Integration of omic networks in a developmental atlas of maize

Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors

The transcription regulatory network inside a eukaryotic cell is defined by the combinatorial actions of transcription factors (TFs). However, TF binding studies in plants are too few in number to produce a general picture of this complex network. In this study, we use large-scale ChIP-seq to reconstruct it in the maize leaf, and train machine-learning models to predict TF binding and co-localization. The resulting network covers 77% of the expressed genes, and shows a scale-free topology and functional modularity like a real-world network. TF binding sequence preferences are conserved within family, while co-binding could be key for their binding specificity. Cross-species comparison shows that core network nodes at the top of the transmission of information being more conserved than those at the bottom. This study reveals the complex and redundant nature of the plant transcription regulatory network, and sheds light on its architecture, organizing principle and evolutionary trajectory.

The Wheat GENIE3 Network Provides Biologically-Relevant Information in Polyploid Wheat

Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.

Genes and gene models, an important distinction

Genome sequencing has fundamentally changed how plant biologists think about genes. All or nearly all genes can ultimately be associated with a gene model. However, many gene models appear to play little or no role in the traits of an organism. A range of structural, molecular, population and evolutionary features all show a separation between genes with known phenotypes and the overall set of annotated gene models. These different features could be combined to develop models to distinguish the genes that determine the traits of plants from the subset gene other annotated gene models which are unlikely to play a role in doing so. Efforts to identify the subset of annotated gene models likely involved in specifying the characteristics of plants would help aid a wide range of researchers.

A transcriptomic analysis reveals the adaptability of the growth and physiology of immature tassel to long-term soil water deficit in Zea mays L

Drought is a key threat to maize growth and yield. Understanding the mechanism of immature tassel (IT) response to long term drought is of paramount importance. Here, the maize inbred line PH6WC was tested under well-watered (CK) and two water deficit treatments (WD1 and WD2). The final IT length in the WD1 and WD2 treatments decreased by nearly 6.2% and 21.2% compared to the CK, respectively, and the average accumulation rate IT dry matter was 1.5-fold and 1.8-fold slower, respectively. Furthermore, RNA sequencing analysis was conducted on the IT sampled at 30 days after the WD treatments. In total, the cellular component in gene ontology (GO) analysis suggested that the differentially expressed genes were significantly enriched in three common terms (apoplast, plant-type cell wall, and anchored component of membrane) among the CK vs WD1, CK vs WD2, and WD1 vs WD2 comparisons. Next, a co-expression network analysis identified 44 modules that contained global expression genes. Finally, by combining the GO analysis with modules, nine genes involved in carbohydrate metabolism and the antioxidant system were screened out, and the six corresponding physiological parameters were all significantly increased under the WD treatments. These results showed that, although the IT length and dry matter decreased, the IT enhanced the adaptation to drought by regulating their own genetic and physiological changes.

CXCL4 Links Inflammation and Fibrosis by Reprogramming Monocyte-Derived Dendritic Cells in vitro

Fibrosis is a condition shared by numerous inflammatory diseases. Our incomplete understanding of the molecular mechanisms underlying fibrosis has severely hampered effective drug development. CXCL4 is associated with the onset and extent of fibrosis development in multiple inflammatory and fibrotic diseases. Here, we used monocyte-derived cells as a model system to study the effects of CXCL4 exposure on dendritic cell development by integrating 65 longitudinal and paired whole genome transcriptional and methylation profiles. Using data-driven gene regulatory network analyses, we demonstrate that CXCL4 dramatically alters the trajectory of monocyte differentiation, inducing a novel pro-inflammatory and pro-fibrotic phenotype mediated via key transcriptional regulators including CIITA. Importantly, these pro-inflammatory cells directly trigger a fibrotic cascade by producing extracellular matrix molecules and inducing myofibroblast differentiation. Inhibition of CIITA mimicked CXCL4 in inducing a pro-inflammatory and pro-fibrotic phenotype, validating the relevance of the gene regulatory network. Our study unveils that CXCL4 acts as a key secreted factor driving innate immune training and forming the long-sought link between inflammation and fibrosis.

Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

The genomic sequences of crops continue to be produced at a frenetic pace. It remains challenging to develop complete annotations of functional genes and regulatory elements in these genomes. Chromatin accessibility assays enable discovery of functional elements; however, to uncover the full portfolio of cis-elements would require profiling of many combinations of cell types, tissues, developmental stages, and environments. Here, we explore the potential to use DNA methylation profiles to develop more complete annotations. Using leaf tissue in maize, we define ∼100,000 unmethylated regions (UMRs) that account for 5.8% of the genome; 33,375 UMRs are found greater than 2 kb from genes. UMRs are highly stable in multiple vegetative tissues, and they capture the vast majority of accessible chromatin regions from leaf tissue. However, many UMRs are not accessible in leaf, and these represent regions with potential to become accessible in specific cell types or developmental stages. These UMRs often occur near genes that are expressed in other tissues and are enriched for binding sites of transcription factors. The leaf-inaccessible UMRs exhibit unique chromatin modification patterns and are enriched for chromatin interactions with nearby genes. The total UMR space in four additional monocots ranges from 80 to 120 megabases, which is remarkably similar considering the range in genome size of 271 megabases to 4.8 gigabases. In summary, based on the profile from a single tissue, DNA methylation signatures provide powerful filters to distill large genomes down to the small fraction of putative functional genes and regulatory elements.

