Biology subjects

Batley, J.

Publications and source records attributed to Batley, J..

18 recordsLinked to original sources

bioRxiv2026

Unsupervised Clustering Enables Cohort-Specific Variant Recalibration in Crops

Genomic selection (GS) and trait discovery in crops require reliable marker datasets, yet variant discovery remains constrained by the lack of standardised, high-confidence reference resources. Publicly available plant genomic resources are often based on outdated reference genomes, heterogenous pipelines, and generic variant hard-filtering thresholds derived from human studies. Consequently, implementation of the Genome Analysis Toolkit (GATK) Best Practices framework, including machine learning-based variant quality score recalibration (VQSR), remains challenging in crop genomes. Here, we present a crop-adapted framework for unsupervised variant quality assessment and VQSR enabling advanced SNP and insertion-deletion (INDEL) discovery without predefined high-confidence reference variant sets. Using Brassica napus as a model, we use the Illumina 60k Brassica SNP array to generate a reference-specific truth set for data pre-processing and independent evaluation of an unsupervised machine-learning approach for constructing cohort-specific VQSR resources. Gaussian mixture model (GMM)-based clustering of multidimensional variant annotation profiles identifies high-, intermediate-, and low-quality variant classes, providing flexible training resources for VQSR without requiring labelled training data. We further validate the framework in diploid Brassica oleracea and hexaploid wheat (Triticum aestivum) across cohorts differing in population size, genetic diversity, and genome architecture. Despite population- and species-specific differences in variant annotation profiles, GMM-based clustering consistently identifies informative variant quality classes and enables cohort-specific recalibration of both SNPs and INDELs. Our results demonstrate that unsupervised machine learning can extend GATK Best Practices to crop species lacking comprehensive genomic resources, providing a scalable approach for generating high-quality variant datasets for crop genomics and downstream breeding applications.

plant biology↗

bioRxiv2026

Capturing the missing gene content of elite wheat by analysis of wheat landraces

There is a need to breed superior wheat cultivars to meet increasing global food demand. However, modern cultivars have undergone a substantial loss of genetic diversity due to intensive breeding. A pool of genetic diversity remains untapped in wheat landraces, and pangenomics can help identify genes of potential agronomic importance in these old lines that can be applied to accelerate wheat improvement. Here, we have constructed the largest wheat pangenome to date, representing 1,061 diverse individuals (827 landraces and 234 modern cultivars) from 47 countries across six continents. We identified 10,426 predicted gene models specific to landraces that are enriched for functions associated with disease resistance, abiotic stress adaptation, and symbiosis. Our results reveal that landraces harbour an extensive repertoire of genes that are absent from modern wheat cultivars and provide a foundational resource for the systematic reintroduction of adaptive variation to enhance wheat resilience and sustainability in the face of climate change.

plant biology↗

bioRxiv2025

Genome sequence of Talaromyces trachyspermus, a biocontrol fungus isolated from broomrape

Applying antimicrobial compounds derived from microorganisms for plant disease management is one of the objectives of sustainable agriculture. The genus Talaromyces is known for its species ability to produce a diverse group of antimicrobial compounds. For example, T. trachyspermus has been reported to produce secondary metabolites, cell wall-degrading enzymes, and plant growth-promoting factors. Identification of novel promising metabolites and enzymes from T. trachyspermus is still in its infancy. Also, there is a lack of information about the genomic resources for its secondary metabolites and hydrolytic enzymes. Therefore, this study aimed to analyse the genome of a biocontrol isolate of this species to investigate its biocontrol mechanisms at the genomic level, focusing on secondary metabolites and cell wall degrading enzymes. The whole genome of T. trachyspermus isolate IRAN 3054C, obtained from necrotic Orobanch ramosa stems in Iran with biocontrol ability, was sequenced using the Illumina platform. We performed both de novo and resequencing analyses of the genome, obtaining a 31.3 Mb assembly. The abundance of protein groups associated with biocontrol activities was assessed in the studied genome. Fungismash was used to detect and annotate secondary metabolites. The analysis revealed the presence of several secondary metabolite biosynthesis gene clusters (BGCs), with a high frequency of polyketide synthases (T1PKS) and nonribosomal peptide synthetases (NRPS), which are known to produce bioactive compounds with antimicrobial properties. Among the identified secondary metabolites, Fusarin, YWA1, Dimethylcoprogen, and Squalestatin S1 exhibited the highest similarity to known compounds. Furthermore, sequences similar to Phyllostictine A/B and Cornexistin indicate potential herbicidal properties. The genome also had domains for enzymes involved in phosphate solubilisation, siderophore production, and fungal cell wall degradation, which are essential for biocontrol and plant growth promotion. Our findings highlight the genomic richness of T. trachyspermus IRAN 3054C for biocontrol. Further metabolomics studies are needed to validate the actual production of these secondary metabolites and explore their functional roles in biocontrol.

