Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

Reconciliation of wheat 660K and 90K SNP arrays and their utilization in dough rheological properties of bread wheat

INTRODUCTION

High-density Wheat 660K and 90K SNP arrays are powerful tools for understanding the genetic basis of wheat traits. However, their inconsistantly physical positions that were caused by different versions of Chinese Spring genome during developing arrays are confused and inconvenient for further application.

OBJECTIVE

With the repid development of wheat geonome sequencing, we aim to reconciliate Wheat 660K and 90K SNP arrays in modern cultivar and reveal the genetic basis of dough rheological properties in bread wheat.

METHODS

We refined physical positions of Wheat 660K and 90K SNP arrays in the currently popular wheat cultivar AK58 genome that was released more recently. We next performed genome-wide association studies (GWAS) and linkage analysis to identify important genetic loci related to quality traits using updated and un-updated arrays, respectively.

RESULTS

Refining results showed that 92.3% and 83% of SNPs in the Wheat 660K and 90K SNP arrays were precisely mapped to the AK58 genome, respective. GWAS results by the updated 660K and 90K arrays indicated that 26 intervals composed of 1032 significant SNPs were associated with 9 quality traits in multiple environments. The significant interval for stability time on 1D was narrowed into an 8.4-Mb region using the updated arrays, whereas the interval is 405 Mb using the un-updated arrays. Linkage analysis revealed an important QTL QST.henau-1D.2 for stability time with 1.64 Mb. Integration of GWAS and QTL results narrowed the significant interval into 6.46 Mb containing 35 annotation genes by collinearity analysis. After T-test, gene expression analysis, seven of them are potential candidate genes and thus favorable haplotypes are identified to benefit marker-assisted selection.

CONCLUSION

A reconciliation of Wheat 660K and 90K arrays promote their efficient applications. Important genetic loci and favorable haplotypes identified in this study provided valuable information for wheat quality breeding.

Elucidating the genetic basis of bulb-related traits in garlic (Allium sativum) through genome-wide association study

The genetic architecture of garlic bulb related traits were still not well elucidated due to its big and complex genome. In this study, genotyping-by-sequencing (GBS) in 163 garlic accessions mainly from China were conducted. All the 163 garlic accessions were divided into three subpopulations, and largely consistent with geographic origins. Genome-wide association study (GWAS) was conducted for 5 garlic bulb related traits across four environments. Totally, 26 significantly loci were identified in two or more environments and located within or near 431 genes, and explain 14.0-31.7 % of the phenotypic variances. Among these, qBW5.1 was nearly with the qBH5.1. Four loci were reported previously, whereas the remaining 22 are likely to be new. Gene ontology enrichment analysis showed that the candidate genes were significantly enriched in metabolic process, biosynthetic process and catalytic activity. Nine candidate genes encode the zinc finger domain-containing protein, serine/threonine-protein kinase, peroxygenase, auxin-induced protein, ethylene-responsive transcription and E3-Ubiquitin protein ligases were identified and validated. Additionally, a meaningful achievement is one kompetitive allele-specific PCR marker, Kasp_chr7_BW for bulb weight were successfully developed and validated in a diverse panel. These results uncover the genetic mechanism of garlic bulb related traits and provide accessions and KASP markers for further garlic molecular breeding.

Genetic relationship analysis and core collection construction of Eucalyptus grandis from Dongmen improved variety base: the largest eucalypt germplasm resource in China

BACKGROUND

Eucalyptus grandis, which was first comprehensively and systematically introduced to China in the 1980s, is one of the most important fast-growing tree species in the forestry industry. However, to date, no core collection has been selected from the germplasm resources of E. grandis based on growth and genetic relationship analysis.

RESULTS

In the present study, 545 individuals of E. grandis collected from 28 populations across 5 countries were selected for genetic diversity analysis using 16 selected SSR markers. The polymorphism information content (PIC) was employed to assess genetic diversity, yielding a mean value of 0.707. Genetic structure analysis was conducted on 492 individuals from 13 combined populations, revealing three clusters as the most suitable number. Principal coordinate analysis (PCoA) demonstrated that the populations were divided into three major clusters. Additionally, the analysis of molecular variance (AMOVA) indicated that the majority of variation occurred within populations.

CONCLUSIONS

Based on the criteria for screening the core collection, we constructed a population consisting of 158 individuals and created unique fingerprinting codes. These results provide a crucial theoretical foundation for the protection and utilization of germplasm resources of E. grandis in China, which will be helpful in the selection of genetically distant parents for future multigenerational hybridization programs.

Development of a 50K SNP array for whole-genome analysis and its application in the genetic localization of eggplant (Solanum melongena L.) fruit shape

Introduction

Current eggplant variety breeding is still mainly based on conventional methods, and there remains a lack of effective molecular breeding systems for complex traits controlled by multiple genes, such as yield and quality. To accelerate the research progress of eggplant genetics and molecular breeding, it is necessary to implement a genome-based breeding strategy.

Methods

Therefore, in this study, a SNP array containing 50K liquid-phase probes was designed on the basis of the resequencing data of 577 eggplants.

Results

The developed 50K liquid-phase probes were used to perform targeted capture sequencing on 12 eggplant lines, and the efficiency of probe capture exceeded 99.25%. Principal component, phylogenetic, and population structure analyses divided the 577 eggplants into 7 subgroups, and statistical analysis was performed on the fruit shape and color of the materials in the different subgroups. Further analysis of the geographical distribution of 428 Chinese eggplant materials revealed that the geographical regions of different subgroups were similar. The 50K SNP liquid-phase array was used to perform bulked- segregant analysis combined with whole-genome resequencing (BSA-seq) of fruit shape in the F2 population, which consisted of 1435 lines constructed with E421 as the maternal parent and 145 as the paternal parent. The BSA-seq data were located in the 78444173-84449348 interval on chromosome 3, with a size of 6 Mb, which was narrowed to 712.6 kb through fine mapping. Further sequence alignment and expression analysis revealed SmIQD14 as a candidate gene controlling eggplant fruit shape. The 50K SNP liquid-phase array can be widely used in future eggplant molecular breeding research.

Identification of Taihang-chicken-specific genetic markers using genome-wide SNPs and machine learning: BREED-SPECIFIC SNPS OF TAIHANG CHICKEN

Taihang is an indigenous breed in Hebei Province and has a long history of evolution. To uncover the genetic basis and protect the genetic resources, it is important to develop accurate markers to identify Taihang at the molecular level. In this study, a total of 137 individuals from Taihang and other 4 breeds were selected to construct a genome-wide SNP map. The population genetic structure analysis revealed clear differentiation among the five breeds. A total of 47 SNPs were identified for differentiating Taihang from other breeds based on the fixation index (FST), linkage disequilibrium (LD) pruning, and machine learning, further validated using principal component analysis (PCA) and genetic relationship matrix (GRM). The 47 SNPs were annotated to genes associated with production, growth and development, immunity, adaptation, and appearance. Overall, the combination of 47 SNPs enables precise identification of Taihang, which significantly contributes to the preservation of native genetic resources.