Genome-wide association studies and QTL mapping uncover the genetic architecture of ear tip-barrenness in maize

Ear tip-barrenness (ETB) phenotype threatens crop yield, because it reduces the kernel number per ear. The genetic basis of ETB in maize remains largely unknown. Herein, a genome-wide association study (GWAS) and quantitative trait loci (QTL) mapping were jointly applied to identify the significant genetic loci interrelated with ETB. Six significant SNPs were detected at a stringent P-value threshold (1.95 × 10^-6 ). Additionally, four environment-stable SNPs were co-detected across a single environment and best linear unbiased prediction (BLUP) model at a less stringent P-value threshold (1 × 10^-4 ). The above 10 SNPs were closely linked to 6 candidate genes, which mainly involved seed development, photosynthesis and ethylene response. Moreover, the ratio of superior allele at each significant SNP ranged from 0 to 83.33% in 30 investigated maize elite lines. QTL mapping identified 14 QTL with phenotypic variation explained (PVE) ranging from 3.64 to 7.09%, of which one QTL (qETB2-1) was repeatedly identified in two environments. Combined analysis of GWAS and QTL mapping showed that one SNP (PZE-102175229, chromosome 2: 217 66 Mb) was located in the QTL (qETB2-2, chromosome 2: 215 90-217 82 Mb). Eighteen gene models situated in the linkage disequilibrium (LD) region of the co-localized SNP were further used to evaluate their correlation with ETB by candidate gene association analysis. Two superior haplotypes and two superior alleles were detected among 74 lines for Zm00001d007195, Zm00001d007197 and Zm00001d007201. These results provide more information for clarifying the molecular mechanism of ETB and for speeding up the genetic improvement of maize varieties.

Dynamic regulation of Pep-induced immunity through post-translational control of defence transcript splicing

The survival of all living organisms requires the ability to detect attacks and swiftly counter them with protective immune responses. Despite considerable mechanistic advances, the interconnectivity of signalling modules often remains unclear. A newly characterized protein, IMMUNOREGULATORY RNA-BINDING PROTEIN (IRR), negatively regulates immune responses in both maize and Arabidopsis, with disrupted function resulting in enhanced disease resistance. IRR associates with and promotes canonical splicing of transcripts encoding defence signalling proteins, including the key negative regulator of pattern-recognition receptor signalling complexes, CALCIUM-DEPENDENT PROTEIN KINASE 28 (CPK28). On immune activation by Plant Elicitor Peptides (Peps), IRR is dephosphorylated, disrupting interaction with CPK28 transcripts and resulting in the accumulation of an alternative splice variant encoding a truncated CPK28 protein with impaired kinase activity and diminished function as a negative regulator. We demonstrate a new mechanism linking Pep-induced post-translational modification of IRR with post-transcriptionally mediated attenuation of CPK28 function to dynamically amplify Pep signalling and immune output.

Genomic, Transcriptomic and Epigenomic Tools to Study the Domestication of Plants and Animals: A Field Guide for Beginners

In the last decade, genomics and the related fields of transcriptomics and epigenomics have revolutionized the study of the domestication process in plants and animals, leading to new discoveries and new unresolved questions. Given that some domesticated taxa have been more studied than others, the extent of genomic data can range from vast to nonexistent, depending on the domesticated taxon of interest. This review is meant as a rough guide for students and academics that want to start a domestication research project using modern genomic tools, as well as for researchers already conducting domestication studies that are interested in following a genomic approach and looking for alternate strategies (cheaper or more efficient) and future directions. We summarize the theoretical and technical background needed to carry out domestication genomics, starting from the acquisition of a reference genome and genome assembly, to the sampling design for population genomics, paleogenomics, transcriptomics, epigenomics and experimental validation of domestication-related genes. We also describe some examples of the aforementioned approaches and the relevant discoveries they made to understand the domestication of the studied taxa.

Lipid Metabolism: Critical Roles in Male Fertility and Other Aspects of Reproductive Development in Plants

Fatty acids and their derivatives are essential building blocks for anther cuticle and pollen wall formation. Disruption of lipid metabolism during anther and pollen development often leads to genic male sterility (GMS). To date, many lipid metabolism-related GMS genes that are involved in the formation of anther cuticle, pollen wall, and subcellular organelle membranes in anther wall layers have been identified and characterized. In this review, we summarize recent progress on characterizing lipid metabolism-related genes and their roles in male fertility and other aspects of reproductive development in plants. On the basis of cloned GMS genes controlling biosynthesis and transport of anther cutin, wax, sporopollenin, and tryphine in Arabidopsis, rice, and maize as well as other plant species, updated lipid metabolic networks underlying anther cuticle development and pollen wall formation were proposed. Through bioinformatics analysis of anther RNA-sequencing datasets from three maize inbred lines (Oh43, W23, and B73), a total of 125 novel lipid metabolism-related genes putatively involved in male fertility in maize were deduced. More, we discuss the pathways regulating lipid metabolism-related GMS genes at the transcriptional and post-transcriptional levels. Finally, we highlight recent findings on lipid metabolism-related genes and their roles in other aspects of plant reproductive development. A comprehensive understanding of lipid metabolism, genes involved, and their roles in plant reproductive development will facilitate the application of lipid metabolism-related genes in gene editing, haploid and callus induction, molecular breeding and hybrid seed production in crops.

Elongating maize root: zone-specific combinations of polysaccharides from type I and type II primary cell walls

The dynamics of cell wall polysaccharides may modulate the cell wall mechanics and thus control the expansion growth of plant cells. The unique composition of type II primary cell wall characteristic of grasses suggests that they employ specific mechanisms for cell enlargement. We characterized the transcriptomes in five zones along maize root, clustered the expression of genes for numerous glycosyltransferases and performed extensive immunohistochemical analysis to relate the changes in cell wall polysaccharides to critical stages of cell development in Poaceae. Specific patterns of cell wall formation differentiate the initiation, realization and cessation of elongation growth. Cell walls of meristem and early elongation zone represent a mixture of type I and type II specific polysaccharides. Xyloglucans and homogalacturonans are synthesized there actively together with mixed-linkage glucans and glucuronoarabinoxylans. Rhamnogalacturonans-I with the side-chains of branched 1,4-galactan and arabinan persisted in cell walls throughout the development. Thus, the machinery to generate the type I primary cell wall constituents is completely established and operates. The expression of glycosyltransferases responsible for mixed-linkage glucan and glucuronoarabinoxylan synthesis peaks at active or late elongation. These findings widen the number of jigsaw pieces which should be put together to solve the puzzle of grass cell growth.