genomics↗

bioRxiv2023

Karyotype instability varies by species and genotype combination in allohexaploid Brassica

Synthetic Brassica allohexaploids (2n = AABBCC) do not exist naturally but can be produced between six different parent species combinations, and can be used to investigate processes of polyploid formation and genome stabilization. In this study, we investigated hybridization potential, accumulation and frequency of copy number variants (CNVs), fertility, and karyotype stability in advanced generations of diverse allohexaploid genotypes belonging to different Brassica allohexaploid species combinations (NCJ types: B. napus x B. carinata x B. juncea; junleracea types: B. juncea x B. oleracea; naponigra types: B. napus x B. nigra; and carirapa types: B. rapa x B. carinata). Only 3.2% of allohexaploid plants investigated were euploids, with high frequencies of rearrangements. Significant differences between genotypes and between lineages within parent genotype combinations were found for frequencies of euploids and rearrangements, with one NCJ line showing relatively high karyotype stability. Hybridization between different allohexaploids was mostly achievable, with 0 - 4.6 seeds per flower bud on average, and with strong effects of maternal genotype. Novel hybrids between allohexaploid lineages showed similar fertility and stability to their parents. In the novel hybrid population, a significant correlation was observed between the inheritance of A-genome chromosome fragments (relative to C-genome fragments) and the total number of seeds produced per plant (r = 0.24). Our results suggest that synthetic Brassica allohexaploids can develop genomic stability, but that this occurs at very low frequencies, and may not always be under selective pressure due to the unpredictable relationship between fertility and genome composition in these hybrid types. Article SummaryBrassica plants with three sets of chromosomes (allohexaploids) do not exist in nature, but can be made from combinations between six different species. Here, we compared different combinations to see which are the most genomically stable and fertile, and found major differences between all allohexaploid types as well as one putatively stable line. Crosses between allohexaploid types could also be achieved in most cases, although hybrids were not more stable or fertile than their parents.

genetics↗

bioRxiv2023

Local haplotype visualization for trait association analysis with crosshap

SummaryGWAS excels at harnessing dense genomic variant datasets to identify candidate regions responsible for producing a given phenotype. However, GWAS and traditional fine-mapping methods do not provide insight into the complex local landscape of linkage that contains and has been shaped by the causal variant(s). Here, we present crosshap, an R package that performs robust density-based clustering of variants based on their linkage profiles to capture haplotype structures in a local genomic region of interest. Following this, crosshap is equipped with visualization tools for choosing optimal clustering parameters ({varepsilon}) before producing an intuitive figure that provides an overview of the complex relationships between linked variants, haplotype combinations, phenotypic traits and metadata. Availability and implementationThe crosshap package is freely available under the MIT license and can be downloaded directly from CRAN with R>4.0.0. The development version is available on GitHub alongside issue support (https://github.com/jacobimarsh/crosshap). Tutorial vignettes and documentation are available (https://jacobimarsh.github.io/crosshap/).

bioinformatics↗

bioRxiv2023

Genetic basis of expression and splicing underlying spike architecture in wheat (Triticum aestivum L.)

