Enhancement of plant cold tolerance by soybean RCC1 family gene GmTCF1a

Genome-wide characterization of regulator of chromosome condensation 1 (RCC1) gene family in Artemisia annua L. revealed a conservation evolutionary pattern

BACKGROUND

Artemisia annua is the major source for artemisinin production. The artemisinin content in A. annua is affected by different types of light especially the UV light. UVR8, a member of RCC1 gene family was found to be the UV-B receptor in plants. The gene structures, evolutionary history and expression profile of UVR8 or RCC1 genes remain undiscovered in A. annua.

RESULTS

Twenty-two RCC1 genes (AaRCC1) were identified in each haplotype genome of two diploid strains of A. annua, LQ-9 and HAN1. Varied gene structures and sequences among paralogs were observed. The divergence of most RCC1 genes occurred at 46.7 - 51 MYA which overlapped with species divergence of core Asteraceae during the Eocene, while no recent novel RCC1 members were found in A. annua genome. The number of RCC1 genes remained stable among eudicots and RCC1 genes underwent purifying selection. The expression profile of AaRCC1 is analogous to that of Arabidopsis thaliana (AtRCC1) when responding to environmental stress.

CONCLUSIONS

This study provided a comprehensive characterization of the AaRCC1 gene family and suggested that RCC1 genes were conserved in gene number, structures, constitution of amino acids and expression profiles among eudicots.

Genome-Wide Identification of GmSPS Gene Family in Soybean and Expression Analysis in Response to Cold Stress

Sucrose metabolism plays a critical role in development, stress response, and yield formation of plants. Sucrose phosphate synthase (SPS) is the key rate-limiting enzyme in the sucrose synthesis pathway. To date, genome-wide survey and comprehensive analysis of the SPS gene family in soybean (Glycine max) have yet to be performed. In this study, seven genes encoding SPS were identified in soybean genome. The structural characteristics, phylogenetics, tissue expression patterns, and cold stress response of these GmSPSs were investigated. A comparative phylogenetic analysis of SPS proteins in soybean, Medicago truncatula, Medicago sativa, Lotus japonicus, Arabidopsis, and rice revealed four families. GmSPSs were clustered into three families from A to C, and have undergone five segmental duplication events under purifying selection. All GmSPS genes had various expression patterns in different tissues, and family A members GmSPS13/17 were highly expressed in nodules. Remarkably, all GmSPS promoters contain multiple low-temperature-responsive elements such as potential binding sites of inducer of CBF expression 1 (ICE1), the central regulator in cold response. qRT-PCR proved that these GmSPS genes, especially GmSPS8/18, were induced by cold treatment in soybean leaves, and the expression pattern of GmICE1 under cold treatment was similar to that of GmSPS8/18. Further transient expression analysis in Nicotiana benthamiana and electrophoretic mobility shift assay (EMSA) indicated that GmSPS8 and GmSPS18 transcriptions were directly activated by GmICE1. Taken together, our findings may aid in future efforts to clarify the potential roles of GmSPS genes in response to cold stress in soybean.

Functional annotation of proteins for signaling network inference in non-model species

Molecular biology aims to understand cellular responses and regulatory dynamics in complex biological systems. However, these studies remain challenging in non-model species due to poor functional annotation of regulatory proteins. To overcome this limitation, we develop a multi-layer neural network that determines protein functionality directly from the protein sequence. We annotate kinases and phosphatases in Glycine max. We use the functional annotations from our neural network, Bayesian inference principles, and high resolution phosphoproteomics to infer phosphorylation signaling cascades in soybean exposed to cold, and identify Glyma.10G173000 (TOI5) and Glyma.19G007300 (TOT3) as key temperature regulators. Importantly, the signaling cascade inference does not rely upon known kinase motifs or interaction data, enabling de novo identification of kinase-substrate interactions. Conclusively, our neural network shows generalization and scalability, as such we extend our predictions to Oryza sativa, Zea mays, Sorghum bicolor, and Triticum aestivum. Taken together, we develop a signaling inference approach for non-model species leveraging our predicted kinases and phosphatases.

