Understanding and utilizing crop genome diversity via high-resolution genotyping

Fashion meets science: how advanced breeding approaches could revolutionize the textile industry

Natural fibers have garnered considerable attention owing to their desirable textile properties and advantageous effects on human health. Nevertheless, natural fibers lag behind synthetic fibers in terms of both quality and yield, as these attributes are largely genetically determined. In this article, a comprehensive overview of the natural and synthetic fiber production landscape over the last 10 years is presented, with a particular focus on the role of scientific breeding techniques in improving fiber quality traits in key crops like cotton, hemp, ramie, and flax. Additionally, the article delves into cutting-edge genomics-assisted breeding techniques, including QTL mapping, genome-wide association studies, transgenesis, and genome editing, and their potential role in enhancing fiber quality traits in these crops. A user-friendly compendium of 11226 available QTLs and significant marker-trait associations derived from 136 studies, associated with diverse fiber quality traits in these crops is furnished. Furthermore, the potential applications of transcriptomics in these pivotal crops, elucidating the distinct genes implicated in augmenting fiber quality attributes are investigated. Additionally, information on 11257 candidate/characterized or cloned genes sourced from various studies, emphasizing their key role in the development of high-quality fiber crops is collated. Additionally, the review sheds light on the current progress of marker-assisted selection for fiber quality traits in each crop, providing detailed insights into improved cultivars released for different fiber crops. In conclusion, it is asserted that the application of modern breeding tools holds tremendous potential in catalyzing a transformative shift in the textile industry.

Identification of transcription factor BnHDG4-A08 as a novel candidate associated with the accumulation of oleic, linoleic, linolenic, and erucic acid in Brassica napus

KEY MESSAGE

We screened 47 significantly associated haplotype blocks for oleic, linoleic, linolenic, and erucic acid, with 17 blocks influencing multiple traits. A novel candidate of transcription factor BnHDG4 A08 influencing oleic, linoleic, linolenic, and erucic acid was identified, by a joint strategy of haplotype-based genome-wide association study, genomic resequencing, gene cloning, and co-expression network Fatty acid (FA) composition determines the quality and economic value of rapeseed oil (Brassica napus). However, the molecular network of FAs is unclear. In the current study, multi-strategies of haplotype-based genome-wide association study (GWAS), genomic resequencing, gene cloning, and co-expression network were joint to reveal novel genetic factors influencing FA accumulation in rapeseed. We identified 47 significantly associated haplotype blocks for oleic, linoleic, linolenic, and erucic acid, with 17 blocks influencing multiple traits, using a haplotype-based GWAS with phenotype data from 203 Chinese semi-winter accessions. A total of 61 rapeseed orthologs involved in acyl-lipid metabolism, carbohydrate metabolism, or photosynthesis were identified in these 17 blocks. Among these genes, BnHDG4-A08, encoding a class IV homeodomain leucine-zipper transcription factor, exhibited two single-nucleotide polymorphisms (SNPs) in the exon and intron, with significant associations with oleic, linoleic, linolenic, and erucic acid. Gene cloning further validated two SNPs in the exon of BnHDG4-A08 in a population with 75 accessions, leading to two amino acid changes (T372A and P366L) and significant variation of oleic, linoleic, linolenic, and erucic acid. A competitive allele-specific PCR (KASP) marker based on the SNPs was successfully developed and validated. Moreover, 98 genes exhibiting direct interconnections and high weight values with BnHDG4-A08 were identified through co-expression network analysis using transcriptome data from 13 accessions. Our study identified a novel FA candidate of transcription factor BnHDG4-A08 influencing oleic, linoleic, linolenic, and erucic acid. This gene provides a potential promising gene resource for the novel mechanistic understanding of transcription factors regulating FA accumulation.

Haplotype-based breeding: A new insight in crop improvement

Haplotype-based breeding (HBB) is one of the cutting-edge technologies in the realm of crop improvement due to the increasing availability of Single Nucleotide Polymorphisms identified by Next Generation Sequencing technologies. The complexity of the data can be decreased with fewer statistical tests and a lower probability of spurious associations by combining thousands of SNPs into a few hundred haplotype blocks. The presence of strong genomic regions in breeding lines of most crop species facilitates the use of haplotypes to improve the efficiency of genomic and marker-assisted selection. Haplotype-based breeding as a Genomic Assisted Breeding (GAB) approach harnesses the genome sequence data to pinpoint the allelic variation used to hasten the breeding cycle and circumvent the challenges associated with linkage drag. This review article demonstrates ways to identify candidate genes, superior haplotype identification, haplo-pheno analysis, and haplotype-based marker-assisted selection. The crop improvement strategies that utilize superior haplotypes will hasten the breeding progress to safeguard global food security.

Genetic Diversity and Population Structure of a Large USDA Sesame Collection

Sesame, Sesamum indicum L., is one of the oldest domesticated crops used for its oil and protein in many parts of the world. To build genomic resources for sesame that could be used to improve sesame productivity and responses to stresses, a USDA sesame germplasm collection of 501 accessions originating from 36 countries was used in this study. The panel was genotyped using genotyping-by-sequencing (GBS) technology to explore its genetic diversity and population structure and the relatedness among its accessions. A total of 24,735 high-quality single-nucleotide polymorphism (SNP) markers were identified over the 13 chromosomes. The marker density was 1900 SNP per chromosome, with an average polymorphism information content (PIC) value of 0.267. The marker polymorphisms and heterozygosity estimators indicated the usefulness of the identified SNPs to be used in future genetic studies and breeding activities. The population structure, principal components analysis (PCA), and unrooted neighbor-joining phylogenetic tree analyses classified two distinct subpopulations, indicating a wide genetic diversity within the USDA sesame collection. Analysis of molecular variance (AMOVA) revealed that 29.5% of the variation in this population was due to subpopulations, while 57.5% of the variation was due to variation among the accessions within the subpopulations. These results showed the degree of differentiation between the two subpopulations as well as within each subpopulation. The high fixation index (FST) between the distinguished subpopulations indicates a wide genetic diversity and high genetic differentiation among and within the identified subpopulations. The linkage disequilibrium (LD) pattern averaged 161 Kbp for the whole sesame genome, while the LD decay ranged from 168 Kbp at chromosome LG09 to 123 Kbp in chromosome LG05. These findings could explain the complications of linkage drag among the traits during selections. The selected accessions and genotyped SNPs provide tools to enhance genetic gain in sesame breeding programs through molecular approaches.