Identification of genetic loci for powdery mildew resistance in common wheat

Powdery mildew (PM) poses an extreme threat to wheat yields and quality. In this study, 262 recombinant inbred lines (RILs) of Doumai and Shi 4185 cross were used to map PM resistance genes across four environments. High-density genetic linkage map of the Doumai/Shi 4185 RIL population was constructed using the wheat Illumina iSelect 90K single-nucleotide polymorphism (SNP) array. In total, four stable quantitative trait loci (QTLs) for PM resistance, QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS, were detected and explained 5.6%-15.6% of the phenotypic variances. Doumai contributed all the resistance alleles of QPm.caas-2AS, QPm.caas-4AS, QPm.caas-4BL, and QPm.caas-6BS. Among these, QPm.caas-4AS and QPm.caas-6BS overlapped with the previously reported loci, whereas QPm.caas-2AS and QPm.caas-4BL are potentially novel. In addition, six high-confidence genes encoding the NBS-LRR-like resistance protein, disease resistance protein family, and calcium/calmodulin-dependent serine/threonine-kinase were selected as the candidate genes for PM resistance. Three kompetitive allele-specific PCR (KASP) markers, Kasp_PMR_2AS for QPm.caas-2AS, Kasp_PMR_4BL for QPm.caas-4BL, and Kasp_PMR_6BS for QPm.caas-6BS, were developed, and their genetic effects were validated in a natural population including 100 cultivars. These findings will offer valuable QTLs and available KASP markers to enhance wheat marker-assisted breeding for PM resistance.

Disentangling sources of gene tree discordance for Hordeum species via target-enriched sequencing assays

Hordeum is an economically and evolutionarily important genus within the Triticeae tribe of the family Poaceae, and contains 33 widely distributed and diverse species which cytologically represent four subgenomes (H, Xa, Xu and I). These wild species (except Hordeum spontaneum, which is the primary gene pool of barley) are secondary or tertiary gene-pool germplasms for barley and wheat improvement, and uncovering their complicated evolutionary relationships would benefit for future breeding programs. Here, we developed a complexity-reduced pipeline via capturing genome-wide distributed fragments via two novel target-enriched assays (HorCap v1.0 and BarPlex v1.0) in conjugation with high-throughput sequencing of the enrichments. Both assays were tested for genotyping 40 species from three genera (Hordeum, Triticum, and Aegilops) containing 82 samples 67 accessions. Either of both assays worked efficiently in genotyping, while integration of both assays can significantly improve the robustness and resolution of the Hordeum phylogenetic trees. Interestingly, the incomplete lineage sorting (ILS) was inferred for the first time as the major factor causing phylogenetic discordance among the four subgenomes, whereas in New World species (carrying I genome) post-speciation introgression events were revealed. Through revising the evolutionary relationships of the Hordeum species based on an ancestral state reconstruction for the diploids and parental donor inference for the polyploids, our results raised new queries about the Hordeum phylogeny. Moreover, both newly-developed assays are applicable in genotyping and phylogenetic analysis of Hordeum and other Triticeae wild species.

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance

KEY MESSAGE

Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

Streamlined whole-genome genotyping through NGS-enhanced thermal asymmetric interlaced (TAIL)-PCR

Whole-genome genotyping (WGG) stands as a pivotal element in genomic-assisted plant breeding. Nevertheless, sequencing-based approaches for WGG continue to be costly, primarily owing to the high expenses associated with library preparation and the laborious protocol. During prior development of foreground and background integrated genotyping by sequencing (FBI-seq), we discovered that any sequence-specific primer (SP) inherently possesses the capability to amplify a massive array of stable and reproducible non-specific PCR products across the genome. Here, we further improved FBI-seq by replacing the adapter ligated by Tn5 transposase with an arbitrary degenerate (AD) primer. The protocol for the enhanced FBI-seq unexpectedly mirrors a simplified thermal asymmetric interlaced (TAIL)-PCR, a technique that is widely used for isolation of flanking sequences. However, the improved TAIL-PCR maximizes the primer-template mismatched annealing capabilities of both SP and AD primers. In addition, leveraging of next-generation sequencing enhances the ability of this technique to assay tens of thousands of genome-wide loci for any species. This cost-effective, user-friendly, and powerful WGG tool, which we have named TAIL-PCR by sequencing (TAIL-peq), holds great potential for widespread application in breeding programs, thereby facilitating genome-assisted crop improvement.

Validation of SNP Markers for Diversity Analysis, Quality Control, and Trait Selection in a Biofortified Cassava Population

A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future.

Triumphs of genomic-assisted breeding in crop improvement

Conventional breeding approaches have played a significant role in meeting the food demand remarkably well until now. However, the increasing population, yield plateaus in certain crops, and limited recombination necessitate using genomic resources for genomics-assisted crop improvement programs. As a result of advancements in the next-generation sequence technology, GABs have developed dramatically to characterize allelic variants and facilitate their rapid and efficient incorporation in crop improvement programs. Genomics-assisted breeding (GAB) has played an important role in harnessing the potential of modern genomic tools, exploiting allelic variation from genetic resources and developing cultivars over the past decade. The availability of pangenomes for major crops has been a significant development, albeit with varying degrees of completeness. Even though adopting these technologies is essentially determined on economic grounds and cost-effective assays, which create a wealth of information that can be successfully used to exploit the latent potential of crops. GAB has been instrumental in harnessing the potential of modern genomic resources and exploiting allelic variation for genetic enhancement and cultivar development. GAB strategies will be indispensable for designing future crops and are expected to play a crucial role in breeding climate-smart crop cultivars with higher nutritional value.

Identification of QTL for Alkylresorcinols in Wheat and Development of KASP Markers for Marker-Assisted Selection of Health-Promoting Varieties

This study evaluated alkylresorcinol concentration (ARC) in recombinant inbred lines (RILs) from the cross of Zhongmai 578 and Jimai 22 in three environments. ARC exhibited a continuous distribution ranging from 337.4 to 758.0, 495.4-768.0, and 456.3-764.7 μg/g, respectively, in three environments. Analysis of variance (ANOVA) indicated significant (P < 0.001) impacts of genotypes, environments, and their interactions. The broad-sense heritability of ARC was 0.76. Genome-wide linkage mapping analysis identified four stable quantitative trait loci (QTL) for ARC on chromosomes 2A, 3A, 4D, and 7A. Kompetitive allele-specific PCR (KASP) marker of each QTL was developed and validated in 206 representative wheat varieties. Wheat varieties harboring 0, 1, 2, 3, and 4 favorable alleles had ARC of 499.1, 587.8, 644.7, 668.5, and 711.1 μg/g, respectively. This study suggests that combining multiple minor-effect QTL through KASP markers can serve as an effective strategy for breeding high-ARC wheat, thereby enhancing innovations in functional food production.

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.

Tagging large CNV blocks in wheat boosts digitalization of germplasm resources by ultra-low-coverage sequencing

BACKGROUND

The massive structural variations and frequent introgression highly contribute to the genetic diversity of wheat, while the huge and complex genome of polyploid wheat hinders efficient genotyping of abundant varieties towards accurate identification, management, and exploitation of germplasm resources.

