Combined Large-Scale Phenotyping and Transcriptomics in Maize Reveals a Robust Growth Regulatory Network

Inference of Dynamic Growth Regulatory Network in Cancer Using High-Throughput Transcriptomic Data

Growth is regulated by gene expression variation at different developmental stages of biological processes such as cell differentiation, disease progression, or drug response. In cancer, a stage-specific regulatory model constructed to infer the dynamic expression changes in genes contributing to tissue growth or proliferation is referred as a dynamic growth regulatory network (dGRN). Over the past decade, gene expression data has been widely used for reconstructing dGRN by computing correlations between the differentially expressed genes (DEGs). A wide variety of pipelines are available to construct the GRNs using DEGs and the choice of a particular method or tool depends on the nature of the study. In this protocol, we have outlined a step-by-step guide for the analysis of DEGs using RNA-Seq data, beginning from data acquisition, pre-processing, mapping to reference genome, and construction of a correlation-based co-expression network to further downstream analysis. We have also outlined the steps for the inclusion of publicly available interaction/regulation information into the dGRN followed by relevant topological inferences. This tutorial has been designed in a way that early researchers can refer to for an easy and comprehensive glimpse of methodologies used in the inference of dGRN using transcriptomics data.

BREEDIT: a multiplex genome editing strategy to improve complex quantitative traits in maize

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Although new technologies are being applied to tackle this problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in CRISPR/Cas9-mediated gene engineering have paved the way to accelerate plant breeding to meet this increasing demand. However, many traits are governed by multiple small-effect genes operating in complex interactive networks. Here, we present the gene discovery pipeline BREEDIT, which combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought tolerance. We induced gene knockouts in 48 growth-related genes into maize (Zea mays) using CRISPR/Cas9 and generated a collection of over 1,000 gene-edited plants. The edited populations displayed (on average) 5%-10% increases in leaf length and up to 20% increases in leaf width compared with the controls. For each gene family, edits in subsets of genes could be associated with enhanced traits, allowing us to reduce the gene space to be considered for trait improvement. BREEDIT could be rapidly applied to generate a diverse collection of mutants to identify promising gene modifications for later use in breeding programs.

Leaf Development in Medicago truncatula

Forage yield is largely dependent on leaf development, during which the number of leaves, leaflets, leaf size, and shape are determined. In this mini-review, we briefly summarize recent studies of leaf development in Medicago truncatula, a model plant for legumes, with a focus on factors that could affect biomass of leaves. These include: floral development and related genes, lateral organ boundary genes, auxin biosynthesis, transportation and signaling genes, and WOX related genes.

Using breeding and quantitative genetics to understand the C4 pathway

Reducing photorespiration in C3 crops could significantly increase rates of photosynthesis and yield. One method to achieve this would be to integrate C4 photosynthesis into C3 species. This objective is challenging as it involves engineering incompletely understood traits into C3 leaves, including complex changes to their biochemistry, cell biology, and anatomy. Quantitative genetics and selective breeding offer underexplored routes to identify regulators of these processes. We first review examples of natural intraspecific variation in C4 photosynthesis as well as the potential for hybridization between C3 and C4 species. We then discuss how quantitative genetic approaches including artificial selection and genome-wide association could be used to better understand the C4 syndrome and in so doing guide the engineering of the C4 pathway into C3 crops.

A forward genetics approach integrating genome-wide association study and expression quantitative trait locus mapping to dissect leaf development in maize (Zea mays)

The characterization of the genetic basis of maize (Zea mays) leaf development may support breeding efforts to obtain plants with higher vigor and productivity. In this study, a mapping panel of 197 biparental and multiparental maize recombinant inbred lines (RILs) was analyzed for multiple leaf traits at the seedling stage. RNA sequencing was used to estimate the transcription levels of 29 573 gene models in RILs and to derive 373 769 single nucleotide polymorphisms (SNPs), and a forward genetics approach combining these data was used to pinpoint candidate genes involved in leaf development. First, leaf traits were correlated with gene expression levels to identify transcript-trait correlations. Then, leaf traits were associated with SNPs in a genome-wide association (GWA) study. An expression quantitative trait locus mapping approach was followed to associate SNPs with gene expression levels, prioritizing candidate genes identified based on transcript-trait correlations and GWAs. Finally, a network analysis was conducted to cluster all transcripts in 38 co-expression modules. By integrating forward genetics approaches, we identified 25 candidate genes highly enriched for specific functional categories, providing evidence supporting the role of vacuolar proton pumps, cell wall effectors, and vesicular traffic controllers in leaf growth. These results tackle the complexity of leaf trait determination and may support precision breeding in maize.

grasviq: an image analysis framework for automatically quantifying vein number and morphology in grass leaves

