Maize gene atlas developed by RNA sequencing and comparative evaluation of transcriptomes based on RNA sequencing and microarrays

The Analysis, Description, and Examination of the Maize LAC Gene Family's Reaction to Abiotic and Biotic Stress

Laccase (LAC) is a diverse group of genes found throughout the plant genome essential for plant growth and the response to stress by converting monolignin into intricate lignin formations. However, a comprehensive investigation of maize laccase has not yet been documented. A bioinformatics approach was utilized in this research to conduct a thorough examination of maize (Zea mays L.), resulting in the identification and categorization of 22 laccase genes (ZmLAC) into six subfamilies. The gene structure and motifs of each subgroup were largely consistent. The distribution of the 22 LAC genes was uneven among the maize chromosomes, with the exception of chromosome 9. The differentiation of the genes was based on fragment replication, and the differentiation time was about 33.37 million years ago. ZmLAC proteins are primarily acidic proteins. There are 18 cis-acting elements in the promoter sequences of the maize LAC gene family associated with growth and development, stress, hormones, light response, and stress response. The analysis of tissue-specific expression revealed a high expression of the maize LAC gene family prior to the V9 stage, with minimal expression at post-V9. Upon reviewing the RNA-seq information from the publicly available transcriptome, it was discovered that ZmLAC5, ZmLAC10, and ZmLAC17 exhibited significant expression levels when exposed to various biotic and abiotic stress factors, suggesting their crucial involvement in stress responses and potential value for further research. This study offers an understanding of the functions of the LAC genes in maize's response to biotic and abiotic stress, along with a theoretical basis for comprehending the molecular processes at play.

Genomic variation in weedy and cultivated broomcorn millet accessions uncovers the genetic architecture of agronomic traits

Large-scale genomic variations are fundamental resources for crop genetics and breeding. Here we sequenced 1,904 genomes of broomcorn millet to an average of 40× sequencing depth and constructed a comprehensive variation map of weedy and cultivated accessions. Being one of the oldest cultivated crops, broomcorn millet has extremely low nucleotide diversity and remarkably rapid decay of linkage disequilibrium. Genome-wide association studies identified 186 loci for 12 agronomic traits. Many causative candidate genes, such as PmGW8 for grain size and PmLG1 for panicle shape, showed strong selection signatures during domestication. Weedy accessions contained many beneficial variations for the grain traits that are largely lost in cultivated accessions. Weedy and cultivated broomcorn millet have adopted different loci controlling flowering time for regional adaptation in parallel. Our study uncovers the unique population genomic features of broomcorn millet and provides an agronomically important resource for cereal crops.

Genome-wide analysis of 14-3-3 gene family in four gramineae and its response to mycorrhizal symbiosis in maize

14-3-3 proteins (regulatory protein family) are phosphate serine-binding proteins. A number of transcription factors and signaling proteins have been shown to bind to the 14-3-3 protein in plants, which plays a role in regulating their growth (seed dormancy, cell elongation and division, vegetative and reproduction growth and stress response (salt stress, drought stress, cold stress). Therefore, the 14-3-3 genes are crucial in controlling how plants respond to stress and develop. However, little is known about the function of 14-3-3 gene families in gramineae. In this study, 49 14-3-3 genes were identified from four gramineae, including maize, rice, sorghum and brachypodium, and their phylogeny, structure, collinearity and expression patterns of these genes were systematically analyzed. Genome synchronization analysis showed large-scale replication events of 14-3-3 genes in these gramineae plants. Moreover, gene expression revealed that the 14-3-3 genes respond to biotic and abiotic stresses differently in different tissues. Upon arbuscular mycorrhizal (AM) symbiosis, the expression level of 14-3-3 genes in maize significantly increased, suggesting the important role of 14-3-3 genes in maize-AM symbiosis. Our results provide a better understanding on the occurrence of 14-3-3 genes in Gramineae plants, and several important candidate genes were found for futher study on AMF symbiotic regulation in maize.

