Evolutionary Conservation and Divergence of Gene Coexpression Networks in Gossypium (Cotton) Seeds

Comparative transcriptomic analysis provides insights into the genetic networks regulating oil differential production in oil crops

BACKGROUND

Plants differ more than threefold in seed oil contents (SOCs). Soybean (Glycine max), cotton (Gossypium hirsutum), rapeseed (Brassica napus), and sesame (Sesamum indicum) are four important oil crops with markedly different SOCs and fatty acid compositions.

RESULTS

Compared to grain crops like maize and rice, expanded acyl-lipid metabolism genes and relatively higher expression levels of genes involved in seed oil synthesis (SOS) in the oil crops contributed to the oil accumulation in seeds. Here, we conducted comparative transcriptomics on oil crops with two different SOC materials. In common, DIHYDROLIPOAMIDE DEHYDROGENASE, STEAROYL-ACYL CARRIER PROTEIN DESATURASE, PHOSPHOLIPID:DIACYLGLYCEROL ACYLTRANSFERASE, and oil-body protein genes were both differentially expressed between the high- and low-oil materials of each crop. By comparing functional components of SOS networks, we found that the strong correlations between genes in "glycolysis/gluconeogenesis" and "fatty acid synthesis" were conserved in both grain and oil crops, with PYRUVATE KINASE being the common factor affecting starch and lipid accumulation. Network alignment also found a conserved clique among oil crops affecting seed oil accumulation, which has been validated in Arabidopsis. Differently, secondary and protein metabolism affected oil synthesis to different degrees in different crops, and high SOC was due to less competition of the same precursors. The comparison of Arabidopsis mutants and wild type showed that CINNAMYL ALCOHOL DEHYDROGENASE 9, the conserved regulator we identified, was a factor resulting in different relative contents of lignins to oil in seeds. The interconnection of lipids and proteins was common but in different ways among crops, which partly led to differential oil production.

CONCLUSIONS

This study goes beyond the observations made in studies of individual species to provide new insights into which genes and networks may be fundamental to seed oil accumulation from a multispecies perspective.

Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data

BACKGROUND

Understanding the mechanisms underlining forage production and its biomass nutritive quality at the omics level is crucial for boosting the output of high-quality dry matter per unit of land. Despite the advent of multiple omics integration for the study of biological systems in major crops, investigations on forage species are still scarce.

RESULTS

Our results identified substantial changes in gene co-expression and metabolite-metabolite network topologies as a result of genetic perturbation by hybridizing L. perenne with another species within the genus (L. multiflorum) relative to across genera (F. pratensis). However, conserved hub genes and hub metabolomic features were detected between pedigree classes, some of which were highly heritable and displayed one or more significant edges with agronomic traits in a weighted omics-phenotype network. In spite of tagging relevant biological molecules as, for example, the light-induced rice 1 (LIR1), hub features were not necessarily better explanatory variables for omics-assisted prediction than features stochastically sampled and all available regressors.

CONCLUSIONS

The utilization of computational techniques for the reconstruction of co-expression networks facilitates the identification of key omic features that serve as central nodes and demonstrate correlation with the manifestation of observed traits. Our results also indicate a robust association between early multi-omic traits measured in a greenhouse setting and phenotypic traits evaluated under field conditions.

Cotton fiber as a model for understanding shifts in cell development under domestication

Cotton fiber provides the predominant plant textile in the world, and it is also a model for plant cell wall biosynthesis. The development of the single-celled cotton fiber takes place across several overlapping but discrete stages, including fiber initiation, elongation, the transition from elongation to secondary cell wall formation, cell wall thickening, and maturation and cell death. During each stage, the developing fiber undergoes a complex restructuring of genome-wide gene expression change and physiological/biosynthetic processes, which ultimately generate a strikingly elongated and nearly pure cellulose product that forms the basis of the global cotton industry. Here, we provide an overview of this developmental process focusing both on its temporal as well as evolutionary dimensions. We suggest potential avenues for further improvement of cotton as a crop plant.