Beyond facilitating transport and providing mechanical support to the leaf, veins have important roles in the performance and productivity of plants and the ecosystem. In recent decades, computational image analysis has accelerated the extraction and quantification of vein traits, benefiting fields of research from agriculture to climatology. However, most of the existing leaf vein image analysis programs have been developed for the reticulate venation found in dicots. Despite the agroeconomic importance of cereal grass crops, like Oryza sativa (rice) and Zea mays (maize), a dedicated image analysis program for the parallel venation found in monocots has yet to be developed. To address the need for an image-based vein phenotyping tool for model and agronomic grass species, we developed the grass vein image quantification (grasviq) framework. Designed specifically for parallel venation, this framework automatically segments and quantifies vein patterns from images of cleared leaf pieces using classical computer vision techniques. Using image data sets from maize inbred lines and auxin biosynthesis and transport mutants in maize, we demonstrate the utility of grasviq for quantifying important vein traits, including vein density, vein width and interveinal distance. Furthermore, we show that the framework can resolve quantitative differences and identify vein patterning defects, which is advantageous for genetic experiments and mutant screens. We report that grasviq can perform high-throughput vein quantification, with precision on a par with that of manual quantification. Therefore, we envision that grasviq will be adopted for vein phenomics in maize and other grass species.

Transcriptome Analysis of Ginkgo biloba L. Leaves across Late Developmental Stages Based on RNA-Seq and Co-Expression Network

The final size of plant leaves is strictly controlled by environmental and genetic factors, which coordinate cell expansion and cell cycle activity in space and time; however, the regulatory mechanisms of leaf growth are still poorly understood. Ginkgo biloba is a dioecious species native to China with medicinally and phylogenetically important characteristics, and its fan-shaped leaves are unique in gymnosperms, while the mechanism of G. biloba leaf development remains unclear. In this study we studied the transcriptome of G. biloba leaves at three developmental stages using high-throughput RNA-seq technology. Approximately 4167 differentially expressed genes (DEGs) were obtained, and a total of 12,137 genes were structure optimized together with 732 new genes identified. More than 50 growth-related factors and gene modules were identified based on DEG and Weighted Gene Co-expression Network Analysis. These results could remarkably expand the existing transcriptome resources of G. biloba, and provide references for subsequent analysis of ginkgo leaf development.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Translational gene regulation in plants: A green new deal

The molecular machinery for protein synthesis is profoundly similar between plants and other eukaryotes. Mechanisms of translational gene regulation are embedded into the broader network of RNA-level processes including RNA quality control and RNA turnover. However, over eons of their separate history, plants acquired new components, dropped others, and generally evolved an alternate way of making the parts list of protein synthesis work. Research over the past 5 years has unveiled how plants utilize translational control to defend themselves against viruses, regulate translation in response to metabolites, and reversibly adjust translation to a wide variety of environmental parameters. Moreover, during seed and pollen development plants make use of RNA granules and other translational controls to underpin developmental transitions between quiescent and metabolically active stages. The economics of resource allocation over the daily light-dark cycle also include controls over cellular protein synthesis. Important new insights into translational control on cytosolic ribosomes continue to emerge from studies of translational control mechanisms in viruses. Finally, sketches of coherent signaling pathways that connect external stimuli with a translational response are emerging, anchored in part around TOR and GCN2 kinase signaling networks. These again reveal some mechanisms that are familiar and others that are different from other eukaryotes, motivating deeper studies on translational control in plants. This article is categorized under: Translation > Translation Regulation RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications.

Leaf shape in Populus tremula is a complex, omnigenic trait

Leaf shape is a defining feature of how we recognize and classify plant species. Although there is extensive variation in leaf shape within many species, few studies have disentangled the underlying genetic architecture. We characterized the genetic architecture of leaf shape variation in Eurasian aspen (Populus tremula L.) by performing genome-wide association study (GWAS) for physiognomy traits. To ascertain the roles of identified GWAS candidate genes within the leaf development transcriptional program, we generated RNA-Seq data that we used to perform gene co-expression network analyses from a developmental series, which is publicly available within the PlantGenIE resource. We additionally used existing gene expression measurements across the population to analyze GWAS candidate genes in the context of a population-wide co-expression network and to identify genes that were differentially expressed between groups of individuals with contrasting leaf shapes. These data were integrated with expression GWAS (eQTL) results to define a set of candidate genes associated with leaf shape variation. Our results identified no clear adaptive link to leaf shape variation and indicate that leaf shape traits are genetically complex, likely determined by numerous small-effect variations in gene expression. Genes associated with shape variation were peripheral within the population-wide co-expression network, were not highly connected within the leaf development co-expression network, and exhibited signatures of relaxed selection. As such, our results are consistent with the omnigenic model.