Conserved noncoding sequences and de novo Mutator insertion alleles are imprinted in maize

Genomic imprinting is an epigenetic phenomenon in which differential allele expression occurs in a parent-of-origin-dependent manner. Imprinting in plants is tightly linked to transposable elements (TEs), and it has been hypothesized that genomic imprinting may be a consequence of demethylation of TEs. Here, we performed high-throughput sequencing of ribonucleic acids from four maize (Zea mays) endosperms that segregated newly silenced Mutator (Mu) transposons and identified 110 paternally expressed imprinted genes (PEGs) and 139 maternally expressed imprinted genes (MEGs). Additionally, two potentially novel paternally suppressed MEGs are associated with de novo Mu insertions. In addition, we find evidence for parent-of-origin effects on expression of 407 conserved noncoding sequences (CNSs) in maize endosperm. The imprinted CNSs are largely localized within genic regions and near genes, but the imprinting status of the CNSs are largely independent of their associated genes. Both imprinted CNSs and PEGs have been subject to relaxed selection. However, our data suggest that although MEGs were already subject to a higher mutation rate prior to their being imprinted, imprinting may be the cause of the relaxed selection of PEGs. In addition, although DNA methylation is lower in the maternal alleles of both the maternally and paternally expressed CNSs (mat and pat CNSs), the difference between the two alleles in H3K27me3 levels was only observed in pat CNSs. Together, our findings point to the importance of both transposons and CNSs in genomic imprinting in maize.

Deciphering Macromolecular Interactions Involved in Abiotic Stress Signaling: A Review of Bioinformatics Analysis

Plant functioning and responses to abiotic stresses largely involve regulations at the transcriptomic level via complex interactions of signal molecules, signaling cascades, and regulators. Nevertheless, all the signaling networks involved in responses to abiotic stresses have not yet been fully established. The in-depth analysis of transcriptomes in stressed plants has become a relevant state-of-the-art methodology to study these regulations and signaling pathways that allow plants to cope with or attempt to survive abiotic stresses. The plant science and molecular biology community has developed databases about genes, proteins, protein-protein interactions, protein-DNA interactions and ontologies, which are valuable sources of knowledge for deciphering such regulatory and signaling networks. The use of these data and the development of bioinformatics tools help to make sense of transcriptomic data in specific contexts, such as that of abiotic stress signaling, using functional biological approaches. The aim of this chapter is to present and assess some of the essential online tools and resources that will allow novices in bioinformatics to decipher transcriptomic data in order to characterize the cellular processes and functions involved in abiotic stress responses and signaling. The analysis of case studies further describes how these tools can be used to conceive signaling networks on the basis of transcriptomic data. In these case studies, particular attention was paid to the characterization of abiotic stress responses and signaling related to chemical and xenobiotic stressors.

Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics

RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species.

The Heterogeneity in the Landscape of Gene Dominance in Maize is Accompanied by Unique Chromatin Environments

Subgenome dominance after whole-genome duplication (WGD) has been observed in many plant species. However, the degree to which the chromatin environment affects this bias has not been explored. Here, we compared the dominant subgenome (maize1) and the recessive subgenome (maize2) with respect to patterns of sequence substitutions, genes expression, transposable element accumulation, small interfering RNAs, DNA methylation, histone modifications, and accessible chromatin regions (ACRs). Our data show that the degree of bias between subgenomes for all the measured variables does not vary significantly when both of the WGD genes are located in pericentromeric regions. Our data further indicate that the location of maize1 genes in chromosomal arms is pivotal for maize1 to maintain its dominance, but location has a less effect on maize2 homoeologs. In addition to homoeologous genes, we compared ACRs, which often harbor cis-regulatory elements, between the two subgenomes and demonstrate that maize1 ACRs have a higher level of chromatin accessibility, a lower level of sequence substitution, and are enriched in chromosomal arms. Furthermore, we find that a loss of maize1 ACRs near their nearby genes is associated with a reduction in purifying selection and expression of maize1 genes relative to their maize2 homoeologs. Taken together, our data suggest that chromatin environment and cis-regulatory elements are important determinants shaping the divergence and evolution of duplicated genes.

Classification and Expression Profile of the U-Box E3 Ubiquitin Ligase Enzyme Gene Family in Maize (Zea mays L.)