IntroductionWheat is one of the most important staple crops worldwide, and an important source of human protein and mineral element intake. Continuously increasing stable production of wheat is critical for global food security under the challenge of population growth and limited resource input. ObjectiveSpike architecture determines the potential grain yield of wheat. However, the mechanisms of transcriptional regulation of spike architecture in wheat remain largely unknown, limiting further genetic improvement of wheat yield. In this study we explored the genetic basis of spike architecture in wheat. MethodsPopulation RNA-seq methods were used to identify the eQTLs and sQTLs associated with spike architecture and applied this to dissection of the genetic basis of gene expression and splicing controlling these complex yield-related traits. ResultsIn total, 4,143 expression quantitative trait loci (eQTLs) and 12,933 splice QTLs (sQTLs) were identified in wheat based on 178 RNA-seq samples, revealing 774 cis-eQTLs and 321 cis-sQTLs for 86 eGenes and 73 sGenes, respectively. Integration of eQTLs and sQTLs with genome-wide association study (GWAS) identified dozens of additional novel candidate genes that may contribute to spike-related traits. Gene network analysis showed that eQTLs and sQTLs were widely involved in the co-expression modules that regulate wheat spike architecture. Notably, the eQTL locus AX-108754757 regulated the expression of 5 eGenes that negatively controled grain number per spike. AX-111592099 regulated both the splicing and expression of TraesCS7B02G442100, encoding an E3 ubiquitin ligase, and playing a central role in regulating spike length. ConclusionThis study provides new insights into the genetic basis of spike architecture. This improved understanding of spike-related traits in wheat will contribute to more rapid genetic improvement.

plant biology↗

bioRxiv2022

Not all pathways are the same - unique adaptations to submerged environments emerge from comparative seagrass genomics

Seagrasses are an ecologically important group of plants that have returned to the sea from terrestrial ancestors on at least three occasions (Cymodoceaceae, Posidoniaceae, Zosteraceae). Seagrass-specific genomic adaptations to marine life are known from the Zosteraceae. However, independent lineages may have devised different solutions to life underwater. Here, we present two new genome assemblies from endemic Australian seagrasses, Amphibolis antarctica (Cymodoceaceae) and Posidonia australis (Posidoniaceae). We found large differences in genome size between Amphibolis and Posidonia driven by repeat expansion in Posidonia. We show that parts of ethylene pathways known to be lost in Zosteraceae are partially retained in older seagrass lineages (Cymodoceaeceae and Posidoniaceae). We describe adaptations within salinity, disease resistance, cell wall, and photosynthesis-related pathways not shared with other seagrasses. These findings provide insight into the impact of recolonising marine environments on formerly terrestrial plant genomes, with some adaptations previously thought to be universal to marine living not having occurred in A. antarctica and P. australis.

plant biology↗

bioRxiv2022

Wheat Panache - a pangenome graph database representing presence/absence variation across 16 bread wheat genomes

Bread wheat is one of humanitys most important staple crops, characterized by a large and complex genome with a high level of gene presence/absence variation between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate due to the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess presence/absence variation between bread wheat genomes. Database URL: http://www.appliedbioinformatics.com.au/wheat_panache