RESULTS

We develop a novel workflow that identifies 1240 high-quality large copy number variation blocks (CNVb) in wheat at the pan-genome level, demonstrating that CNVb can serve as an ideal DNA fingerprinting marker for discriminating massive varieties, with the accuracy validated by PCR assay. We then construct a digitalized genotyping CNVb map across 1599 global wheat accessions. Key CNVb markers are linked with trait-associated introgressions, such as the 1RS·1BL translocation and 2NvS translocation, and the beneficial alleles, such as the end-use quality allele Glu-D1d (Dx5 + Dy10) and the semi-dwarf r-e-z allele. Furthermore, we demonstrate that these tagged CNVb markers promote a stable and cost-effective strategy for evaluating wheat germplasm resources with ultra-low-coverage sequencing data, competing with SNP array for applications such as evaluating new varieties, efficient management of collections in gene banks, and describing wheat germplasm resources in a digitalized manner. We also develop a user-friendly interactive platform, WheatCNVb ( http://wheat.cau.edu.cn/WheatCNVb/ ), for exploring the CNVb profiles over ever-increasing wheat accessions, and also propose a QR-code-like representation of individual digital CNVb fingerprint. This platform also allows uploading new CNVb profiles for comparison with stored varieties.

CONCLUSIONS

The CNVb-based approach provides a low-cost and high-throughput genotyping strategy for enabling digitalized wheat germplasm management and modern breeding with precise and practical decision-making.

Development and application of whole-chromosome painting of chromosomes 7A and 8A of Arachis duranensis based on chromosome-specific single-copy oligonucleotides

For peanut, the lack of stable cytological markers is a barrier to tracking specific chromosomes, elucidating the genetic relationships between genomes and identifying chromosomal variations. Chromosome mapping using single-copy oligonucleotide (oligo) probe libraries has unique advantages for identifying homologous chromosomes and chromosomal rearrangements. In this study, we developed two whole-chromosome single-copy oligo probe libraries, LS-7A and LS-8A, based on the reference genome sequences of chromosomes 7A and 8A of Arachis duranensis. Fluorescence in situ hybridization (FISH) analysis confirmed that the libraries could specifically paint chromosomes 7 and 8. In addition, sequential FISH and electronic localization of LS-7A and LS-8A in A. duranensis (AA) and A. ipaensis (BB) showed that chromosomes 7A and 8A contained translocations and inversions relative to chromosomes 7B and 8B. Analysis of the chromosomes of wild Arachis species using LS-8A confirmed that this library could accurately and effectively identify A genome species. Finally, LS-7A and LS-8A were used to paint the chromosomes of interspecific hybrids and their progenies, which verified the authenticity of the interspecific hybrids and identified a disomic addition line. This study provides a model for developing specific oligo probes to identify the structural variations of other chromosomes in Arachis and demonstrates the practical utility of LS-7A and LS-8A.

Developing an SNP dataset for efficiently evaluating soybean germplasm resources using the genome sequencing data of 3,661 soybean accessions

BACKGROUND

Single nucleotide polymorphism (SNP) markers play significant roles in accelerating breeding and basic crop research. Several soybean SNP panels have been developed. However, there is still a lack of SNP panels for differentiating between wild and cultivated populations, as well as for detecting polymorphisms within both wild and cultivated populations.

RESULTS

This study utilized publicly available resequencing data from over 3,000 soybean accessions to identify differentiating and highly conserved SNP and insertion/deletion (InDel) markers between wild and cultivated soybean populations. Additionally, a naturally occurring mutant gene library was constructed by analyzing large-effect SNPs and InDels in the population.

CONCLUSION

The markers obtained in this study are associated with numerous genes governing agronomic traits, thus facilitating the evaluation of soybean germplasms and the efficient differentiation between wild and cultivated soybeans. The natural mutant gene library permits the quick identification of individuals with natural mutations in functional genes, providing convenience for accelerating soybean breeding using reverse genetics.

An SNP based genotyping assay for genes associated with drought tolerance in bread wheat

BACKGROUND

SnRK2 plays vital role in responding to adverse abiotic stimuli. The applicability of TaSnRK2.4 and TaSnRK2.9 was investigated to leverage the potential of these genes in indigenous wheat breeding programs.

METHODS

Genetic diversity was assessed using pre-existing markers for TaSnRK2.4 and TaSnRK2.9. Furthermore, new markers were also developed to enhance their broader applicability. KASP markers were designed for TaSnRK2.4, while CAPS-based markers were tailored for TaSnRK2.9.

RESULTS

Analysis revealed lack of polymorphism in TaSnRK2.4 among Pakistani wheat germplasm under study. To validate this finding, available gel-based markers for TaSnRK2.4 were employed, producing consistent results and offering limited potential for application in marker-assisted wheat breeding with Pakistani wheat material. For TaSnRK2.9-5A, CAPS2.9-5A-1 and CAPS2.9-5A-2 markers were designed to target SNP positions at 308 nt and 1700 nt revealing four distinct haplotypes. Association analysis highlighted the significance of Hap-5A-1 of TaSnRK2.9-5A, which exhibited association with an increased number of productive tillers (NPT), grains per spike (GPS), and reduced plant height (PH) under well-watered (WW) conditions. Moreover, it showed positive influence on NPT under WW conditions, GPS under water-limited (WL) conditions, and PH under both WW and WL conditions. High selection intensity observed for Hap-5A-1 underscores the valuable role it has played in Pakistani wheat breeding programs. Gene expression studies of TaSnRK2.9-5A revealed the involvement of this gene in response to PEG, NaCl, low temperature and ABA treatments.

CONCLUSION

These findings propose that TaSnRK2.9 can be effectively employed for improving wheat through marker-assisted selection in wheat breeding efforts.

Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters

KEY MESSAGE

Selection response in truncation selection across multiple sets of candidates hinges on their post-selection proportions, which can deviate grossly from their initial proportions. For BLUPs, using a uniform threshold for all candidates maximizes the selection response, irrespective of differences in population parameters. Plant breeding programs typically involve multiple families from either the same or different populations, varying in means, genetic variances and prediction accuracy of BLUPs or BLUEs for true genetic values (TGVs) of candidates. We extend the classical breeder's equation for truncation selection from single to multiple sets of genotypes, indicating that the expected overall selection response ( Δ G Tot ) for TGVs depends on the selection response within individual sets and their post-selection proportions. For BLUEs, we show that maximizingΔ G Tot requires thresholds optimally tailored for each set, contingent on their population parameters. For BLUPs, we prove thatΔ G Tot is maximized by applying a uniform threshold across all candidates from all sets. We provide explicit formulas for the origin of the selected candidates from different sets and show that their proportions before and after selection can differ substantially, especially for sets with inferior properties and low proportion. We discuss implications of these results for (a) optimum allocation of resources to training and prediction sets and (b) the need to counteract narrowing the genetic variation under genomic selection. For genomic selection of hybrids based on BLUPs of GCA of their parent lines, selecting distinct proportions in the two parent populations can be advantageous, if these differ substantially in the variance and/or prediction accuracy of GCA. Our study sheds light on the complex interplay of selection thresholds and population parameters for the selection response in plant breeding programs, offering insights into the effective resource management and prudent application of genomic selection for improved crop development.