Identification of transcription factors controlling floral morphology in wild Petunia species with contrasting pollination syndromes

Adaptation to different pollinators is an important driver of speciation in the angiosperms. Genetic approaches such as QTL mapping have been successfully used to identify the underlying speciation genes. However, these methods are often limited by widespread suppression of recombination due to divergence between species. While the mutations that caused the interspecific differences in floral color and scent have been elucidated in a variety of plant genera, the genes that are responsible for morphological differences remain mostly unknown. Differences in floral organ length determine the pollination efficiency of hawkmoths and hummingbirds, and therefore the genes that control these differences are potential speciation genes. Identifying such genes is challenging, especially in non-model species and when studying complex traits for which little prior genetic and biochemical knowledge is available. Here we combine transcriptomics with detailed growth analysis to identify candidate transcription factors underlying interspecific variation in the styles of Petunia flowers. Starting from a set of 2284 genes, stepwise filtering for expression in styles, differential expression between species, correlation with growth-related traits, allele-specific expression in interspecific hybrids, and/or high-impact polymorphisms resulted in a set of 43 candidate speciation genes. Validation by virus-induced gene silencing identified two MYB transcription factors, EOBI and EOBII, that were previously shown to regulate floral scent emission, a trait associated with pollination by hawkmoths.

Enabling reusability of plant phenomic datasets with MIAPPE 1.1

Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

Enabling reusability of plant phenomic datasets with MIAPPE 1.1

Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

Enabling reusability of plant phenomic datasets with MIAPPE 1.1

Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

Maize E2F transcription factors. Expression, association to promoters of S-phase genes and interaction with the RBR1 protein in chromatin during seed germination

For seed germination, it is necessary to restart the cell cycle, a process regulated at multiple levels including transcriptional control, that is executed by the E2F family of transcription factors. We identified 12 genes of the E2F family in maize that are expressed differentially during the first 28 h post imbibition (HAI). E2Fa/b1;1 and E2Fc proteins were characterized as an activator and a putative repressor respectively, both forming heterodimers with DPb2 that bind differentially to consensus E2F response elements in promoters of E2F target genes. Transcripts of target genes for these transcription factors accumulate during germination; in dry seeds E2Fc protein is enriched in the target promoters and is replaced by E2Fa/b1;1 as germination advances. RBR1 is found in the same promoters in non-imbibed and 28 HAI seeds, when DNA replication has concluded, and transcription of the E2F targets should stop. During germination promoters of these target genes seem to be decorated with histone marks related to relaxed chromatin structure. Therefore, E2Fs appear to occupy their target genes in a context of open chromatin, with RBR1 fine tuning the progression between the phases.

Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions

The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.

Phenotyping: New Windows into the Plant for Breeders

Plant phenotyping enables noninvasive quantification of plant structure and function and interactions with environments. High-capacity phenotyping reaches hitherto inaccessible phenotypic characteristics. Diverse, challenging, and valuable applications of phenotyping have originated among scientists, prebreeders, and breeders as they study the phenotypic diversity of genetic resources and apply increasingly complex traits to crop improvement. Noninvasive technologies are used to analyze experimental and breeding populations. We cover the most recent research in controlled-environment and field phenotyping for seed, shoot, and root traits. Select field phenotyping technologies have become state of the art and show promise for speeding up the breeding process in early generations. We highlight the technologies behind the rapid advances in proximal and remote sensing of plants in fields. We conclude by discussing the new disciplines working with the phenotyping community: data science, to address the challenge of generating FAIR (findable, accessible, interoperable, and reusable) data, and robotics, to apply phenotyping directly on farms.

Linking crop traits to transcriptome differences in a progeny population of tetraploid potato

BACKGROUND

Potato is the third most consumed crop in the world. Breeding for traits such as yield, product quality and pathogen resistance are main priorities. Identifying molecular signatures of these and other important traits is important in future breeding efforts. In this study, a progeny population from a cross between a breeding line, SW93-1015, and a cultivar, Désirée, was studied by trait analysis and RNA-seq in order to develop understanding of segregating traits at the molecular level and identify transcripts with expressional correlation to these traits. Transcript markers with predictive value for field performance applicable under controlled environments would be of great value for plant breeding.

RESULTS

A total of 34 progeny lines from SW93-1015 and Désirée were phenotyped for 17 different traits in a field in Nordic climate conditions and controlled climate settings. A master transcriptome was constructed with all 34 progeny lines and the parents through a de novo assembly of RNA-seq reads. Gene expression data obtained in a controlled environment from the 34 lines was correlated to traits by different similarity indices, including Pearson and Spearman, as well as DUO, which calculates the co-occurrence between high and low values for gene expression and trait. Our study linked transcripts to traits such as yield, growth rate, high laying tubers, late and tuber blight, tuber greening and early flowering. We found several transcripts associated to late blight resistance and transcripts encoding receptors were associated to Dickeya solani susceptibility. Transcript levels of a UBX-domain protein was negatively associated to yield and a GLABRA2 expression modulator was negatively associated to growth rate.

