Pyramiding of triple Clubroot resistance loci conferred superior resistance without negative effects on agronomic traits in Brassica napus.

Clubroot disease caused by Plasmodiophora brassicae is becoming a serious threat to rapeseed (Brassica napus) production worldwide. Breeding resistant varieties using CR (clubroot resistance) loci is the most promising solution. Using marker-assisted selection and speed-breeding technologies, we generated Brassica napus materials in homozygous or heterozygous states using CRA3.7, CRA08.1, and CRA3.2 loci in the elite parental line of the Zhongshuang11 background. We developed three elite lines with two CR loci in different combinations and one line with three CR loci at the homozygous state. In our study, we used six different clubroot strains (Xinmin, Lincang, Yuxi, Chengdu, Chongqing, and Jixi) which are categorized into three groups based on our screening results. The newly pyramided lines with two or more CR loci displayed better disease resistance than the parental lines carrying single CR loci. There is an obvious gene dosage effect between CR loci and disease resistance levels. For example, pyramided lines with triple CR loci in the homozygous state showed superior resistance for all pathogens tested. Moreover, CR loci in the homozygous state are better on disease resistance than the heterozygous state. More importantly, no negative effect was observed on agronomic traits for the presence of multiple CR loci in the same background. Overall, these data suggest that the pyramiding of triple clubroot resistance loci conferred superior resistance with no negative effects on agronomic traits in Brassica napus.

A comprehensive phenotypic and genotypic evaluation of Spanish groundnuts from diverse crosses to identify superior and stable donors for fresh seed dormancy.

Breeding high yielding groundnut cultivars with 2-3 weeks of fresh seed dormancy, particularly in Spanish-type cultivars, enhances the sustainability of agriculture in groundnuts. In this context, we conducted a comprehensive phenotypic and genotypic evaluation of advanced breeding lines developed in the genetic background of Spanish types. By employing multi-phenotyping and marker data, we identified PBS 15044, 16004, 16013, 16015, 16016, 16017, 16020, 16021, 16026, 16031, 16035, 16037, 16038, 16039, 16041, and 16042 with 2-3 weeks dormancy (> 90%).The various parametric and non-parametric estimates identified the stable fresh dormant genotypes with one or more superior economic trait. PBS 16021, 15044, 16038, and 16039 identified with high hundred pod weight (HPW) were also reported having high intensity of dormancy (> 90% for up to 3 weeks); PBS 15044, 16016, PBS 16038 and PBS 16039 with high hundred kernel weight (HKW) also reported with up to 3 weeks fresh seed dormancy; and PBS 16013, 16031, and 16038 with up to 3 weeks fresh seed dormancy had high shelling percentage (SP). They can be used to develop lines with the desired level of dormancy, and high yields, by designing appropriate breeding strategies.

GWAS elucidated grain yield genetics in Indian spring wheat under diverse water conditions.

KEY MESSAGE: Underpinned natural variations and key genes associated with yield under different water regimes, and identified genomic signatures of genetic gain in the Indian wheat breeding program. A novel KASP marker for TKW under water stress was developed and validated. A comprehensive genome-wide association study was conducted on 300 spring wheat genotypes to elucidate the natural variations associated with grain yield and its eleven contributing traits under fully irrigated, restricted water, and simulated no water conditions. Utilizing the 35K Wheat Breeders' Array, we identified 1155 quantitative trait nucleotides (QTNs), with 207 QTNs exhibiting stability across diverse conditions. These QTNs were further delimited into 539 genomic regions using a genome-wide LD value of 3.0 Mbp, revealing pleiotropic control across traits and conditions. Sub-genome A was significantly associated with traits under irrigated conditions, while sub-genome B showed more QTNs under water stressed conditions. Favourable alleles with significantly associated QTNs were delineated, with a notable pyramiding effect for enhancing trait performance. Additionally, allele of only 921 QTNs significantly affected the population mean. Allele profiling highlighted C-306 as a most potential source of drought tolerance. Moreover, 762 genes overlapping significant QTNs were identified, narrowing down to 27 putative candidate genes overlapping 29 novel and functional SNPs expressing (≥ 0.5 tpm) relevance across various growth conditions. A new KASP assay was developed, targeting a gene TraesCS2A03G1123700 regulating thousand kernel weight under severe drought condition. Genomic selection models (GBLUP, BayesB, MxE, and R-Norm) demonstrated an average prediction accuracy of 0.06-0.58 across environments, indicating potential for trait selection. Retrospective analysis of the Indian wheat breeding program supported a genetic gain in GY at the rate of ca. 0.56% per breeding cycle, since 1960, supporting the identification of genomic signatures driving trait selection and genetic gain. These findings offer insight into improving the rate of genetic gain in wheat breeding programs globally.