Early Sowing on Some Soybean Genotypes under Organic Farming Conditions

The demand for soybeans in Europe motivates breeders, researchers, and growers to find suitable cultivars to adapt and extend the soybean crop to improper climate areas. Weed control is a crucial aspect of crop technology in organic agriculture, but particularly for soybean crops. In laboratory conditions, the cumulative stress index for seedlings was determined to identify the susceptible cultivars. A field experiment with 14 soybean accessions and 2 sowing dates was conducted under organic farming conditions over the course of three years, from 2020 to 2022. Plant population density was found to be significantly (p < 0.01 and p < 0.1) negatively correlated to the degree of resistance to low temperature as well as infestation degree with weeds (for p < 0.05 and p < 0.1), with the exception of early sowing in 2021. Yield was significantly (p < 0.05, p < 0.01, p < 0.1) correlated with plant population density, with the exception of optimal sowing in 2022. Early sowing variants emerged with vigor in the first two years, breeding lines and registered varieties showed low input, and organic agriculture systems showed low yields in the drought years of 2020 and 2022. Although early sowing even in the first two years proved to be a practice that increased the cultivars' performance, in 2022, due to the long period of chilling stress in the field, this option had negative effects on yield due to the high weed frequency. Therefore, the early sowing strategy for the soybean crop in this particular case of non-irrigated conditions in a temperate continental area proved to be a risky practice.

Genome-wide identification and expression analysis of the regulator of chromosome condensation 1 gene family in wheat (Triticum aestivum L.)

Wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD) is the world's most widely cultivated crop and an important staple food for humans, accounting for one-fifth of calories consumed. Proteins encoded by the regulator of chromosome condensation 1 (RCC1) are highly conserved among eukaryotes and consist of seven repeated domains that fold into a seven-bladed propeller structure. In this study, a total of 76 RCC1 genes of bread wheat were identified via a genome-wide search, and their phylogenetic relationship, gene structure, protein-conserved domain, chromosome localization, conserved motif, and transcription factor binding sites were systematically analyzed using the bioinformatics approach to indicate the evolutionary and functional features of these genes. The expression patterns of 76 TaRCC1 family genes in wheat under various stresses were further analyzed, and RT-PCR verified that RCC1-3A (TraesCS3A02G362800), RCC1-3B (TraesCS3B02G395200), and RCC1-3D (TraesCS3D02G35650) were significantly induced by salt, cold, and drought stresses. Additionally, the co-expression network analysis and binding site prediction suggested that Myb-7B (TraesCS7B02G188000) and Myb-7D (TraesCS7D02G295400) may bind to the promoter of RCC1-3A/3B and upregulate their expression in response to abiotic stresses in wheat. The results have furthered our understanding of the wheat RCC1 family members and will provide important information for subsequent studies and the use of RCC1 genes in wheat.

Progress and Prospects of the Molecular Basis of Soybean Cold Tolerance

Cold stress is a major factor influencing the geographical distribution of soybean growth and causes immense losses in productivity. Understanding the molecular mechanisms that the soybean has undergone to survive cold temperatures will have immense value in improving soybean cold tolerance. This review focuses on the molecular mechanisms involved in soybean response to cold. We summarized the recent studies on soybean cold-tolerant quantitative trait loci (QTLs), transcription factors, associated cold-regulated (COR) genes, and the regulatory pathways in response to cold stress. Cold-tolerant QTLs were found to be overlapped with the genomic region of maturity loci of E1, E3, E4, pubescence color locus of T, stem growth habit gene locus of Dt1, and leaf shape locus of Ln, indicating that pleiotropic loci may control multiple traits, including cold tolerance. The C-repeat responsive element binding factors (CBFs) are evolutionarily conserved across species. The expression of most GmDREB1s was upregulated by cold stress and overexpression of GmDREB1B;1 in soybean protoplast, and transgenic Arabidopsis plants can increase the expression of genes with the DRE core motif in their promoter regions under cold stress. Other soybean cold-responsive regulators, such as GmMYBJ1, GmNEK1, GmZF1, GmbZIP, GmTCF1a, SCOF-1 and so on, enhance cold tolerance by regulating the expression of COR genes in transgenic Arabidopsis. CBF-dependent and CBF-independent pathways are cross-talking and work together to activate cold stress gene expression. Even though it requires further dissection for precise understanding, the function of soybean cold-responsive transcription factors and associated COR genes studied in Arabidopsis shed light on the molecular mechanism of cold responses in soybeans and other crops. Furthermore, the findings may also provide practical applications for breeding cold-tolerant soybean varieties in high-latitude and high-altitude regions.