The U-box E3 (PUB) family genes encode the E3 ubiquitin ligase enzyme, which determines substrate specific recognition during protein ubiquitination. They are widespread in plants and are critical for plant growth, development, and response to external stresses. However, there are few studies on the functional characteristic of PUB gene family in the important staple crop, maize (Zea mays L.). In this study, the PUB gene in maize was aimed to identify and classify through whole-genome screening. Phylogenetic tree, gene structure, conserved motif, chromosome location, gene duplication (GD), synteny, and cis-acting regulatory element of PUB member were analyzed. The expression profiles of ZmPUB gene family in maize during development and under abiotic stress and hormones treatment were analyzed by the RNA-seq data. A total of 79 PUB genes were identified in maize genome, and they were stratified into seven categories. There were 25 pairs of segmental duplications (SD) and 1 pair of tandem duplication (TD) identified in the maize PUB gene family. A close relationship was observed between the monocot plant maize and rice in PUB gene family. There were 94 kinds of cis-acting elements identified in the maize PUB gene family, which included 46 biotic- and abiotic-responsive elements, 19 hormone-responsive elements, 13 metabolic and growth-related elements. The expression profiles of maize PUB gene family showed characteristics of tissue specificity and response to abiotic stress and hormones treatment. These results provided an extensive overview of the maize PUB gene family.

Identification of Novel Genes Associated with Partial Resistance to Aphanomyces Root Rot in Field Pea by BSR-Seq Analysis

Aphanomyces root rot, caused by Aphanomyces euteiches, causes severe yield loss in field pea (Pisum sativum). The identification of a pea germplasm resistant to this disease is an important breeding objective. Polygenetic resistance has been reported in the field pea cultivar '00-2067'. To facilitate marker-assisted selection (MAS), bulked segregant RNA-seq (BSR-seq) analysis was conducted using an F8 RIL population derived from the cross of 'Carman' × '00-2067'. Root rot development was assessed under controlled conditions in replicated experiments. Resistant (R) and susceptible (S) bulks were constructed based on the root rot severity in a greenhouse study. The BSR-seq analysis of the R bulks generated 44,595,510~51,658,688 reads, of which the aligned sequences were linked to 44,757 genes in a reference genome. In total, 2356 differentially expressed genes were identified, of which 44 were used for gene annotation, including defense-related pathways (jasmonate, ethylene and salicylate) and the GO biological process. A total of 344.1 K SNPs were identified between the R and S bulks, of which 395 variants were located in 31 candidate genes. The identification of novel genes associated with partial resistance to Aphanomyces root rot in field pea by BSR-seq may facilitate efforts to improve management of this important disease.

Integrated gene co-expression network analysis reveals unique developmental processes of Aurelia aurita

The typical life cycle of the moon jellyfish (Aurelia aurita) includes the planula, polyp, strobila, ephyra, and medusa developmental stages. These stages exhibit huge differences in both external morphology and internal physiological functions. However, the gene co-expression network involved in these post-embryonic developmental processes has not been studied yet. Here, based on 15 RNA sequencing samples covering all five stages of the A. aurita life cycle, we systematically analyzed the gene co-expression network and obtained 35 relevant modules. Furthermore, we identified the highly correlated modules and hub genes for each stage. These hub genes are implicated to play important roles in the developmental processes of A. aurita, which should help improve our understanding of the jellyfish life cycle.

Phylogenetic and Expression Studies of Small GTP-Binding Proteins in Solanum lycopersicum Super Strain B

This investigation involved a comparative analysis of the small GTPase superfamily in S. lycopersicum super strain B compared to their analogues in leguminous and other non-leguminous species. The small GTPases superfamily members were recognized by tBLASTn searches. The sequences of amino acid were aligned using Clustal Omega and the analysis of phylogeny was performed with the MEGA7 package. Protein alignments were applied for all studied species. Three-dimensional models of RABA2, ROP9, and ROP10 from Solanum lycopersicum “Super strain B” were performed. The levels of mRNA of the Rab, Arf, Rop, and Ran subfamilies were detected in aerial tissues vs. roots. Significant divergences were found in the number of members and groups comprising each subfamily of the small GTPases and Glycine max had the highest count. High expression of Rab and Arf proteins was shown in the roots of legumes whilst in non-legume plants, the highest values were recorded in aerial tissues. S. lycopersicum super strain B had the highest expression of Rab and Arf proteins in its aerial tissues, which may indicate that diazotroph strains have supreme activities in the aerial tissues of strain B and act as associated N-fixing bacteria. The phylogenies of the small GTPase superfamily of the studied plants did not reveal asymmetric evolution of the Ra, Arf, Rop, and Ran subfamilies. Multiple sequence alignments derived from each of the Rab, Arf, and Rop proteins of S. lycopersicum super strain B showed a low frequency of substitutions in their domains. GTPases superfamily members have definite functions during infection, delivery, and maintenance of N2-fixing diazotroph but show some alterations in their function among S. lycopersicum super strain B, and other species.

