase in crop production and quality. For the past two decades, since the completion of human genome sequencing, genomic tools and sequencing technologies have advanced remarkably, and adopting these innovations has enabled us to cost down and/or speed up the plant breeding process. Currently, with the growing mass of genomic data and digitalized biological data, interdisciplinary approaches using new technologies could lead to a new paradigm of plant breeding. In this review, we summarize the overall history and advances of plant breeding, which have been aided by plant genomic research. We highlight the key advances in the field of plant genomics that have impacted plant breeding over the past decades and introduce the current status of innovative approaches such as genomic selection, which could overcome limitations of conventional breeding and enhance the rate of genetic gain.

Genome- wide structural and functional variant discovery of rice landraces using genotyping by sequencing

Rice landraces are vital genetic resources for agronomic and quality traits but the undeniable collection of Kerala landraces remains poorly delineated. To effectively conserve, manage, and use these resources, understanding the genomic structure of germplasm is essential. Genotyping by sequencing (GBS) enables identification of an immense number of single nucleotide polymorphism (SNP) and insertion deletion (InDel) from 96 rice germplasm. In the present study, a total of 16.9 × 10⁷ reads were generated, and among that 16.3 × 10⁷ reads were mapped to the indica reference genome. Exploring GBS data unfolded a wide genomic variations including 82,59,639 SNPs and 1,07,140 Indels. Both neighbor-joining tree and principal coordinate analysis with InDel markers revealed the selected germplasm in this study as highly diverse in structure. We assembled unmapped reads which were further employed for gene ontology analysis. These unmapped sequences that are generally expelled from subsequent studies of GBS data analysis may exist as an unexplored resort for several novel significant biological findings. The discovery of SNPs from the haplotyping results of GS3 and GIF1 genes provided insight into marker- assisted selection based on grain size and yield and can be utilized for rice yield improvement. To our knowledge, this is the first report on structural variation analysis using the GBS platform in rice landraces collected from Kerala. Genomic information from this study endows with valuable resources for perceptive rice landrace structure and can also facilitate sequencing-based molecular breeding.

Arabidopsis plants expressing only the redox-regulated Rca-α isoform have constrained photosynthesis and plant growth

Rubisco activase (Rca) facilitates the release of sugar-phosphate inhibitors from the active sites of Rubisco and thereby plays a central role in initiating and sustaining Rubisco activation. In Arabidopsis, alternative splicing of a single Rca gene results in two Rca isoforms, Rca-α and Rca-β. Redox modulation of Rca-α regulates the function of Rca-α and Rca-β acting together to control Rubisco activation. Although Arabidopsis Rca-α alone less effectively activates Rubisco in vitro, it is not known how CO₂ assimilation and plant growth are impacted. Here, we show that two independent transgenic Arabidopsis lines expressing Rca-α in the absence of Rca-β ('Rca-α only' lines) grew more slowly in various light conditions, especially under low light or fluctuating light intensity, and in a short day photoperiod compared to wildtype. Photosynthetic induction was slower in the Rca-α only lines, and they maintained a lower rate of CO₂ assimilation during both photoperiod types. Our findings suggest Rca oligomers composed of Rca-α only are less effective in initiating and sustaining the activation of Rubisco than when Rca-β is also present. Currently there are no examples of any plant species that naturally express Rca-α only but numerous examples of species expressing Rca-β only. That Rca-α exists in most plant species, including many C3 and C4 food and bioenergy crops, implies its presence is adaptive under some circumstances.

A high-density SNP-based linkage map using genotyping-by-sequencing and its utilization for improved genome assembly of chickpea (Cicer arietinum L.)