CONCLUSION

In our study, we identify 100's of transcripts, putatively linked based on expression with 17 traits of potato, representing both well-known and novel associations. This approach can be used to link the transcriptome to traits. We explore the possibility of associating the level of transcript expression from controlled, optimal environments to traits in a progeny population with different methods introducing the application of DUO for the first time on transcriptome data. We verify the expression pattern for five of the putative transcript markers in another progeny population.

Comparative transcriptomics enables the identification of functional orthologous genes involved in early leaf growth

Leaf growth is a complex trait for which many similarities exist in different plant species, suggesting functional conservation of the underlying pathways. However, a global view of orthologous genes involved in leaf growth showing conserved expression in dicots and monocots is currently missing. Here, we present a genome-wide comparative transcriptome analysis between Arabidopsis and maize, identifying conserved biological processes and gene functions active during leaf growth. Despite the orthology complexity between these distantly related plants, 926 orthologous gene groups including 2829 Arabidopsis and 2974 maize genes with similar expression during leaf growth were found, indicating conservation of the underlying molecular networks. We found 65% of these genes to be involved in one-to-one orthology, whereas only 28.7% of the groups with divergent expression had one-to-one orthology. Within the pool of genes with conserved expression, 19 transcription factor families were identified, demonstrating expression conservation of regulators active during leaf growth. Additionally, 25 Arabidopsis and 25 maize putative targets of the TCP transcription factors with conserved expression were determined based on the presence of enriched transcription factor binding sites. Based on large-scale phenotypic data, we observed that genes with conserved expression have a higher probability to be involved in leaf growth and that leaf-related phenotypes are more frequently present for genes having orthologues between dicots and monocots than clade-specific genes. This study shows the power of integrating transcriptomic with orthology data to identify or select candidates for functional studies during leaf development in flowering plants.

Redox homeostasis in the growth zone of the rice leaf plays a key role in cold tolerance

We analysed the cellular and molecular changes in the leaf growth zone of tolerant and sensitive rice varieties in response to suboptimal temperatures. Cold reduced the final leaf length by 35% and 51% in tolerant and sensitive varieties, respectively. Tolerant lines exhibited a smaller reduction of the leaf elongation rate and greater compensation by an increased duration of leaf growth. Kinematic analysis showed that cold reduced cell production in the meristem and the expansion rate in the elongation zone, but the latter was compensated for by a doubling of the duration of cell expansion. We performed iTRAQ proteome analysis on proliferating and expanding parts of the leaf growth zone. We identified 559 and 542 proteins, of which 163 and 210 were differentially expressed between zones, and 96 and 68 between treatments, in the tolerant and sensitive lines, respectively. The categories protein biosynthesis and redox homeostasis were significantly overrepresented in the up-regulated proteins. We therefore measured redox metabolites and enzyme activities in the leaf growth zone, demonstrating that tolerance of rice lines to suboptimal temperatures correlates with the ability to up-regulate enzymatic antioxidants in the meristem and non-enzymatic antioxidants in the elongation zone.

A systems biology approach uncovers a gene co-expression network associated with cell wall degradability in maize

Understanding the mechanisms triggering variation of cell wall degradability is a prerequisite to improving the energy value of lignocellulosic biomass for animal feed or biorefinery. Here, we implemented a multiscale systems approach to shed light on the genetic basis of cell wall degradability in maize. We demonstrated that allele replacement in two pairs of near-isogenic lines at a region encompassing a major quantitative trait locus (QTL) for cell wall degradability led to phenotypic variation of a similar magnitude and sign to that expected from a QTL analysis of cell wall degradability in the F271 × F288 recombinant inbred line progeny. Using DNA sequences within the QTL interval of both F271 and F288 inbred lines and Illumina RNA sequencing datasets from internodes of the selected near-isogenic lines, we annotated the genes present in the QTL interval and provided evidence that allelic variation at the introgressed QTL region gives rise to coordinated changes in gene expression. The identification of a gene co-expression network associated with cell wall-related trait variation revealed that the favorable F288 alleles exploit biological processes related to oxidation-reduction, regulation of hydrogen peroxide metabolism, protein folding and hormone responses. Nested in modules of co-expressed genes, potential new cell-wall regulators were identified, including two transcription factors of the group VII ethylene response factor family, that could be exploited to fine-tune cell wall degradability. Overall, these findings provide new insights into the regulatory mechanisms by which a major locus influences cell wall degradability, paving the way for its map-based cloning in maize.