Identification of Candidate Gene Signatures and Regulatory Networks in Endometriosis and its Related Infertility by Integrated Analysis

Endometriosis is a common gynecological disease associated with infertility, and it represents an economic burden worldwide. However, the molecular mechanisms underlying endometriosis development have not yet been fully elucidated. Here, we aimed to identify reliable key genes and the related regulatory network that may be involved in endometriosis. Differentially expressed genes (DEGs) were identified through integrated analysis of four expression datasets of endometriosis from Gene Expression Omnibus. Gene functional analysis and protein-protein interaction network construction were performed to reveal the potential function of DEGs. Subsequently, candidate hub genes were defined and validated in GSE105764 dataset, and the associated regulatory networks were constructed. Additionally, GSE120103 dataset was applied to identify the differential expression between the infertile and fertile groups of patients with stage IV endometriosis. Finally, real-time quantitative polymerase chain reaction analysis was performed to identify the differential expression of hub genes in the collected clinical specimens. Robust rank aggregation integrated analysis determined 158 DEGs. Epithelial cell differentiation was the most significantly enriched biological process, and leukocyte transendothelial migration was the most significantly enriched pathway. Eight hub genes including CLDN3, CLDN5, CLDN7, CLDN11, HOXC8, HOXC6, HOXB6, and HOXB7 were identified, and most of these were validated as abnormally expressed genes in both the infertile group and patients with endometriosis. Transcriptional factors and microRNAs related to these genes were identified. Altogether, our integrated analysis identified critical gene signatures, involved pathways, and regulatory networks, which could provide clinically significant insights into the molecular mechanisms underlying endometriosis and its related infertility.

Transcriptome atlas of Phalaenopsis equestris

The vast diversity of Orchidaceae together with sophisticated adaptations to pollinators and other unique features make this family an attractive model for evolutionary and functional studies. The sequenced genome of Phalaenopsis equestris facilitates Orchidaceae research. Here, we present an RNA-seq-based transcriptome map of P. equestris that covers 19 organs of the plant, including leaves, roots, floral organs and the shoot apical meristem. We demonstrated the high quality of the data and showed the similarity of the P. equestris transcriptome map with the gene expression atlases of other plants. The transcriptome map can be easily accessed through our database Transcriptome Variation Analysis (TraVA) for visualizing gene expression profiles. As an example of the application, we analyzed the expression of Phalaenopsis “orphan” genes–those that do not have recognizable similarity with the genes of other plants. We found that approximately half of these genes were not expressed; the ones that were expressed were predominantly expressed in reproductive structures.

Key Metabolite Differences Between Korean Pine (Pinus koraiensis) Seeds With Primary Physiological Dormancy and No-Dormancy

Pinus Koraiensis seeds have physiological dormancy. Cold stratification releases seed dormancy. The changes in metabolite profiles of dormant seeds and cold stratified seeds during shorter incubation time in a favorable condition for seed germination have been studied. However, a more-long-term detection of the changes in metabolites in dormant seeds can identify the real metabolic pathways responsible for dormancy. Metabolite composition was investigated in embryo and megagametophyte of primary physiological dormant seeds (DS) of P. Koraiensis collected at 0, 1, 2, 4, and 6 weeks of incubation and of non-primary physiological dormant seeds (NDS) sampled at 0 and 1 week of incubation, seed coat rupture stage, and radicle protrusion stage. Embryos contained higher levels of most metabolites than megagametophyte. Strong accumulation of most metabolites in DS occurred at 1 and 4 weeks of incubation. A larger reduction in the relative levels of most phosphorylated sugars and amino acids in NDS was found between 1-week-incubation and seed coat rupture stage. The relative levels of metabolites involved in carbohydrate metabolism, especially the pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle, were higher in the embryos of 4-week-incubated DS, but the relative contents of intermediate metabolites of most amino acid metabolism were lower compared to 1-week-incubated NDS. We suggested that the disturbed carbohydrate metabolism and amino acid metabolism in the embryos of DS after 4 weeks of incubation maybe related to primary dormancy. Our study provides information for a better understanding of the mechanism of seed dormancy.