Genotyping-by-sequencing (GBS) allows rapid identification of markers for use in development of linkage maps, which expedite efficient breeding programs. In the present study, we have utilized GBS approach to identify and genotype single-nucleotide polymorphism (SNP) markers in an inter-specific RIL population of Cicer arietinum L. X C. reticulatum. A total of 141,639 raw SNPs were identified using the TASSEL-GBS pipeline. After stringent filtering, 8208 candidate SNPs were identified of which ~ 37% were localized in the intragenic regions followed by genic regions (~ 30%) and intergenic regions (~ 27%). We then utilized 6920 stringent selected SNPs from present study and 6714 SNPs and microsatellite markers available from previous studies for construction of linkage map. The resulting high-density linkage map comprising of eight linkage groups contained 13,590 markers which spanned 1299.14 cM of map length with an average marker density of 0.095 cM. Further, the derived linkage map was used to improve the available assembly of desi chickpea genome by anchoring 443 previously unplaced scaffolds onto eight linkage groups. The present efforts have refined anchoring of the desi chickpea genome assembly to 55.57% of the ~ 520 Mb of assembled desi genome. To the best of our knowledge, the linkage map generated in the present study represents one of the most dense linkage map developed for the crop till date. It will serve as a valuable resource for fine mapping and positional cloning of important quantitative trait loci (QTLs) associated with agronomical traits and also for anchoring and ordering of future genome sequence assemblies.

Fostering Conservation via an Integrated Use of Conventional Approaches and High-Throughput SPET Genotyping: A Case Study Using the Endangered Canarian Endemics Solanum lidii and S. vespertilio (Solanaceae)

Islands provide unique opportunities to integrated research approaches to study evolution and conservation because boundaries are circumscribed, geological ages are often precise, and many taxa are greatly imperiled. We combined morphological and hybridization studies with high-throughput genotyping platforms to streamline relationships in the endangered monophyletic and highly diverse lineage of Solanum in the Canarian archipelago, where three endemic taxa are currently recognized. Inter-taxa hybridizations were performed, and morphological expression was assessed with a common-garden approach. Using the eggplant Single Primer Enrichment Technology (SPET) platform with 5,093 probes, 74 individuals of three endemic taxa (Solanum lidii, S. vespertilio subsp. vespertilio, and S. vespertilio subsp. doramae) were sampled for SNPs. While morphological and breeding studies showed clear distinctions and some continuous variation, inter-taxon hybrids were fertile and heterotic for vigor traits. SPET genotyping revealed 1,421 high-quality SNPs and supported four, not three, distinct taxonomic entities associated with post-emergence geological, ecological and geographic factors of the islands. Given the lack of barriers to hybridization among all the taxa and their molecular differences, great care must be taken in population management. Conservation strategies must take account of the sexual and breeding systems and genotypic distribution among populations to successfully conserve and restore threatened/endangered island taxa, as exemplified by Solanum on the Canary Islands.

Sequence-based genetic mapping of Cynodon dactylon Pers. reveals new insights into genome evolution in Poaceae

Bermudagrass (Cynodon dactylon Pers.) is an important warm-season perennial used extensively for turf, forage, soil conservation and remediation worldwide. However, limited genomic information has hindered the application of molecular tools towards understanding genome evolution and in breeding new cultivars. We genotype a first-generation selfed population derived from the tetraploid (4x = 36) ‘A12359’ using genotyping-by-sequencing. A high-density genetic map of 18 linkage groups (LGs) is constructed with 3,544 markers. Comparative genomic analyses reveal that each of nine homeologous LG pairs of C. dactylon corresponds to one of the first nine chromosomes of Oropetium thomaeum. Two nested paleo-ancestor chromosome fusions (ρ6-ρ9-ρ6, ρ2-ρ10-ρ2) may have resulted in a 12-to-10 chromosome reduction. A segmental dissemination of the paleo-chromosome ρ12 (ρ1-ρ12-ρ1, ρ6-ρ12-ρ6) leads to the 10-to-9 chromosome reduction in C. dactylon genome. The genetic map will assist in an ongoing whole genome sequence assembly and facilitate marker-assisted selection (MAS) in developing new cultivars.

Tilin Fang et al. study the genome of Bermudagrass (Cynodon dactylon Pers.). They use genotyping-by-sequencing and provide a genetic map with a 10-fold increase in genetic marker density. Comparative genomics analyses reveal chromosome rearrangements. Their work will contribute to whole genome assembly efforts which will be beneficial for developing new cultivars.

