Genome assembly of the JD17 soybean provides a new reference genome for comparative genomics

Chromosome-level genome assembly of a high-yield Chinese soybean variety Mengdou1137 unlocks genetic potential of disease and lodging resistance

KEY MESSAGE

We assembled the genome of Mengdou1137 with high quality and revealed the specific disease resistance genes and a large number of genomic variations related to agronomic traits. As a cornerstone in the global agricultural landscape, soybean stands as a pivotal oilseed crop, underpinning both nutritional and industrial applications. The burgeoning development of novel soybean varieties significantly propels the crop's industrialization, offering enhanced traits that cater to diverse agricultural and commercial needs. In this study, we present the de novo assembly of the genome a high-yield Chinese soybean variety Mengdou1137, employing an integrated approach of both long-read and short-read sequencing technologies to achieve comprehensive genomic insights. Achieving a notable assembly with a genome size of 999.99 Mb, our work features a contig N50 of 14.92 Mb and a scaffold N50 of 50.26 Mb, successfully anchoring 98.24% of sequences across the 20 chromosomes. Through meticulous comparative analysis with existing soybean genomes, our research unveiled 115 Mengdou1137-specific disease resistance genes alongside a substantial array of agronomical trait-associated genomic variants. Among the salient genomic features, we identified a favorable haplotype of the dwarf gene PH13, a critical determinant of plant stature, underscoring its potential for breeding compact soybean varieties with lodging resistance. This high-quality assembly of the Mengdou1137 genome not only enriches the repository of soybean genetic resources but also paves the way for future innovations in soybean breeding and trait improvement, offering valuable insights for the enhancement of this crucial agricultural commodity.

Soybean2035: A decadal vision for soybean functional genomics and breeding

Soybean, the fourth most important crop in the world, uniquely serves as a source of both plant oil and plant protein for the world's food and animal feed. Although soybean production has increased approximately 13-fold over the past 60 years, the continually growing global population necessitates further increases in soybean production. In the past, especially in the last decade, significant progress has been made in both functional genomics and molecular breeding. However, many more challenges should be overcome to meet the anticipated future demand. Here, we summarize past achievements in the areas of soybean omics, functional genomics, and molecular breeding. Furthermore, we analyze trends in these areas, including shortages and challenges, and propose new directions, potential approaches, and possible outputs toward 2035. Our views and perspectives provide insight into accelerating the development of elite soybean varieties to meet the increasing demands of soybean production.

Genome-Wide Association Study on Imputed Genotypes of 180 Eurasian Soybean Glycine max Varieties for Oil and Protein Contents in Seeds

Soybean (Glycine max) is a leguminous plant with a broad range of applications, particularly in agriculture and food production, where its seed composition-especially oil and protein content-is highly valued. Improving these traits is a primary focus of soybean breeding programs. In this study, we conducted a genome-wide association study (GWAS) to identify genetic loci linked to oil and protein content in seeds, using imputed genotype data for 180 Eurasian soybean varieties and the novel "genotypic twins" approach. This dataset encompassed 87 Russian and European cultivars and 93 breeding lines from Western Siberia. We identified 11 novel loci significantly associated with oil and protein content in seeds (p-value < 1.5 × 10-6), including one locus on chromosome 11 linked to protein content and 10 loci associated with oil content (chromosomes 1, 5, 11, 16, 17, and 18). The protein-associated locus is located near a gene encoding a CBL-interacting protein kinase, which is involved in key biological processes, including stress response mechanisms such as drought and osmotic stress. The oil-associated loci were linked to genes with diverse functions, including lipid transport, nutrient reservoir activity, and stress responses, such as Sec14p-like phosphatidylinositol transfer proteins and Germin-like proteins. These findings suggest that the loci identified not only influence oil and protein content but may also contribute to plant resilience under environmental stress conditions. The data obtained from this study provide valuable genetic markers that can be used in breeding programs to optimize oil and protein content, particularly in varieties adapted to Russian climates, and contribute to the development of high-yielding, nutritionally enhanced soybean cultivars.

Chromosome-specific barcode system with centromeric repeat in cultivated soybean and wild progenitor

Wild soybean Glycine soja is the progenitor of cultivated soybean Glycine max Information on soybean functional centromeres is limited despite extensive genome analysis. These species are an ideal model for studying centromere dynamics for domestication and breeding. We performed a detailed chromatin immunoprecipitation analysis using centromere-specific histone H3 protein to delineate two distinct centromeric DNA sequences with unusual repeating units with monomer sizes of 90-92 bp (CentGm-1) and 413-bp (CentGm-4) shorter and longer than standard nucleosomes. These two unrelated DNA sequences with no sequence similarity are part of functional centromeres in both species. Our results provide a comparison of centromere properties between a cultivated and a wild species under the effect of the same kinetochore protein. Possible sequence homogenization specific to each chromosome could highlight the mechanism for evolutionary conservation of centromeric properties independent of domestication and breeding. Moreover, a unique barcode system to track each chromosome is developed using CentGm-4 units. Our results with a unifying centromere composition model using CentGm-1 and CentGm-4 superfamilies could have far-reaching implications for comparative and evolutionary genome research.