Investigation of Imidazolinone Herbicide Resistance Gene with KASP Markers for Japonica/Geng Rice Varieties in the Huanghuaihai Region of China

Rice is a staple food for more than half of the global population due to its food security and sustainable development. Weeds compete with crops for sunlight and indispensable nutrients, affecting the yield and quality of crops. Breeding herbicide-tolerant rice varieties paired with herbicide application is expected to help with weed control. In this study, 194 Japonica/Geng rice varieties or lines collected from the Huanghuaihai region of China were screened by Kompetitive Allele-Specific PCR (KASP) markers based on four mutation sites within OsALS1 (LOC_Os02g30630), which is the target of imidazolinone (IMI) herbicides. Only the OsALS1627N haplotype was identified in 18 varieties, including the previously reported Jingeng818 (JG818), and its herbicide resistance was validated by treatment with three IMIs. To investigate the origin of the OsALS1627N haplotype in the identified varieties, six codominant PCR-based markers tightly linked with OsALS1 were developed. PCR analysis revealed that the other 17 IMI-tolerant varieties were derived from JG818. We randomly selected three IMI-tolerant varieties for comparative whole-genome resequencing with known receptor parent varieties. Sequence alignment revealed that more loci from JG818 have been introduced into IMI-tolerant varieties. However, all three IMI-tolerant varieties carried clustered third type single nucleotide polymorphism (SNP) sites from unknown parents, indicating that these varieties were not directly derived from JG818, whereas those from different intermediate improved lines were crossed with JG818. Overall, we found that only OsALS1627N from JG818 has been broadly introduced into the Huanghuaihai region of China. Additionally, the 17 identified IMI-tolerant varieties provide alternative opportunities for improving such varieties along with other good traits.

QTL Mapping of Adult Plant Resistance to Powdery Mildew in Chinese Wheat Landrace Baidatou

Wheat powdery mildew, caused by the biotrophic fungus Blumeria graminis f. sp. tritici (Bgt), is one of the most devastating diseases affecting wheat throughout the world. Breeding and growing resistant wheat cultivars is one of the most economic and effective methods to control the disease, and as such, identifying and mapping the new and effective resistance genes is critical. Baidatou, a Chinese wheat landrace, shows excellent field resistance to powdery mildew. To identify the resistance gene(s) in Baidatou, 170 F7:8 recombinant inbred lines (RILs) derived from the cross Mingxian 169/Baidatou were evaluated for powdery mildew response at the adult-plant stage in the experimental fields in Yangling (YL) of Shaanxi Province and Tianshui (TS) in Gansu Province in 2019, 2020, and 2021. The relative area under disease progress curve (rAUDPC) of Mingxian 169/Baidatou F7:8 RILs indicated that the resistance of Baidatou to powdery mildew was controlled by quantitative trait loci (QTLs). Based on bulk segregation analysis combined with the 660K single nucleotide polymorphism (SNP) array and genotyping by target sequencing (16K SNP) of the entire RIL population, two QTLs, QPmbdt.nwafu-2AS and QPmbdt.nwafu-3AS, were identified, and these accounted for up to 44.5% of the phenotypic variation. One of the QTLs was located on the 3.32 cM genetic interval on wheat chromosome 2AS between the kompetitive allele-specific PCR markers AX-111012288 and AX_174233809, and another was located on the 9.6 cM genetic interval on chromosome 3AS between the SNP markers 3A_684044820 and 3A_686681822. These markers could be useful for successful breeding of powdery mildew resistance in wheat.

Genome-Wide Association Study to Identify Marker-Trait Associations for Seed Color in Colored Wheat (Triticum aestivum L.)

This study conducted phenotypic evaluations on a wheat F3 population derived from 155 F2 plants. Traits related to seed color, including chlorophyll a, chlorophyll b, carotenoid, anthocyanin, L*, a*, and b*, were assessed, revealing highly significant correlations among various traits. Genotyping using 81,587 SNP markers resulted in 3969 high-quality markers, revealing a genome-wide distribution with varying densities across chromosomes. A genome-wide association study using fixed and random model circulating probability unification (FarmCPU) and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified 11 significant marker-trait associations (MTAs) associated with L*, a*, and b*, and chromosomal distribution patterns revealed predominant locations on chromosomes 2A, 2B, and 4B. A comprehensive annotation uncovered 69 genes within the genomic vicinity of each MTA, providing potential functional insights. Gene expression analysis during seed development identified greater than 2-fold increases or decreases in expression in colored wheat for 16 of 69 genes. Among these, eight genes, including transcription factors and genes related to flavonoid and ubiquitination pathways, exhibited distinct expression patterns during seed development, providing further approaches for exploring seed coloration. This comprehensive exploration expands our understanding of the genetic basis of seed color and paves the way for informed discussions on the molecular intricacies contributing to this phenotypic trait.

Unraveling plant-microbe interactions: can integrated omics approaches offer concrete answers?

Advances in high throughput omics techniques provide avenues to decipher plant microbiomes. However, there is limited information on how integrated informatics can help provide deeper insights into plant-microbe interactions in a concerted way. Integrating multi-omics datasets can transform our understanding of the plant microbiome from unspecified genetic influences on interacting species to specific gene-by-gene interactions. Here, we highlight recent progress and emerging strategies in crop microbiome omics research and review key aspects of how the integration of host and microbial omics-based datasets can be used to provide a comprehensive outline of complex crop-microbe interactions. We describe how these technological advances have helped unravel crucial plant and microbial genes and pathways that control beneficial, pathogenic, and commensal plant-microbe interactions. We identify crucial knowledge gaps and synthesize current limitations in our understanding of crop microbiome omics approaches. We highlight recent studies in which multi-omics-based approaches have led to improved models of crop microbial community structure and function. Finally, we recommend holistic approaches in integrating host and microbial omics datasets to achieve precision and efficiency in data analysis, which is crucial for biotic and abiotic stress control and in understanding the contribution of the microbiota in shaping plant fitness.

Research Note: Development and application of specific molecular identity cards for "Yufen 1" H line chickens

The "Yufen 1" H line chicken (YF) has excellent characteristics including early sexual maturity and high egg production, and the conservation of its genetic diversity is the core of the breeding activity. To overcome misrepresented breeds and protect the integrity of the germplasm genetic resources, it is important to develop accurate and convenient methods to identify YF. In this study, whole genome resequencing was performed on the YF population, and bioinformatics analysis was conducted by combining the data from different breeds. Linkage disequilibrium (LD) analysis revealed that YF had the slowest LD-decay rate, suggesting strong natural and artificial selection in its history. Through selective sweep analysis, 1,126 selected regions in YF were identified, which contained 163,661 single nucleotide polymorphisms (SNPs). In particular, 5 specific SNPs (SNP1: Chr2:45509616, SNP2: Chr2:45510792, SNP3: Chr9:13788193, SNP4: Chr9:13795646, SNP5: Chr9:13798154) were found exclusively in the YF population. Subsequently, PCR amplification and Sanger sequencing confirmed the presence of these 5 SNPs in YF. Finally, 4 SNPs (SNP1, SNP2, SNP4, SNP5) were screened and verified using the Kompetitive Allele Specific PCR (KASP) typing technique. These SNPs can be used as specific molecular identity cards (IDs) for YF authentication. The present study is of great significance to ensure sustainable conservation and promotion of YF germplasm resources.