IonBreeders: bioinformatics plugins toward genomics-assisted breeding

Polymorphism information generated by next-generation sequencing (NGS) technologies has enabled applications of genome-wide markers assisted breeding. However, handling such large-scale data remains a challenge for experimental researchers and breeders, calling for the urgent development of a flexible and straightforward analysis tool for NGS data. We developed "IonBreeders" as bioinformatics plugins that implement general analysis steps from genotyping to genomic prediction. IonBreeders comprises three plugins, "ABH", "IMPUTATION", and "GENOMIC PREDICTION", for format conversion of genotyping data, preprocessing and imputation of genotyping data, and genomic prediction, respectively. "ABH" converts genotyping data derived from NGS into the ABH format, which is acceptable for our further plugins and with other breeding software tools, R/qtl, MapMaker, and AntMap. "IMPUTATION" filters out non-informative markers and imputes missing marker genotypes. In "GENOMIC PREDICTION", users can use four statistical methods based on their target trait, quantitative trait locus effect, and number of markers, and construct a prediction model for genomic selection. IonBreeders is operated in Torrent Suite, but can also handle genotype data in standard formats, e.g., Variant Call Format (VCF), by format conversion using free software or our provided scripts.

Genotyping by RAD Sequencing Analysis Assessed the Genetic Distinctiveness of Experimental Lines and Narrowed Down the Genomic Region Responsible for Leaf Shape in Endive (Cichorium endivia L.)

The characterization of genetic diversity in elite breeding stocks is crucial for the registration and protection of new varieties. Moreover, experimental population structure analysis and information about the genetic distinctiveness of commercial materials are essential for crop breeding programs. The purpose of our research was to assess the genetic relationships of 32 endive (Cichorium endivia L.) breeding lines, 18 from var. latifolium (escarole) and 14 from var. crispum (curly), using heterologous Cichorium intybus-derived simple sequence repeats (SSR) markers and single-nucleotide polymorphisms (SNP) markers. We found that 14 out of 29 SSR markers were successfully amplified, but only 8 of them were related to polymorphic loci. To overcome the limitation of the low number of informative SSR marker loci, an alternative SNP-based approach was employed. The 4621 SNPs produced by a restriction site-associated DNA marker sequencing approach were able to fully discriminate the 32 endive accessions; most importantly, as many as 50 marker loci were found to distinguish the curly group from the escarole group. Interestingly, 24 of the marker loci mapped within a peripheral segment of chromosome 8 of lettuce (Lactuca sativa L.), spanning a chromosomal region of 49.6 Mb. Following Sanger sequencing-based validation, three genes were determined to carry nonsynonymous SNPs, and one of them matched a putative ortholog of AtELP1, subunit 1 of the Elongator complex. Considering that several previously characterized Elongator complex subunit mutants exhibited elongated and/or curly leaf phenotypes, this gene should be taken into consideration for a better understanding of the underlying mechanism controlling leaf shape in endive.

Development of new genetic resources for faba bean (Vicia faba L.) breeding through the discovery of gene-based SNP markers and the construction of a high-density consensus map

Faba bean (Vicia faba L.) is a pulse crop of high nutritional value and high importance for sustainable agriculture and soil protection. With the objective of identifying gene-based SNPs, transcriptome sequencing was performed in order to reduce faba bean genome complexity. A set of 1,819 gene-based SNP markers polymorphic in three recombinant line populations was selected to enable the construction of a high-density consensus genetic map encompassing 1,728 markers well distributed in six linkage groups and spanning 1,547.71 cM with an average inter-marker distance of 0.89 cM. Orthology-based comparison of the faba bean consensus map with legume genome assemblies highlighted synteny patterns that partly reflected the phylogenetic relationships among species. Solid blocks of macrosynteny were observed between faba bean and the most closely-related sequenced legume species such as pea, barrel medic or chickpea. Numerous blocks could also be identified in more divergent species such as common bean or cowpea. The genetic tools developed in this work can be used in association mapping, genetic diversity, linkage disequilibrium or comparative genomics and provide a backbone for map-based cloning. This will make the identification of candidate genes of interest more efficient and will accelerate marker-assisted selection (MAS) and genomic-assisted breeding (GAB) in faba bean.