Creation of rice doubled haploids with low amylose content using in vitro anther culture.

In vitro androgenesis is a unique model for producing homozygous doubled haploid plants. The use of haploid biotechnology accelerates to obtain of doubled haploid plants, which is very important in rice breeding. The purpose of this work is to improve the production of doubled haploids in rice anther culture in vitro and selection of doubled haploid plants with valuable traits. The study the influence of nutrient media on the production of calli and plant regeneration processes in anther culture of 35 rice genotypes was revealed a significant influence of nutrient media on callus production. It was shown that the addition to culture medium phytohormones ratio with high level of cytokinin (5.0 mg/L BAP) and a low level of auxin (0.5 mg/L NAA), supplemented with amino acid composition promotes high production of green regenerated plants (68.75%) compared to albino plants (31.25%). As a result, doubled haploid lines of the glutinous variety Violetta were selected, which characterized by a low amylose content variation (from 1.86 to 2.80%). These doubled haploids are superior to the original variety in some yield traits and represent valuable breeding material.

Anther Culture Protocols for Barley and Wheat.

Doubled haploid (DH) techniques remain valuable tools for wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) genetic improvement, and DH populations are used extensively in breeding and research endeavors. Several techniques are available for DH production in wheat and barley. Here, we describe two simple, robust anther culture methods used to produce more than 15,000 DH wheat and barley lines annually in Australia.

Germination Assays for Comparable Seed Dormancy Depth and Distinction of Seed Color by Multiplex PCR in Wheat.

Seed dormancy is an important trait in cereal breeding, as it prevents preharvest sprouting (PHS). Although seed dormancy is a multifactorial trait, seed color has been demonstrated to be a major dormancy-related factor controlled by few genes. The R-1 gene is a seed color regulator that encodes a MYB-type transcription factor in wheat. A set of genetic markers designed against R-1 can provide a powerful tool for swift wheat breeding. Depth of seed dormancy varies not only among lines but also during seed development in each line. In this chapter, we describe how developmental seeds can be collected to perform germination tests, how seed color can be observed after NaOH staining, and how to genotype wheat R-1 genes using multiplex PCR.

Regulation of Seed Dormancy Genes in Triticeae Species.

Wild progenitors of Triticeae crops generally have long dormancy periods. Domesticated crops inherited these longer dormancy alleles from their wild progenitors, which have since been modified and selected during cultivation and utilization by humans. Thus, allelic combinations at different seed dormancy loci are currently represented in Triticeae germplasm preserved in seed repositories and gene banks as accessions and materials of breeding programs. Methods to evaluate seed dormancy are key to explore, analyze, and exploit optimal alleles in dormancy genes. Recent developments in genomics have accelerated the identification and analysis of seed dormancy loci in Triticeae species. Transgenic experiments have been conducted to validate if candidate genes affect seed dormancy and more recently have yielded an array of mutations derived from genome editing for practical applications. The information gathered on these seed dormancy loci provides a deeper knowledge of germplasm diversity and offers strategies to control seed dormancy in breeding programs in Triticeae crops.

Evaluation Methods for Preharvest Sprouting Resistance in Japanese Wheat Breeding Programs.