bioinformatics↗

bioRxiv2022

DNABERT-based explainable lncRNA identification in plant genome assemblies

Long non-coding ribonucleic acids (lncRNAs) have been shown to play an important role in plant gene regulation, involving both epigenetic and transcript regulation. LncRNAs are transcripts longer than 200 nucleotides that are not translated into functional proteins but can be translated into small peptides. Machine learning models have predominantly used transcriptome data with manually defined features to detect lncRNAs, however, they often underrepresent the abundance of lncRNAs and can be biased in their detection. Here we present a study using Natural Language Processing (NLP) models to identify plant lncRNAs from genomic sequences rather than transcriptomic data. The NLP models were trained to predict lncRNAs for seven model and crop species (Zea mays, Arabidopsis thaliana, Brassica napus, Brassica oleracea, Brassica rapa, Glycine max and Oryza sativa) using publicly available genomic references. We demonstrated that lncRNAs can be accurately predicted from genomic sequences with the highest accuracy of 83.4% for Z. mays and the lowest accuracy of 57.9% for B. rapa, revealing that genome assembly quality might affect the accuracy of lncRNA identification. Furthermore, we demonstrated the potential of using NLP models for cross-species prediction with an average of 63.1% accuracy using target species not previously seen by the model. As more species are incorporated into the training datasets, we expect the accuracy to increase, becoming a more reliable tool for uncovering novel lncRNAs. Finally, we show that the models can be interpreted using explainable artificial intelligence to identify motifs important to lncRNA prediction and that these motifs frequently flanked the lncRNA sequence. HighlightsO_LIWe demonstrate for the first time the identification of lncRNAs from genomic sequences, instead of transcriptome sequences, allowing the identification of lowly expressed lncRNAs. C_LIO_LIA deep learning model (natural language processing) was employed to predict lncRNAs in two monocot and five dicot plant species. C_LIO_LIWe used explainable machine learning to extract the genomic motifs associated with lncRNA identification and highlighted potentially conserved structures. C_LI

bioinformatics↗

bioRxiv2021

Brassica napus genes Rlm4 and Rlm7, conferring resistance to Leptosphaeria maculans, are alleles of the Rlm9 wall-associated kinase-like resistance locus

Brassica napus (canola/rapeseed) race specific resistance genes against blackleg disease, caused by the ascomycete fungus Leptosphaeria maculans, have been commonly used in canola breeding. To date; LepR3, Rlm2 and Rlm9 R genes against L. maculans have been cloned from B. napus. LepR3 and Rlm2 are Receptor Like Proteins (RLP) and the recently reported Rlm9 is a Wall Associated Kinase-Like (WAKL) protein. Rlm9 located on chromosome A07 is closely linked with Rlm3, Rlm4, RLm7 genes. Recognition of AvrLm5-9 and AvrLm3 by their corresponding Rlm9 and Rlm3 proteins is masked in the presence of AvrLm4-7. Here we report cloning of Rlm4 and Rlm7 by generating genome sequence of the doubled haploid (DH) B. napus cv Topas DH16516 introgression lines Topas-Rlm4 and Topas-Rlm7. Candidate Rlm4 and Rlm7 genes were identified form the genome sequence and gene structures were determined by mapping RNA-sequence reads, generated from infected cotyledon tissues, to the genome of Topas-Rlm4 and Topas-Rlm7. Rlm4 and Rlm7 genomic constructs with their native promoters were transferred into the blackleg susceptible B. napus cv Westar N-o-1. Complementation of resistance response in the transgenic Westar:Rlm4 and Westar:Rlm7 that were inoculated with L. maculans transgenic isolates 2367:AvrRlm4-7 or 2367:AvrLm7 confirmed the function of Rlm4 and Rlm7 genes. Wild type L. maculans isolate 2367 that does not contain AvrLm4-7 or AvrLm7, and transgenic 2367:AvrLm3 and 2367:AvrLm5-9 did not induce resistance proving the specificity of Rlm4 and Rlm7 response. Rlm4 and Rlm7 alleles are also allelic to Rlm9. Rlm4 and Rlm7 genes encode WAKL proteins. Comparison of highly homologous sequences of Rlm4 and Rlm7 with each other and with the sequence of additional alleles, using whole genome sequencing of additional 128 lines, identified a limited number of point mutation located within the predicted extracellular receptor domains.

plant biology↗

bioRxiv2021

Yield is negatively correlated with nucleotide-binding leucine-rich repeat gene content in soybean

The availability of increasing quantities of crop pangenome data permits the detailed association of gene content with agronomic traits. Here, we investigate disease resistance gene content of diverse soybean cultivars and report a significant negative correlation between the number of NLR resistance (R) genes and yield. We find no association between R-genes with seed weight, oil or protein content, and we find no correlation between yield and the number of RLK, RLP genes, or the total number of genes. These results suggest that recent yield improvement in soybean may be partially associated with the selective loss of NLR genes. Three quarters of soybean NLR genes do not show presence/absence variation, limiting the ability to select for their absence, and so the deletion or disabling of select NLR genes may support future yield improvement.