Genome-wide SNP identification in Prunus rootstocks germplasm collections using Genotyping-by-Sequencing: phylogenetic analysis, distribution of SNPs and prediction of their effect on gene function

Genotyping-by-Sequencing (GBS) was applied in a set of 53 diploid Prunus rootstocks and five scion cultivars from three subgenera (Amygdalus, Prunus and Cerasus) for genome-wide SNP identification and to assess genetic diversity of both Chilean and Spanish germplasm collections. A group of 45,382 high quality SNPs (MAF >0.05; missing data <5%) were selected for analysis of this group of 58 accessions. These SNPs were distributed in genic and intergenic regions in the eight pseudomolecules of the peach genome (Peach v2.0), with an average of 53% located in exonic regions. The genetic diversity detected among the studied accessions divided them in three groups, which are in agreement with their current taxonomic classification. SNPs were classified based on their putative effect on annotated genes and KOG analysis was carried out to provide a deeper understanding of the function of 119 genes affected by high-impact SNPs. Results demonstrate the high utility for Prunus rootstocks identification and studies of diversity in Prunus species. Also, given the high number of SNPs identified in exonic regions, this strategy represents an important tool for finding candidate genes underlying traits of interest and potential functional markers for use in marker-assisted selection.

Enhancing Hybrid Prediction in Pearl Millet Using Genomic and/or Multi-Environment Phenotypic Information of Inbreds

Genomic selection (GS) is an emerging methodology that helps select superior lines among experimental cultivars in plant breeding programs. It offers the opportunity to increase the productivity of cultivars by delivering increased genetic gains and reducing the breeding cycles. This methodology requires inexpensive and sufficiently dense marker information to be successful, and with whole genome sequencing, it has become an important tool in many crops. The recent assembly of the pearl millet genome has made it possible to employ GS models to improve the selection procedure in pearl millet breeding programs. Here, three GS models were implemented and compared using grain yield and dense molecular marker information of pearl millet obtained from two different genotyping platforms (C [conventional GBS RAD-seq] and T [tunable GBS tGBS]). The models were evaluated using three different cross-validation (CV) schemes mimicking real situations that breeders face in breeding programs: CV2 resembles an incomplete field trial, CV1 predicts the performance of untested hybrids, and CV0 predicts the performance of hybrids in unobserved environments. We found that (i) adding phenotypic information of parental inbreds to the calibration sets improved predictive ability, (ii) accounting for genotype-by-environment interaction also increased the performance of the models, and (iii) superior strategies should consider the use of the molecular markers derived from the T platform (tGBS).

Multiregional origins of the domesticated tetraploid wheats

We used genotyping-by-sequencing (GBS) to investigate the evolutionary history of domesticated tetraploid wheats. With a panel of 189 wild and domesticated wheats, we identified 1,172,469 single nucleotide polymorphisms (SNPs) with a read depth ≥3. Principal component analyses (PCAs) separated the Triticum turgidum and Triticum timopheevii accessions, as well as wild T. turgidum from the domesticated emmers and the naked wheats, showing that SNP typing by GBS is capable of providing robust information on the genetic relationships between wheat species and subspecies. The PCAs and a neighbour-joining analysis suggested that domesticated tetraploid wheats have closest affinity with wild emmers from the northern Fertile Crescent, consistent with the results of previous genetic studies on the origins of domesticated wheat. However, a more detailed examination of admixture and allele sharing between domesticates and different wild populations, along with genome-wide association studies (GWAS), showed that the domesticated tetraploid wheats have also received a substantial genetic input from wild emmers from the southern Levant. Taking account of archaeological evidence that tetraploid wheats were first cultivated in the southern Levant, we suggest that a pre-domesticated crop spread from this region to southeast Turkey and became mixed with a wild emmer population from the northern Fertile Crescent. Fixation of the domestication traits in this mixed population would account for the allele sharing and GWAS results that we report. We also propose that feralization of the component of the pre-domesticated population that did not acquire domestication traits has resulted in the modern wild population from southeast Turkey displaying features of both the domesticates and wild emmer from the southern Levant, and hence appearing to be the sole progenitor of domesticated tetraploids when the phylogenetic relationships are studied by methods that assume a treelike pattern of evolution.