Non-homology-based prediction of gene functions in maize (Zea mays ssp. mays)

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions. As a result, homology is widely used for gene function prediction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random-forest-based prediction consistently provided the most accurate gene function prediction. Non-homology-based functional annotation provides complementary strengths to homology-based annotation, with higher average performance in Biological Process GO terms, the domain where homology-based functional annotation performs the worst, and weaker performance in Molecular Function GO terms, the domain where the accuracy of homology-based functional annotation is highest. GO prediction models trained with homology-based annotations were able to successfully predict annotations from a manually curated "gold standard" GO annotation set. Non-homology-based functional annotation based on machine learning may ultimately prove useful both as a method to assign predicted functions to orphan genes which lack functionally characterized homologs, and to identify and correct functional annotation errors which were propagated through homology-based functional annotations.

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

Across all facets of biology, the rapid progress in high-throughput data generation has enabled us to perform multi-omics systems biology research. Transcriptomics, proteomics, and metabolomics data can answer targeted biological questions regarding the expression of transcripts, proteins, and metabolites, independently, but a systematic multi-omics integration (MOI) can comprehensively assimilate, annotate, and model these large data sets. Previous MOI studies and reviews have detailed its usage and practicality on various organisms including human, animals, microbes, and plants. Plants are especially challenging due to large poorly annotated genomes, multi-organelles, and diverse secondary metabolites. Hence, constructive and methodological guidelines on how to perform MOI for plants are needed, particularly for researchers newly embarking on this topic. In this review, we thoroughly classify multi-omics studies on plants and verify workflows to ensure successful omics integration with accurate data representation. We also propose three levels of MOI, namely element-based (level 1), pathway-based (level 2), and mathematical-based integration (level 3). These MOI levels are described in relation to recent publications and tools, to highlight their practicality and function. The drawbacks and limitations of these MOI are also discussed for future improvement toward more amenable strategies in plant systems biology.

Dicer-like 5 deficiency confers temperature-sensitive male sterility in maize

Small RNAs play important roles during plant development by regulating transcript levels of target mRNAs, maintaining genome integrity, and reinforcing DNA methylation. Dicer-like 5 (Dcl5) is proposed to be responsible for precise slicing in many monocots to generate diverse 24-nt phased, secondary small interfering RNAs (phasiRNAs), which are exceptionally abundant in meiotic anthers of diverse flowering plants. The importance and functions of these phasiRNAs remain unclear. Here, we characterized several mutants of dcl5, including alleles generated by the clustered regularly interspaced short palindromic repeats (CRISPR)–Cas9 system and a transposon-disrupted allele. We report that dcl5 mutants have few or no 24-nt phasiRNAs, develop short anthers with defective tapetal cells, and exhibit temperature-sensitive male fertility. We propose that DCL5 and 24-nt phasiRNAs are critical for fertility under growth regimes for optimal yield.

Small RNAs act to regulate gene or transposon activity during plant development. Here, the authors show that maize Dicer-like 5 is required for 24-nt phased, secondary small interfering RNA production in anthers and that dicer-like 5 mutants show abnormal tapetal development and temperature-sensitive sterility.

ZEAMAP, a Comprehensive Database Adapted to the Maize Multi-Omics Era

As one of the most extensively cultivated crops, maize (Zea mays L.) has been extensively studied by researchers and breeders for over a century. With advances in high-throughput detection of various omics data, a wealth of multi-dimensional and multi-omics information has been accumulated for maize and its wild relative, teosinte. Integration of this information has the potential to accelerate genetic research and generate improvements in maize agronomic traits. To this end, we constructed ZEAMAP, a comprehensive database incorporating multiple reference genomes, annotations, comparative genomics, transcriptomes, open chromatin regions, chromatin interactions, high-quality genetic variants, phenotypes, metabolomics, genetic maps, genetic mapping loci, population structures, and populational DNA methylation signals within maize inbred lines. ZEAMAP is user friendly, with the ability to interactively integrate, visualize, and cross-reference multiple different omics datasets.

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Functional annotations and comparative genomics of maize and teosinte genomes

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Multi-omics data generated from the same maize inbred lines panel

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Interactive tools to query, cross-refer, and visualize the omics data

Dark response genes: a group of endogenous pendulum/timing players in maize?

MAIN CONCLUSION

Maize has a set of dark response genes, expression of which is influenced by multiple factor and varies with maize inbred lines but without germplasm specificity. The response to photoperiod is a common biological issue across the species kingdoms. Dark is as important as light in photoperiod. However, further in-depth understanding of responses of maize (Zea mays) to light and dark transition under photoperiod is hindered due to the lack of understanding of dark response genes. With multiple public "-omic" datasets of temperate and tropical/subtropical maize, 16 maize dark response genes, ZmDRGs, were found and had rhythmic expression under dark and light-dark cycle. ZmDRGs 6-8 were tandemly duplicated. ZmDRGs 2, 13, and 14 had a chromosomal collinearity with other maize genes. ZmDRGs 1-11 and 13-16 had copy-number variations. ZmDRGs 2, 9, and 16 showed 5'-end sequence deletion mutations. Some ZmDRGs had chromatin interactions and underwent DNA methylation and/or m6A mRNA methylation. Chromosomal histones associated with 15 ZmDRGs were methylated and acetylated. ZmDRGs 1, 2, 4, 9, and 13 involved photoperiodic phenotypes. ZmDRG16 was within flowering-related QTLs. ZmDRGs 1, 3, and 6-11 were present in cis-acting expression QTLs (eQTLs). ZmDRGs 1, 4, 6-9, 11, 12, and 14-16 showed co-expression with other maize genes. Some of ZmDRG-encoded ZmDRGs showed obvious differences in abundance and phosphorylation.