Different methodologies have been applied for the selection of preharvest sprouting resistance in cereal breeding programs. We describe here a series of methods used in practical wheat breeding programs in Japan, including phenotyping based on germination score after artificial rain treatments and genotyping using DNA markers. These methods can be modified and applied to breeding programs in which preharvest sprouting is a problem during cereal cultivation.

Polyploidy in maize: from evolution to breeding.

Polyploidy played an important role in the evolution of the three most important crops: wheat, maize and rice, each of them providing a unique model for studying allopolyploidy, segmental alloploidy or paleopolyploidy. However, its genetic and evolutionary role is still vague. The undelying mechanisms and consequences of polyploidy remain fundamental objectives in the study of eukaryotes. Maize is one of the underutilized crops at the polyploid level. This species has no stable natural polyploids, the existing ones being artificially obtained. From the experimental polyploid series of maize, only the tetraploid forms (4n = 40) are of interest. They are characterized by some valuable morphological, physiological and biochemical features, superior to the diploid forms from which they originated, but also by some drawbacks such as: reduced fertility, slower development, longer vegetation period, low productivity and adaptedness. Due to these barriers to using tetraploids in field production, maize tetraploids primarily found utility in scientific studies regarding genetic variability, inbreeding, heterosis and gene dosage effect. Since the first mention of a triploid maize plant to present, many scientists and schools, devoted their efforts to capitalize on the use of polyploidy in maize. Despite its common disadvantages as a crop, significant progress in developing tetraploid maize with good agronomic performance was achieved leading to registered tetraploid maize varieties. In this review we summarize and discuss the different aspects of polyploidy in maize, such as evolutionary context, methods of induction, morphology, fertility issue, inheritance patterns, gene expression and potential use.

Quantitative trait locus analysis of gray leaf spot resistance in the maize IBM Syn10 DH population.

KEY MESSAGE: The exploration and dissection of a set of QTLs and candidate genes for gray leaf spot disease resistance using two fully assembled parental genomes may help expedite maize resistance breeding. The fungal disease of maize known as gray leaf spot (GLS), caused by Cercospora zeae-maydis and Cercospora zeina, is a significant concern in China, Southern Africa, and the USA. Resistance to GLS is governed by multiple genes with an additive effect and is influenced by both genotype and environment. The most effective way to reduce the cost of production is to develop resistant hybrids. In this study, we utilized the IBM Syn 10 Doubled Haploid (IBM Syn10 DH) population to identify quantitative trait loci (QTLs) associated with resistance to gray leaf spot (GLS) in multiple locations. Analysis of seven distinct environments revealed a total of 58 QTLs, 49 of which formed 12 discrete clusters distributed across chromosomes 1, 2, 3, 4, 8 and 10. By comparing these findings with published research, we identified colocalized QTLs or GWAS loci within eleven clustering intervals. By integrating transcriptome data with genomic structural variations between parental individuals, we identified a total of 110 genes that exhibit both robust disparities in gene expression and structural alterations. Further analysis revealed 19 potential candidate genes encoding conserved resistance gene domains, including putative leucine-rich repeat receptors, NLP transcription factors, fucosyltransferases, and putative xyloglucan galactosyltransferases. Our results provide a valuable resource and linked loci for GLS marker resistance selection breeding in maize.

An Introduction to Plant Cell, Tissue, and Organ Culture: Current Status and Perspectives.

Plant cell, tissue, and organ cultures (PCTOC) have been used as experimental systems in basic research, allowing gene function demonstration through gene overexpression or repression and investigating the processes involved in embryogenesis and organogenesis or those related to the potential production of secondary metabolites, among others. On the other hand, PCTOC has also been applied at the commercial level for the vegetative multiplication (micropropagation) of diverse plant species, mainly ornamentals but also horticultural crops such as potato or fruit and tree species, and to produce high-quality disease-free plants. Moreover, PCTOC protocols are important auxiliary systems in crop breeding crops to generate pure lines (homozygous) to produce hybrids for the obtention of polyploid plants with higher yields or better performance. PCTOC has been utilized to preserve and conserve the germplasm of different crops or threatened species. Plant genetic improvement through genetic engineering and genome editing has been only possible thanks to the establishment of efficient in vitro plant regeneration protocols. Different companies currently focus on commercializing plant secondary metabolites with interesting biological activities using in vitro PCTOC. The impact of omics on PCTOC is discussed.