An affordable and convenient diagnostic marker to identify male and female hop plants

Hop production utilizes exclusively female plants, whereas male plants only serve to generate novel variation within breeding programs through crossing. Currently, hop lacks a rapid and accurate diagnostic marker to determine whether plants are male or female. Without a diagnostic marker, breeding programs may take 1-2 years to determine the sex of new seedlings. Previous research on sex-linked markers was restricted to specific populations or breeding programs and therefore had limited transferability or suffered from low scalability. A large collection of 765 hop genotypes with known sex phenotypes, genotyping-by-sequencing, and genome-wide association mapping revealed a highly significant marker on the sex chromosome (LOD score = 208.7) that predicted sex within our population with 96.2% accuracy. In this study, we developed a PCR allele competitive extension (PACE) assay for the diagnostic SNP and tested three quick DNA extraction methodologies for rapid, high-throughput genotyping. Additionally, the marker was validated in a separate population of 94 individuals from 15 families from the USDA-ARS hop breeding program in Prosser, WA with 96% accuracy. This diagnostic marker is located in a gene predicted to encode the basic helix-loop-helix transcription factor protein, a family of proteins that have been previously implicated in male sterility in a variety of plant species, which may indicate a role in determining hop sex. The marker is diagnostic, accurate, affordable, and highly scalable and has the potential to improve efficiency in hop breeding.

A SNP variation in the Sucrose synthase (SoSUS) gene associated with sugar-related traits in sugarcane

Background

Sugarcane (Saccharum spp.) is an economically significant crop for both the sugar and biofuel industries. Breeding sugarcane cultivars with high-performance agronomic traits is the most effective approach for meeting the rising demand for sugar and biofuels. Molecular markers associated with relevant agronomic traits could drastically reduce the time and resources required to develop new sugarcane varieties. Previous sugarcane candidate gene association analyses have found single nucleotide polymorphism (SNP) markers associated with sugar-related traits. This study aims to validate these associated SNP markers of six genes, including Lesion simulating disease 1 (LSD), Calreticulin (CALR), Sucrose synthase 1 (SUS1), DEAD-box ATP-dependent RNA helicase (RH), KANADI1 (KAN1), and Sodium/hydrogen exchanger 7 (NHX7), in a diverse population in 2-year and two-location evaluations.

Methods

After genotyping of seven targeted SNP markers was performed by PCR Allelic Competitive Extension (PACE) SNP genotyping, the association with sugar-related traits and important cane yield component traits was determined on a set of 159 sugarcane genotypes. The marker-trait relationships were validated and identified by both t-test analysis and an association analysis based on the general linear model.

Results

The mSoSUS1_SNPCh10.T/C and mSoKAN1_SNPCh7.T/C markers that were designed from the SUS1 and KAN1 genes, respectively, showed significant associations with different amounts of sugar-related traits and yield components. The mSoSUS1_SNPCh10.T/C marker was found to have more significant association with sugar-related traits, including pol, CCS, brix, fiber and sugar yield, with p values of 6.08 × 10-6 to 4.35 × 10-2, as well as some cane yield component traits with p values of 1.61 × 10-4 to 3.35 × 10-2. The significant association is consistent across four environments.

Conclusion

Sucrose synthase (SUS) is considered a crucial enzyme involved in sucrose metabolism. This marker is a high potential functional marker that may be used in sugarcane breeding programs to select superior sugarcane with good fiber and high sugar contents.

Development of an SNP marker set for marker-assisted backcrossing using genotyping-by-sequencing in tetraploid perilla

High-quality molecular markers are essential for marker-assisted selection to accelerate breeding progress. Compared with diploid species, recently diverged polyploid crop species tend to have highly similar homeologous subgenomes, which is expected to limit the development of broadly applicable locus-specific single-nucleotide polymorphism (SNP) assays. Furthermore, it is particularly challenging to make genome-wide marker sets for species that lack a reference genome. Here, we report the development of a genome-wide set of kompetitive allele specific PCR (KASP) markers for marker-assisted recurrent selection (MARS) in the tetraploid minor crop perilla. To find locus-specific SNP markers across the perilla genome, we used genotyping-by-sequencing (GBS) to construct linkage maps of two F2 populations. The two resulting high-resolution linkage maps comprised 2326 and 2454 SNP markers that spanned a total genetic distance of 2133 cM across 16 linkage groups and 2169 cM across 21 linkage groups, respectively. We then obtained a final genetic map consisting of 22 linkage groups with 1123 common markers from the two genetic maps. We selected 96 genome-wide markers for MARS and confirmed the accuracy of markers in the two F2 populations using a high-throughput Fluidigm system. We confirmed that 91.8% of the SNP genotyping results from the Fluidigm assay were the same as the results obtained through GBS. These results provide a foundation for marker-assisted backcrossing and the development of new varieties of perilla.

Genetic analysis of iron, zinc and grain yield in wheat-Aegilops derivatives using multi-locus GWAS

BACKGROUND

Wheat is a major staple crop and helps to reduce worldwide micronutrient deficiency. Investigating the genetics that control the concentrations of iron (Fe) and zinc (Zn) in wheat is crucial. Hence, we undertook a comprehensive study aimed at elucidating the genomic regions linked to the contents of Fe and Zn in the grain.

METHODS AND RESULTS

We performed the multi-locus genome-wide association (ML-GWAS) using a panel of 161 wheat-Aegilops substitution and addition lines to dissect the genomic regions controlling grain iron (GFeC), and grain zinc (GZnC) contents. The wheat panel was genotyped using 10,825 high-quality SNPs and phenotyped in three different environments (E1-E3) during 2017-2019. A total of 111 marker-trait associations (MTAs) (at p-value < 0.001) were detected that belong to all three sub-genomes of wheat. The highest number of MTAs were identified for GFeC (58), followed by GZnC (44) and yield (9). Further, six stable MTAs were identified for these three traits and also two pleiotropic MTAs were identified for GFeC and GZnC. A total of 1291 putative candidate genes (CGs) were also identified for all three traits. These CGs encode a diverse set of proteins, including heavy metal-associated (HMA), bZIP family protein, AP2/ERF, and protein previously associated with GFeC, GZnC, and grain yield.

CONCLUSIONS

The significant MTAs and CGs pinpointed in this current study are poised to play a pivotal role in enhancing both the nutritional quality and yield of wheat, utilizing marker-assisted selection (MAS) techniques.

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.

Genome-wide linkage mapping of root system architecture-related traits in common wheat (Triticum aestivum L.)

Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.

QTL Mapping Reveals Both All-Stage and Adult-Plant Resistance to Powdery Mildew in Chinese Elite Wheat Cultivars

Powdery mildew caused by Blumeria graminis f. sp. tritici is a threat to wheat production in China. Mapping quantitative trait loci (QTL) for resistance to powdery mildew and developing breeder-friendly markers are important initial steps in breeding resistant cultivars. An all-stage resistance gene and several QTL were identified using a population of 254 recombinant inbred lines developed from a Jingdong 8/Aikang 58 cross. The population was evaluated for powdery mildew resistance across six field environments over three consecutive growing seasons utilizing two different mixtures of B. graminis f. sp. tritici isolates, named #Bgt-HB and #Bgt-BJ. Using genotypic data obtained from the Wheat TraitBreed 50K single-nucleotide polymorphism array, seven stable QTL were identified on chromosome arms 1DL, 2AL, 2DS, 4DL, 5AL, 6BL.1, and 6BL.2. The QTL on 2AL conferred all-stage resistance to B. graminis f. sp. tritici race E20 in greenhouse tests and explained up to 52% of the phenotypic variance in field trials but was resistant only against #Bgt-HB. The gene involved in this QTL was predicted to be Pm4a based on genome location and gene sequence. QPmja.caas-1DL, QPmja.caas-4DL, and QPmja.caas-6BL.1 were identified as potentially new QTL for powdery mildew resistance. QPmja.caas-2DS and QPmja.caas-6BL.1 were effective against both B. graminis f. sp. tritici mixtures, indicating their probable broad-spectrum resistance. A Kompetitive allele-specific PCR marker closely linked to QPmja.caas-2DS was developed and validated in a panel of 286 wheat cultivars. Because both Jingdong 8 and Aikang 58 have been leading cultivars and breeding parents, the QTL and marker reported represent valuable resources for wheat researchers and breeders.