Drought and heat stress: insights into tolerance mechanisms and breeding strategies for pigeonpea improvement

MAIN CONCLUSION

Pigeonpea has potential to foster sustainable agriculture and resilience in evolving climate change; understanding bio-physiological and molecular mechanisms of heat and drought stress tolerance is imperative to developing resilience cultivars. Pigeonpea is an important legume crop that has potential resilience in the face of evolving climate scenarios. However, compared to other legumes, there has been limited research on abiotic stress tolerance in pigeonpea, particularly towards drought stress (DS) and heat stress (HS). To address this gap, this review delves into the genetic, physiological, and molecular mechanisms that govern pigeonpea's response to DS and HS. It emphasizes the need to understand how this crop combats these stresses and exhibits different types of tolerance and adaptation mechanisms through component traits. The current article provides a comprehensive overview of the complex interplay of factors contributing to the resilience of pigeonpea under adverse environmental conditions. Furthermore, the review synthesizes information on major breeding techniques, encompassing both conventional methods and modern molecular omics-assisted tools and techniques. It highlights the potential of genomics and phenomics tools and their pivotal role in enhancing adaptability and resilience in pigeonpea. Despite the progress made in genomics, phenomics and big data analytics, the complexity of drought and heat tolerance in pigeonpea necessitate continuous exploration at multi-omic levels. High-throughput phenotyping (HTP) is crucial for gaining insights into perplexed interactions among genotype, environment, and management practices (GxExM). Thus, integration of advanced technologies in breeding programs is critical for developing pigeonpea varieties that can withstand the challenges posed by climate change. This review is expected to serve as a valuable resource for researchers, providing a deeper understanding of the mechanisms underlying abiotic stress tolerance in pigeonpea and offering insights into modern breeding strategies that can contribute to the development of resilient varieties suited for changing environmental conditions.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs.

The Use of DArTseq Technology to Identify Markers Linked to Genes Responsible for Seed Germination and Seed Vigor in Maize

Seed vigor and seed germination are very important traits, determined by several factors including genetic and physical purity, mechanical damage, and physiological condition, characterized by maintaining a high seed vigor and stable content after storage. The search for molecular markers related to improvement in seed vigor under adverse condition is an important issue in maize breeding currently. Higher sowing quality of seeds is necessary for the development of the agriculture production and better ability to resist all kinds of adversity in the seeds’ storage. Condition is a very important factor affecting the yield of plants, thanks to the construction of their vitality. Identification of molecular markers associated with seed germination and seed vigor may prove to be very important in the selection of high-yielding maize varieties. The aim of this study was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the seed germination and seed vigor in inbred lines of maize (Zea mays L.). The plant material used for the research was 152 inbred maize lines. The seed germination and seed vigor were analyzed. For identification of SNP and SilicoDArT markers related to the seed germination and seed vigor, the SilicoDarT technique developed by Diversity Arrays Technology was used. The analysis of variance indicated a statistically significant differentiation between genotypes for both observed traits. Positive (r = 0.41) correlation (p < 0.001) between seed germination and seed vigor was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNP) were selected as a result of association mapping, which showed them to be significantly related to the analyzed traits. The 890 molecular markers were associated with seed vigor, and 1323 with seed germination. Fifty-six markers (47 SilicoDArT and nine SNP) were significant for both traits. Of these 56 markers, the 20 most significant were selected (five of these markers were significant at the level of 0.001 for seed vigor and at the level of 0.05 for seed germination, another five markers were significant at the level of 0.001 for seed germination and at the level of 0.05 for seed vigor, five markers significant at the level of 0.001 only for seed vigor and five significant at the level of 0.001 only for seed germination also selected). These markers were used for physical mapping to determine their location on the genetic map. Finally, it was found that six of these markers (five silicoDArT—2,435,784, 4,772,587, 4,776,334, 2,507,310, 25,981,291, and one SNP—2,386,217) are located inside genes, the action of which may affect both seed germination and seed vigor. These markers can be used to select genotypes with high vigor and good seed germination.

Regional association and transcriptome analysis revealed candidate genes controlling plant height in Brassica napus

Plant height is a key morphological trait in rapeseed, which not only plays an important role in determining plant architecture, but is also an important characteristic related to yield. Presently, the improvement of plant architecture is a major challenge in rapeseed breeding. This work was carried out to identify genetic loci related to plant height in rapeseed. In this study, a genome-wide association study (GWAS) of plant height was performed using a Brassica 60 K Illumina Infinium SNP array and 203 Brassica napus accessions. Eleven haplotypes containing important candidate genes were detected and significantly associated with plant height on chromosomes A02, A03, A05, A07, A08, C03, C06, and C09. Moreover, regional association analysis of 50 resequenced rapeseed inbred lines was used to further analyze these eleven haplotypes and revealed nucleotide variation in the BnFBR12-A08 and BnCCR1-C03 gene regions related to the phenotypic variation in plant height. Furthermore, coexpression network analysis showed that BnFBR12-A08 and BnCCR1-C03 were directly connected with hormone genes and transcription factors and formed a potential network regulating the plant height of rapeseed. Our results will aid in the development of haplotype functional markers to further improve plant height in rapeseed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01337-1.

Descriptive Genomic Analysis and Sequence Genotyping of the Two Papaya Species (Vasconcellea pubescens and Vasconcellea chilensis) Using GBS Tools

A genotyping by sequencing (GBS) approach was used to analyze the organization of genetic diversity in V. pubescens and V. chilensis. GBS identified 4675 and 4451 SNPs/INDELs in two papaya species. The cultivated orchards of V. pubescens exhibited scarce genetic diversity and low but significant genetic differentiation. The neutrality test yielded a negative and significant result, suggesting that V. pubescens suffered a selective sweep or a rapid expansion after a bottleneck during domestication. In contrast, V. chilensis exhibited a high level of genetic diversity. The genetic differentiation among the populations was slight, but it was possible to distinguish the two genetic groups. The neutrality test indicated no evidence that natural selection and genetic drift affect the natural population of V. chilensis. Using the Carica papaya genome as a reference, we identified critical SNPs/INDELs associated with putative genes. Most of the identified genes are related to stress responses (salt and nematode) and vegetative and reproductive development. These results will be helpful for future breeding and conservation programs of the Caricaceae family.