Genetics, Breeding and Genetic Engineering to Improve Cottonseed Oil and Protein: A Review

Upland cotton (Gossypium hirsutum) is the world's leading fiber crop and one of the most important oilseed crops. Genetic improvement of cotton has primarily focused on fiber yield and quality. However, there is an increased interest and demand for enhanced cottonseed traits, including protein, oil, fatty acids, and amino acids for broad food, feed and biofuel applications. As a byproduct of cotton production, cottonseed is an important source of edible oil in many countries and could also be a vital source of protein for human consumption. The focus of cotton breeding on high yield and better fiber quality has substantially reduced the natural genetic variation available for effective cottonseed quality improvement within Upland cotton. However, genetic variation in cottonseed oil and protein content exists within the genus of Gossypium and cultivated cotton. A plethora of genes and quantitative trait loci (QTLs) (associated with cottonseed oil, fatty acids, protein and amino acids) have been identified, providing important information for genetic improvement of cottonseed quality. Genetic engineering in cotton through RNA interference and insertions of additional genes of other genetic sources, in addition to the more recent development of genome editing technology has achieved considerable progress in altering the relative levels of protein, oil, fatty acid profile, and amino acids composition in cottonseed for enhanced nutritional value and expanded industrial applications. The objective of this review is to summarize and discuss the cottonseed oil biosynthetic pathway and major genes involved, genetic basis of cottonseed oil and protein content, genetic engineering, genome editing through CRISPR/Cas9, and QTLs associated with quantity and quality enhancement of cottonseed oil and protein.

Spatial and Temporal Transcriptomic Heredity and Asymmetry in an Artificially Constructed Allotetraploid Wheat (AADD)

Polyploidy, or whole-genome duplication (WGD), often induces dramatic changes in gene expression due to "transcriptome shock. " However, questions remain about how allopolyploidy (the merging of multiple nuclear genomes in the same nucleus) affects gene expression within and across multiple tissues and developmental stages during the initial foundation of allopolyploid plants. Here, we systematically investigated the immediate effect of allopolyploidy on gene expression variation in an artificial allopolyploidy system consisting of a constructed allotetraploid wheat (AADD genome, accession AT2) and its diploid progenitors Triticum urartu and Aegilops tauschii. We performed comprehensive RNA sequencing of 81 samples from different genotypes, tissues, and developmental stages. First, we found that intrinsic interspecific differences between the diploid parents played a major role in establishing the expression architecture of the allopolyploid. Nonetheless, allopolyploidy per se also induced dramatic and asymmetric patterns of differential gene expression between the subgenomes, and genes from the D subgenome exhibited a more drastic response. Second, analysis of homoeolog expression bias (HEB) revealed that the D subgenome exhibited significant expression bias and that de novo-generated HEB was attributed mainly to asymmetrical differential gene expression. Homoeolog-specific expression (HSE) analyses showed that the cis-only regulatory pattern was predominant in AT2, reflecting significant divergence between the parents. Co-expression network analysis revealed that homoeolog expression connectivity (HEC) was significantly correlated with sequence divergence in cis elements between subgenomes. Interestingly, allopolyploidy-induced reconstruction of network modules was also associated with different HSE patterns. Finally, a transcriptome atlas of spike development demonstrated that the phenotypic similarity of AT2 to T. urartu may be attributed to the combination of relatively stable expression of A-subgenome genes and drastic downregulation of their D-subgenome homoeologs. These findings provide a broad, multidimensional characterization of allopolyploidy-induced transcriptomic responses and suggest that allopolyploidy can have immediate and complex regulatory effects on the expression of nuclear genes.

Construction and Analysis of Coexpression Network to Understand Biological Responses in Chickens Infected by Eimeria tenella

Coccidiosis, caused by various Eimeria species, is a major parasitic disease in chickens. Our understanding of how chickens respond to coccidian infections is highly limited at both the molecular and cellular levels. In this study, coexpression modules were identified by weighted gene coexpression network analysis in chickens infected with Eimeria tenella. A total of 15 correlation modules were identified using 5,175 genes with 24 chicken samples, 12 with primary and 12 with secondary E. tenella infection. The analysis of the interactions between these modules showed a high degree of scale independence. Gene Ontology and Kyoto Encyclopedia of Gene and Genomes enrichment analyses revealed that genes in these functional modules were involved in a broad categories of functions, such as immune response, amino acid metabolism, cellular responses to lipids, sterol biosynthetic processes, and RNA transport. Two modules viz yellow and magenta were identified significantly associating with infection status. Preservation analysis showed that most of the modules identified in E. tenella infections were highly or moderately preserved in chickens infected with either Eimeria acervulina or Eimeria maxima. These analyses outline a biological responses landscape for chickens infected by E. tenella, and also indicates that infections with these three Eimeria species elicit similar biological responses in chickens at the system level. These findings provide new clues and ideas for investigating the relationship between parasites and host, and the control of parasitic diseases.