Plant virus interaction mechanism and associated pathways in mosaic disease of small cardamom (Elettaria cardamomum Maton) by RNA-Seq approach

Small cardamom (Elettaria cardamomum), grown in limited coastal tropical countries is one of the costliest and widely exported agri-produce having global turnover of >10 billion USD. Mosaic/marble disease is one of the major impediments that requires understanding of disease at molecular level. Neither whole genome sequence nor any genomic resources are available, thus RNA seq approach can be a rapid and economical alternative. De novo transcriptome assembly was done with Illumina Hiseq data. A total of 5317 DEGs, 2267 TFs, 114 pathways and 175,952 genic region putative markers were obtained. Gene regulatory network analysis deciphered molecular events involved in marble disease. This is the first transcriptomic report revealing disease mechanism mediated by perturbation in auxin homeostasis and ethylene signalling leading to senescence. The web-genomic resource (SCMVTDb) catalogues putative molecular markers, candidate genes and transcript information. SCMVTDb can be used in germplasm improvement against mosaic disease in endeavour of small cardamom productivity. Availability of genomic resource, SCMVTDb: http://webtom.cabgrid.res.in/scmvtdb/.

Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis

Maize (Zea mays mays) oil is a rich source of polyunsaturated fatty acids (FAs) and energy, making it a valuable resource for human food, animal feed, and bio-energy. Although this trait has been studied via conventional genome-wide association study (GWAS), the single nucleotide polymorphism (SNP)-trait associations generated by GWAS may miss the underlying associations when traits are based on many genes, each with small effects that can be overshadowed by genetic background and environmental variation. Detecting these SNPs statistically is also limited by the levels set for false discovery rate. A complementary pathways analysis that emphasizes the cumulative aspects of SNP-trait associations, rather than just the significance of single SNPs, was performed to understand the balance of lipid metabolism, conversion, and catabolism in this study. This pathway analysis indicated that acyl-lipid pathways, including biosynthesis of wax esters, sphingolipids, phospholipids and flavonoids, along with FA and triacylglycerol (TAG) biosynthesis, were important for increasing oil and FA content. The allelic variation found among the genes involved in many degradation pathways, and many biosynthesis pathways leading from FAs and carbon partitioning pathways, was critical for determining final FA content, changing FA ratios and, ultimately, to final oil content. The pathways and pathway networks identified in this study, and especially the acyl-lipid associated pathways identified beyond what had been found with GWAS alone, provide a real opportunity to precisely and efficiently manipulate high-oil maize genetic improvement.

Genetics of barley tiller and leaf development

In cereals, tillering and leaf development are key factors in the concept of crop ideotype, introduced in the 1960s to enhance crop yield, via manipulation of plant architecture. In the present review, we discuss advances in genetic analysis of barley shoot architecture, focusing on tillering, leaf size and angle. We also discuss novel phenotyping techniques, such as 2D and 3D imaging, that have been introduced in the era of phenomics, facilitating reliable trait measurement. We discuss the identification of genes and pathways that are involved in barley tillering and leaf development, highlighting key hormones involved in the control of plant architecture in barley and rice. Knowledge on genetic control of traits related to plant architecture provides useful resources for designing ideotypes for enhanced barley yield and performance.

A hidden link between leaf development and senescence

Leaf senescence is the final step of leaf development and is usually accompanied by visible color changes from green to yellow or brown. Unlike the senescence of the whole body of animals and unicellular organisms, which is often associated with death, leaf senescence in plants requires highly integrative processes towards cell death with nutrient recycling and storage. Since leaf senescence plays pivotal roles in the production of plant biomass and grain yield, the mechanisms of degradation and relocation of macromolecules as well as the regulation of signaling and biosynthetic pathways have received much attention. The importance of the plant hormone ethylene in the onset of leaf senescence has been clearly documented. However, research has increasingly demonstrated that the function of ethylene in the regulation of leaf senescence is dependent on leaf development. This review raises the issue of how ethylene requires developmental regulators and focuses on the developmental aspect of leaf senescence. It also emphasizes the remarkable impact that developmental regulators have on regulating the onset of leaf senescence.

Co-expression network of transcription factors reveal ethylene-responsive element-binding factor as key regulator of wood phenotype in Eucalyptus tereticornis

Suitability of wood biomass for pulp production is dependent on the cellular architecture and composition of secondary cell wall. Presently, systems genetics approach is being employed to understand the molecular basis of trait variation and co-expression network analysis has enabled holistic understanding of complex trait such as secondary development. Transcription factors (TFs) are reported as key regulators of meristematic growth and wood formation. The hierarchical TF network is a multi-layered system which interacts with downstream structural genes involved in biosynthesis of cellulose, hemicelluloses and lignin. Several TFs have been associated with wood formation in tree species such as Populus, Eucalyptus, Picea and Pinus. However, TF-specific co-expression networks to understand the interaction between these regulators are not reported. In the present study, co-expression network was developed for TFs expressed during wood formation in Eucalyptus tereticornis and ethylene-responsive element-binding factor, EtERF2, was identified as the major hub transcript which co-expressed with other secondary cell wall biogenesis-specific TFs such as EtSND2, EtVND1, EtVND4, EtVND6, EtMYB70, EtGRAS and EtSCL8. This study reveals a probable role of ethylene in determining natural variation in wood properties in Eucalyptus species. Understanding this transcriptional regulation underpinning the complex bio-processing trait of wood biomass will complement the Eucalyptus breeding program through selection of industrially suitable phenotypes by marker-assisted selection.