Associative and Physical Mapping of Markers Related to Fusarium in Maize Resistance, Obtained by Next-Generation Sequencing (NGS)

On the basis of studies carried out in the last few years, it is estimated that maize diseases cause yield losses of up to 30% each year. The most dangerous diseases are currently considered to be caused by fungi of the genus Fusarium, which are the main culprits of root rot, ear rots, and stalk rot. Early plant infection causes grain diminution, as well as a significant deterioration in nutritional value and fodder quality due to the presence of harmful mycotoxins. Therefore, the aim of the research was to identify new markers of the SilicoDArT and SNP type, which could be used for the mass selection of varieties resistant to fusarium. The plant material consisted of 186 inbred maize lines. The lines came from experimental plots belonging to two Polish breeding companies: Plant Breeding Smolice Ltd., (Co., Kobylin, Poland). Plant Breeding and Acclimatization Institute-National Research Institute Group (51°41'23.16″ N, 17°4'18.241″ E), and Małopolska Plant Breeding Kobierzyce, Poland Ltd., (Co., Kobierzyce, Poland) (50°58'19.411″ N, 16°55'47.323″ E). As a result of next-generation sequencing, a total of 81,602 molecular markers were obtained, of which, as a result of the associative mapping, 2962 (321 SilicoDArT and 2641 SNP) significantly related to plant resistance to fusarium were selected. Out of 2962 markers significantly related to plant resistance in the fusarium, seven markers (SilicoDArT, SNP) were selected, which were significant at the level of 0.001. They were used for physical mapping. As a result of the analysis, it was found that two out of seven selected markers (15,097-SilicoDArT and 58,771-SNP) are located inside genes, on chromosomes 2 and 3, respectively. Marker 15,097 is anchored to the gene encoding putrescine N-hydroxycinnamoyltransferase while marker 58,771 is anchored to the gene encoding the peroxidase precursor 72. Based on the literature data, both of these genes may be associated with plant resistance to fusarium. Therefore, the markers 15,097 (SilicoDArT) and 58,771 (SNP) can be used in breeding programs to select lines resistant to fusarium.

A Seaweed Extract-Based Biostimulant Mitigates Drought Stress in Sugarcane

Drought is one of the most important abiotic stresses responsible for reduced crop yields. Drought stress induces morphological and physiological changes in plants and severely impacts plant metabolism due to cellular oxidative stress, even in C4 crops, such as sugarcane. Seaweed extract-based biostimulants can mitigate negative plant responses caused by drought stress. However, the effects of foliar application of such biostimulants on sugarcane exposed to drought stress, particularly on plant metabolism, stalk and sugar yields, juice purity, and sugarcane technological quality, have received little attention. Accordingly, this study aimed to evaluate the effects of foliar application of a seaweed extract-based biostimulant on late-harvest sugarcane during the driest period of the year. Three experiments were implemented in commercial sugarcane fields in Brazil in the 2018 (site 1), 2019 (site 2), and 2020 (site 3) harvest seasons. The treatments consisted of the application and no application of seaweed extract (SWE) as a foliar biostimulant in June (sites 2 and 3) or July (site 1). The treatments were applied to the fourth ratoon of sugarcane variety RB855536 at site 1 and the fifth and third ratoons of sugarcane variety SP803290 at sites 2 and 3, respectively. SWE was applied at a dose of 500 ml a.i. ha-1 in a water volume of 100 L ha-1. SWE mitigated the negative effects of drought stress and increased stalk yield per hectare by up to 3.08 Mg ha-1. In addition, SWE increased stalk sucrose accumulation, resulting in an increase in sugar yield of 3.4 kg Mg-1 per hectare and higher industrial quality of the raw material. In SWE-treated plants, Trolox-equivalent antioxidant capacity and antioxidant enzyme activity increased, while malondialdehyde (MDA) levels decreased. Leaf analysis showed that SWE application efficiently improved metabolic activity, as evidenced by a decrease in carbohydrate reserve levels in leaves and an increase in total sugars. By positively stabilizing the plant's cellular redox balance, SWE increased biomass production, resulting in an increase in energy generation. Thus, foliar SWE application can alleviate drought stress while enhancing sugarcane development, stalk yield, sugar production, and plant physiological and enzymatic processes.

Seed germination and vigor: ensuring crop sustainability in a changing climate

In the coming decades, maintaining a steady food supply for the increasing world population will require high-yielding crop plants which can be productive under increasingly variable conditions. Maintaining high yields will require the successful and uniform establishment of plants in the field under altered environmental conditions. Seed vigor, a complex agronomic trait that includes seed longevity, germination speed, seedling growth, and early stress tolerance, determines the duration and success of this establishment period. Elevated temperature during early seed development can decrease seed size, number, and fertility, delay germination and reduce seed vigor in crops such as cereals, legumes, and vegetable crops. Heat stress in mature seeds can reduce seed vigor in crops such as lettuce, oat, and chickpea. Warming trends and increasing temperature variability can increase seed dormancy and reduce germination rates, especially in crops that require lower temperatures for germination and seedling establishment. To improve seed germination speed and success, much research has focused on selecting quality seeds for replanting, priming seeds before sowing, and breeding varieties with improved seed performance. Recent strides in understanding the genetic basis of variation in seed vigor have used genomics and transcriptomics to identify candidate genes for improving germination, and several studies have explored the potential impact of climate change on the percentage and timing of germination. In this review, we discuss these recent advances in the genetic underpinnings of seed performance as well as how climate change is expected to affect vigor in current varieties of staple, vegetable, and other crops.

CerealsDB: A Whistle-Stop Tour of an Open Access SNP Resource

The CerealsDB website, created by members of the Functional Genomics Group at the University of Bristol, provides access to a database containing SNP and genotyping data for hexaploid wheat and, to a lesser extent, its progenitors and several of its relatives. The site is principally aimed at plant breeders and research scientists who wish to obtain information regarding SNP markers; for example, obtain primers used for their identification or the sequences upon which they are based. The database underpinning the website contains circa one million putative varietal SNPs of which several hundreds of thousands have been experimentally validated on a range of common genotyping platforms. For each SNP marker, the site also hosts the allelic scores for thousands of elite wheat varieties, landrace cultivars, and wheat relatives. Tools are available to help negotiate and visualize the datasets. The website has been designed to be simple and straightforward to use and is completely open access.