Evolution and Characterization of Acetyl Coenzyme A: Diacylglycerol Acyltransferase Genes in Cotton Identify the Roles of GhDGAT3D in Oil Biosynthesis and Fatty Acid Composition

Cottonseed oil is rich in unsaturated fatty acids (UFAs) and serves as an edible oil in human nutrition. Reports suggest that acyl-coenzyme A: diacylglycerol acyltransferases (DGAT) and wax ester synthase/DGAT (WSD1) genes encode a key group of enzymes that catalyze the final step for triacylglycerol biosynthesis and enable an important rate-limiting process. However, their roles in oil biosynthesis and the fatty acid profile of cotton seed are poorly understood. Therefore, the aim of this study was to identify and characterize DGAT and WSD1 genes in cotton plants and examine their roles in oil biosynthesis, the fatty acid profile of cotton seeds, and abiotic stress responses. In this study, 36 GhDGAT and GhWSD1 genes were identified in upland cotton (G. hirsutum) and found to be clustered into four groups: GhDGAT1, GhDGAT2, GhDGAT3, and GhWSD1. Gene structure and domain analyses showed that the GhDGAT and GhWSD1 genes in each group are highly conserved. Gene synteny analysis indicated that segmental and tandem duplication events occurred frequently during cotton evolution. Expression analysis revealed that GhDGAT and GhWSD1 genes function widely in cotton development and stress responses; moreover, several environmental stress and hormone response-related cis-elements were detected in the GhDGAT and GhWSD1 promoter regions. The predicted target transcription factors and miRNAs imply an extensive role of GhDGAT and GhWSD1 genes in stress responses. Increases in GhDGAT3 gene expression with increases in cottonseed oil accumulation were observed. Transformation study results showed that there was an increase in C18:1 content and a decrease in C18:2 and C18:3 contents in seeds of Arabidopsis transgenic plants overexpressing GhDGAT3D compared with that of control plants. Overall, these findings contributed to the understanding of the functions of GhDGAT and GhWSD1 genes in upland cotton, providing basic information for further research.

Evolutionary Contribution of Duplicated Genes to Genome Evolution in the Ginseng Species Complex

Genes duplicated by whole genome duplication (WGD) and small-scale duplication (SSD) have played important roles in adaptive evolution of all flowering plants. However, it still remains underinvestigated how the distinct models of duplication events and their contending evolutionary patterns have shaped the genome and epigenomes of extant plant species. In this study, we investigated the contribution of the WGD- and SSD-derived duplicate genes to the genome evolution of one diploid and three closely related allotetraploid Panax species based on genome, methylome, and proteome data sets. Our genome-wide comparative analyses revealed that although the ginseng species complex was recently diverged, they have evolved distinct overall patterns of nucleotide variation, cytosine methylation, and protein-level expression. In particular, genetic and epigenetic asymmetries observed in the recent WGD-derived genes are largely consistent across the ginseng species complex. In addition, our results revealed that gene duplicates generated by ancient WGD and SSD mechanisms exhibited distinct evolutionary patterns. We found the ancient WGD-derived genes (i.e., ancient collinear gene) are genetically more conserved and hypomethylated at the cytosine sites. In contrast, some of the SSD-derived genes (i.e., dispersal duplicated gene) showed hypermethylation and high variance in nucleotide variation pattern. Functional enrichment analyses of the duplicated genes indicated that adaptation-related traits (i.e., photosynthesis) created during the distant ancient WGDs are further strengthened by both the more recent WGD and SSD. Together, our findings suggest that different types of duplicated genes may have played distinct but relaying evolutionary roles in the polyploidization and speciation processes in the ginseng species complex.