Systems biology for crop improvement

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

Understanding Omics Driven Plant Improvement and de novo Crop Domestication: Some Examples

In the current era, one of biggest challenges is to shorten the breeding cycle for rapid generation of a new crop variety having high yield capacity, disease resistance, high nutrient content, etc. Advances in the "-omics" technology have revolutionized the discovery of genes and bio-molecules with remarkable precision, resulting in significant development of plant-focused metabolic databases and resources. Metabolomics has been widely used in several model plants and crop species to examine metabolic drift and changes in metabolic composition during various developmental stages and in response to stimuli. Over the last few decades, these efforts have resulted in a significantly improved understanding of the metabolic pathways of plants through identification of several unknown intermediates. This has assisted in developing several new metabolically engineered important crops with desirable agronomic traits, and has facilitated the de novo domestication of new crops for sustainable agriculture and food security. In this review, we discuss how "omics" technologies, particularly metabolomics, has enhanced our understanding of important traits and allowed speedy domestication of novel crop plants.

Transcriptomic Analysis of a Susceptible African Maize Line to Fusarium verticillioides Infection

Maize (Zea mays L.) is a staple crop providing food security to millions of people in sub Saharan Africa. Fusarium verticillioides, an important fungal pathogen, infects maize causing ‘Fusarium Ear Rot’ disease, which decreases maize kernel yield and the quality of the crop harvested. Currently, no African maize line is completely resistant to infection by F. verticillioides. This study investigated an African maize line, Zea mays CML144, infected with F. verticillioides. Analysis of morphological characteristics showed significant differences between mock-infected and infected plants. RNA-sequencing (RNA-seq) was conducted on plants 14 days post-inoculation to identify differentially expressed genes (DEGs) involved in F. verticillioides infection. Analysis of RNA-seq data revealed DEGs that were both significantly up- and down-regulated in the infected samples compared to the mock-infected control. The maize TPS1 and cytochrome P450 genes were up-regulated, suggesting that kauralexins were involved in the CML144 defense response. This was substantiated by kauralexin analyses, which showed that kauralexins, belonging to class A and B, accumulated in infected maize tissue. Gene ontology terms relating to response to stimulus, chemical stimulus and carbohydrate metabolic processes were enriched, and the genes belonging to these GO-terms were down-regulated. Quantitative real-time PCR was performed on selected DEGs and measurement of phytoalexin accumulation validated the RNA-seq data and GO-analysis results. A comparison of DEGs from this study to DEGs found in F. verticillioides (ITEM 1744) infected susceptible (CO354) and resistant (CO441) maize genotypes in a previous study, matched 18 DEGs with 17 up-regulated and one down-regulated, respectively. This is the first transcriptomic study on the African maize line, CML144, in response to F. verticillioides infection.

(Differential) Co-Expression Analysis of Gene Expression: A Survey of Best Practices

Analysis of gene expression data is widely used in transcriptomic studies to understand functions of molecules inside a cell and interactions among molecules. Differential co-expression analysis studies diseases and phenotypic variations by finding modules of genes whose co-expression patterns vary across conditions. We review the best practices in gene expression data analysis in terms of analysis of (differential) co-expression, co-expression network, differential networking, and differential connectivity considering both microarray and RNA-seq data along with comparisons. We highlight hurdles in RNA-seq data analysis using methods developed for microarrays. We include discussion of necessary tools for gene expression analysis throughout the paper. In addition, we shed light on scRNA-seq data analysis by including preprocessing and scRNA-seq in co-expression analysis along with useful tools specific to scRNA-seq. To get insights, biological interpretation and functional profiling is included. Finally, we provide guidelines for the analyst, along with research issues and challenges which should be addressed.

Use of Dual RNA-seq for Systems Biology Analysis of Zea mays and Aspergillus flavus Interaction

The interaction between Aspergillus flavus and Zea mays is complex, and the identification of plant genes and pathways conferring resistance to the fungus has been challenging. Therefore, the authors undertook a systems biology approach involving dual RNA-seq to determine the simultaneous response from the host and the pathogen. What was dramatically highlighted in the analysis is the uniformity in the development patterns of gene expression of the host and the pathogen during infection. This led to the development of a "stage of infection index" that was subsequently used to categorize the samples before down-stream system biology analysis. Additionally, we were able to ascertain that key maize genes in pathways such as the jasmonate, ethylene and ROS pathways, were up-regulated in the study. The stage of infection index used for the transcriptomic analysis revealed that A. flavus produces a relatively limited number of transcripts during the early stages (0 to 12 h) of infection. At later stages, in A. flavus, transcripts and pathways involved in endosomal transport, aflatoxin production, and carbohydrate metabolism were up-regulated. Multiple WRKY genes targeting the activation of the resistance pathways (i.e., jasmonate, phenylpropanoid, and ethylene) were detected using causal inference analysis. This analysis also revealed, for the first time, the activation of Z. mays resistance genes influencing the expression of specific A. flavus genes. Our results show that A. flavus seems to be reacting to a hostile environment resulting from the activation of resistance pathways in Z. mays. This study revealed the dynamic nature of the interaction between the two organisms.