Genome-Wide Association Mapping of Processing Quality Traits in Common Wheat (Triticum aestivum L.)

Processing quality is an important economic wheat trait. The marker-assisted selection (MAS) method plays a vital role in accelerating genetic improvement of processing quality. In the present study, processing quality in a panel of 165 cultivars grown in four environments was evaluated by mixograph. An association mapping analysis using 90 K and 660 K single nucleotide polymorphism (SNP) arrays identified 24 loci in chromosomes 1A, 1B (4), 1D, 2A, 2B (2), 3A, 3B, 3D (2), 4A (3), 4B, 5D (2), 6A, 7B (2) and 7D (2), explaining 10.2-42.5% of the phenotypic variances. Totally, 15 loci were stably detected in two or more environments. Nine loci coincided with known genes or QTL, whereas the other fifteen were novel loci. Seven candidate genes encoded 3-ketoacyl-CoA synthase, lipoxygenase, pyridoxal phosphate-dependent decarboxylase, sucrose synthase 3 and a plant lipid transfer protein/Par allergen. SNPs significantly associated with processing quality and accessions with more favorable alleles can be used for marker-assisted selection.

Identification and Molecular Mapping of the Gene YrFL in Wheat Cultivar Flanders with Durable Resistance to Stripe Rust

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most severe diseases of wheat (Triticum aestivum L.) worldwide. Identification and characterization of resistance genes is advantageous to cultivating wheat varieties with durable resistance, which is the most economic and effective strategy to control stripe rust. Flanders, a common wheat cultivar released in France in 1986, confers effective resistance to stripe rust both at the seedling and adult plant stages. To elucidate the genetic basis of resistance in Flanders, F1, F2, and F2:3 generations derived from the cross Mingxian169 × Flanders were evaluated with the most prevalent Chinese Pst race CYR33 at the seedling stage. Inheritance analysis showed that the stripe rust resistance of Flanders was controlled by a single dominant gene, temporarily designated as YrFL. Bulked segregant analysis (BSA) combined with a wheat 660K single-nucleotide polymorphism (SNP) array indicated that polymorphic SNP markers were mainly located in the 0 to 150 Mb on wheat chromosome 5A. One hundred and eleven kompetitive allele-specific PCR (KASP) and 39 simple sequence repeat (SSR) markers on chromosome 5A were used to locate the YrFL. Linkage analysis mapped YrFL with 19 KASP and three SSR markers on wheat chromosome 5AS, and the genetic distances of the closest flanking markers AX108925494 and Xbarc56 to YrFL were 0.6 and 2.0 cM, respectively. Chromosome location, resistance characterization, and molecular marker positions indicated that YrFL is likely a novel stripe rust resistance gene on wheat chromosome 5AS and could be pyramided with other resistance genes to improve resistance in wheat breeding programs.

Genome-wide QTL mapping for stripe rust resistance in spring wheat line PI 660122 using the Wheat 15K SNP array

Introduction

Stripe rust is a global disease of wheat. Identification of new resistance genes is key to developing and growing resistant varieties for control of the disease. Wheat line PI 660122 has exhibited a high level of stripe rust resistance for over a decade. However, the genetics of stripe rust resistance in this line has not been studied. A set of 239 recombinant inbred lines (RILs) was developed from a cross between PI 660122 and an elite Chinese cultivar Zhengmai 9023.

Methods

The RIL population was phenotyped for stripe rust response in three field environments and genotyped with the Wheat 15K single-nucleotide polymorphism (SNP) array.

Results

A total of nine quantitative trait loci (QTLs) for stripe rust resistance were mapped to chromosomes 1B (one QTL), 2B (one QTL), 4B (two QTLs), 4D (two QTLs), 6A (one QTL), 6D (one QTL), and 7D (one QTL), of which seven QTLs were stable and designated as QYrPI660122.swust-4BS, QYrPI660122.swust-4BL, QYrPI660122.swust-4DS, QYrPI660122.swust-4DL, QYrZM9023.swust-6AS, QYrZM9023.swust-6DS, and QYrPI660122.swust-7DS. QYrPI660122.swust-4DS was a major all-stage resistance QTL explaining the highest percentage (10.67%-20.97%) of the total phenotypic variation and was mapped to a 12.15-cM interval flanked by SNP markers AX-110046962 and AX-111093894 on chromosome 4DS.

Discussion

The QTL and their linked SNP markers in this study can be used in wheat breeding to improve resistance to stripe rust. In addition, 26 lines were selected based on stripe rust resistance and agronomic traits in the field for further selection and release of new cultivars.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map

BACKGROUND

Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties.

METHODS AND RESULTS

Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term.

CONCLUSION

Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Molecular breeding for improvement of photothermal adaptability in soybean

Soybean (Glycine max (L.) Merr.) is a typical short-day and temperate crop that is sensitive to photoperiod and temperature. Responses of soybean to photothermal conditions determine plant growth and development, which affect its architecture, yield formation, and capacity for geographic adaptation. Flowering time, maturity, and other traits associated with photothermal adaptability are controlled by multiple major-effect and minor-effect genes and genotype-by-environment interactions. Genetic studies have identified at least 11 loci (E1-E4, E6-E11, and J) that participate in photoperiodic regulation of flowering time and maturity in soybean. Molecular cloning and characterization of major-effect flowering genes have clarified the photoperiod-dependent flowering pathway, in which the photoreceptor gene phytochrome A, circadian evening complex (EC) components, central flowering repressor E1, and FLOWERING LOCUS T family genes play key roles in regulation of flowering time, maturity, and adaptability to photothermal conditions. Here, we provide an overview of recent progress in genetic and molecular analysis of traits associated with photothermal adaptability, summarizing advances in molecular breeding practices and tools for improving these traits. Furthermore, we discuss methods for breeding soybean varieties with better adaptability to specific ecological regions, with emphasis on a novel strategy, the Potalaization model, which allows breeding of widely adapted soybean varieties through the use of multiple molecular tools in existing elite widely adapted varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01406-z.

Genome-wide genotyping data renew knowledge on genetic diversity of a worldwide alfalfa collection and give insights on genetic control of phenology traits

China's and Europe's dependence on imported protein is a threat to the food self-sufficiency of these regions. It could be solved by growing more legumes, including alfalfa that is the highest protein producer under temperate climate. To create productive and high-value varieties, the use of large genetic diversity combined with genomic evaluation could improve current breeding programs. To study alfalfa diversity, we have used a set of 395 alfalfa accessions (i.e. populations), mainly from Europe, North and South America and China, with fall dormancy ranging from 3 to 7 on a scale of 11. Five breeders provided materials (617 accessions) that were compared to the 400 accessions. All accessions were genotyped using Genotyping-by-Sequencing (GBS) to obtain SNP allele frequency. These genomic data were used to describe genetic diversity and identify genetic groups. The accessions were phenotyped for phenology traits (fall dormancy and flowering date) at two locations (Lusignan in France, Novi Sad in Serbia) from 2018 to 2021. The QTL were detected by a Multi-Locus Mixed Model (mlmm). Subsequently, the quality of the genomic prediction for each trait was assessed. Cross-validation was used to assess the quality of prediction by testing GBLUP, Bayesian Ridge Regression (BRR), and Bayesian Lasso methods. A genetic structure with seven groups was found. Most of these groups were related to the geographical origin of the accessions and showed that European and American material is genetically distinct from Chinese material. Several QTL associated with fall dormancy were found and most of these were linked to genes. In our study, the infinitesimal methods showed a higher prediction quality than the Bayesian Lasso, and the genomic prediction achieved high (>0.75) predicting abilities in some cases. Our results are encouraging for alfalfa breeding by showing that it is possible to achieve high genomic prediction quality.