Conservation and Divergence in Duplicated Fiber Coexpression Networks Accompanying Domestication of the Polyploid Gossypium hirsutum L

Gossypium hirsutum L. (Upland cotton) has an evolutionary history involving inter-genomic hybridization, polyploidization, and subsequent domestication. We analyzed the developmental dynamics of the cotton fiber transcriptome accompanying domestication using gene coexpression networks for both joint and homoeologous networks. Remarkably, most genes exhibited expression for at least one homoeolog, confirming previous reports of widespread gene usage in cotton fibers. Most coexpression modules comprising the joint network are preserved in each subgenomic network and are enriched for similar biological processes, showing a general preservation of network modular structure for the two co-resident genomes in the polyploid. Interestingly, only one fifth of homoeologs co-occur in the same module when separated, despite similar modular structures between the joint and homoeologous networks. These results suggest that the genome-wide divergence between homoeologous genes is sufficient to separate their co-expression profiles at the intermodular level, despite conservation of intramodular relationships within each subgenome. Most modules exhibit D-homoeolog expression bias, although specific modules do exhibit A-homoeolog bias. Comparisons between wild and domesticated coexpression networks revealed a much tighter and denser network structure in domesticated fiber, as evidenced by its fewer modules, 13-fold increase in the number of development-related module member genes, and the poor preservation of the wild network topology. These results demonstrate the amazing complexity that underlies the domestication of cotton fiber.

Genomics of Evolutionary Novelty in Hybrids and Polyploids

It has long been recognized that hybridization and polyploidy are prominent processes in plant evolution. Although classically recognized as significant in speciation and adaptation, recognition of the importance of interspecific gene flow has dramatically increased during the genomics era, concomitant with an unending flood of empirical examples, with or without genome doubling. Interspecific gene flow is thus increasingly thought to lead to evolutionary innovation and diversification, via adaptive introgression, homoploid hybrid speciation and allopolyploid speciation. Less well understood, however, are the suite of genetic and genomic mechanisms set in motion by the merger of differentiated genomes, and the temporal scale over which recombinational complexity mediated by gene flow might be expressed and exposed to natural selection. We focus on these issues here, considering the types of molecular genetic and genomic processes that might be set in motion by the saltational event of genome merger between two diverged species, either with or without genome doubling, and how these various processes can contribute to novel phenotypes. Genetic mechanisms include the infusion of new alleles and the genesis of novel structural variation including translocations and inversions, homoeologous exchanges, transposable element mobilization and novel insertional effects, presence-absence variation and copy number variation. Polyploidy generates massive transcriptomic and regulatory alteration, presumably set in motion by disrupted stoichiometries of regulatory factors, small RNAs and other genome interactions that cascade from single-gene expression change up through entire networks of transformed regulatory modules. We highlight both these novel combinatorial possibilities and the range of temporal scales over which such complexity might be generated, and thus exposed to natural selection and drift.

Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids

Polyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, EAGLE-RC and GSNAP-PolyCat outperform other quantification pipelines tested, and their derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an overestimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.

Co-expression clustering across flower development identifies modules for diverse floral forms in Achimenes (Gesneriaceae)

BACKGROUND

Genetic pathways involved with flower color and shape are thought to play an important role in the development of flowers associated with different pollination syndromes, such as those associated with bee, butterfly, or hummingbird pollination. Because pollination syndromes are complex traits that are orchestrated by multiple genes and pathways, the gene regulatory networks have not been explored. Gene co-expression networks provide a systems level approach to identify important contributors to floral diversification.

METHODS

RNA-sequencing was used to assay gene expression across two stages of flower development (an early bud and an intermediate stage) in 10 species of Achimenes (Gesneriaceae). Two stage-specific co-expression networks were created from 9,503 orthologs and analyzed to identify module hubs and the network periphery. Module association with bee, butterfly, and hummingbird pollination syndromes was tested using phylogenetic mixed models. The relationship between network connectivity and evolutionary rates (d N/d S) was tested using linear models.

RESULTS

Networks contained 65 and 62 modules that were largely preserved between developmental stages and contained few stage-specific modules. Over a third of the modules in both networks were associated with flower color, shape, and pollination syndrome. Within these modules, several hub nodes were identified that related to the production of anthocyanin and carotenoid pigments and the development of flower shape. Evolutionary rates were decreased in highly connected genes and elevated in peripheral genes.

DISCUSSION

This study aids in the understanding of the genetic architecture and network properties underlying the development of floral form and provides valuable candidate modules and genes for future studies.

