Next-generation bulked segregant analysis for Breeding 4.0

Identification of QTLs and Key Genes Enhancing Lodging Resistance in Soybean Through Chemical and Physical Trait Analysis

Lodging of soybean (Glycine max (L.) Merril.) significantly reduces seed yield and quality, particularly in high-yielding environments. This phenomenon occurs when stems weaken under the weight of the plants, complicating harvesting. This study investigated the relationship between soybean stem chemical composition, physical traits, and lodging resistance to improve yield and resilience. We found that as plant density increased, stem hardness decreased, and the elasticity increased, heightening the risk of lodging. Conversely, high temperature (28 °C) boosted lignin, cellulose and pectin content in the stem cell walls, enhancing the lodging resistance. Additionally, after excluding differences in phylogenetic relationships through cluster analysis, we mapped environment-stable genes linked to lodging resistance and identified new QTLs on Chr3 and Chr16. Candidate genes associated with these QTLs were confirmed using qRT-PCR and hormone treatments across diverse soybean varieties. It was found that the expression of stem tip genes was closely related to stem node diameter. These findings provide a theoretical foundation for breeding high-yielding soybean varieties with improved lodging resistance, and advance efforts to develop resilient soybean cultivars.

A strategy for identification and characterization of genic mutations using a temperature-sensitive chlorotic soybean mutant as an example

Screening a transposon-mutagenized soybean population led to the discovery of a recessively inherited chlorotic phenotype. This "y24" phenotype results in smaller stature, weaker stems, and a smaller root system. Genome sequencing identified 15 candidate genes with mutations likely to result in a loss of function. Amplicon sequencing of a segregating population was then used to narrow the list to a single candidate mutation, a single-base change in Glyma.07G102300 that disrupts splicing of the second intron. Single cell transcriptomic profiling indicates that this gene is expressed primarily in mesophyll cells, and RNA sequencing data indicate that it is upregulated in germinating seedlings by cold stress. Previous studies have shown that mutations to Os05g34040, the rice ortholog of Glyma.07G102300, produced a chlorotic phenotype that was more pronounced in cool temperatures. Growing soybean y24 mutants at lower temperatures also resulted in a more severe phenotype. In addition, transgenic expression of wild-type Glyma.07G102300 in the knockout mutant of the Arabidopsis ortholog At4930720 rescues the chlorotic phenotype, further supporting the hypothesis that the mutation in Glyma.07G102300 is causal of the y24 phenotype. The variant analysis strategy used to identify the genes underlying this phenotype provides a template for the study of other soybean mutants.

Big data and artificial intelligence-aided crop breeding: Progress and prospects

The past decade has witnessed rapid developments in gene discovery, biological big data (BBD), artificial intelligence (AI)-aided technologies, and molecular breeding. These advancements are expected to accelerate crop breeding under the pressure of increasing demands for food. Here, we first summarize current breeding methods and discuss the need for new ways to support breeding efforts. Then, we review how to combine BBD and AI technologies for genetic dissection, exploring functional genes, predicting regulatory elements and functional domains, and phenotypic prediction. Finally, we propose the concept of intelligent precision design breeding (IPDB) driven by AI technology and offer ideas about how to implement IPDB. We hope that IPDB will enhance the predictability, efficiency, and cost of crop breeding compared with current technologies. As an example of IPDB, we explore the possibilities offered by CropGPT, which combines biological techniques, bioinformatics, and breeding art from breeders, and presents an open, shareable, and cooperative breeding system. IPDB provides integrated services and communication platforms for biologists, bioinformatics experts, germplasm resource specialists, breeders, dealers, and farmers, and should be well suited for future breeding.

Genetic mapping of regions associated with root system architecture in rice using MutMap QTL-seq

The root system architecture is an important complex trait in rice. With changing climatic conditions and soil nutrient deficiencies, there is an immediate need to breed nutrient-use-efficient rice varieties with robust root system architectural (RSA) traits. To map the genomic regions associated with crucial component traits of RSA viz. root length and root volume, a biparental F2 mapping population was developed using TI-128, an Ethyl Methane Sulphonate (EMS) mutant of a mega variety BPT-5204 having high root length (RL) and root volume (RV) with wild type BPT-5204. Extreme bulks having high RL and RV and low RL and RV were the whole genome re-sequenced along with parents. Genetic mapping using the MutMap QTL-Seq approach elucidated two genomic intervals on Chr.12 (3.14-3.74 Mb, 18.11-20.85 Mb), and on Chr.2 (23.18-23.68 Mb) as potential regions associated with both RL and RV. The Kompetitive Allele Specific PCR (KASP) assays for SNPs with delta SNP index near 1 were associated with higher RL and RV in the panel of sixty-two genotypes varying in root length and volume. The KASP_SNPs viz. Chr12_S4 (C→T; Chr12:3243938), located in the 3' UTR region of LOC_Os12g06670 encoding a protein kinase domain-containing protein and Chr2_S6 (C→T; Chr2:23181622) present upstream in the regulator of chromosomal condensation protein LOC_Os2g38350. Validation of these genes using qRT-PCR and in-silico studies using various online tools and databases revealed higher expression in TI-128 as compared to BPT- 5204 at the seedling and panicle initiation stages implying the functional role in enhancing RL and RV.