Molecular mechanisms underpinning phosphorus-use efficiency in rice

Orthophosphate (H₂ PO₄^- , Pi) is an essential macronutrient integral to energy metabolism as well as a component of membrane lipids, nucleic acids, including ribosomal RNA, and therefore essential for protein synthesis. The Pi concentration in the solution of most soils worldwide is usually far too low for maximum growth of crops, including rice. This has prompted the massive use of inefficient, polluting, and nonrenewable phosphorus (P) fertilizers in agriculture. We urgently need alternative and more sustainable approaches to decrease agriculture's dependence on Pi fertilizers. These include manipulating crops by (a) enhancing the ability of their roots to acquire limiting Pi from the soil (i.e. increased P-acquisition efficiency) and/or (b) increasing the total biomass/yield produced per molecule of Pi acquired from the soil (i.e. increased P-use efficiency). Improved P-use efficiency may be achieved by producing high-yielding plants with lower P concentrations or by improving the remobilization of acquired P within the plant so as to maximize growth and biomass allocation to developing organs. Membrane lipid remodelling coupled with hydrolysis of RNA and smaller P-esters in senescing organs fuels P remobilization in rice, the world's most important cereal crop.

Extrapolation of significant genes and transcriptional regulatory networks involved in Zea mays in response in UV-B stress

A wide range of plant species growth influenced when they exposed to solar UV-B radiation. Leaves of the plant are highly affected by UV-B radiation lead to the reduction in the growth of the plant. Current work demonstrates the comparative transcriptional changes and visible symptoms occurred in the maize leaf growth zone (GZ). Primary objective of this study was to identify differentially expressed genes (DEGs) responsible for leaf growth and their association in the transcriptional regulatory network under UV-B stress. Whole transcriptomic data was analysed and the quality check was tested for each sample and further genome-wide mapping and DEGs were performed. Gene Ontology (GO) based functional annotation, associated transcriptional networks and molecular pathways were annotated. Reduction in cell production due to UV-B stress causes a decrease in leaf's length and size was observed. Further, the specific role of the DEGs, in UV-B signalling pathways and other molecular functions responsible for leaf cell death was discovered. Results also infer that the major changes occurred in the cell cycle, transcriptional regulation, post-transcriptional modification, phytohormones, flavonoids biosynthesis, and chromatin remodeling. UV-B signalling pathways and the transcriptional regulatory networks infer the different molecular steps along with downstream transcriptional and post-transcriptional control of metabolic enzymes used in long-term memory adoption and attainment resistance to UV-B stress identified. Effects of UV-B radiation on leaf growth was noted in this study. UV-B stress response genes and associated transcriptional regulatory networks were identified, can be used in developing the marker assist UB-B stress tolerant genotypes of the maize.

Genome-Wide Association and Metabolic Pathway Analysis of Corn Earworm Resistance in Maize

Maize ( L.) is a staple crop of economic, industrial, and food security importance. Damage to the growing ears by corn earworm [ (Boddie)] is a major economic burden and increases secondary fungal infections and mycotoxin levels. To identify biochemical pathways associated with native resistance mechanisms, a genome-wide association analysis was performed, followed by pathway analysis using a gene-set enrichment-based approach. The gene-set enrichment exposed the cumulative effects of genes in pathways to identify those that contributed the most to resistance. Single nucleotide polymorphism-trait associations were linked to genes including transcription factors, protein kinases, hormone-responsive proteins, hydrolases, pectinases, xylogluconases, and the flavonol synthase gene (in the maysin biosynthesis pathway). The most significantly associated metabolic pathways identified included those that modified cell wall components, especially homogalacturonan, wax esters, and fatty acids; those involved in antibiosis, especially 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), flavonoids, and phenolics; and those involved in plant growth, including N uptake and energy production. The pathways identified in this study, and especially the cell wall-associated pathways, identified here for the first time, provide clues to resistance mechanisms that could guide the identification of new resistant ideotypes and candidate genes for creation of resistant maize germplasm via selection of natural variants or gene editing.