Genetic Diversity, Pedigree Relationships, and A Haplotype-Based DNA Fingerprinting System of Red Bayberry Cultivars

High throughput sequencing was used to reveal the distribution of whole-genome variations in cultivated Morella rubra (Sieb. et Zucc.). A total of 3,151,123 SNPs, 371,757 small indels, and 15,904 SVs were detected in 52 accessions. Verification by Sanger sequencing demonstrated that the positive rate of the SNPs was approximately 97.3%. Search for more genetic variations was expanded to 141 red bayberry accessions, most of which were cultivars, by sequencing 19 selected genomic segments (SEG1-19). The results showed that each segment harbored, on average, 7.8 alleles (haplotypes), a haplotype diversity of 0.42, and a polymorphic information content (PIC) of 0.40. Seventy-two different genotypes were identified from the 141 accessions, and statistical analysis showed that the accessions with duplicated genotypes were either somatic mutants or simply synonyms. Core set selection results showed that a minimum of 34 genotypes could already have covered all the alleles on the segments. A DNA fingerprinting system was developed for red bayberry, which used the diversity information of only 8 DNA segments yet still achieved a very high efficiency without losing robustness. No large clade was robustly supported by hierarchical clustering, and well-supported small clusters mainly included close relatives. These results should lead to an improved understanding of the genetic diversity of red bayberry and be valuable for future molecular breeding and variety protection.

Targeted genotyping by sequencing: a new way to genome profile the cat

Targeted GBS is a recent approach for obtaining an effective characterization for hundreds to thousands of markers. The high throughput of next-generation sequencing technologies, moreover, allows sample multiplexing. The aims of this study were to (i) define a panel of single nucleotide polymorphisms (SNPs) in the cat, (ii) use GBS for profiling 16 cats, and (iii) evaluate the performance with respect to the inference using standard approaches at different coverage thresholds, thereby providing useful information for designing similar experiments. Probes for sequencing 230 variants were designed based on the Felis_catus_8.0. 8.0 genome. The regions comprised anonymous and non-anonymous SNPs. Sixteen cat samples were analysed, some of which had already been genotyped in a large group of loci and one having been whole-genome sequenced in the 99_Lives Cat Genome Sequencing Project. The accuracy of the method was assessed by comparing the GBS results with the genotypes already available. Overall, GBS achieved good performance, with 92-96% correct assignments, depending on the coverage threshold used to define the set of trustable genotypes. Analyses confirmed that (i) the reliability of the inference of each genotype depends on the coverage at that locus and (ii) the fraction of target loci whose genotype can be inferred correctly is a function of the total coverage. GBS proves to be a valid alternative to other methods. Data suggested a depth of less than 11× is required for greater than 95% accuracy. However, sequencing depth must be adapted to the total size of the targets to ensure proper genotype inference.

Advances in Omics Approaches for Abiotic Stress Tolerance in Tomato

Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.

Genotyping-by-Sequencing of Gossypium hirsutum Races and Cultivars Uncovers Novel Patterns of Genetic Relationships and Domestication Footprints

Determining the genetic rearrangement and domestication footprints in Gossypium hirsutum cultivars and primitive race genotypes are essential for effective gene conservation efforts and the development of advanced breeding molecular markers for marker-assisted breeding. In this study, 94 accessions representing the 7 primitive races of G hirsutum, along with 9 G hirsutum and 12 Gossypium barbadense cultivated accessions were evaluated. The genotyping-by-sequencing (GBS) approach was employed and 146 558 single nucleotide polymorphisms (SNP) were generated. Distinct SNP signatures were identified through the combination of selection scans and association analyses. Phylogenetic analyses were also conducted, and we concluded that the Latifolium, Richmondi, and Marie-Galante race accessions were more genetically related to the G hirsutum cultivars and tend to cluster together. Fifty-four outlier SNP loci were identified by selection-scan analysis, and 3 SNPs were located in genes related to the processes of plant responding to stress conditions and confirmed through further genome-wide signals of marker-phenotype association analysis, which indicate a clear selection signature for such trait. These results identified useful candidate gene locus for cotton breeding programs.

Reference Genome Anchoring of High-Density Markers for Association Mapping and Genomic Prediction in European Winter Wheat

In this study, we anchored genotyping-by-sequencing data to the International Wheat Genome Sequencing Consortium Reference Sequence v1.0 assembly to generate over 40,000 high quality single nucleotide polymorphism markers on a panel of 376 elite European winter wheat varieties released between 1946 and 2007. We compared association mapping and genomic prediction accuracy for a range of productivity traits with previous results based on lower density dominant DArT markers. The results demonstrate that the availability of RefSeq v1.0 supports higher precision trait mapping and provides the density of markers required to obtain accurate predictions of traits controlled by multiple small effect loci, including grain yield.