CONCLUSION

Sixteen ZmDRGs 1-16 are associated with the dark response of maize. In the process of post-domestication and/or breeding, the ZmDRGs undergo the changes without germplasm specificity, including epigenetic modifications, gene copy numbers, chromatin interactions, and deletion mutations. In addition to effects by these factors, ZmDRG expression is influenced by promoter elements, cis-acting eQTLs, and co-expression networks.

Structural evolution drives diversification of the large LRR-RLK gene family

●Cells are continuously exposed to chemical signals that they must discriminate between and respond to appropriately. In embryophytes, the leucine-rich repeat receptor-like kinases (LRR-RLKs) are signal receptors critical in development and defense. LRR-RLKs have diversified to hundreds of genes in many plant genomes. Although intensively studied, a well-resolved LRR-RLK gene tree has remained elusive. ●To resolve the LRR-RLK gene tree, we developed an improved gene discovery method based on iterative hidden Markov model searching and phylogenetic inference. We used this method to infer complete gene trees for each of the LRR-RLK subclades and reconstructed the deepest nodes of the full gene family. ●We discovered that the LRR-RLK gene family is even larger than previously thought, and that protein domain gains and losses are prevalent. These structural modifications, some of which likely predate embryophyte diversification, led to misclassification of some LRR-RLK variants as members of other gene families. Our work corrects this misclassification. ●Our results reveal ongoing structural evolution generating novel LRR-RLK genes. These new genes are raw material for the diversification of signaling in development and defense. Our methods also enable phylogenetic reconstruction in any large gene family.

MaizeGDB 2018: the maize multi-genome genetics and genomics database

Since its 2015 update, MaizeGDB, the Maize Genetics and Genomics database, has expanded to support the sequenced genomes of many maize inbred lines in addition to the B73 reference genome assembly. Curation and development efforts have targeted high quality datasets and tools to support maize trait analysis, germplasm analysis, genetic studies, and breeding. MaizeGDB hosts a wide range of data including recent support of new data types including genome metadata, RNA-seq, proteomics, synteny, and large-scale diversity. To improve access and visualization of data types several new tools have been implemented to: access large-scale maize diversity data (SNPversity), download and compare gene expression data (qTeller), visualize pedigree data (Pedigree Viewer), link genes with phenotype images (MaizeDIG), and enable flexible user-specified queries to the MaizeGDB database (MaizeMine). MaizeGDB also continues to be the community hub for maize research, coordinating activities and providing technical support to the maize research community. Here we report the changes MaizeGDB has made within the last three years to keep pace with recent software and research advances, as well as the pan-genomic landscape that cheaper and better sequencing technologies have made possible. MaizeGDB is accessible online at https://www.maizegdb.org.

Genome-wide association study leads to novel genetic insights into resistance to Aspergillus flavus in maize kernels

BACKGROUND

Fungus infection in staple grains affects the food storage and threatens food security. The Aspergillus flavus is known to infect multiple grains and produce mycotoxin Aflatoxin B1, which is mutagenic, teratogenic and causes immunosuppression in animals. However, the molecular mechanism of maize resistance to A. flavus is largely unknown.

RESULTS

Here we used corn kernels to investigate resistance genes to A. flavus using genome-wide association study (GWAS) of 313 inbred lines. We characterized the resistance levels of kernels after inoculating with A. flavus. The GWAS with 558,529 SNPs identified four associated loci involving 29 candidate genes that were linked to seed development, resistance or infection, and involved in signal pathways, seed development, germination, dormancy, epigenetic modification, and antimicrobial activity. In addition, a few candidate genes were also associated with several G-protein signaling and phytohormones that might involve in synergistic work conferring different resistance during seed development. Expression of 16 genes out of 29 during kernel development was also associated with resistance levels.

CONCLUSIONS

We characterized the resistance levels of 313 maize kernels after inoculating with A. flavus, and found four associated loci and 16 candidate maize genes. The expressed 16 genes involved in kernel structure and kernel composition most likely contribute to mature maize kernels' resistance to A. flavus, and in particular, in the development of pericarp. The linked candidate genes could be experimentally transformed to validate and manipulate fungal resistance. Thus this result adds value to maize kernels in breeding programs.

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.

Gene Balance Predicts Transcriptional Responses Immediately Following Ploidy Change in Arabidopsis thaliana

The gene balance hypothesis postulates that there is selection on gene copy number (gene dosage) to preserve the stoichiometric balance among interacting proteins. This presupposes that gene product abundance is governed by gene dosage and that gene dosage responses are consistent for interacting genes in a dosage-balance-sensitive network or complex. Gene dosage responses, however, have rarely been quantified, and the available data suggest that they are highly variable. We sequenced the transcriptomes of two synthetic autopolyploid accessions of Arabidopsis (Arabidopsis thaliana) and their diploid progenitors, as well as one natural tetraploid and its synthetic diploid produced via haploid induction, to estimate transcriptome size and dosage responses immediately following ploidy change. Similar to what has been observed in previous studies, overall transcriptome size does not exhibit a simple doubling in response to genome doubling, and individual gene dosage responses are highly variable in all three accessions, indicating that expression is not strictly coupled with gene dosage. Nonetheless, putatively dosage balance-sensitive gene groups (Gene Ontology terms, metabolic networks, gene families, and predicted interacting proteins) exhibit smaller and more coordinated dosage responses than do putatively dosage-insensitive gene groups, suggesting that constraints on dosage balance operate immediately following whole-genome duplication and that duplicate gene retention patterns are shaped by selection to preserve dosage balance.