Inhibitory Effect of Chitosan and Phosphate Cross-linked Chitosan against Cucumber Mosaic Virus and Pepper Mild Mottle Virus

Cucumber mosaic virus (CMV) and Pepper mild mottle virus (PMMoV) causes severe economic loss in crop productivity of both agriculture and horticulture crops in Korea. The previous surveys showed that naturally available biopolymer material - chitosan (CS), which is from shrimp cells, reduced CMV accumulation on pepper. To improve the antiviral activity of CS, it was synthesized to form phosphate cross-linked chitosan (PCS) and compared with the original CS. Initially, the activity of CS and PCS (0.01%, 0.05%, and 0.1% concentration) compound against PMMoV infection and replication was tested using a half-leaf assay on Nicotiana glutinosa leaves. The total number of local lesions represented on a leaf of N. glutinosa were counted and analyzed with phosphate buffer treated leaves as a negative control. The leaves treated with a 0.1% concentration of CS or PCS compounds exhibited an inhibition effect by 40-75% compared with the control leaves. The same treatment significantly reduced about 40% CMV accumulation measured by double antibody sandwich enzyme-linked immunosorbent assay and increased the relative expression levels of the NPR1, PR-1, cysteine protease inhibitor gene, LOX, PAL, SRC2, CRF3 and ERF4 genes analyzed by quantitative reverse transcriptase-polymerase chain reaction, in chili pepper plants.

Features and applications of haplotypes in crop breeding

Climate change with altered pest-disease dynamics and rising abiotic stresses threatens resource-constrained agricultural production systems worldwide. Genomics-assisted breeding (GAB) approaches have greatly contributed to enhancing crop breeding efficiency and delivering better varieties. Fast-growing capacity and affordability of DNA sequencing has motivated large-scale germplasm sequencing projects, thus opening exciting avenues for mining haplotypes for breeding applications. This review article highlights ways to mine haplotypes and apply them for complex trait dissection and in GAB approaches including haplotype-GWAS, haplotype-based breeding, haplotype-assisted genomic selection. Improvement strategies that efficiently deploy superior haplotypes to hasten breeding progress will be key to safeguarding global food security.

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.

Next-Generation Breeding Strategies for Climate-Ready Crops

Climate change is a threat to global food security due to the reduction of crop productivity around the globe. Food security is a matter of concern for stakeholders and policymakers as the global population is predicted to bypass 10 billion in the coming years. Crop improvement via modern breeding techniques along with efficient agronomic practices innovations in microbiome applications, and exploiting the natural variations in underutilized crops is an excellent way forward to fulfill future food requirements. In this review, we describe the next-generation breeding tools that can be used to increase crop production by developing climate-resilient superior genotypes to cope with the future challenges of global food security. Recent innovations in genomic-assisted breeding (GAB) strategies allow the construction of highly annotated crop pan-genomes to give a snapshot of the full landscape of genetic diversity (GD) and recapture the lost gene repertoire of a species. Pan-genomes provide new platforms to exploit these unique genes or genetic variation for optimizing breeding programs. The advent of next-generation clustered regularly interspaced short palindromic repeat/CRISPR-associated (CRISPR/Cas) systems, such as prime editing, base editing, and de nova domestication, has institutionalized the idea that genome editing is revamped for crop improvement. Also, the availability of versatile Cas orthologs, including Cas9, Cas12, Cas13, and Cas14, improved the editing efficiency. Now, the CRISPR/Cas systems have numerous applications in crop research and successfully edit the major crop to develop resistance against abiotic and biotic stress. By adopting high-throughput phenotyping approaches and big data analytics tools like artificial intelligence (AI) and machine learning (ML), agriculture is heading toward automation or digitalization. The integration of speed breeding with genomic and phenomic tools can allow rapid gene identifications and ultimately accelerate crop improvement programs. In addition, the integration of next-generation multidisciplinary breeding platforms can open exciting avenues to develop climate-ready crops toward global food security.

Genomic Approaches to Identify Molecular Bases of Crop Resistance to Diseases and to Develop Future Breeding Strategies

Plant diseases are responsible for substantial crop losses each year and affect food security and agricultural sustainability. The improvement of crop resistance to pathogens through breeding represents an environmentally sound method for managing disease and minimizing these losses. The challenge is to breed varieties with a stable and broad-spectrum resistance. Different approaches, from markers to recent genomic and 'post-genomic era' technologies, will be reviewed in order to contribute to a better understanding of the complexity of host-pathogen interactions and genes, including those with small phenotypic effects and mechanisms that underlie resistance. An efficient combination of these approaches is herein proposed as the basis to develop a successful breeding strategy to obtain resistant crop varieties that yield higher in increasing disease scenarios.

Regional association analysis coupled with transcriptome analyses reveal candidate genes affecting seed oil accumulation in Brassica napus

Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions in combination with co-expression analysis reveal candidate genes affecting oil accumulation in Brassica napus. One of the breeding goals in rapeseed production is to enhance the seed oil content to cater to the increased demand for vegetable oils due to a growing global population. To investigate the genetic basis of variation in seed oil content, we used 60 K Brassica Infinium SNP array along with phenotype data of 203 Chinese semi-winter rapeseed accessions to perform a genome-wide analysis of haplotype blocks associated with the oil content. Nine haplotype regions harbouring lipid synthesis/transport-, carbohydrate metabolism- and photosynthesis-related genes were identified as significantly associated with the oil content and were mapped to chromosomes A02, A04, A05, A07, C03, C04, C05, C08 and C09, respectively. Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions combined with transcriptome datasets from 13 accessions was further performed on these nine haplotype regions. This revealed natural variation in the BnTGD3-A02 and BnSSE1-A05 gene regions correlated with the phenotypic variation of the oil content within the A02 and A04 chromosome haplotype regions, respectively. Moreover, co-expression network analysis revealed that BnTGD3-A02 and BnSSE1-A05 were directly linked with fatty acid beta-oxidation-related gene BnKAT2-C04, thus forming a molecular network involved in the potential regulation of seed oil accumulation. The results of this study could be used to combine favourable haplotype alleles for further improvement of the seed oil content in rapeseed.

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.