Basil (Ocimum basilicum) Landraces Can Be Used in a Water-Limited Environment

Basil (Ocimum basilicum L.) is a member of the Labiatae family and is one of the most widely consumed aromatic and medicinal plants in many countries due to its numerous properties and uses. The objective of the study was to determine whether landraces are better adapted to water-limited environments compared to commercial cultivars. Irrigation levels and genotypes affected plant height and leaf area index, with 25% and 33% higher values observed under complete irrigation, respectively. Additionally, limited water availability resulted in a 20% reduction in dry matter yield and a 21% reduction in essential oil yield over the three years in all of the genotypes tested, specifically in the lower irrigation treatment (d₄₀), compared to the control treatment (d₁₀₀). The landraces that performed the best under limited water supply were Athos white spike (AWS) and Gigas white spike (GWS), indicating their suitability for environments with limited water resources. The results demonstrate that there are landraces that can be utilized in dryland climates with appropriate water management, enabling water conservation and utilization of fields in water-scarce areas for irrigation purposes.

Biochemical and phenological characterization of diverse wheats and their association with drought tolerance genes

Drought is one of the most important wheat production limiting factor, and can lead to severe yield losses. This study was designed to examine the effect of drought stress on wheat physiology and morphology under three different field capacities (FC) viz. 80% (control), 50% (moderate) and 30% (severe drought stress) in a diverse collection of wheat germplasm including cultivars, landraces, synthetic hexaploid and their derivatives. Traits like grain weight, thousand grain weight and biomass were reduced by 38.23%, 18.91% and 26.47% respectively at 30% FC, whereas the reduction rate for these traits at 50% FC were 19.57%, 8.88% and 18.68%. In principal component analysis (PCA), the first two components PC1 and PC2 accounted for 58.63% of the total variation and separated the cultivars and landraces from synthetic-based germplasm. Landraces showed wide range of phenotypic variations at 30% FC compared to synthetic-based germplasm and improved cultivars. However, least reduction in grain weight was observed in improved cultivars which indicated the progress in developing drought resilient cultivars. Allelic variations of the drought-related genes including TaSnRK2.9-5A, TaLTPs-11, TaLTPs-12, TaSAP-7B-, TaPPH-13, Dreb-B1 and 1fehw3 were significantly associated with the phenological traits under drought stress in all 91 wheats including 40 landraces, 9 varieties, 34 synthetic hexaploids and 8 synthetic derivatives. The favorable haplotypes of 1fehw3, Dreb-B1, TaLTPs-11 and TaLTPs-12 increased grain weight, and biomass. Our results iterated the fact that landraces could be promising source to deploy drought adaptability in wheat breeding. The study further identified drought tolerant wheat genetic resources across various backgrounds and identified favourable haplotypes of water-saving genes which should be considered to develop drought tolerant varieties.

Population Structure of Modern Winter Wheat Accessions from Central Asia

Despite the importance of winter wheat in Central Asian countries, there are limited reports describing their diversity within this region. In this study, the population structures of 115 modern winter wheat cultivars from four Central Asian countries were compared to germplasms from six other geographic origins using 10,746 polymorphic single-nucleotide polymorphism (SNP) markers. After applying the STRUCTURE package, we found that in terms of the most optimal K steps, samples from Kazakhstan and Kyrgyzstan were grouped together with samples from Russia, while samples from Tajikistan and Uzbekistan were grouped with samples from Afghanistan. The mean value of Nei's genetic diversity index for the germplasm from four groups from Central Asia was 0.261, which is comparable to that of the six other groups studied: Europe, Australia, the USA, Afghanistan, Turkey, and Russia. The Principal Coordinate Analysis (PCoA) showed that samples from Kyrgyzstan, Tajikistan, and Uzbekistan were close to samples from Turkey, while Kazakh accessions were located near samples from Russia. The evaluation of 10,746 SNPs in Central Asian wheat suggested that 1006 markers had opposing allele frequencies. Further assessment of the physical positions of these 1006 SNPs in the Wheat Ensembl database indicated that most of these markers are constituents of genes associated with plant stress tolerance and adaptability. Therefore, the SNP markers identified can be effectively used in regional winter wheat breeding projects for facilitating plant adaptation and stress resistance.

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

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

Genome-Wide Characterization and Sequence Polymorphism Analyses of Glycine max Fibrillin (FBN) Revealed Its Role in Response to Drought Condition

The fibrillin (FBN) gene family is widely distributed in all photosynthetic organisms. Members of this gene family are involved in plant growth and development and their response to various biotic and abiotic stress factors. In this study, 16 members of FBN were identified in Glycine max and characterized by using different bioinformatics tools. Phylogenetic analysis classified FBN genes into seven groups. The presence of stress-related cis-elements in the upstream region of GmFBN highlighted their role in tolerance against abiotic stresses. To further decipher the function, physiochemical properties, conserved motifs, chromosomal localization, subcellular localization, and cis-acting regulatory elements were also analyzed. Gene expression analysis based on FPKM values revealed that GmFBNs greatly enhanced soybean drought tolerance and controlled the expression of several genes involved in drought response, except for GmFBN-4, GmFBN-5, GmFBN-6, GmFBN-7 and GmFBN-9. For high throughput genotyping, an SNP-based CAPS marker was also developed for the GmFBN-15 gene. The CAPS marker differentiated soybean genotypes based on the presence of either the GmFBN-15-G or GmFBN-15-A alleles in the CDS region. Association analysis showed that G. max accessions containing the GmFBN-15-A allele at the respective locus showed higher thousand seed weight compared to accessions containing the GmFBN-15-G allele. This research has provided the basic information to further decipher the function of FBN in soybean.

Genetic Analysis of Potato Breeding Collection Using Single-Nucleotide Polymorphism (SNP) Markers

The autotetraploid potato (Solanum tuberosum L.) is an important crop in China, and it is widely cultivated from Northeast China to South China. Thousands of varieties are bred by breeding institutions or companies, and distinguishing the different varieties based on morphological characteristics is difficult. Using DNA fingerprints is an efficient method to identify varieties that plays an increasingly important role in germplasm identification and property rights protection. In this study, the genetic diversity and population structure of 135 autotetraploid potatoes were evaluated using specific-locus amplified fragment sequencing (SLAF-seq) methods. A total of 3,397,137 high-quality single-nucleotide polymorphisms (SNPs), which were distributed across 12 chromosomes, were obtained. Principal component analysis (PCA), neighbour-joining genetic trees, and model-based structure analysis showed that these autotetraploid potato subpopulations, classified by their SNPs, were not consistent with their geographical origins. On the basis of the obtained 3,397,137 SNPs, 160 perfect SNPs were selected, and 71 SNPs were successfully converted to penta-primer amplification refractory mutation (PARMS-SNP) markers. Additionally, 190 autotetraploid potato varieties were analysed using these 71 PARMS-SNP markers. The PCA results show that the accessions were not completely classified on the basis of their geographical origins. The SNP DNA fingerprints of the 190 autotetraploid potato varieties were also constructed. The SNP fingerprint results show that both synonyms and homonyms were present amongst the 190 autotetraploid potatoes. Above all, these novel SNP markers can lay a good foundation for the analysis of potato genetic diversity, DUS (distinctness, uniformity, and stability) testing, and plant variety protection.