High expression in maize pollen correlates with genetic contributions to pollen fitness as well as with coordinated transcription from neighboring transposable elements

In flowering plants, gene expression in the haploid male gametophyte (pollen) is essential for sperm delivery and double fertilization. Pollen also undergoes dynamic epigenetic regulation of expression from transposable elements (TEs), but how this process interacts with gene expression is not clearly understood. To explore relationships among these processes, we quantified transcript levels in four male reproductive stages of maize (tassel primordia, microspores, mature pollen, and sperm cells) via RNA-seq. We found that, in contrast with vegetative cell-limited TE expression in Arabidopsis pollen, TE transcripts in maize accumulate as early as the microspore stage and are also present in sperm cells. Intriguingly, coordinate expression was observed between highly expressed protein-coding genes and their neighboring TEs, specifically in mature pollen and sperm cells. To investigate a potential relationship between elevated gene transcript level and pollen function, we measured the fitness cost (male-specific transmission defect) of GFP-tagged coding sequence insertion mutations in over 50 genes identified as highly expressed in the pollen vegetative cell, sperm cell, or seedling (as a sporophytic control). Insertions in seedling genes or sperm cell genes (with one exception) exhibited no difference from the expected 1:1 transmission ratio. In contrast, insertions in over 20% of vegetative cell genes were associated with significant reductions in fitness, showing a positive correlation of transcript level with non-Mendelian segregation when mutant. Insertions in maize gamete expressed2 (Zm gex2), the sole sperm cell gene with measured contributions to fitness, also triggered seed defects when crossed as a male, indicating a conserved role in double fertilization, given the similar phenotype previously demonstrated for the Arabidopsis ortholog GEX2. Overall, our study demonstrates a developmentally programmed and coordinated transcriptional activation of TEs and genes in pollen, and further identifies maize pollen as a model in which transcriptomic data have predictive value for quantitative phenotypes.

Integrated multi-omics framework of the plant response to jasmonic acid

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways.

Integrated multi-omics framework of the plant response to jasmonic acid

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways.

Discovery of modules involved in the biosynthesis and regulation of maize phenolic compounds

Phenolic compounds are among the most diverse and widespread of specialized plant compounds and underly many important agronomic traits. Our comprehensive analysis of the maize genome unraveled new aspects of the genes involved in phenylpropanoid, monolignol, and flavonoid production in this important crop. Remarkably, just 19 genes accounted for 70 % of the overall mRNA accumulation of these genes across 95 tissues, indicating that these are the main contributors to the flux of phenolic metabolites. Eighty genes with intermediate to low expression play minor and more specialized roles. Remaining genes are likely undergoing loss of function or are expressed in limited cell types. Phylogenetic and expression analyses revealed which members of gene families governing metabolic entry and branch points exhibit duplication, subfunctionalization, or loss of function. Co-expression analysis applied to genes in sequential biosynthetic steps revealed that certain isoforms are highly co-expressed and are candidates for metabolic complexes that ensure metabolite delivery to correct cellular compartments. Co-expression of biosynthesis genes with transcription factors discovered connections that provided candidate components for regulatory modules governing this pathway. Our study provides a comprehensive analysis of maize phenylpropanoid related genes, identifies major pathway contributors, and novel candidate enzymatic and regulatory modules of the metabolic network.

CUBIC: an atlas of genetic architecture promises directed maize improvement

BACKGROUND

Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders.

RESULTS

Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width.

CONCLUSIONS

Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits.

The Past, Present, and Future of Maize Improvement: Domestication, Genomics, and Functional Genomic Routes toward Crop Enhancement

After being domesticated from teosinte, cultivated maize (Zea mays ssp. mays) spread worldwide and now is one of the most important staple crops. Due to its tremendous phenotypic and genotypic diversity, maize also becomes to be one of the most widely used model plant species for fundamental research, with many important discoveries reported by maize researchers. Here, we provide an overview of the history of maize domestication and key genes controlling major domestication-related traits, review the currently available resources for functional genomics studies in maize, and discuss the functions of most of the maize genes that have been positionally cloned and can be used for crop improvement. Finally, we provide some perspectives on future directions regarding functional genomics research and the breeding of maize and other crops.

Tissue-specific gene expression and protein abundance patterns are associated with fractionation bias in maize

BACKGROUND

Maize experienced a whole-genome duplication event approximately 5 to 12 million years ago. Because this event occurred after speciation from sorghum, the pre-duplication subgenomes can be partially reconstructed by mapping syntenic regions to the sorghum chromosomes. During evolution, maize has had uneven gene loss between each ancient subgenome. Fractionation and divergence between these genomes continue today, constantly changing genetic make-up and phenotypes and influencing agronomic traits.

RESULTS

Here we regenerate the subgenome reconstructions for the most recent maize reference genome assembly. Based on both expression and abundance data for homeologous gene pairs across multiple tissues, we observed functional divergence of genes across subgenomes. Although the genes in the larger maize subgenome are often expressing more highly than their homeologs in the smaller subgenome, we observed cases where homeolog expression dominance switches in different tissues. We demonstrate for the first time that protein abundances are higher in the larger subgenome, but they also show tissue-specific dominance, a pattern similar to RNA expression dominance. We also find that pollen expression is uniquely decoupled from protein abundance.

CONCLUSION

Our study shows that the larger subgenome has a greater range of functional assignments and that there is a relative lack of overlap between the subgenomes in terms of gene functions than would be suggested by similar patterns of gene expression and protein abundance. Our study also revealed that some reactions are catalyzed uniquely by the larger and smaller subgenomes. The tissue-specific, nonequivalent expression-level dominance pattern observed here implies a change in regulatory control which favors differentiated selective pressure on the retained duplicates leading to eventual change in gene functions.

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size-related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10^-6 ) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10^-3 ) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable-effect SNPs and the co-localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co-localized SNPs, of which zma-miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma-miR164e resulted in the down-regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker-assisted selection (MAS) for high-yield breeding in maize.

Quantitative Profiling of Protein Abundance and Phosphorylation State in Plant Tissues Using Tandem Mass Tags

Proteins produce or regulate nearly every component of cells. Thus, the ability to quantitatively determine the protein abundance and posttranslational modification (PTM) state is a critical aspect toward our understanding of biological processes. In this chapter, we describe methods to globally quantify protein abundance and phosphorylation state using isobaric labeling with tandem mass tags followed by phosphopeptide enrichment.