Linkage mapping and QTL analysis of flowering time using ddRAD sequencing with genotype error correction in Brassica napus

BACKGROUND

Brassica napus is an important oilseed crop cultivated worldwide. During domestication and breeding of B. napus, flowering time has been a target of selection because of its substantial impact on yield. Here we use double digest restriction-site associated DNA sequencing (ddRAD) to investigate the genetic basis of flowering in B. napus. An F2 mapping population was derived from a cross between an early-flowering spring type and a late-flowering winter type.

RESULTS

Flowering time in the mapping population differed by up to 25 days between individuals. High genotype error rates persisted after initial quality controls, as suggested by a genotype discordance of ~ 12% between biological sequencing replicates. After genotype error correction, a linkage map spanning 3981.31 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trait locus (QTL) on chromosome C2 was detected, covering eight flowering time genes including FLC.

CONCLUSIONS

These findings demonstrate the effectiveness of the ddRAD approach to sample the B. napus genome. Our results also suggest that ddRAD genotype error rates can be higher than expected in F2 populations. Quality filtering and genotype correction and imputation can substantially reduce these error rates and allow effective linkage mapping and QTL analysis.

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.

Genotyping by multiplexed sequencing (GMS): A customizable platform for genomic selection

As genotyping technologies continue to evolve, so have their throughput and multiplexing capabilities. In this study, we demonstrate a new PCR-based genotyping technology that multiplexes thousands of single nucleotide polymorphism (SNP) markers with high-throughput capabilities in a simple protocol using a two-step PCR approach. The bioinformatic pipeline is user friendly and yields results that are intuitive to interpret. This method was tested on two recombinant inbred line (RIL) populations that had previous genotyping data from the Illumina Infinium assay for Triticum aestivum L. and the two data sets were found to be 100% in agreement. The genotyping by multiplexed sequencing (GMS) protocol multiplexes 1,656 wheat SNP markers, 207 syntenic barley SNP markers, and 49 known informative markers, which generate a possible 2,433 data points (including homoeoalleles and paralogs). This genotyping approach has the flexibility of being sequenced on either the Ion Torrent or Illumina next generation sequencing (NGS) platforms. Products are the result of direct sequencing and are therefore more reliable than scatter plot analysis which is the output of other genotyping methods such as the Illumina Infinium assay, komeptitive allele specific PCR and other like technologies.

GWAS and co-expression network combination uncovers multigenes with close linkage effects on the oleic acid content accumulation in Brassica napus

Background

Strong artificial and natural selection causes the formation of highly conserved haplotypes that harbor agronomically important genes. GWAS combination with haplotype analysis has evolved as an effective method to dissect the genetic architecture of complex traits in crop species.

Results

We used the 60 K Brassica Infinium SNP array to perform a genome-wide analysis of haplotype blocks associated with oleic acid (C18:1) in rapeseed. Six haplotype regions were identified as significantly associated with oleic acid (C18:1) that mapped to chromosomes A02, A07, A08, C01, C02, and C03. Additionally, whole-genome sequencing of 50 rapeseed accessions revealed three genes (BnmtACP2-A02, BnABCI13-A02 and BnECI1-A02) in the A02 chromosome haplotype region and two genes (BnFAD8-C02 and BnSDP1-C02) in the C02 chromosome haplotype region that were closely linked to oleic acid content phenotypic variation. Moreover, the co-expression network analysis uncovered candidate genes from these two different haplotype regions with potential regulatory interrelationships with oleic acid content accumulation.

Conclusions

Our results suggest that several candidate genes are closely linked, which provides us with an opportunity to develop functional haplotype markers for the improvement of the oleic acid content in rapeseed.

Whole Genome Scan Reveals Molecular Signatures of Divergence and Selection Related to Important Traits in Durum Wheat Germplasm

The first breeding program in the world for durum wheat was conceived in Italy in the early 1900s. Over the decades, pressure exerted by natural and artificial selection could have progressively reduced the genetic diversity of the durum wheat germplasm. In the present study, a large panel of Italian durum wheat accessions that includes landraces, old and modern cultivars was subjected to genotyping using the Illumina iSelect 15K wheat SNP array. The aim was to assess the impact that selection has in shaping Italian durum wheat genetic diversity and to exploit the patterns of genetic diversity between populations to identify molecular signatures of divergence and selection. Relatively small differences in genetic diversity have been observed among accessions, which have been selected and cultivated in Italy over the past 150 years. Indeed, directional selection combined with that operated by farmers/breeders resulted in the increase of linkage disequilibrium (LD) and in changes of the allelic frequencies in DNA regions that control important agronomic traits. Results from this study also show that major well-known genes and/or QTLs affecting plant height (RHT), earliness (VRN, PPD) and grain quality (GLU, PSY, PSD, LYC, PPO, LOX3) co-localized with outlier SNP loci. Interestingly, many of these SNPs fall in genomic regions where genes involved in nitrogen metabolism are. This finding highlights the key role these genes have played in the transition from landraces to modern cultivars. Finally, our study remarks on the need to fully exploit the genetic diversity of Italian landraces by intense pre-breeding activities aimed at introducing a new source of adaptability and resistance in the genetic background of modern cultivars, to contrast the effect of climate change. The list of divergent loci and loci under selection associated with useful agronomic traits represents an invaluable resource to detect new allelic variants for target genes and for guiding new genomic selection programs in durum wheat.

Discovery of Functional SNPs via Genome-Wide Exploration of Malaysian Pigmented Rice Varieties

Recently, rice breeding program has shown increased interests on the pigmented rice varieties due to their benefits to human health. However, the genetic variation of pigmented rice varieties is still scarce and remains unexplored. Hence, we performed genome-wide SNP analysis from the genome resequencing of four Malaysian pigmented rice varieties, representing two black and two red rice varieties. The genome of four pigmented varieties was mapped against Nipponbare reference genome sequences, and 1.9 million SNPs were discovered. Of these, 622 SNPs with polymorphic sites were identified in 258 protein-coding genes related to metabolism, stress response, and transporter. Comparative analysis of 622 SNPs with polymorphic sites against six rice SNP datasets from the Ensembl Plants variation database was performed, and 70 SNPs were identified as novel SNPs. Analysis of SNPs in the flavonoid biosynthetic genes revealed 40 nonsynonymous SNPs, which has potential as molecular markers for rice seed colour identification. The highlighted SNPs in this study show effort in producing valuable genomic resources for application in the rice breeding program, towards the genetic improvement of new and improved pigmented rice varieties.