Growth rate rather than growth duration drives growth heterosis in maize B104 hybrids

Research in maize is often performed using inbred lines that can be readily transformed, such as B104. However, because the B104 line flowers late, the kernels do not always mature before the end of the growing season, hampering routine seed yield evaluations of biotech traits introduced in B104 at many geographical locations. Therefore, we generated five hybrids by crossing B104 with the early-flowering inbred lines CML91, F7, H99, Mo17, and W153R and showed in three consecutive years that the hybrid lines proved to be suitable to evaluate seed yield under field conditions in a temperate climate. By assessing the two main processes driving maize leaf growth, being rate of growth (leaf elongation rate or LER) and the duration of growth (leaf elongation duration or LED) in this panel of hybrids, we showed that leaf growth heterosis was mainly the result of increased LER and not or to a lesser extent of LED. Ectopic expression of the transgenes GA20-oxidase (GA20-OX) and PLASTOCHRON1 (PLA1), known to stimulate the LER and LED, respectively, in the hybrids showed that leaf length heterosis can be stimulated by increased LER, but not by LED, indicating that LER rather than LED is the target for enhancing leaf growth heterosis.

The reduction in maize leaf growth under mild drought affects the transition between cell division and cell expansion and cannot be restored by elevated gibberellic acid levels

Growth is characterized by the interplay between cell division and cell expansion, two processes that occur separated along the growth zone at the maize leaf. To gain further insight into the transition between cell division and cell expansion, conditions were investigated in which the position of this transition zone was positively or negatively affected. High levels of gibberellic acid (GA) in plants overexpressing the GA biosynthesis gene GA20-OXIDASE (GA20OX-1^OE ) shifted the transition zone more distally, whereas mild drought, which is associated with lowered GA biosynthesis, resulted in a more basal positioning. However, the increased levels of GA in the GA20OX-1^OE line were insufficient to convey tolerance to the mild drought treatment, indicating that another mechanism in addition to lowered GA levels is restricting growth during drought. Transcriptome analysis with high spatial resolution indicated that mild drought specifically induces a reprogramming of transcriptional regulation in the division zone. 'Leaf Growth Viewer' was developed as an online searchable tool containing the high-resolution data.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize

Grain weight is one of the most important yield components and a developmentally complex structure comprised of two major compartments (endosperm and pericarp) in maize (Zea mays L.), however, very little is known concerning the coordinated accumulation of the numerous proteins involved. Herein, we used isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic method to analyze the characteristics of dynamic proteomics for endosperm and pericarp during grain development. Totally, 9539 proteins were identified for both components at four development stages, among which 1401 proteins were non-redundant, 232 proteins were specific in pericarp and 153 proteins were specific in endosperm. A functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the tissue development. Three and 76 proteins involved in 49 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were integrated for the specific endosperm and pericarp proteins, respectively, reflecting their complex metabolic interactions. In addition, four proteins with important functions and different expression levels were chosen for gene cloning and expression analysis. Different concordance between mRNA level and the protein abundance was observed across different proteins, stages, and tissues as in previous research. These results could provide useful message for understanding the developmental mechanisms in grain development in maize.

Growth rate correlates negatively with protein turnover in Arabidopsis accessions

Previous studies with Arabidopsis accessions revealed that biomass correlates negatively to dusk starch content and total protein, and positively to the maximum activities of enzymes in photosynthesis. We hypothesized that large accessions have lower ribosome abundance and lower rates of protein synthesis, and that this is compensated by lower rates of protein degradation. This would increase growth efficiency and allow more investment in photosynthetic machinery. We analysed ribosome abundance and polysome loading in 19 accessions, modelled the rates of protein synthesis and compared them with the observed rate of growth. Large accessions contained less ribosomes than small accessions, due mainly to cytosolic ribosome abundance falling at night in large accessions. The modelled rates of protein synthesis resembled those required for growth in large accessions, but were up to 30% in excess in small accessions. We then employed ¹³ CO₂ pulse-chase labelling to measure the rates of protein synthesis and degradation in 13 accessions. Small accessions had a slightly higher rate of protein synthesis and much higher rates of protein degradation than large accessions. Protein turnover was negligible in large accessions but equivalent to up to 30% of synthesised protein day^-1 in small accessions. We discuss to what extent the decrease in growth in small accessions can be quantitatively explained by known costs of protein turnover and what factors may lead to the altered diurnal dynamics and increase of ribosome abundance in small accessions, and propose that there is a trade-off between protein turnover and maximisation of growth rate.

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis

BACKGROUND

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response.

RESULTS

In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways.