Targeted Quantification of Phosphopeptides by Parallel Reaction Monitoring (PRM)

Parallel reaction monitoring (PRM) is a liquid chromatography-mass spectrometry (LC-MS)-based targeted peptide/protein quantification method that was initially implemented for Orbitrap mass spectrometers. Here, we describe detailed workflows that utilize the freely available MaxQuant and Skyline software packages to target peptides of interest, primarily focusing on phosphopeptides.

RGPDB: database of root-associated genes and promoters in maize, soybean, and sorghum

Root-associated genes play an important role in plants. Despite the fact that there have been studies on root biology, information on genes that are specifically expressed or upregulated in roots is poorly collected. There exist very few databases dedicated to genes and promoters associated with root biology, preventing effective root-related studies. Therefore, we analyzed multiple types of omics data to identify root-associated genes in maize, soybean, and sorghum and constructed a comprehensive online database of these genes and their promoter sequences. This database creates a pivotal platform capable of stimulating and facilitating further studies on manipulating root growth and development.

Regulation of auxin transcriptional responses

The plant hormone auxin acts as a signaling molecule to regulate a vast number of developmental responses throughout all stages of plant growth. Tight control and coordination of auxin signaling is required for the generation of specific auxin‐response outputs. The nuclear auxin signaling pathway controls auxin‐responsive gene transcription through the TRANSPORT INHIBITOR RESPONSE1/AUXIN SIGNALING F‐BOX pathway. Recent work has uncovered important details into how regulation of auxin signaling components can generate unique and specific responses to determine auxin outputs. In this review, we discuss what is known about the core auxin signaling components and explore mechanisms important for regulating auxin response specificity.

A review of recent updates to our understanding of auxin signaling.

Transposable elements contribute to dynamic genome content in maize

Transposable elements (TEs) are ubiquitous components of eukaryotic genomes and can create variation in genome organization and content. Most maize genomes are composed of TEs. We developed an approach to define shared and variable TE insertions across genome assemblies and applied this method to four maize genomes (B73, W22, Mo17 and PH207) with uniform structural annotations of TEs. Among these genomes we identified approximately 400 000 TEs that are polymorphic, encompassing 1.6 Gb of variable TE sequence. These polymorphic TEs include a combination of recent transposition events as well as deletions of older TEs. There are examples of polymorphic TEs within each of the superfamilies of TEs and they are found distributed across the genome, including in regions of recent shared ancestry among individuals. There are many examples of polymorphic TEs within or near maize genes. In addition, there are 2380 gene annotations in the B73 genome that are located within variable TEs, providing evidence for the role of TEs in contributing to the substantial differences in annotated gene content among these genotypes. TEs are highly variable in our survey of four temperate maize genomes, highlighting the major contribution of TEs in driving variation in genome organization and gene content. OPEN RESEARCH BADGES: This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://github.com/SNAnderson/maizeTE_variation; https://mcstitzer.github.io/maize_TEs.

Widespread long-range cis-regulatory elements in the maize genome

Genetic mapping studies on crops suggest that agronomic traits can be controlled by gene-distal intergenic loci. Despite the biological importance and the potential agronomic utility of these loci, they remain virtually uncharacterized in all crop species to date. Here, we provide genetic, epigenomic and functional molecular evidence to support the widespread existence of gene-distal (hereafter, distal) loci that act as long-range transcriptional cis-regulatory elements (CREs) in the maize genome. Such loci are enriched for euchromatic features that suggest their regulatory functions. Chromatin loops link together putative CREs with genes and recapitulate genetic interactions. Putative CREs also display elevated transcriptional enhancer activities, as measured by self-transcribing active regulatory region sequencing. These results provide functional support for the widespread existence of CREs that act over large genomic distances to control gene expression.

Challenges of Translating Gene Regulatory Information into Agronomic Improvements

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

Dynamic Patterns of Transcript Abundance of Transposable Element Families in Maize

Transposable Elements (TEs) are mobile elements that contribute the majority of DNA sequences in the maize genome. Due to their repetitive nature, genomic studies of TEs are complicated by the difficulty of properly attributing multi-mapped short reads to specific genomic loci. Here, we utilize a method to attribute RNA-seq reads to TE families rather than particular loci in order to characterize transcript abundance for TE families in the maize genome. We applied this method to assess per-family expression of transposable elements in >800 published RNA-seq libraries representing a range of maize development, genotypes, and hybrids. While a relatively small proportion of TE families are transcribed, expression is highly dynamic with most families exhibiting tissue-specific expression. A large number of TE families were specifically detected in pollen and endosperm, consistent with reproductive dynamics that maintain silencing of TEs in the germ line. We find that B73 transcript abundance is a poor predictor of TE expression in other genotypes and that transcript levels can differ even for shared TEs. Finally, by assessing recombinant inbred line and hybrid transcriptomes, complex patterns of TE transcript abundance across genotypes emerged. Taken together, this study reveals a dynamic contribution of TEs to maize transcriptomes.

Whole-Genome and Transposed Duplication Contributes to the Expansion and Diversification of TLC Genes in Maize

TLC (TRAM/LAG/CRN8) proteins play important roles in ceramide metabolism and mycotoxin resistance. Herein a comparative genomics analysis of TLCs was performed in 31 plant and 3 species from other kingdoms, with an emphasis mainly on maize. TLCs were conserved across kingdoms and expanded in angiosperms, largely due to whole-genome/segmental duplication (WGD/SD) under purifying selection. Phylogeny reconstruction by maximum-likelihood method uncovered five TLC clades, subsequently named as TRAM/LAG, CLN8, PS-TLC, TM136 and TLCD clades. Each clade of TLCs shared specific transmembrane regions and motif composition. Divisions of conserved motifs to subunits may have occurred in TM136-type TLCs. Focusing on maize, five WGD and two DNA-mediated transposed duplication (TD) pairs were discovered, accounting for 61.11% ZmTLCs. Combined with further expression analysis, significant divergence was found in expression patterns between most maize WGD pairs, indicating subfunctionalization or/and neofunctionalization. Moreover, ZmTLC5, a deduced parental copy in a TD pair, was highly induced under FB₁ and fungus pathogen injection and exhibited potential capacity to respond to environmental stimuli. Additionally, population genetics analysis showed that ZmTLC10 in the CLN8-clade may have experienced significant positive selection and differentiated between wild and inbred maize populations. Overall, our results help to decipher the evolutionary history of TLCs in maize and plants, facilitating further functional analysis of them.