plant biology↗

bioRxiv2021

Allele segregation analysis of F1 hybrids between independent Brassica allohexaploid lineages

In the Brassica genus we find both diploid species (one genome) and allotetraploid species (two different genomes) but no naturally occurring hexaploid species (three different genomes, AABBCC). Although hexaploids can be produced via human intervention, these neo- polyploids have quite unstable genomes and usually suffer from severe genome reshuffling. Whether these genome rearrangements continue in later generations and whether genomic arrangements follow similar, reproducible patterns between different lines is still unknown. We crossed Brassica hexaploids resulting from different species combinations to produce five F1 hybrids, and analyzed the karyotypes of the parents and the F1 hybrids, as well as allele segregation in a resulting test-cross population via molecular karyotyping using SNP array genotyping. Although some genomic regions were found to be more likely to be duplicated, deleted or rearranged, a consensus pattern was not shared between genotypes. Brassica hexaploids had a high tolerance for fixed structural rearrangements, but which rearrangements occur and become fixed over many generations does not seem to show either strong reproducibility or to indicate selection for stability. On average, we observed 10 de novo chromosome rearrangements contributed almost equally from both parents to the F1 hybrids. At the same time, the F1 hybrid meiosis produced on average 8.6 new rearrangements. Hence, the increased heterozygosity in the F1 hybrid did not significantly improve genome stability in our hexaploid hybrids, and might have had the opposite effect. However, hybridization between lineages was readily achieved and may be exploited for future genetics and breeding purposes.

genetics↗

bioRxiv2021

Haplotype mapping uncovers unexplored variation in wild and domesticated soybean at the major protein locus cqProt-003

Here, we present association and linkage analysis of 985 wild, landrace and cultivar soybean accessions in a pan genomic dataset to characterize the major high-protein/low-oil associated locus cqProt-003 located on chromosome 20. A significant trait associated region within a 173 kb linkage block was identified and variants in the region were characterised, identifying 34 high confidence SNPs, 4 insertions, 1 deletion and a larger 304 bp structural variant in the high-protein haplotype. Trinucleotide tandem repeats of variable length present in the third exon of gene 20G085100 are strongly correlated with the high-protein phenotype and likely represent causal variation. Structural variation has previously been found in the same gene, for which we report the global distribution of the 304bp deletion and have identified additional nested variation present in high-protein individuals. Mapping variation at the cqProt-003 locus across demographic groups suggests that the high-protein haplotype is common in wild accessions (94.7%), rare in landraces (10.6%) and near absent in cultivated breeding pools (4.1%), suggesting its decrease in frequency primarily correlates with domestication and continued during subsequent improvement. However, the variation that has persisted in under-utilized wild and landrace populations holds high breeding potential for breeders willing to forego seed oil to maximise protein content. The results of this study include the identification of distinct haplotype structures within the high-protein population, and a broad characterization of the genomic context and linkage patterns of cqProt-003 across global populations, supporting future functional characterisation and modification. Key messageThe major soy protein QTL, cqProt-003, was analysed for haplotype diversity and global distribution, results indicate 304bp deletion and variable tandem repeats in protein coding regions are likely causal candidates.

plant biology↗

bioRxiv2021

Genomic rearrangements have consequences for introgression breeding as revealed by genome assemblies of wild and cultivated lentil species

Understanding the genomic relationship between wild and cultivated genomes would facilitate access to the untapped variability found in crop wild relatives. We developed genome assemblies of a cultivated lentil (Lens culinaris) as well as a wild relative (L. ervoides). Comparative analyses revealed large-scale structural rearrangements and additional repetitive DNA in the cultivated genome, resulting in regions of reduced recombination, segregation distortion and permanent heterozygosity in the offspring of a cross between the two species. These novel findings provide plant breeders with better insight into how best to approach accessing the novel variability available in wild relatives.