Genome-wide analysis of the HSP101/CLPB gene family for heat tolerance in hexaploid wheat

Heat Shock Protein 101 (HSP101), the homolog of Caseinolytic Protease B (CLPB) proteins, has functional conservation across species to play roles in heat acclimation and plant development. In wheat, several TaHSP101/CLPB genes were identified, but have not been comprehensively characterized. Given the complexity of a polyploid genome with its phenomena of homoeologous expression bias, detailed analysis on the whole TaCLPB family members is important to understand the genetic basis of heat tolerance in hexaploid wheat. In this study, a genome-wide analysis revealed thirteen members of TaCLPB gene family and their expression patterns in various tissues, developmental stages, and stress conditions. Detailed characterization of TaCLPB gene and protein structures suggested potential variations of the sub-cellular localization and their functional regulations. We revealed homoeologous specific variations among TaCLPB gene copies that have not been reported earlier. A study of the Chromosome 1 TaCLPB in four wheat genotypes demonstrated unique patterns of the homoeologous gene expression under moderate and extreme heat treatments. The results give insight into the strategies to improve heat tolerance by targeting one or some of the TaCLPB genes in wheat.

Genetic Analysis of the Transition from Wild to Domesticated Cotton (Gossypium hirsutum L.)

The evolution and domestication of cotton is of great interest from both economic and evolutionary standpoints. Although many genetic and genomic resources have been generated for cotton, the genetic underpinnings of the transition from wild to domesticated cotton remain poorly known. Here we generated an intraspecific QTL mapping population specifically targeting domesticated cotton phenotypes. We used 466 F₂ individuals derived from an intraspecific cross between the wild Gossypium hirsutum var. yucatanense (TX2094) and the elite cultivar G. hirsutum cv. Acala Maxxa, in two environments, to identify 120 QTL associated with phenotypic changes under domestication. While the number of QTL recovered in each subpopulation was similar, only 22 QTL were considered coincident (i.e., shared) between the two locations, eight of which shared peak markers. Although approximately half of QTL were located in the A-subgenome, many key fiber QTL were detected in the D-subgenome, which was derived from a species with unspinnable fiber. We found that many QTL are environment-specific, with few shared between the two environments, indicating that QTL associated with G. hirsutum domestication are genomically clustered but environmentally labile. Possible candidate genes were recovered and are discussed in the context of the phenotype. We conclude that the evolutionary forces that shape intraspecific divergence and domestication in cotton are complex, and that phenotypic transformations likely involved multiple interacting and environmentally responsive factors.

Unraveling cis and trans regulatory evolution during cotton domestication

Cis and trans regulatory divergence underlies phenotypic and evolutionary diversification. Relatively little is understood about the complexity of regulatory evolution accompanying crop domestication, particularly for polyploid plants. Here, we compare the fiber transcriptomes between wild and domesticated cotton (Gossypium hirsutum) and their reciprocal F1 hybrids, revealing genome-wide (~15%) and often compensatory cis and trans regulatory changes under divergence and domestication. The high level of trans evolution (54%-64%) observed is likely enabled by genomic redundancy following polyploidy. Our results reveal that regulatory variation is significantly associated with sequence evolution, inheritance of parental expression patterns, co-expression gene network properties, and genomic loci responsible for domestication traits. With respect to regulatory evolution, the two subgenomes of allotetraploid cotton are often uncoupled. Overall, our work underscores the complexity of regulatory evolution during fiber domestication and may facilitate new approaches for improving cotton and other polyploid plants.

Meta-analysis of drought-tolerant genotypes in Oryza sativa: A network-based approach

BACKGROUND

Drought is a severe environmental stress. It is estimated that about 50% of the world rice production is affected mainly by drought. Apart from conventional breeding strategies to develop drought-tolerant crops, innovative computational approaches may provide insights into the underlying molecular mechanisms of stress response and identify drought-responsive markers. Here we propose a network-based computational approach involving a meta-analytic study of seven drought-tolerant rice genotypes under drought stress.