Low-fluence blue light-induced phosphorylation of Zmphot1 mediates the first positive phototropism

Phototropin1 (phot1) perceives low- to high-fluence blue light stimuli and mediates both the first and second positive phototropisms. High-fluence blue light is known to induce autophosphorylation of phot1, leading to the second positive phototropism. However, the phosphorylation status of phot1 by low-fluence blue light that induces the first positive phototropism had not been observed. Here, we conducted a phosphoproteomic analysis of maize coleoptiles to investigate the fluence-dependent phosphorylation status of Zmphot1. High-fluence blue light induced phosphorylation of Zmphot1 at several sites. Notably, low-fluence blue light significantly increased the phosphorylation level of Ser291 in Zmphot1. Furthermore, Ser291-phosphorylated and Ser369Ser376-diphosphorylated peptides were found to be more abundant in the low-fluence blue light-irradiated sides than in the shaded sides of coleoptiles. The roles of these phosphorylation events in phototropism were explored by heterologous expression of ZmPHOT1 in the Arabidopsis thaliana phot1phot2 mutant. The first positive phototropism was restored in wild-type ZmPHOT1-expressing plants; however, plants expressing S291A-ZmPHOT1 or S369AS376A-ZmPHOT1 showed significantly reduced complementation rates. All transgenic plants tested in this study exhibited a normal second positive phototropism. These findings provide the first indication that low-fluence blue light induces phosphorylation of Zmphot1 and that this induced phosphorylation is crucial for the first positive phototropism.

Protein and Proteome Atlas for Plants under Stresses: New Highlights and Ways for Integrated Omics in Post-Genomics Era

In the post-genomics era, integrative omics studies for biochemical, physiological, and molecular changes of plants in response to stress conditions play more crucial roles. Among them, atlas analysis of plants under different abiotic stresses, including salinity, drought, and toxic conditions, has become more important for uncovering the potential key genes and proteins in different plant tissues. High-quality genomic data and integrated analyses of transcriptomic, proteomic, metabolomics, and phenomic patterns provide a deeper understanding of how plants grow and survive under environmental stresses. This editorial mini-review aims to synthesize the 27 papers including two timely reviews that have contributed to this Special Issue, which focuses on concluding the recent progress in the Protein and Proteome Atlas in plants under different stresses. It covers various aspects of plant proteins ranging from agricultural proteomics, structure and function of proteins, novel techniques and approaches for gene and protein identification, protein quantification, proteomics for post-translational modifications (PTMs), and new insights into proteomics. The proteomics-based results in this issue will help the readers to gain novel insights for the understanding of complicated physiological processes in crops and other important plants in response to stressed conditions. Furthermore, these target genes and proteins that are important candidates for further functional validation in economic plants and crops can be studied.

Rethinking the PDH Bypass and GABA Shunt as Thiamin-Deficiency Workarounds

The PDH bypass and the GABA shunt serve to maintain mainline metabolic fluxes during episodes of organellar thiamin diphosphate deficiency.

Maize HSFA2 and HSBP2 antagonistically modulate raffinose biosynthesis and heat tolerance in Arabidopsis

Raffinose is thought to play an important role in plant tolerance of abiotic stress. We report here that maize HEAT SHOCK FACTOR A2 (ZmHSFA2) and HEAT SHOCK BINDING PROTEIN 2 (ZmHSBP2) physically interact with each other and antagonistically modulate expression of GALACTINOL SYNTHASE2 (ZmGOLS2) and raffinose biosynthesis in transformed maize protoplasts and Arabidopsis plants. Overexpression of ZmHSFA2 in Arabidopsis increased the expression of Arabidopsis AtGOLS1, AtGOLS2 and AtRS5 (RAFFINOSE SYNTHASE), increased the raffinose content in leaves and enhanced plant heat stress tolerance. Contrary to ZmHSFA2, overexpression of ZmHSBP2 in Arabidopsis decreased expression of AtGOLS1, AtGOLS2 and AtRS5, decreased the raffinose content in leaves and reduced plant heat stress tolerance. ZmHSFA2 and ZmHSBP2 also interact with their Arabidopsis counterparts AtHSBP and AtHSFA2 as determined using bimolecular fluorescence complementation assays. Furthermore, endogenous ZmHSBP2 and Rluc, controlled by the ZmHSBP2 promoter, are transcriptionally activated by ZmHSFA2 and inhibited by ZmHSBP2 in maize protoplasts. These findings provide insights into the transcriptional regulation of raffinose biosynthetic genes, and the tolerance their product confers to plant heat stress.

Data Integration in Poplar: 'Omics Layers and Integration Strategies

Populus trichocarpa is an important biofuel feedstock that has been the target of extensive research and is emerging as a model organism for plants, especially woody perennials. This research has generated several large ‘omics datasets. However, only few studies in Populus have attempted to integrate various data types. This review will summarize various ‘omics data layers, focusing on their application in Populus species. Subsequently, network and signal processing techniques for the integration and analysis of these data types will be discussed, with particular reference to examples in Populus.