Selection of Parental Material to Maximize Heterosis Using SNP and SilicoDarT Markers in Maize

The chief aim of plant breeding is to improve varieties so as to increase their yield and breeding traits. One of the first stages of breeding is the selection of parental forms from the available gene pool of existing varieties. To date, costly and laborious methods based on multiple crossbreeding and phenotypic selection have been necessary to properly assess genetic resources in terms of productivity, quality parameters, and susceptibility to biotic and abiotic stressors. The often long and complicated breeding cycle can be significantly shortened through selection using DNA markers. To this end, use is made of close couplings between the marker and the locus responsible for the inheritance of the functional trait. The aim of this study was to identify single nucleotide polymorphism (SNP) and SilicoDArT markers associated with yield traits and to predict the heterosis effect for yield traits in maize (Zea mays L.). The plant material used in the research consisted of 19 inbred maize lines derived from different starting materials, and 13 hybrids resulting from crossing them. A two-year field experiment with inbred lines and hybrids was established at two Polish breeding stations on 10 m2 plots in a randomized block design with three replicates. The biometric measurements included cob length, cob diameter, core length, core diameter, number of rows of grain, number of grains in a row, mass of grain from the cob, weight of one thousand grains, and yield. The isolated DNA was subjected to DArTseq genotyping. Association mapping was performed in this study using a method based on the mixed linear model with the population structure estimated by eigenanalysis (principal component analysis of all markers) and modeled by random effects. Narew, Popis, Kozak, M Glejt, and Grom were the hybrids used in the study that showed the highest significant heterosis effect in 2013 and 2014. The similarity between parental components determined on the basis of SNP and SilicoDArT marker analysis did not exceed 33%. It was found that the genetic similarity between parental components, determined on the basis of SNP and SilicoDArT markers, reflected their degree of relationship, and correlated significantly with the effect of heterosis. As the results indicate, the parental components for heterosis crosses can be selected based on genetic similarity between parental components evaluated using SNP and SilicoDArT markers, supported with information on the origin of parental forms. Of the markers we analyzed, 76 were selected as being significantly associated with at least six traits observed in 2013 and 2014 at both the Łagiewniki and Smolice stations.

Ascophyllum nodosum-Based Biostimulants: Sustainable Applications in Agriculture for the Stimulation of Plant Growth, Stress Tolerance, and Disease Management

Abiotic and biotic stresses limit the growth and productivity of plants. In the current global scenario, in order to meet the requirements of the ever-increasing world population, chemical pesticides and synthetic fertilizers are used to boost agricultural production. These harmful chemicals pose a serious threat to the health of humans, animals, plants, and the entire biosphere. To minimize the agricultural chemical footprint, extracts of Ascophyllum nodosum (ANE) have been explored for their ability to improve plant growth and agricultural productivity. The scientific literature reviewed in this article attempts to explain how certain bioactive compounds present in extracts aid to improve plant tolerances to abiotic and/or biotic stresses, plant growth promotion, and their effects on root/microbe interactions. These reports have highlighted the use of various seaweed extracts in improving nutrient use efficiency in treated plants. These studies include investigations of physiological, biochemical, and molecular mechanisms as evidenced using model plants. However, the various modes of action of A. nodosum extracts have not been previously reviewed. The information presented in this review depicts the multiple, beneficial effects of A. nodosum-based biostimulant extracts on plant growth and their defense responses and suggests new opportunities for further applications for marked benefits in production and quality in the agriculture and horticultural sectors.

Broadening the bread wheat D genome

Although Ae. tauschii has been extensively utilised for wheat breeding, the D-genome-containing allopolyploids have largely remained unexploited. In this review, we discuss approaches that can be used to exploit the D genomes of the different Aegilops species for the improvement of bread wheat. The D genome of allohexaploid bread wheat (Triticum aestivum, 2n = AABBDD) is the least diverse of the three wheat genomes and is unarguably less diverse than that of diploid progenitor Aegilops tauschii (2n = DD). Useful genetic variation and phenotypic traits also exist within each of the wheat group species containing a copy of the D genome: allopolyploid Aegilops species Ae. cylindrica (2n = D^cD^cC^cC^c), Ae. crassa 4x (2n = D¹D¹X^crX^cr), Ae. crassa 6x (2n = D¹D¹X^crX^crD^crD^cr), Ae. ventricosa (2n = D^vD^vN^vN^v), Ae. vavilovii (2n = D¹D¹X^crX^crS^vS^v) and Ae. juvenalis (2n = D¹D¹X^crX^crU^jU^j). Although Ae. tauschii has been extensively utilised for wheat breeding, the D-genome-containing allopolyploids have largely remained unexploited. Some of these D genomes appear to be modified relative to the bread wheat and Ae. tauschii D genomes, and others present in the allopolyploids may also contain useful variation as a result of adaptation to an allopolyploid, multi-genome environment. We summarise the genetic relationships, karyotypic variation and phenotypic traits known to be present in each of the D genome species that could be of relevance for bread wheat improvement and discuss approaches that can be used to exploit the D genomes of the different Aegilops species for the improvement of bread wheat. Better understanding of factors controlling chromosome inheritance and recombination in wheat group interspecific hybrids, as well as effective utilisation of new and developing genetics and genomics technologies, have great potential to improve the agronomic potential of the bread wheat D genome.

Construction of a high-density interspecific (Lens culinaris x L. odemensis) genetic map based on functional markers for mapping morphological and agronomical traits, and QTLs affecting resistance to Ascochyta in lentil

Usage of high-throughput sequencing approaches allow for the generation and characterization of reference transcriptome datasets that support gene-based marker discovery, which in turn can be used to build genetic maps among other purposes. We have obtained a transcriptome assembly including 49,453 genes for the lentil (Lens culinaris Medik.) cultivar Alpo using RNAseq methodology. This transcriptome was used as reference to obtain 6,306 quality polymorphic markers (SNPs and short indels) analyzing genotype data from a RIL population at F7 generation derived from the interspecific cross between L. culinaris cv. Alpo and L. odemensis accession ILWL235. L. odemensis is a wild species included in the secondary gene pool and can be used as a source for gene introgression in lentil breeding programs. Marker data were used to construct the first genetic interspecific map between these two species. This linkage map has been used to precisely identify regions of the CDC-Redberry lentil draft genome in which the candidate genes for some qualitative traits (seed coat spotting pattern, flower color, and stem pigmentation) could be located. The genome regions corresponding to a significant single quantitative trait locus (QTL) controlling "time to flowering" located in chromosome 6 and three QTLs regulating seed size and positioned in chromosomes 1 and 5 (two QTLs) were also identified. Significant QTLs for Ascochyta blight resistance in lentil were mapped to chromosome 6 in the genome region or close to it where QTLs for Ascochyta blight resistance have previously been reported.