RESULTS

Co-expression networks enable large-scale analysis of gene-pair associations and tightly coupled clusters that may represent coordinated biological processes. Considering differentially expressed genes in the co-expressed modules and supplementing external information such as resistance/tolerance QTLs, transcription factors, network-based topological measures, we identify and prioritize drought-adaptive co-expressed gene modules and potential candidate genes. Using the candidate genes that are well-represented across the datasets as 'seed' genes, two drought-specific protein-protein interaction networks (PPINs) are constructed with up- and down-regulated genes. Cluster analysis of the up-regulated PPIN revealed ABA signalling pathway as a central process in drought response with a probable crosstalk with energy metabolic processes. Tightly coupled gene clusters representing up-regulation of core cellular respiratory processes and enhanced degradation of branched chain amino acids and cell wall metabolism are identified. Cluster analysis of down-regulated PPIN provides a snapshot of major processes associated with photosynthesis, growth, development and protein synthesis, most of which are shut down during drought. Differential regulation of phytohormones, e.g., jasmonic acid, cell wall metabolism, signalling and posttranslational modifications associated with biotic stress are elucidated. Functional characterization of topologically important, drought-responsive uncharacterized genes that may play a role in important processes such as ABA signalling, calcium signalling, photosynthesis and cell wall metabolism is discussed. Further transgenic studies on these genes may help in elucidating their biological role under stress conditions.

CONCLUSION

Currently, a large number of resources for rice functional genomics exist which are mostly underutilized by the scientific community. In this study, a computational approach integrating information from various resources such as gene co-expression networks, protein-protein interactions and pathway-level information is proposed to provide a systems-level view of complex drought-responsive processes across the drought-tolerant genotypes.

Recent advances in gene function prediction using context-specific coexpression networks in plants

Predicting gene functions from genome sequence alone has been difficult, and the functions of a large fraction of plant genes remain unknown. However, leveraging the vast amount of currently available gene expression data has the potential to facilitate our understanding of plant gene functions, especially in determining complex traits. Gene coexpression networks-created by integrating multiple expression datasets-connect genes with similar patterns of expression across multiple conditions. Dense gene communities in such networks, commonly referred to as modules, often indicate that the member genes are functionally related. As such, these modules serve as tools for generating new testable hypotheses, including the prediction of gene function and importance. Recently, we have seen a paradigm shift from the traditional "global" to more defined, context-specific coexpression networks. Such coexpression networks imply genetic correlations in specific biological contexts such as during development or in response to a stress. In this short review, we highlight a few recent studies that attempt to fill the large gaps in our knowledge about cellular functions of plant genes using context-specific coexpression networks.

Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory

The classic Darwinian theory and the Synthetic evolutionary theory and their linear models, while invaluable to study the origins and evolution of species, are not primarily designed to model the evolution of organisations, typically that of ecosystems, nor that of processes. How could evolutionary theory better explain the evolution of biological complexity and diversity? Inclusive network-based analyses of dynamic systems could retrace interactions between (related or unrelated) components. This theoretical shift from a Tree of Life to a Dynamic Interaction Network of Life, which is supported by diverse molecular, cellular, microbiological, organismal, ecological and evolutionary studies, would further unify evolutionary biology.

Non-Additive Transcriptomic Responses to Inoculation with Rhizobia in a Young Allopolyploid Compared with Its Diploid Progenitors

Root nodule symbioses (nodulation) and whole genome duplication (WGD, polyploidy) are both important phenomena in the legume family (Leguminosae). Recently, it has been proposed that polyploidy may have played a critical role in the origin or refinement of nodulation. However, while nodulation and polyploidy have been studied independently, there have been no direct studies of mechanisms affecting the interactions between these phenomena in symbiotic, nodule-forming species. Here, we examined the transcriptome-level responses to inoculation in the young allopolyploid Glycine dolichocarpa (T2) and its diploid progenitor species to identify underlying processes leading to the enhanced nodulation responses previously identified in T2. We assessed the differential expression of genes and, using weighted gene co-expression network analysis (WGCNA), identified modules associated with nodulation and compared their expression between species. These transcriptomic analyses revealed patterns of non-additive expression in T2, with evidence of transcriptional responses to inoculation that were distinct from one or both progenitors. These differential responses elucidate mechanisms underlying the nodulation-related differences observed between T2 and the diploid progenitors. Our results indicate that T2 has reduced stress-related transcription, coupled with enhanced transcription of modules and genes implicated in hormonal signaling, both of which are important for nodulation.