Transcriptome-Enabled Network Inference Revealed the GmCOL1 Feed-Forward Loop and Its Roles in Photoperiodic Flowering of Soybean

Clarifying the Temporal Dynamics of the Circadian Clock and Flowering Gene Network Using Overexpression and Targeted Mutagenesis of Soybean EARLY FLOWERING 3-1 ( GmELF3-1 )

With progressing climate fluctuations, an understanding of the molecular mechanisms of crop plants that regulate their flowering responses to environments is crucial. To achieve this goal, we aimed at clarifying the gene regulatory networks among the circadian clock and flowering genes in soybean ( Glycine max ). Based on our network inference approach , we hypothesize that GmELF3-1 , one of the Evening Complex (EC) gene homologs in soybean's circadian clock, may have an integrative role in transcriptional regulation of the circadian clock and flowering gene network. In this study, we verify GmELF3-1 ' s regulatory roles in its potential downstream genes by modulating the activity of GmELF3-1 using overexpression and CRISPR-Cas9 in soybean protoplasts. Our results indicate that GmELF3-1 may control the expression of the PRR genes in the circadian clock and the flowering gene GmCOL1a .

Systematic characterization of photoperiodic gene expression patterns reveals diverse seasonal transcriptional systems in Arabidopsis

Photoperiod is an annual cue measured by biological systems to align growth and reproduction with the seasons. In plants, photoperiodic flowering has been intensively studied for over 100 years, but we lack a complete picture of the transcriptional networks and cellular processes that are photoperiodic. We performed a transcriptomics experiment on Arabidopsis plants grown in 3 different photoperiods and found that thousands of genes show photoperiodic alteration in gene expression. Gene clustering, daily expression integral calculations, and cis-element analysis then separate photoperiodic genes into co-expression subgroups that display 19 diverse seasonal expression patterns, opening the possibility that many photoperiod measurement systems work in parallel in Arabidopsis. Then, functional enrichment analysis predicts co-expression of important cellular pathways. To test these predictions, we generated a comprehensive catalog of genes in the phenylpropanoid biosynthesis pathway, overlaid gene expression data, and demonstrated that photoperiod intersects with 2 major phenylpropanoid pathways differentially, controlling flavonoids but not lignin. Finally, we describe the development of a new app that visualizes photoperiod transcriptomic data for the wider community.

Molecular breeding for improvement of photothermal adaptability in soybean

Soybean (Glycine max (L.) Merr.) is a typical short-day and temperate crop that is sensitive to photoperiod and temperature. Responses of soybean to photothermal conditions determine plant growth and development, which affect its architecture, yield formation, and capacity for geographic adaptation. Flowering time, maturity, and other traits associated with photothermal adaptability are controlled by multiple major-effect and minor-effect genes and genotype-by-environment interactions. Genetic studies have identified at least 11 loci (E1-E4, E6-E11, and J) that participate in photoperiodic regulation of flowering time and maturity in soybean. Molecular cloning and characterization of major-effect flowering genes have clarified the photoperiod-dependent flowering pathway, in which the photoreceptor gene phytochrome A, circadian evening complex (EC) components, central flowering repressor E1, and FLOWERING LOCUS T family genes play key roles in regulation of flowering time, maturity, and adaptability to photothermal conditions. Here, we provide an overview of recent progress in genetic and molecular analysis of traits associated with photothermal adaptability, summarizing advances in molecular breeding practices and tools for improving these traits. Furthermore, we discuss methods for breeding soybean varieties with better adaptability to specific ecological regions, with emphasis on a novel strategy, the Potalaization model, which allows breeding of widely adapted soybean varieties through the use of multiple molecular tools in existing elite widely adapted varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01406-z.