High-dimensional multi-omics measured in controlled conditions are useful for maize platform and field trait predictions.

KEY MESSAGE: Transcriptomics and proteomics information collected on a platform can predict additive and non-additive effects for platform traits and additive effects for field traits. The effects of climate change in the form of drought, heat stress, and irregular seasonal changes threaten global crop production. The ability of multi-omics data, such as transcripts and proteins, to reflect a plant's response to such climatic factors can be capitalized in prediction models to maximize crop improvement. Implementing multi-omics characterization in field evaluations is challenging due to high costs. It is, however, possible to do it on reference genotypes in controlled conditions. Using omics measured on a platform, we tested different multi-omics-based prediction approaches, using a high dimensional linear mixed model (MegaLMM) to predict genotypes for platform traits and agronomic field traits in a panel of 244 maize hybrids. We considered two prediction scenarios: in the first one, new hybrids are predicted (CV-NH), and in the second one, partially observed hybrids are predicted (CV-POH). For both scenarios, all hybrids were characterized for omics on the platform. We observed that omics can predict both additive and non-additive genetic effects for the platform traits, resulting in much higher predictive abilities than GBLUP. It highlights their efficiency in capturing regulatory processes in relation to growth conditions. For the field traits, we observed that the additive components of omics only slightly improved predictive abilities for predicting new hybrids (CV-NH, model MegaGAO) and for predicting partially observed hybrids (CV-POH, model GAOxW-BLUP) in comparison to GBLUP. We conclude that measuring the omics in the fields would be of considerable interest in predicting productivity if the costs of omics drop significantly.

Genome-wide association study reveals marker-trait associations for major agronomic traits in proso millet (Panicum miliaceum L.).

MAIN CONCLUSION: The pilot-scale genome-wide association study in the US proso millet identified twenty marker-trait associations for five morpho-agronomic traits identifying genomic regions for future studies (e.g. molecular breeding and map-based cloning). Proso millet (Panicum miliaceum L.) is an ancient grain recognized for its excellent water-use efficiency and short growing season. It is an indispensable part of the winter wheat-based dryland cropping system in the High Plains of the USA. Its grains are endowed with high nutritional and health-promoting properties, making it increasingly popular in the global market for healthy grains. There is a dearth of genomic resources in proso millet for developing molecular tools to complement conventional breeding for developing high-yielding varieties. Genome-wide association study (GWAS) is a widely used method to dissect the genetics of complex traits. In this pilot study of the first-ever GWAS in the US proso millet, 71 globally diverse genotypes of 109 the US proso millet core collection were evaluated for five major morpho-agronomic traits at two locations in western Nebraska, and GWAS was conducted to identify single nucleotide polymorphisms (SNPs) associated with these traits. Analysis of variance showed that there was a significant difference among the genotypes, and all five traits were also found to be highly correlated with each other. Sequence reads from genotyping-by-sequencing (GBS) were used to identify 11,147 high-quality bi-allelic SNPs. Population structure analysis with those SNPs showed stratification within the core collection. The GWAS identified twenty marker-trait associations (MTAs) for the five traits. Twenty-nine putative candidate genes associated with the five traits were also identified. These genomic regions can be used to develop genetic markers for marker-assisted selection in proso millet breeding.

Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

KEY MESSAGE: Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with high-dimensional data such as climate and soil information is becoming a common practice in breeding programs. This study explored new ways to combine non-genetic information in genomic prediction models using machine learning. Using the multi-environment trial data from the Genomes To Fields initiative, different models to predict maize grain yield were adjusted using various inputs: genetic, environmental, or a combination of both, either in an additive (genetic-and-environmental; G+E) or a multiplicative (genotype-by-environment interaction; GEI) manner. When including environmental data, the mean prediction accuracy of machine learning genomic prediction models increased up to 7% over the well-established Factor Analytic Multiplicative Mixed Model among the three cross-validation scenarios evaluated. Moreover, using the G+E model was more advantageous than the GEI model given the superior, or at least comparable, prediction accuracy, the lower usage of computational memory and time, and the flexibility of accounting for interactions by construction. Our results illustrate the flexibility provided by the ML framework, particularly with feature engineering. We show that the feature engineering stage offers a viable option for envirotyping and generates valuable information for machine learning-based genomic prediction models. Furthermore, we verified that the genotype-by-environment interactions may be considered using tree-based approaches without explicitly including interactions in the model. These findings support the growing interest in merging high-dimensional genotypic and environmental data into predictive modeling.

Cytogenetic identification and molecular mapping for the wheat-Thinopyrum ponticum introgression line with resistance to Fusarium head blight.

KEY MESSAGE: Xinong 511, a new wheat-Thinopyrum ponticum variety with excellent fusarium head blight resistance, the QTLs were mapped to the wheat chromosomes 5B and 7A with named QFhb.nwafu-5B and QFhb.nwafu-7A, respectively. Novel Fusarium head blight (FHB) resistance germplasms and genes are valuable for wheat improvement and breeding efforts. Thinopyrum ponticum, a wild relative of common wheat, is a valuable germplasm of disease resistance for wheat improvement and breeding. Xinong 511 (XN511) is a high-quality wheat variety widely cultivated in the Yellow and Huai Rivers Valley of China with stable FHB-resistance. Through analysis of pedigree materials of the wheat cultivar XN511, we found that the genetic material and FHB resistance from Th. ponticum were transmitted to the introgression line, indicating that the FHB resistance in XN511 likely originates from Th. ponticum. To further explore the genetic basis of FHB resistance in XN511, QTL mapping was conducted using the RILs population of XN511 and the susceptible line Aikang 58 (AK58). Survey with makers closely-linked to Fhb1, Fhb2, Fhb4, Fhb5, and Fhb7, indicated that both XN511 and the susceptible lines do not contain these QTL. Using bulked segregant analysis RNA-seq (BSR-Seq) and newly developed allele-specific PCR (AS-PCR) markers, QTLs in XN511 were successfully located on wheat chromosomes 5B and 7A. These findings are significant for further understanding and utilizing FHB resistance genes in wheat improvement.

Enhanced recombination empowers the detection and mapping of Quantitative Trait Loci.

Modern plant breeding, such as genomic selection and gene editing, is based on the knowledge of the genetic architecture of desired traits. Quantitative trait loci (QTL) analysis, which combines high throughput phenotyping and genotyping of segregating populations, is a powerful tool to identify these genetic determinants and to decipher the underlying mechanisms. However, meiotic recombination, which shuffles genetic information between generations, is limited: Typically only one to two exchange points, called crossovers, occur between a pair of homologous chromosomes. Here we test the effect on QTL analysis of boosting recombination, by mutating the anti-crossover factors RECQ4 and FIGL1 in Arabidopsis thaliana full hybrids and lines in which a single chromosome is hybrid. We show that increasing recombination ~6-fold empowers the detection and resolution of QTLs, reaching the gene scale with only a few hundred plants. Further, enhanced recombination unmasks some secondary QTLs undetected under normal recombination. These results show the benefits of enhanced recombination to decipher the genetic bases of traits.

A catalogue of recombination coldspots in interspecific tomato hybrids.