Evolutionary flexibility in flooding response circuitry in angiosperms

Flooding due to extreme weather threatens crops and ecosystems. To understand variation in gene regulatory networks activated by submergence, we conducted a high-resolution analysis of chromatin accessibility and gene expression at three scales of transcript control in four angiosperms, ranging from a dryland-adapted wild species to a wetland crop. The data define a cohort of conserved submergence-activated genes with signatures of overlapping cis regulation by four transcription factor families. Syntenic genes are more highly expressed than nonsyntenic genes, yet both can have the cis motifs and chromatin accessibility associated with submergence up-regulation. Whereas the flexible circuitry spans the eudicot-monocot divide, the frequency of specific cis motifs, extent of chromatin accessibility, and degree of submergence activation are more prevalent in the wetland crop and may have adaptive importance.

Monitoring the interplay between transposable element families and DNA methylation in maize

DNA methylation and epigenetic silencing play important roles in the regulation of transposable elements (TEs) in many eukaryotic genomes. A majority of the maize genome is derived from TEs that can be classified into different orders and families based on their mechanism of transposition and sequence similarity, respectively. TEs themselves are highly methylated and it can be tempting to view them as a single uniform group. However, the analysis of DNA methylation profiles in flanking regions provides evidence for distinct groups of chromatin properties at different TE families. These differences among TE families are reproducible in different tissues and different inbred lines. TE families with varying levels of DNA methylation in flanking regions also show distinct patterns of chromatin accessibility and modifications within the TEs. The differences in the patterns of DNA methylation flanking TE families arise from a combination of non-random insertion preferences of TE families, changes in DNA methylation triggered by the insertion of the TE and subsequent selection pressure. A set of nearly 70,000 TE polymorphisms among four assembled maize genomes were used to monitor the level of DNA methylation at haplotypes with and without the TE insertions. In many cases, TE families with high levels of DNA methylation in flanking sequence are enriched for insertions into highly methylated regions. The majority of the >2,500 TE insertions into unmethylated regions result in changes in DNA methylation in haplotypes with the TE, suggesting the widespread potential for TE insertions to condition altered methylation in conserved regions of the genome. This study highlights the interplay between TEs and the methylome of a major crop species.

Unified feature association networks through integration of transcriptomic and proteomic data

High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks, networks that have a large number of edges that link nodes of different-omic types (transcripts, proteins, lipids etc). We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm mechanisms of disease.

Gene Expression Maps in Plants: Current State and Prospects

For many years, progress in the identification of gene functions has been based on classical genetic approaches. However, considerable recent omics developments have brought to the fore indirect but high-resolution methods of gene function identification such as transcriptomics, proteomics, and metabolomics. A transcriptome map is a powerful source of functional information and the result of the genome-wide expression analysis of a broad sampling of tissues and/or organs from different developmental stages and/or environmental conditions. In plant science, the application of transcriptome maps extends from the inference of gene regulatory networks to evolutionary studies. However, only some of these data have been integrated into databases, thus enabling analyses to be conducted without raw data; without this integration, extensive data preprocessing is required, which limits data usability. In this review, we summarize the state of plant transcriptome maps, analyze the problems associated with the combined analysis of large-scale data from various studies, and outline possible solutions to these problems.

Identification of the expressome by machine learning on omics data

Accurate annotation of plant genomes remains complex due to the presence of many pseudogenes arising from whole-genome duplication-generated redundancy or the capture and movement of gene fragments by transposable elements. Machine learning on genome-wide epigenetic marks, informed by transcriptomic and proteomic training data, could be used to improve annotations through classification of all putative protein-coding genes as either constitutively silent or able to be expressed. Expressed genes were subclassified as able to express both mRNAs and proteins or only RNAs, and CG gene body methylation was associated only with the former subclass. More than 60,000 protein-coding genes have been annotated in the reference genome of maize inbred B73. About two-thirds of these genes are transcribed and are designated the filtered gene set (FGS). Classification of genes by our trained random forest algorithm was accurate and relied only on histone modifications or DNA methylation patterns within the gene body; promoter methylation was unimportant. Other inbred lines are known to transcribe significantly different sets of genes, indicating that the FGS is specific to B73. We accurately classified the sets of transcribed genes in additional inbred lines, arising from inbred-specific DNA methylation patterns. This approach highlights the potential of using chromatin information to improve annotations of functional genes.

The Second Site Modifier, Sympathy for the ligule, Encodes a Homolog of Arabidopsis ENHANCED DISEASE RESISTANCE4 and Rescues the Liguleless narrow Maize Mutant

Liguleless narrow1 encodes a plasma membrane-localized receptor-like kinase required for normal development of maize (Zea mays) leaves, internodes, and inflorescences. The semidominant Lgn-R mutation lacks kinase activity, and phenotypic severity is dependent on inbred background. We created near isogenic lines and assayed the phenotype in multiple environments. Lgn-R plants that carry the B73 version of Sympathy for the ligule (Sol-B) fail to grow under hot conditions, but those that carry the Mo17 version (Sol-M) survive at hot temperatures and are significantly taller at cool temperatures. To identify Sol, we used recombinant mapping and analyzed the Lgn-R phenotype in additional inbred backgrounds. We identified amino acid sequence variations in GRMZM2G075262 that segregate with severity of the Lgn-R phenotypes. This gene is expressed at high levels in Lgn-R B73, but expression drops to nonmutant levels with one copy of Sol-M An EMS mutation solidified the identity of SOL as a maize homolog of Arabidopsis (Arabidopsis thaliana) ENHANCED DISEASE RESISTANCE4 (EDR4). SOL, like EDR4, is induced in response to pathogen-associated molecular patterns such as flg22. Integrated transcriptomic and phosphoproteomic analyses suggest that Lgn-R plants constitutively activate an immune signaling cascade that induces temperature-sensitive responses in addition to defects in leaf development. We propose that aspects of the severe Lgn-R developmental phenotype result from constitutive defense induction and that SOL potentially functions in repressing this response in Mo17 but not B73. Identification of LGN and its interaction with SOL provides insight into the integration of developmental control and immune responses.