CONCLUSIONS

Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

UV-B Inhibits Leaf Growth through Changes in Growth Regulating Factors and Gibberellin Levels

Ultraviolet-B (UV-B) radiation affects leaf growth in a wide range of species. In this work, we demonstrate that UV-B levels present in solar radiation inhibit maize (Zea mays) leaf growth without causing any other visible stress symptoms, including the accumulation of DNA damage. We conducted kinematic analyses of cell division and expansion to understand the impact of UV-B radiation on these cellular processes. Our results demonstrate that the decrease in leaf growth in UV-B-irradiated leaves is a consequence of a reduction in cell production and a shortened growth zone (GZ). To determine the molecular pathways involved in UV-B inhibition of leaf growth, we performed RNA sequencing on isolated GZ tissues of control and UV-B-exposed plants. Our results show a link between the observed leaf growth inhibition and the expression of specific cell cycle and developmental genes, including growth-regulating factors (GRFs) and transcripts for proteins participating in different hormone pathways. Interestingly, the decrease in the GZ size correlates with a decrease in the concentration of GA19, the immediate precursor of the active gibberellin, GA1, by UV-B in this zone, which is regulated, at least in part, by the expression of GRF1 and possibly other transcription factors of the GRF family.

Altered expression of maize PLASTOCHRON1 enhances biomass and seed yield by extending cell division duration

Maize is the highest yielding cereal crop grown worldwide for grain or silage. Here, we show that modulating the expression of the maize PLASTOCHRON1 (ZmPLA1) gene, encoding a cytochrome P450 (CYP78A1), results in increased organ growth, seedling vigour, stover biomass and seed yield. The engineered trait is robust as it improves yield in an inbred as well as in a panel of hybrids, at several locations and over multiple seasons in the field. Transcriptome studies, hormone measurements and the expression of the auxin responsive DR5rev:mRFPer marker suggest that PLA1 may function through an increase in auxin. Detailed analysis of growth over time demonstrates that PLA1 stimulates the duration of leaf elongation by maintaining dividing cells in a proliferative, undifferentiated state for a longer period of time. The prolonged duration of growth also compensates for growth rate reduction caused by abiotic stresses.

Network-based integration of systems genetics data reveals pathways associated with lignocellulosic biomass accumulation and processing

As a consequence of their remarkable adaptability, fast growth, and superior wood properties, eucalypt tree plantations have emerged as key renewable feedstocks (over 20 million ha globally) for the production of pulp, paper, bioenergy, and other lignocellulosic products. However, most biomass properties such as growth, wood density, and wood chemistry are complex traits that are hard to improve in long-lived perennials. Systems genetics, a process of harnessing multiple levels of component trait information (e.g., transcript, protein, and metabolite variation) in populations that vary in complex traits, has proven effective for dissecting the genetics and biology of such traits. We have applied a network-based data integration (NBDI) method for a systems-level analysis of genes, processes and pathways underlying biomass and bioenergy-related traits using a segregating Eucalyptus hybrid population. We show that the integrative approach can link biologically meaningful sets of genes to complex traits and at the same time reveal the molecular basis of trait variation. Gene sets identified for related woody biomass traits were found to share regulatory loci, cluster in network neighborhoods, and exhibit enrichment for molecular functions such as xylan metabolism and cell wall development. These findings offer a framework for identifying the molecular underpinnings of complex biomass and bioprocessing-related traits. A more thorough understanding of the molecular basis of plant biomass traits should provide additional opportunities for the establishment of a sustainable bio-based economy.

Leaf growth in dicots and monocots: so different yet so alike

In plants, most organs grow post-embryonically through cell division and cell expansion. The coordination of these two growth processes is generally considered to be different between dicots and monocots. In dicot plants, such as the model plant Arabidopsis, leaf growth is most often described as being temporally regulated with cell division ceasing earlier at the tip and continuing longer at the base of the leaf. Conversely, in monocot leaves, the organization of the growth processes is rather viewed as spatially regulated with dividing cells at the base of the leaf, followed by expanding cells and finally mature cells at the tip. As our understanding of the leaf growth processes in the two major classes of flowering plants expands, it becomes increasingly clear that the regulation of the growth processes is to a great extent conserved between dicots and monocots. In this review, we highlight how the temporal and spatial organization of cell division and cell expansion takes place in both dicot and monocot leaves. We also show that there are similarities in the molecular wiring that coordinates these two processes during leaf development.

Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture

Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under nonlethal drought conditions is lacking. Recent advances in genomics, phenomics, and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of Arabidopsis thaliana accessions. The genetic architecture of the growth responses upon mild drought was investigated by subjecting the different leaf growth phenotypes to genome-wide association mapping and by characterizing the transcriptome of young developing leaves. Although no major effect locus was found to be associated with growth in mild drought, the transcriptome analysis delivered further insight into the natural variation of transcriptional responses to mild drought in a specific tissue. Coexpression analysis indicated the presence of gene clusters that co-vary over different genetic backgrounds, among others a cluster of genes with important regulatory functions in the growth response to osmotic stress. It was found that the occurrence of a mild drought stress response in leaves can be inferred with high accuracy across accessions based on the expression profile of 283 genes. A genome-wide association study on the expression data revealed that trans regulation seems to be more important than cis regulation in the transcriptional response to environmental perturbations.