Effect of breeding on nitrogen use efficiency-associated traits in oilseed rape

Oilseed rape is one of the most important dicotyledonous field crops in the world, where it plays a key role in productive cereal crop rotations. However, its production requires high nitrogen fertilization and its nitrogen footprint exceeds that of most other globally important crops. Hence, increased nitrogen use efficiency (NUE) in this crop is of high priority for sustainable agriculture. We report a comprehensive study of macrophysiological characteristics associated with breeding progress, conducted under contrasting nitrogen fertilization levels in a large panel of elite oilseed rape varieties representing breeding progress over the past 20 years. The results indicate that increased plant biomass at flowering, along with increases in primary yield components, have increased NUE in modern varieties. Nitrogen uptake efficiency has improved through breeding, particularly at high nitrogen. Despite low heritability, the number of seeds per silique is associated positively with increased yield in modern varieties. Seed weight remains unaffected by breeding progress; however, recent selection for high seed oil content and for high seed yields appears to have promoted a negative correlation (r= -0.39 at high and r= -0.49 at low nitrogen) between seed weight and seed oil concentration. Overall, our results reveal valuable breeding targets to improve NUE in oilseed rape.

Connecting genome structural variation with complex traits in crop plants

Structural genome variation is a major determinant of useful trait diversity. We describe how genome analysis methods are enabling discovery of trait-associated structural variants and their potential impact on breeding. As our understanding of complex crop genomes continues to grow, there is growing evidence that structural genome variation plays a major role in determining traits important for breeding and agriculture. Identifying the extent and impact of structural variants in crop genomes is becoming increasingly feasible with ongoing advances in the sophistication of genome sequencing technologies, particularly as it becomes easier to generate accurate long sequence reads on a genome-wide scale. In this article, we discuss the origins of structural genome variation in crops from ancient and recent genome duplication and polyploidization events and review high-throughput methods to assay such variants in crop populations in order to find associations with phenotypic traits. There is increasing evidence from such studies that gene presence-absence and copy number variation resulting from segmental chromosome exchanges may be at the heart of adaptive variation of crops to counter abiotic and biotic stress factors. We present examples from major crops that demonstrate the potential of pangenomic diversity as a key resource for future plant breeding for resilience and sustainability.

Technological advances in maize breeding: past, present and future

Maize has for many decades been both one of the most important crops worldwide and one of the primary genetic model organisms. More recently, maize breeding has been impacted by rapid technological advances in sequencing and genotyping technology, transformation including genome editing, doubled haploid technology, parallelled by progress in data sciences and the development of novel breeding approaches utilizing genomic information. Herein, we report on past, current and future developments relevant for maize breeding with regard to (1) genome analysis, (2) germplasm diversity characterization and utilization, (3) manipulation of genetic diversity by transformation and genome editing, (4) inbred line development and hybrid seed production, (5) understanding and prediction of hybrid performance, (6) breeding methodology and (7) synthesis of opportunities and challenges for future maize breeding.

Q&A: modern crop breeding for future food security

Farmers around the world have recently experienced significant crop losses due to severe heat and drought. Such extreme weather events and the need to feed a rapidly growing population have raised concerns for global food security. While plant breeding has been very successful and has delivered today’s highly productive crop varieties, the rate of genetic improvement must double to meet the projected future demands. Here we discuss basic principles and features of crop breeding and how modern technologies could efficiently be explored to boost crop improvement in the face of increasingly challenging production conditions.

Finding invisible quantitative trait loci with missing data

Evolutionary processes during plant polyploidization and speciation have led to extensive presence-absence variation (PAV) in crop genomes, and there is increasing evidence that PAV associates with important traits. Today, high-resolution genetic analysis in major crops frequently implements simple, cost-effective, high-throughput genotyping from single nucleotide polymorphism (SNP) hybridization arrays; however, these are normally not designed to distinguish PAV from failed SNP calls caused by hybridization artefacts. Here, we describe a strategy to recover valuable information from single nucleotide absence polymorphisms (SNaPs) by population-based quality filtering of SNP hybridization data to distinguish patterns associated with genuine deletions from those caused by technical failures. We reveal that including SNaPs in genetic analyses elucidate segregation of small to large-scale structural variants in nested association mapping populations of oilseed rape (Brassica napus), a recent polyploid crop with widespread structural variation. Including SNaP markers in genomewide association studies identified numerous quantitative trait loci, invisible using SNP markers alone, for resistance to two major fungal diseases of oilseed rape, Sclerotinia stem rot and blackleg disease. Our results indicate that PAV has a strong influence on quantitative disease resistance in B. napus and that SNaP analysis using cost-effective SNP array data can provide extensive added value from 'missing data'. This strategy might also be applicable for improving the precision of genetic mapping in many important crop species.

Genetic insights into underground responses to Fusarium graminearum infection in wheat

The ongoing global intensification of wheat production will likely be accompanied by a rising pressure of Fusarium diseases. While utmost attention was given to Fusarium head blight (FHB) belowground plant infections of the pathogen have largely been ignored. The current knowledge about the impact of soil borne Fusarium infection on plant performance and the underlying genetic mechanisms for resistance remain very limited. Here, we present the first large-scale investigation of Fusarium root rot (FRR) resistance using a diverse panel of 215 international wheat lines. We obtained data for a total of 21 resistance-related traits, including large-scale Real-time PCR experiments to quantify fungal spread. Association mapping and subsequent haplotype analyses discovered a number of highly conserved genomic regions associated with resistance, and revealed a significant effect of allele stacking on the stembase discoloration. Resistance alleles were accumulated in European winter wheat germplasm, implying indirect prior selection for improved FRR resistance in elite breeding programs. Our results give first insights into the genetic basis of FRR resistance in wheat and demonstrate how molecular parameters can successfully be explored in genomic prediction. Ongoing work will help to further improve our understanding of the complex interactions of genetic factors influencing FRR resistance.