Increasing natural resistance and resilience in plants is key for ensuring food security within a changing climate. Breeders improve these traits by crossing cultivars with their wild relatives and introgressing specific alleles through meiotic recombination. However, some genomic regions are devoid of recombination especially in crosses between divergent genomes, limiting the combinations of desirable alleles. Here, we used pooled-pollen sequencing to build a map of recombinant and non-recombinant regions between tomato and five wild relatives commonly used for introgressive tomato breeding. We detected hybrid-specific recombination coldspots that underscore the role of structural variations in modifying recombination patterns and maintaining genetic linkage in interspecific crosses. Crossover regions and coldspots show strong association with specific TE superfamilies exhibiting differentially accessible chromatin between somatic and meiotic cells. About two-thirds of the genome are conserved coldspots, located mostly in the pericentromeres and enriched with retrotransposons. The coldspots also harbor genes associated with agronomic traits and stress resistance, revealing undesired consequences of linkage drag and possible barriers to breeding. We presented examples of linkage drag that can potentially be resolved by pairing tomato with other wild species. Overall, this catalogue will help breeders better understand crossover localization and make informed decisions on generating new tomato varieties.

Accuracy of prediction from multi-environment trials for new locations using pedigree information and environmental covariates: the case of sorghum (Sorghum bicolor (L.) Moench) breeding.

KEY MESSAGES: We investigate a method of extracting and fitting synthetic environmental covariates and pedigree information in multilocation trial data analysis to predict genotype performances in untested locations. Plant breeding trials are usually conducted across multiple testing locations to predict genotype performances in the targeted population of environments. The predictive accuracy can be increased by the use of adequate statistical models. We compared linear mixed models with and without synthetic covariates (SCs) and pedigree information under the identity, the diagonal and the factor-analytic variance-covariance structures of the genotype-by-location interactions. A comparison was made to evaluate the accuracy of different models in predicting genotype performances in untested locations using the mean squared error of predicted differences (MSEPD) and the Spearman rank correlation between predicted and adjusted means. A multi-environmental trial (MET) dataset evaluated for yield performance in the dry lowland sorghum (Sorghum bicolor (L.) Moench) breeding program of Ethiopia was used. For validating our models, we followed a leave-one-location-out cross-validation strategy. A total of 65 environmental covariates (ECs) obtained from the sorghum test locations were considered. The SCs were extracted from the ECs using multivariate partial least squares analysis and subsequently fitted in the linear mixed model. Then, the model was extended accounting for pedigree information. According to the MSEPD, models accounting for SC improve predictive accuracy of genotype performances in the three of the variance-covariance structures compared to others without SC. The rank correlation was also higher for the model with the SC. When the SC was fitted, the rank correlation was 0.58 for the factor analytic, 0.51 for the diagonal and 0.46 for the identity variance-covariance structures. Our approach indicates improvement in predictive accuracy with SC in the context of genotype-by-location interactions of a sorghum breeding in Ethiopia.

Genome-wide atlas of rust resistance loci in wheat.

Rust diseases, including leaf rust, stripe/yellow rust, and stem rust, significantly impact wheat (Triticum aestivum L.) yields, causing substantial economic losses every year. Breeding and deployment of cultivars with genetic resistance is the most effective and sustainable approach to control these diseases. The genetic toolkit for wheat breeders to select for rust resistance has rapidly expanded with a multitude of genetic loci identified using the latest advances in genomics, mapping and cloning strategies. The goal of this review was to establish a wheat genome atlas that provides a comprehensive summary of reported loci associated with rust resistance. Our atlas provides a summary of mapped quantitative trait loci (QTL) and characterised genes for the three rusts from 170 publications over the past two decades. A total of 920 QTL or resistance genes were positioned across the 21 chromosomes of wheat based on the latest wheat reference genome (IWGSC RefSeq v2.1). Interestingly, 26 genomic regions contained multiple rust loci suggesting they could have pleiotropic effects on two or more rust diseases. We discuss a range of strategies to exploit this wealth of genetic information to efficiently utilise sources of resistance, including genomic information to stack desirable and multiple QTL to develop wheat cultivars with enhanced resistance to rust disease.