An advanced systems biology framework of feature engineering for cold tolerance genes discovery from integrated omics and non-omics data in soybean

Soybean is sensitive to low temperatures during the crop growing season. An urgent demand for breeding cold-tolerant cultivars to alleviate the production loss is apparent to cope with this scenario. Cold-tolerant trait is a complex and quantitative trait controlled by multiple genes, environmental factors, and their interaction. In this study, we proposed an advanced systems biology framework of feature engineering for the discovery of cold tolerance genes (CTgenes) from integrated omics and non-omics (OnO) data in soybean. An integrative pipeline was introduced for feature selection and feature extraction from different layers in the integrated OnO data using data ensemble methods and the non-parameter random forest prioritization to minimize uncertainties and false positives for accuracy improvement of results. In total, 44, 143, and 45 CTgenes were identified in short-, mid-, and long-term cold treatment, respectively, from the corresponding gene-pool. These CTgenes outperformed the remaining genes, the random genes, and the other candidate genes identified by other approaches in an independent RNA-seq database. Furthermore, we applied pathway enrichment and crosstalk network analyses to uncover relevant physiological pathways with the discovery of underlying cold tolerance in hormone- and defense-related modules. Our CTgenes were validated by using 55 SNP genotype data of 56 soybean samples in cold tolerance experiments. This suggests that the CTgenes identified from our proposed systematic framework can effectively distinguish cold-resistant and cold-sensitive lines. It is an important advancement in the soybean cold-stress response. The proposed pipelines provide an alternative solution to biomarker discovery, module discovery, and sample classification underlying a particular trait in plants in a robust and efficient way.

SaRCC1, a Regulator of Chromosome Condensation 1 (RCC1) Family Protein Gene from Spartina alterniflora, Negatively Regulates Salinity Stress Tolerance in Transgenic Arabidopsis

A regulator of chromosome condensation 1 (RCC1) family protein has been functionally characterized to be involved in various cellular processes. In this study, one RCC1 gene named SaRCC1 was cloned from the full-length cDNA library of Spartinaalterniflora. The open reading frame (ORF) of SaRCC1 was 1440 bp, and it encoded 479 amino acids with a calculated molecular mass of 51.65 kDa. Multiple amino acid sequence alignments showed that SaRCC1 had high identity with other plant RCC1s, and the phylogenetic analysis indicated that SaRCC1 had a closer affinity to Zea mays RCC1 family protein (ZmRCC1). SaRCC1 gene was induced under salt stress conditions, and its encoded protein was located in peroxisome. In order to further investigate the function of SaRCC1, transgenic Arabidopsis plants ectopically both sense-overexpressing and antisense-overexpressing SaRCC1 were generated. SaRCC1-overexpressing lines exhibited an increased salt and ABA hypersensitivity and reduced resistance to salinity stress. On the other hand, the transcripts of some stress-responsive genes in the SaRCC1 transgenic plants were affected in response to salinity stress. Our results provide evidence for the involvement of SaRCC1, negatively regulating salt stress responses by affecting stress-related gene expression in Arabidopsis.

Low Temperature Stress Tolerance: An Insight Into the Omics Approaches for Legume Crops

The change in climatic conditions is the major cause for decline in crop production worldwide. Decreasing crop productivity will further lead to increase in global hunger rate. Climate change results in environmental stress which has negative impact on plant-like deficiencies in growth, crop yield, permanent damage, or death if the plant remains in the stress conditions for prolonged period. Cold stress is one of the main abiotic stresses which have already affected the global crop production. Cold stress adversely affects the plants leading to necrosis, chlorosis, and growth retardation. Various physiological, biochemical, and molecular responses under cold stress have revealed that the cold resistance is more complex than perceived which involves multiple pathways. Like other crops, legumes are also affected by cold stress and therefore, an effective technique to mitigate cold-mediated damage is critical for long-term legume production. Earlier, crop improvement for any stress was challenging for scientific community as conventional breeding approaches like inter-specific or inter-generic hybridization had limited success in crop improvement. The availability of genome sequence, transcriptome, and proteome data provides in-depth sight into different complex mechanisms under cold stress. Identification of QTLs, genes, and proteins responsible for cold stress tolerance will help in improving or developing stress-tolerant legume crop. Cold stress can alter gene expression which further leads to increases in stress protecting metabolites to cope up the plant against the temperature fluctuations. Moreover, genetic engineering can help in development of new cold stress-tolerant varieties of legume crop. This paper provides a general insight into the "omics" approaches for cold stress in legume crops.