plant biology↗

bioRxiv2020

Two independent approaches converge to the cloning of a new Leptosphaeria maculans avirulence effector gene, AvrLmS-Lep2

Leptosphaeria maculans, the causal agent of blackleg disease, interacts with Brassica napus (oilseed rape, canola) in a gene-for-gene manner. The avirulence genes AvrLmS and AvrLep2 were described to be perceived by the resistance genes RlmS and LepR2, respectively, present in the cultivar Surpass 400. Here we report cloning of AvrLmS and AvrLep2 using two independent methods. AvrLmS was cloned using combined in vitro crossing between avirulent and virulent isolates with sequencing of DNA bulks from avirulent or virulent progeny (Bulked-Segregant-Sequencing) to rapidly identify one candidate avirulence gene present in the effector repertoire of L. maculans. AvrLep2 was cloned using a bi-parental cross of avirulent and virulent L. maculans isolates and a classical map-based cloning approach. Taking these two approaches independently, we found that AvrLmS and AvrLep2 are the same gene. Complementation of virulent isolates with this gene confirmed its role in inducing resistance on Surpass 400 and Topas-LepR2. The gene renamed AvrLmS-Lep2 encodes for a small cysteine-rich protein of unknown function with an N-terminal secretory signal peptide, which are common features of the majority of effectors from extracellular fungal plant pathogens. The AvrLmS-Lep2 / LepR2 interaction phenotype was found to vary from a typical hypersensitive response to intermediate resistance sometimes at the edge of, or evolving toward, susceptibility depending on the inoculation conditions. AvrLmS-Lep2 was nevertheless sufficient to significantly reduce the stem lesion size on plant genotypes with LepR2, indicating the potential efficiency of this resistance to control the disease in the field.

molecular biology↗

bioRxiv2020

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

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. 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 3,605.70 cM and compromising 14,630 single nucleotide polymorphisms (SNPs) was constructed. A quantitative trail locus (QTL) on chromosome C2 was detected in the vicinity of flowering time genes including FT and FLC. 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.Competing Interest StatementBASF supported this work and employs SR.View Full Text

plant biology↗

bioRxiv2020

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Recent advances in long-read sequencing have the potential to produce more complete genome assemblies using sequence reads which can span repetitive regions. However, overlap based assembly methods routinely used for this data require significant computing time and resources. Here, we have developed RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step. During benchmarking, we assembled the wheat Chinese Spring (CS) genome using publicly available PacBio reads in parallel in 168 wall hours on a 250 CPU system. The maximum RAM used was 300 Gb and the computing time was 42,000 CPU hours. The approach opens applications for the assembly of other large and complex genomes with much-reduced computing requirements. The RefKA pipeline is available at https://github.com/AppliedBioinformatics/RefKA

bioinformatics↗

bioRxiv2017

Speed breeding: a powerful tool to accelerate crop research and breeding

The growing human population and a changing environment have raised significant concern for global food security, with the current improvement rate of several important crops inadequate to meet future demand [1]. This slow improvement rate is attributed partly to the long generation times of crop plants. Here we present a method called speed breeding, which greatly shortens generation time and accelerates breeding and research programs. Speed breeding can be used to achieve up to 6 generations per year for spring wheat (Triticum aestivum), durum wheat (T. durum), barley (Hordeum vulgare), chickpea (Cicer arietinum), and pea (Pisum sativum) and 4 generations for canola (Brassica napus), instead of 2-3 under normal glasshouse conditions. We demonstrate that speed breeding in fully-enclosed controlled-environment growth chambers can accelerate plant development for research purposes, including phenotyping of adult plant traits, mutant studies, and transformation. The use of supplemental lighting in a glasshouse environment allows rapid generation cycling through single seed descent and potential for adaptation to larger-scale crop improvement programs. Cost-saving through LED supplemental lighting is also outlined. We envisage great potential for integrating speed breeding with other modern crop breeding technologies, including high-throughput genotyping, genome editing, and genomic selection, accelerating the rate of crop improvement.

plant biology↗