Effective Genomic Selection in a Narrow-Genepool Crop with Low-Density Markers: Asian Rapeseed as an Example

Genomic selection (GS) has revolutionized breeding for quantitative traits in plants, offering potential to optimize resource allocation in breeding programs and increase genetic gain per unit of time. Modern high-density single nucleotide polymorphism (SNP) arrays comprising up to several hundred thousand markers provide a user-friendly technology to characterize the genetic constitution of whole populations and for implementing GS in breeding programs. However, GS does not build upon detailed genotype profiling facilitated by maximum marker density. With extensive genome-wide linkage disequilibrium (LD) being a common characteristic of breeding pools, fewer representative markers from available high-density genotyping platforms could be sufficient to capture the association between a genomic region and a phenotypic trait. To examine the effects of reduced marker density on genomic prediction accuracy, we collected data on three traits across 2 yr in a panel of 203 homozygous Chinese semiwinter rapeseed ( L.) inbred lines, broadly encompassing allelic variability in the Asian genepool. We investigated two approaches to selecting subsets of markers: a trait-dependent strategy based on genome-wide association study (GWAS) significance thresholds and a trait-independent method to detect representative tag SNPs. Prediction accuracies were evaluated using cross-validation with ridge-regression best linear unbiased predictions (rrBLUP). With semiwinter rapeseed as a model species, we demonstrate that low-density marker sets comprising a few hundred to a few thousand markers enable high prediction accuracies in breeding populations with strong LD comparable to those achieved with high-density arrays. Our results are valuable for facilitating routine application of cost-efficient GS in breeding programs.

Association Study Reveals Novel Genes Related to Yield and Quality of Fruit in Cape Gooseberry (Physalis peruviana L.)

Association mapping has been proposed as an efficient approach to assist plant breeding programs to investigate the genetic basis of agronomic traits. In this study, we evaluated 18 traits related to yield, (FWP, NF, FWI, and FWII), fruit size-shape (FP, FA, MW, WMH, MH, HMW, DI, FSI, FSII, OVO, OBO), and fruit quality (FIR, CF, and SST), in a diverse collection of 100 accessions of Physalis peruviana including wild, landraces, and anther culture derived lines. We identified seven accessions with suitable traits: fruit weight per plant (FWP) > 7,000 g/plant and cracked fruits (CF) < 4%, to be used as parents in cape gooseberry breeding program. In addition, the accessions were also characterized using Genotyping By Sequencing (GBS). We discovered 27,982 and 36,142 informative SNP markers based on the alignment against the two cape gooseberry references transcriptomes. Besides, 30,344 SNPs were identified based on alignment to the tomato reference genome. Genetic structure analysis showed that the population could be divided into two or three sub-groups, corresponding to landraces-anther culture and wild accessions for K = 2 and wild, landraces, and anther culture plants for K = 3. Association analysis was carried out using a Mixed Linear Model (MLM) and 34 SNP markers were significantly associated. These results reveal the basis of the genetic control of important agronomic traits and may facilitate marker-based breeding in P. peruviana.

Revolution in Genotyping Platforms for Crop Improvement

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

Unlocking new alleles for leaf rust resistance in the Vavilov wheat collection

Thirteen potentially new leaf rust resistance loci were identified in a Vavilov wheat diversity panel. We demonstrated the potential of allele stacking to strengthen resistance against this important pathogen. Leaf rust (LR) caused by Puccinia triticina is an important disease of wheat (Triticum aestivum L.), and the deployment of genetically resistant cultivars is the most viable strategy to minimise yield losses. In this study, we evaluated a diversity panel of 295 bread wheat accessions from the N. I. Vavilov Institute of Plant Genetic Resources (St Petersburg, Russia) for LR resistance and performed genome-wide association studies (GWAS) using 10,748 polymorphic DArT-seq markers. The diversity panel was evaluated at seedling and adult plant growth stages using three P. triticina pathotypes prevalent in Australia. GWAS was applied to 11 phenotypic data sets which identified a total of 52 significant marker-trait associations representing 31 quantitative trait loci (QTL). Among them, 29 QTL were associated with adult plant resistance (APR). Of the 31 QTL, 13 were considered potentially new loci, whereas 4 co-located with previously catalogued Lr genes and 14 aligned to regions reported in other GWAS and genomic prediction studies. One seedling LR resistance QTL located on chromosome 3A showed pronounced levels of linkage disequilibrium among markers (r ² = 0.7), suggested a high allelic fixation. Subsequent haplotype analysis for this region found seven haplotype variants, of which two were strongly associated with LR resistance at seedling stage. Similarly, analysis of an APR QTL on chromosome 7B revealed 22 variants, of which 4 were associated with resistance at the adult plant stage. Furthermore, most of the tested lines in the diversity panel carried 10 or more combined resistance-associated marker alleles, highlighting the potential of allele stacking for long-lasting resistance.

Cruz MT, Kumar A. Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)

BACKGROUND

The identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping.

RESULTS

The drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5-20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance.

CONCLUSION

The results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice.

Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)

BACKGROUND

The identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping.

RESULTS

The drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5-20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance.

CONCLUSION

The results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice.

NGS-Based Genotyping, High-Throughput Phenotyping and Genome-Wide Association Studies Laid the Foundations for Next-Generation Breeding in Horticultural Crops

Demographic trends and changes to climate require a more efficient use of plant genetic resources in breeding programs. Indeed, the release of high-yielding varieties has resulted in crop genetic erosion and loss of diversity. This has produced an increased susceptibility to severe stresses and a reduction of several food quality parameters. Next generation sequencing (NGS) technologies are being increasingly used to explore “gene space” and to provide high-resolution profiling of nucleotide variation within germplasm collections. On the other hand, advances in high-throughput phenotyping are bridging the genotype-to-phenotype gap in crop selection. The combination of allelic and phenotypic data points via genome-wide association studies is facilitating the discovery of genetic loci that are associated with key agronomic traits. In this review, we provide a brief overview on the latest NGS-based and phenotyping technologies and on their role to unlocking the genetic potential of vegetable crops; then, we discuss the paradigm shift that is underway in horticultural crop breeding.

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Enhancing genetic gain in the era of molecular breeding

As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary approaches, team breeding, will be required to address the challenge of maintaining a plentiful and safe food supply for future generations. New opportunities for enhancing genetic gain, a high efficiency breeding pipeline, and broad-sense genetic gain are also discussed prospectively.