Refining flowering date enhances sesame yield independently of day-length

BACKGROUND

The transition from vegetative to reproductive growth is a key factor in yield maximization. Sesame (Sesamum indicum), an indeterminate short-day oilseed crop, is rapidly being introduced into new cultivation areas. Thus, decoding its flowering mechanism is necessary to facilitate adaptation to environmental conditions. In the current study, we uncover the effect of day-length on flowering and yield components using F2 populations segregating for previously identified quantitative trait loci (Si_DTF QTL) confirming these traits.

RESULTS

Generally, day-length affected all phenotypic traits, with short-day preceding days to flowering and reducing yield components. Interestingly, the average days to flowering required for yield maximization was 50 to 55 days, regardless of day-length. In addition, we found that Si_DTF QTL is more associated with seed-yield and yield components than with days to flowering. A bulk-segregation analysis was applied to identify additional QTL differing in allele frequencies between early and late flowering under both day-length conditions. Candidate genes mining within the identified major QTL intervals revealed two flowering-related genes with different expression levels between the parental lines, indicating their contribution to sesame flowering regulation.

CONCLUSIONS

Our findings demonstrate the essential role of flowering date on yield components and will serve as a basis for future sesame breeding.

The complex transcriptional regulation of heat stress response in maize

As one of the most important food and feed crops worldwide, maize suffers much more tremendous damages under heat stress compared to other plants, which seriously inhibits plant growth and reduces productivity. To mitigate the heat-induced damages and adapt to high temperature environment, plants have evolved a series of molecular mechanisms to sense, respond and adapt high temperatures and heat stress. In this review, we summarized recent advances in molecular regulations underlying high temperature sensing, heat stress response and memory in maize, especially focusing on several important pathways and signals in high temperature sensing, and the complex transcriptional regulation of ZmHSFs (Heat Shock Factors) in heat stress response. In addition, we highlighted interactions between ZmHSFs and several epigenetic regulation factors in coordinately regulating heat stress response and memory. Finally, we laid out strategies to systematically elucidate the regulatory network of maize heat stress response, and discussed approaches for breeding future heat-tolerance maize.

Sugarcane breeding: a fantastic past and promising future driven by technology and methods

Sugarcane is the most important sugar and energy crop in the world. During sugarcane breeding, technology is the requirement and methods are the means. As we know, seed is the cornerstone of the development of the sugarcane industry. Over the past century, with the advancement of technology and the expansion of methods, sugarcane breeding has continued to improve, and sugarcane production has realized a leaping growth, providing a large amount of essential sugar and clean energy for the long-term mankind development, especially in the face of the future threats of world population explosion, reduction of available arable land, and various biotic and abiotic stresses. Moreover, due to narrow genetic foundation, serious varietal degradation, lack of breakthrough varieties, as well as long breeding cycle and low probability of gene polymerization, it is particularly important to realize the leapfrog development of sugarcane breeding by seizing the opportunity for the emerging Breeding 4.0, and making full use of modern biotechnology including but not limited to whole genome selection, transgene, gene editing, and synthetic biology, combined with information technology such as remote sensing and deep learning. In view of this, we focus on sugarcane breeding from the perspective of technology and methods, reviewing the main history, pointing out the current status and challenges, and providing a reasonable outlook on the prospects of smart breeding.

Identification and characterization of a temperature sensitive chlorotic soybean mutant

Screening a transposon-mutagenized soybean population led to the discovery of a recessively inherited chlorotic phenotype. This "vir1" phenotype results in smaller stature, weaker stems, and a smaller root system with smaller nodules. Genome sequencing identified 15 candidate genes with mutations likely to result in a loss of function. Amplicon sequencing of a segregating population was then used to narrow the list to a single candidate mutation, a single-base change in Glyma.07G102300 that disrupts splicing of the second intron. Single cell transcriptomic profiling indicates that this gene is expressed primarily in mesophyll cells and RNA sequencing data indicates it is upregulated in germinating seedlings by cold stress. Previous studies have shown that mutations to Os05g34040, the rice homolog of Glyma.07G102300, produced a chlorotic phenotype that was more pronounced in cool temperatures. Growing soybean vir1 mutants at lower temperatures also resulted in a more severe phenotype. In addition, transgenic expression of wild type Glyma.07G102300 in the knockout mutant of the Arabidopsis homolog At4930720 rescues the chlorotic phenotype, further supporting the hypothesis that the mutation in Glyma.07G102300 is causal of the vir1 phenotype.