A stepwise guide for pangenome development in crop plants: an alfalfa (Medicago sativa) case study

BACKGROUND

The concept of pangenomics and the importance of structural variants is gaining recognition within the plant genomics community. Due to advancements in sequencing and computational technology, it has become feasible to sequence the entire genome of numerous individuals of a single species at a reasonable cost. Pangenomes have been constructed for many major diploid crops, including rice, maize, soybean, sorghum, pearl millet, peas, sunflower, grapes, and mustards. However, pangenomes for polyploid species are relatively scarce and are available in only few crops including wheat, cotton, rapeseed, and potatoes.

MAIN BODY

In this review, we explore the various methods used in crop pangenome development, discussing the challenges and implications of these techniques based on insights from published pangenome studies. We offer a systematic guide and discuss the tools available for constructing a pangenome and conducting downstream analyses. Alfalfa, a highly heterozygous, cross pollinated and autotetraploid forage crop species, is used as an example to discuss the concerns and challenges offered by polyploid crop species. We conducted a comparative analysis using linear and graph-based methods by constructing an alfalfa graph pangenome using three publicly available genome assemblies. To illustrate the intricacies captured by pangenome graphs for a complex crop genome, we used five different gene sequences and aligned them against the three graph-based pangenomes. The comparison of the three graph pangenome methods reveals notable variations in the genomic variation captured by each pipeline.

CONCLUSION

Pangenome resources are proving invaluable by offering insights into core and dispensable genes, novel gene discovery, and genome-wide patterns of variation. Developing user-friendly online portals for linear pangenome visualization has made these resources accessible to the broader scientific and breeding community. However, challenges remain with graph-based pangenomes including compatibility with other tools, extraction of sequence for regions of interest, and visualization of genetic variation captured in pangenome graphs. These issues necessitate further refinement of tools and pipelines to effectively address the complexities of polyploid, highly heterozygous, and cross-pollinated species.

High-quality genome of a modern soybean cultivar and resequencing of 547 accessions provide insights into the role of structural variation

Soybean provides protein, oil and multiple health-related compounds. Understanding the effects of structural variations (SVs) on economic traits in modern breeding is important for soybean improvement. Here we assembled the high-quality genome of modern cultivar Nongdadou2 (NDD2) and identified 25,814 SV-gene pairs compared to 29 reported genomes, with 13 NDD2-private SVs validated in 547 deep-resequencing (average = 18.05-fold) accessions, which advances our understanding of genomic variation biology. We found some insertions/deletions involved in seed protein and weight formation, an inversion related to adaptation to drought and a large intertranslocation implicated in a key divergence event in soybean. Of 749,714 SVs from 547 accessions, 6,013 were significantly associated with 22 yield-related and seed-quality-related traits determined in ten location × year environments. We uncovered 1,761 associated SVs that hit genes or regulatory regions, with 12 in GmMQT influencing oil and isoflavone contents. Our work provides resources and insights into SV roles in soybean improvement.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset

BACKGROUND

Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable.

RESULTS

Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq).

CONCLUSIONS

This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

Regulation of seed traits in soybean

Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.

Understandings and future challenges in soybean functional genomics and molecular breeding

Soybean (Glycine max) is a major source of plant protein and oil. Soybean breeding has benefited from advances in functional genomics. In particular, the release of soybean reference genomes has advanced our understanding of soybean adaptation to soil nutrient deficiencies, the molecular mechanism of symbiotic nitrogen (N) fixation, biotic and abiotic stress tolerance, and the roles of flowering time in regional adaptation, plant architecture, and seed yield and quality. Nevertheless, many challenges remain for soybean functional genomics and molecular breeding, mainly related to improving grain yield through high-density planting, maize-soybean intercropping, taking advantage of wild resources, utilization of heterosis, genomic prediction and selection breeding, and precise breeding through genome editing. This review summarizes the current progress in soybean functional genomics and directs future challenges for molecular breeding of soybean.

Full-Length Transcriptome Sequencing Reveals Alternative Splicing and lncRNA Regulation during Nodule Development in Glycine max

Alternative splicing (AS) is a ubiquitous phenomenon among eukaryotic intron-containing genes, which greatly contributes to transcriptome and proteome diversity. Here we performed the isoform sequencing (Iso-Seq) of soybean underground tissues inoculated and uninoculated with Rhizobium and obtained 200,681 full-length transcripts covering 26,183 gene loci. It was found that 80.78% of the multi-exon loci produced more than one splicing variant. Comprehensive analysis of these identified 7874 differentially splicing events with highly diverse splicing patterns during nodule development, especially in defense and transport-related processes. We further profiled genes with differential isoform usage and revealed that 2008 multi-isoform loci underwent stage-specific or simultaneous major isoform switches after Rhizobium inoculation, indicating that AS is a vital way to regulate nodule development. Moreover, we took the lead in identifying 1563 high-confidence long non-coding RNAs (lncRNAs) in soybean, and 157 of them are differentially expressed during nodule development. Therefore, our study uncovers the landscape of AS during the soybean-Rhizobium interaction and provides systematic transcriptomic data for future study of multiple novel directions in soybean.