Modeling plant diseases under climate change: evolutionary perspectives

Infectious plant diseases are a major threat to global agricultural productivity, economic development, and ecological integrity. There is widespread concern that these social and natural disasters caused by infectious plant diseases may escalate with climate change and computer modeling offers a unique opportunity to address this concern. Here, we analyze the intrinsic problems associated with current modeling strategies and highlight the need to integrate evolutionary principles into polytrophic, eco-evolutionary frameworks to improve predictions. We particularly discuss how evolutionary shifts in functional trade-offs, relative adaptability between plants and pathogens, ecosystems, and climate preferences induced by climate change may feedback to future plant disease epidemics and how technological advances can facilitate the generation and integration of this relevant knowledge for better modeling predictions.

Development of SNP marker panels for genotyping by target sequencing (GBTS) and its application in soybean

A high-throughput genotyping platform with customized flexibility, high genotyping accuracy, and low cost is critical for marker-assisted selection and genetic mapping in soybean. Three assay panels were selected from the SoySNP50K, 40K, 20K, and 10K arrays, containing 41,541, 20,748, and 9670 SNP markers, respectively, for genotyping by target sequencing (GBTS). Fifteen representative accessions were used to assess the accuracy and consistency of the SNP alleles identified by the SNP panels and sequencing platform. The SNP alleles were 99.87% identical between technical replicates and 98.86% identical between the 40K SNP GBTS panel and 10× resequencing analysis. The GBTS method was also accurate in the sense that the genotypic dataset of the 15 representative accessions correctly revealed the pedigree of the accessions, and the biparental progeny datasets correctly constructed the linkage maps of the SNPs. The 10K panel was also used to genotype two parent-derived populations and analyze QTLs controlling 100-seed weight, resulting in the identification of the stable associated genetic locus Locus_OSW_06 on chromosome 06. The markers flanking the QTL explained 7.05% and 9.83% of the phenotypic variation, respectively. Compared with GBS and DNA chips, the 40K, 20K, and 10K panels reduced costs by 5.07% and 58.28%, 21.44% and 65.48%, and 35.74% and 71.76%, respectively. Low-cost genotyping panels could facilitate soybean germplasm assessment, genetic linkage map construction, QTL identification, and genomic selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01372-6.

Pyramiding of Multiple Genes to Improve Rice Blast Resistance of Photo-Thermo Sensitive Male Sterile Line, without Yield Penalty in Hybrid Rice Production

Rice blast caused by pathogenic fungus Magnaporthe oryzae is one of the most serious diseases in rice. The pyramiding of effective resistance genes into rice varieties is a potential approach to reduce the damage of blast disease. In this study, combinations of three resistance genes, Pigm, Pi48 and Pi49, were introduced into a thermo-sensitive genic male sterile (PTGMS) line Chuang5S through marker-assisted selection. The results showed that the blast resistance of improved lines increased significantly compared with Chuang5S, and the three gene pyramiding lines (Pigm + Pi48 + Pi49) had higher rice blast resistance level than monogenic line and digenic lines (Pigm +Pi48, Pigm + Pi49). The genetic backgrounds of the improved lines were highly similar (>90%) to the recurrent parent Chuang5S by using the RICE10K SNP chip. In addition, agronomic traits evaluation also showed pyramiding lines with two or three genes similar to Chuang5S. The yields of the hybrids developed from improved PTGMS lines and Chuang5S are not significantly different. The newly developed PTGMS lines can be practically used for the breeding of parental lines and hybrid varieties with broad spectrum blast resistance.

Homozygosity mapping identified loci and candidate genes responsible for freezing tolerance in Camelina sativa

Homozygosity mapping is an effective tool for detecting genomic regions responsible for a given trait when the phenotype is controlled by a limited number of dominant or co-dominant loci. Freezing tolerance is a major attribute in agricultural crops such as camelina. Previous studies indicated that freezing tolerance differences between a tolerant (Joelle) and susceptible (CO46) variety of camelina were controlled by a small number of dominant or co-dominant genes. We performed whole genome homozygosity mapping to identify markers and candidate genes responsible for freezing tolerance difference between these two genotypes. A total of 28 F3 RILs were sequenced to ∼30× coverage, and parental lines were sequenced to >30-40× coverage with Pacific Biosciences high fidelity technology and 60× coverage using Illumina whole genome sequencing. Overall, about 126k homozygous single nucleotide polymorphism markers were identified that differentiate both parents. Moreover, 617 markers were also homozygous in F3 families fixed for freezing tolerance/susceptibility. All these markers mapped to two contigs forming a contiguous stretch of chromosome 11. The homozygosity mapping detected 9 homozygous blocks among the selected markers and 22 candidate genes with strong similarity to regions in or near the homozygous blocks. Two such genes were differentially expressed during cold acclimation in camelina. The largest block contained a cold-regulated plant thionin and a putative rotamase cyclophilin 2 gene previously associated with freezing resistance in arabidopsis (Arabidopsis thaliana). The second largest block contains several cysteine-rich RLK genes and a cold-regulated receptor serine/threonine kinase gene. We hypothesize that one or more of these genes may be primarily responsible for freezing tolerance differences in camelina varieties.

A prolific and robust whole-genome genotyping method using PCR amplification via primer-template mismatched annealing

Whole-genome genotyping methods are important for breeding. However, it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species. In our study, we accidently discovered that in adapter ligation-mediated PCR, the amplification by primer-template mismatched annealing (PTMA) along the genome could generate thousands of stable PCR products. Based on this observation, we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing (FBI-seq) using one specific primer, in which foreground genotyping is performed by primer-template perfect annealing (PTPA), while background genotyping employs PTMA. Unlike DNA arrays, multiple PCR, or genome target enrichments, FBI-seq requires little preliminary work for primer design and synthesis, and it is easily adaptable to different foreground genes and species. FBI-seq therefore provides a prolific, robust, and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the post-genomics era.

Innovative Advances in Plant Genotyping

Over the past decade, advances in plant genotyping have been critical in enabling the identification of genetic diversity, in understanding evolution, and in dissecting important traits in both crops and native plants. The widespread popularity of single-nucleotide polymorphisms (SNPs) has prompted significant improvements to SNP-based genotyping, including SNP arrays, genotyping by sequencing, and whole-genome resequencing. More recent approaches, including genotyping structural variants, utilizing pangenomes to capture species-wide genetic diversity and exploiting machine learning to analyze genotypic data sets, are pushing the boundaries of what plant genotyping can offer. In this chapter, we highlight these innovations and discuss how they will accelerate and advance future genotyping efforts.