Origin, variation, and selection of natural alleles controlling flowering and adaptation in wild and cultivated soybean

Soybean (Glycine max) is an economically important crop worldwide, serving as a major source of oil and protein for human consumption and animal feed. Cultivated soybean was domesticated from wild soybean (Glycine soja) which both species are highly sensitive to photoperiod and can grow over a wide geographical range. The extensive ecological adaptation of wild and cultivated soybean has been facilitated by a series of genes represented as quantitative trait loci (QTLs) that control photoperiodic flowering and maturation. Here, we review the molecular and genetic basis underlying the regulation of photoperiodic flowering in soybean. Soybean has experienced both natural and artificial selection during adaptation to different latitudes, resulting in differential molecular and evolutionary mechanisms between wild and cultivated soybean. The in-depth study of natural and artificial selection for the photoperiodic adaptability of wild and cultivated soybean provides an important theoretical and practical basis for enhancing soybean adaptability and yield via molecular breeding. In addition, we discuss the possible origin of wild soybean, current challenges, and future research directions in this important topic.

Photoperiod controls plant seed size in a CONSTANS-dependent manner

Photoperiodic plants perceive changes in day length as seasonal cues to orchestrate their vegetative and reproductive growth. Although it is known that the floral transition of photoperiod-sensitive plants is tightly controlled by day length, how photoperiod affects their post-flowering development remains to be clearly defined, as do the underlying mechanisms. Here we demonstrate that photoperiod plays a prominent role in seed development. We found that long-day (LD) and short-day (SD) plants produce larger seeds under LD and SD conditions, respectively; however, seed size remains unchanged when CONSTANS (CO), the central regulatory gene of the photoperiodic response pathway, is mutated in Arabidopsis and soybean. We further found that CO directly represses the transcription of AP2 (a known regulatory gene of seed development) under LD conditions in Arabidopsis and SD conditions in soybean, thereby controlling seed size in a photoperiod-dependent manner, and that these effects are exerted through regulation of the proliferation of seed coat epidermal cells. Collectively, our findings reveal that a crucial regulatory cascade involving CO-AP2 modulates photoperiod-mediated seed development in plants and provide new insights into how plants with different photoperiod response types perceive seasonal changes that enable them to optimize their reproductive growth.

Current overview on the genetic basis of key genes involved in soybean domestication

Modern crops were created through the domestication and genetic introgression of wild relatives and adaptive differentiation in new environments. Identifying the domestication-related genes and unveiling their molecular diversity provide clues for understanding how the domesticated variants were selected by ancient people, elucidating how and where these crops were domesticated. Molecular genetics and genomics have explored some domestication-related genes in soybean (Glycine max). Here, we summarize recent studies about the quantitative trait locus (QTL) and genes involved in the domestication traits, introduce the functions of these genes, clarify which alleles of domesticated genes were selected during domestication. A deeper understanding of soybean domestication could help to break the bottleneck of modern breeding by highlighting unused genetic diversity not selected in the original domestication process, as well as highlighting promising new avenues for the identification and research of important agronomic traits among different crop species.

Candidate Genes Modulating Reproductive Timing in Elite US Soybean Lines Identified in Soybean Alleles of Arabidopsis Flowering Orthologs With Divergent Latitude Distribution

Adaptation of soybean cultivars to the photoperiod in which they are grown is critical for optimizing plant yield. However, despite its importance, only the major loci conferring variation in flowering time and maturity of US soybean have been isolated. By contrast, over 200 genes contributing to floral induction in the model organism Arabidopsis thaliana have been described. In this work, putative alleles of a library of soybean orthologs of these Arabidopsis flowering genes were tested for their latitudinal distribution among elite US soybean lines developed in the United States. Furthermore, variants comprising the alleles of genes with significant differences in latitudinal distribution were assessed for amino acid conservation across disparate genera to infer their impact on gene function. From these efforts, several candidate genes from various biological pathways were identified that are likely being exploited toward adaptation of US soybean to various maturity groups.

