Plant pan-genomics and its applications

Evolutionary insights into the organization of chromatin structure and landscape of transcriptional regulation in plants

Development of complex traits necessitates the functioning and coordination of intricate regulatory networks involving multiple genes. Understanding 3D chromatin structure can facilitate insight into the regulation of gene expression by regulatory elements. This potential, of visualizing the role of chromatin organization in the evolution and function of regulatory elements, remains largely unexplored. Here, we describe new perspectives that arise from the dual considerations of sequence variation of regulatory elements and chromatin structure, with a special focus on whole-genome doubling or polyploidy. We underscore the significance of hierarchical chromatin organization in gene regulation during evolution. In addition, we describe strategies for exploring chromatin organization in future investigations of regulatory evolution in plants, enabling insights into the evolutionary influence of regulatory elements on gene expression and, hence, phenotypes.

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein-protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Identification of allelic relationship and translocation region among chromosomal translocation lines that leads to less-seed watermelon

Less-seed and seedless traits are desirable characteristics in watermelon (Citrullus lanatus). Hybridization between watermelon chromosomal translocated lines and wild lines significantly reduced seed counts in the hybrid fruits, approaching even seedless. However, the allelic relationships and the chromosomal translocation breakpoints from different sources are unclear, which limits their utility in breeding practices. This study focused on three groups of chromosomal translocation materials from different sources and conducted inheritance and allelic relationship analysis of translocation points. The results from third-generation genome sequencing and fluorescence in situ hybridization (FISH) revealed that the specific translocations in the naturally mutated material MT-a involved reciprocal translocations between Chr6 and Chr10. The Co60γ radiation-induced mutant material MT-b involved reciprocal translocations between Chr1 and Chr5, Chr4 and Chr8. The Co60γ radiation-induced mutant material MT-c involved complex translocations among Chr1, Chr5, and Chr11. Cytological observation showed that heterozygous translocation hybrids showed chromosomal synapsis abnormalities during meiotic diakinesis. Further, dominant and codominant molecular markers were developed on both sides of the translocation breakpoints, which could facilitate rapid and efficient identification of chromosome translocation lines. This study provides technical guidance for utilizing chromosomal translocation materials in the development of less-seed watermelon varieties.

HEMU: An integrated comparative genomics database and analysis platform for Andropogoneae grasses

This study reports an online database and analysis platform HEMU, which integrates 75 genome assemblies from 20 unique species, large amounts of multi-omics data, and six sophisticated analysis toolkits. HEMU will facilitate comparative genomics analysis within the tribe Andropogoneae.

Technology-enabled great leap in deciphering plant genomes

Plant genomes provide essential and vital basic resources for studying many aspects of plant biology and applications (for example, breeding). From 2000 to 2020, 1,144 genomes of 782 plant species were sequenced. In the past three years (2021-2023), 2,373 genomes of 1,031 plant species, including 793 newly sequenced species, have been assembled, representing a great leap. The 2,373 newly assembled genomes, of which 63 are telomere-to-telomere assemblies and 921 have been generated in pan-genome projects, cover the major phylogenetic clades. Substantial advances in read length, throughput, accuracy and cost-effectiveness have notably simplified the achievement of high-quality assemblies. Moreover, the development of multiple software tools using different algorithms offers the opportunity to generate more complete and complex assemblies. A database named N3: plants, genomes, technologies has been developed to accommodate the metadata associated with the 3,517 genomes that have been sequenced from 1,575 plant species since 2000. We also provide an outlook for emerging opportunities in plant genome sequencing.

Engineering the future cereal crops with big biological data: toward an intelligence-driven breeding by design

How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality.

Functional genomics of Brassica napus: Progresses, challenges, and perspectives

Brassica napus, commonly known as rapeseed or canola, is a major oil crop contributing over 13% to the stable supply of edible vegetable oil worldwide. Identification and understanding the gene functions in the B. napus genome is crucial for genomic breeding. A group of genes controlling agronomic traits have been successfully cloned through functional genomics studies in B. napus. In this review, we present an overview of the progress made in the functional genomics of B. napus, including the availability of germplasm resources, omics databases and cloned functional genes. Based on the current progress, we also highlight the main challenges and perspectives in this field. The advances in the functional genomics of B. napus contribute to a better understanding of the genetic basis underlying the complex agronomic traits in B. napus and will expedite the breeding of high quality, high resistance and high yield in B. napus varieties.