CONSTANS Polymorphism Modulates Flowering Time and Maturity in Soybean

CONSTANS (CO) plays a critical role in the photoperiodic flowering pathway. However, the function of soybean CO orthologs and the molecular mechanisms in regulating flowering remain largely unknown. This study characterized the natural variations in CO family genes and their association with flowering time and maturity in soybeans. A total of 21 soybean CO family genes (GmCOLs) were cloned and sequenced in 128 varieties covering 14 known maturity groups (MG 0000-MG X from earliest to latest maturity). Regarding the whole genomic region involving these genes, GmCOL1, GmCOL3, GmCOL8, GmCOL9, GmCOL10, and GmCOL13 were conserved, and the remaining 15 genes showed genetic variation that was brought about by mutation, namely, all single-nucleotide polymorphisms (SNPs) and insertions-deletions (InDels). In addition, a few genes showed some strong linkage disequilibrium. Point mutations were found in 15 GmCOL genes, which can lead to changes in the potential protein structure. Early flowering and maturation were related to eight genes (GmCOL1/3/4/8/13/15/16/19). For flowering and maturation, 11 genes (GmCOL2/5/6/14/20/22/23/24/25/26/28) expressed divergent physiognomy. Haplotype analysis indicated that the haplotypes of GmCOL5-Hap2, GmCOL13-Hap2/3, and GmCOL28-Hap2 were associated with flowering dates and soybean maturity. This study helps address the role of GmCOL family genes in adapting to diverse environments, particularly when it is necessary to regulate soybean flowering dates and maturity.

Genetic control and allele variation among soybean maturity groups 000 through IX

Soybean [Glycinemax (L.) Merr.] maturity determines the growing region of a given soybean variety and is a primary factor in yield and other agronomic traits. The objectives of this research were to identify the quantitative trait loci (QTL) associated with maturity groups (MGs) and determine the genetic control of soybean maturity in each MG. Using data from 16,879 soybean accessions, genome-wide association (GWA) analyses were conducted for each paired MG and across MGs 000 through IX. Genome-wide association analyses were also performed using 184 genotypes (MGs V-IX) with days to flowering (DTF) and maturity (DTM) collected in the field. A total of 58 QTL were identified to be significantly associated with MGs in individual GWAs, which included 12 reported maturity loci and two stem termination genes. Genome-wide associations across MGs 000-IX detected a total of 103 QTL and confirmed 54 QTL identified in the individual GWAs. Of significant loci identified, qMG-5.2 had effects on the highest number (9) of MGs, followed by E2, E3, Dt2, qMG-15.5, E1, qMG-13.1, qMG-7.1, and qMG-16.1, which affected five to seven MGs. A high number of genetic loci (8-25) that affected MGs 0-V were observed. Stem termination genes Dt1 and Dt2 mainly had significant allele variation in MGs II-V. Genome-wide associations for DTF, DTM, and reproductive period (RP) in the diversity panel confirmed 15 QTL, of which seven were observed in MGs V-IX. The results generated can help soybean breeders manipulate the maturity loci for genetic improvement of soybean yield.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

Molecular mechanisms for the photoperiodic regulation of flowering in soybean

Photoperiodic flowering is one of the most important factors affecting regional adaptation and yield in soybean (Glycine max). Plant adaptation to long-day conditions at higher latitudes requires early flowering and a reduction or loss of photoperiod sensitivity; adaptation to short-day conditions at lower latitudes involves delayed flowering, which prolongs vegetative growth for maximum yield potential. Due to the influence of numerous major loci and quantitative trait loci (QTLs), soybean has broad adaptability across latitudes. Forward genetic approaches have uncovered the molecular basis for several of these major maturity genes and QTLs. Moreover, the molecular characterization of orthologs of Arabidopsis thaliana flowering genes has enriched our understanding of the photoperiodic flowering pathway in soybean. Building on early insights into the importance of the photoreceptor phytochrome A, several circadian clock components have been integrated into the genetic network controlling flowering in soybean: E1, a repressor of FLOWERING LOCUS T orthologs, plays a central role in this network. Here, we provide an overview of recent progress in elucidating photoperiodic flowering in soybean, how it contributes to our fundamental understanding of flowering time control, and how this information could be used for molecular design and breeding of high-yielding soybean cultivars.

Coordinative regulation of plants growth and development by light and circadian clock

The circadian clock, known as an endogenous timekeeping system, can integrate various cues to regulate plant physiological functions for adapting to the changing environment and thus ensure optimal plant growth. The synchronization of internal clock with external environmental information needs a process termed entrainment, and light is one of the predominant entraining signals for the plant circadian clock. Photoreceptors can detect and transmit light information to the clock core oscillator through transcriptional or post-transcriptional interactions with core-clock components to sustain circadian rhythms and regulate a myriad of downstream responses, including photomorphogenesis and photoperiodic flowering which are key links in the process of growth and development. Here we summarize the current understanding of the molecular network of the circadian clock and how light information is integrated into the circadian system, especially focus on how the circadian clock and light signals coordinately regulate the common downstream outputs. We discuss the functions of the clock and light signals in regulating photoperiodic flowering among various crop species.

The Synchronized Efforts to Decipher the Molecular Basis for Soybean Maturity Loci E1, E2, and E3 That Regulate Flowering and Maturity

The general concept of photoperiodism, i.e., the photoperiodic induction of flowering, was established by Garner and Allard (1920). The genetic factor controlling flowering time, maturity, or photoperiodic responses was observed in soybean soon after the discovery of the photoperiodism. E1, E2, and E3 were named in 1971 and, thereafter, genetically characterized. At the centennial celebration of the discovery of photoperiodism in soybean, we recount our endeavors to successfully decipher the molecular bases for the major maturity loci E1, E2, and E3 in soybean. Through systematic efforts, we successfully cloned the E3 gene in 2009, the E2 gene in 2011, and the E1 gene in 2012. Recently, successful identification of several circadian-related genes such as PRR3a, LUX, and J has enriched the known major E1-FTs pathway. Further research progresses on the identification of new flowering and maturity-related genes as well as coordinated regulation between flowering genes will enable us to understand profoundly flowering gene network and determinants of latitudinal adaptation in soybean.

Dynamical Modeling of the Core Gene Network Controlling Transition to Flowering in Pisum sativum

Transition to flowering is an important stage of plant development. Many regulatory modules that control floral transition are conservative across plants. This process is best studied for the model plant Arabidopsis thaliana. The homologues of Arabidopsis genes responsible for the flowering initiation in legumes have been identified, and available data on their expression provide a good basis for gene network modeling. In this study, we developed several dynamical models of a gene network controlling transition to flowering in pea (Pisum sativum) using two different approaches. We used differential equations for modeling a previously proposed gene regulation scheme of floral initiation in pea and tested possible alternative hypothesis about some regulations. As the second approach, we applied neural networks to infer interactions between genes in the network directly from gene expression data. All models were verified on previously published experimental data on the dynamic expression of the main genes in the wild type and in three mutant genotypes. Based on modeling results, we made conclusions about the functionality of the previously proposed interactions in the gene network and about the influence of different growing conditions on the network architecture. It was shown that regulation of the PIM, FTa1, and FTc genes in pea does not correspond to the previously proposed hypotheses. The modeling suggests that short- and long-day growing conditions are characterized by different gene network architectures. Overall, the results obtained can be used to plan new experiments and create more accurate models to study the flowering initiation in pea and, in a broader context, in legumes.

From graph topology to ODE models for gene regulatory networks

A gene regulatory network can be described at a high level by a directed graph with signed edges, and at a more detailed level by a system of ordinary differential equations (ODEs). The former qualitatively models the causal regulatory interactions between ordered pairs of genes, while the latter quantitatively models the time-varying concentrations of mRNA and proteins. This paper clarifies the connection between the two types of models. We propose a property, called the constant sign property, for a general class of ODE models. The constant sign property characterizes the set of conditions (system parameters, external signals, or internal states) under which an ODE model is consistent with a signed, directed graph. If the constant sign property for an ODE model holds globally for all conditions, then the ODE model has a single signed, directed graph. If the constant sign property for an ODE model only holds locally, which may be more typical, then the ODE model corresponds to different graphs under different sets of conditions. In addition, two versions of constant sign property are given and a relationship between them is proved. As an example, the ODE models that capture the effect of cis-regulatory elements involving protein complex binding, based on the model in the GeneNetWeaver source code, are described in detail and shown to satisfy the global constant sign property with a unique consistent gene regulatory graph. Even a single gene regulatory graph is shown to have many ODE models of GeneNetWeaver type consistent with it due to combinatorial complexity and continuous parameters. Finally the question of how closely data generated by one ODE model can be fit by another ODE model is explored. It is observed that the fit is better if the two models come from the same graph.