Gapless genome assembly and epigenetic profiles reveal gene regulation of whole-genome triplication in lettuce

BACKGROUND

Lettuce, an important member of the Asteraceae family, is a globally cultivated cash vegetable crop. With a highly complex genome (∼2.5 Gb; 2n = 18) rich in repeat sequences, current lettuce reference genomes exhibit thousands of gaps, impeding a comprehensive understanding of the lettuce genome.

FINDINGS

Here, we present a near-complete gapless reference genome for cutting lettuce with high transformability, using long-read PacBio HiFi and Nanopore sequencing data. In comparison to stem lettuce genome, we identify 127,681 structural variations (SVs, present in 0.41 Gb of sequence), reflecting the divergence of leafy and stem lettuce. Interestingly, these SVs are related to transposons and DNA methylation states. Furthermore, we identify 4,612 whole-genome triplication genes exhibiting high expression levels associated with low DNA methylation levels and high N6-methyladenosine RNA modifications. DNA methylation changes are also associated with activation of genes involved in callus formation.

CONCLUSIONS

Our gapless lettuce genome assembly, an unprecedented achievement in the Asteraceae family, establishes a solid foundation for functional genomics, epigenomics, and crop breeding and sheds new light on understanding the complexity of gene regulation associated with the dynamics of DNA and RNA epigenetics in genome evolution.

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

Selection of Flax Genotypes for Pan-Genomic Studies by Sequencing Tagmentation-Based Transcriptome Libraries

Flax (Linum usitatissimum L.) products are used in the food, pharmaceutical, textile, polymer, medical, and other industries. The creation of a pan-genome will be an important advance in flax research and breeding. The selection of flax genotypes that sufficiently cover the species diversity is a crucial step for the pan-genomic study. For this purpose, we have adapted a method based on Illumina sequencing of transcriptome libraries prepared using the Tn5 transposase (tagmentase). This approach reduces the cost of sample preparation compared to commercial kits and allows the generation of a large number of cDNA libraries in a short time. RNA-seq data were obtained for 192 flax plants (3-6 individual plants from 44 flax accessions of different morphology and geographical origin). Evaluation of the genetic relationship between flax plants based on the sequencing data revealed incorrect species identification for five accessions. Therefore, these accessions were excluded from the sample set for the pan-genomic study. For the remaining samples, typical genotypes were selected to provide the most comprehensive genetic diversity of flax for pan-genome construction. Thus, high-throughput sequencing of tagmentation-based transcriptome libraries showed high efficiency in assessing the genetic relationship of flax samples and allowed us to select genotypes for the flax pan-genomic analysis.

Application of Multi-Perspectives in Tea Breeding and the Main Directions

Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant-microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.

Pan-genome for pearl millet that beats the heat

A better understanding of crop genomes reveals that structural variations (SVs) are crucial for genetic improvement. A graph-based pan-genome by Yan et al. uncovered 424 085 genomic SVs and provided novel insights into heat tolerance of pearl millet. We discuss how these SVs can fast-track pearl millet breeding under harsh environments.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

Combination of Hairy Root and Whole-Plant Transformation Protocols to Achieve Efficient CRISPR/Cas9 Genome Editing in Soybean

The new gene-editing technology CRISPR/Cas system has been widely used for genome engineering in various organisms. Since the CRISPR/Cas gene-editing system has a certain possibility of low efficiency and the whole plant transformation of soybean is time-consuming and laborious, it is important to evaluate the editing efficiency of designed CRISPR constructs before the stable whole plant transformation process starts. Here, we provide a modified protocol for generating transgenic hairy soybean roots to assess the efficiency of guide RNA (gRNA) sequences of the CRISPR/Cas constructs within 14 days. The cost- and space-effective protocol was first tested in transgenic soybean harboring the GUS reporter gene for the efficiency of different gRNA sequences. Targeted DNA mutations were detected in 71.43-97.62% of the transgenic hairy roots analyzed as evident by GUS staining and DNA sequencing of the target region. Among the four designed gene-editing sites, the highest editing efficiency occurred at the 3' terminal of the GUS gene. In addition to the reporter gene, the protocol was tested for the gene-editing of 26 soybean genes. Among the gRNAs selected for stable transformation, the editing efficiency of hairy root transformation and stable transformation ranged from 5% to 88.8% and 2.7% to 80%, respectively. The editing efficiencies of stable transformation were positively correlated with those of hairy root transformation with a Pearson correlation coefficient (r) of 0.83. Our results demonstrated that soybean hairy root transformation could rapidly assess the efficiency of designed gRNA sequences on genome editing. This method can not only be directly applied to the functional study of root-specific genes, but more importantly, it can be applied to the pre-screening of gRNA in CRISPR/Cas gene editing.