Isolation and characterization of a 295-bp strong promoter of maize high-affinity phosphate transporter gene ZmPht1; 5 in transgenic Nicotiana benthamiana and Zea mays

MAIN CONCLUSION

The small 295-bp ZmPht1; 5 promoter is sufficient to drive high-intensity expression of target genes, especially under phosphate deprivation conditions, and is therefore useful for crop improvement via transgenic techniques. Phosphate (Pi) deficiency has become a major challenge and limiting factor in world agricultural production. Manipulating the gene expression using appropriate promoters to improve the Pi absorption and utilization efficiency of crops could reduce the requirement for Pi fertilizers. In the study, a 295-bp strong promoter (M2P-7) of maize high-affinity phosphate transporter ZmPht1; 5 was isolated and functionally validated in transgenic Nicotiana benthamiana and maize by analyzing the ZmPht1; 5 promoter (M2P-1) and its 5' truncated variants (M2P-2 ~ M2P-8) in different sizes under normal and Pi-deprivation conditions. The M2P-7 displayed the highest promoter activities among 5' truncated fragments in all tested tissues of transgenic Nicotiana benthamiana at different development stages, which was 1.5 and 3 times higher than the well-used CaMV35S promoter under normal and Pi-deprivation conditions, respectively. In maize, the M2P-7 promoter activity was comparable to the maize ubiquitin1 promoter widely used in monocots under normal condition, which was about 1.3 times that of the ubiquitin1 promoter under Pi-deprivation environments. Moreover, the M2P-7 fragment is only 295 bp in length, thus reducing the construct size, and is therefore beneficial for genetic transformation. Thus, the small promoter M2P-7 of plant origin could be of great use for monocotyledonous and dicotyledonous crop improvement via transgenic techniques based on its promoter activities, expression patterns and small size.

Using multiple reference genomes to identify and resolve annotation inconsistencies

BACKGROUND

Advances in sequencing technologies have led to the release of reference genomes and annotations for multiple individuals within more well-studied systems. While each of these new genome assemblies shares significant portions of synteny between each other, the annotated structure of gene models within these regions can differ. Of particular concern are split-gene misannotations, in which a single gene is incorrectly annotated as two distinct genes or two genes are incorrectly annotated as a single gene. These misannotations can have major impacts on functional prediction, estimates of expression, and many downstream analyses.

RESULTS

We developed a high-throughput method based on pairwise comparisons of annotations that detect potential split-gene misannotations and quantifies support for whether the genes should be merged into a single gene model. We demonstrated the utility of our method using gene annotations of three reference genomes from maize (B73, PH207, and W22), a difficult system from an annotation perspective due to the size and complexity of the genome. On average, we found several hundred of these potential split-gene misannotations in each pairwise comparison, corresponding to 3-5% of gene models across annotations. To determine which state (i.e. one gene or multiple genes) is biologically supported, we utilized RNAseq data from 10 tissues throughout development along with a novel metric and simulation framework. The methods we have developed require minimal human interaction and can be applied to future assemblies to aid in annotation efforts.

CONCLUSIONS

Split-gene misannotations occur at appreciable frequency in maize annotations. We have developed a method to easily identify and correct these misannotations. Importantly, this method is generic in that it can utilize any type of short-read expression data. Failure to account for split-gene misannotations has serious consequences for biological inference, particularly for expression-based analyses.

Using multiple reference genomes to identify and resolve annotation inconsistencies

BACKGROUND

Advances in sequencing technologies have led to the release of reference genomes and annotations for multiple individuals within more well-studied systems. While each of these new genome assemblies shares significant portions of synteny between each other, the annotated structure of gene models within these regions can differ. Of particular concern are split-gene misannotations, in which a single gene is incorrectly annotated as two distinct genes or two genes are incorrectly annotated as a single gene. These misannotations can have major impacts on functional prediction, estimates of expression, and many downstream analyses.

RESULTS

We developed a high-throughput method based on pairwise comparisons of annotations that detect potential split-gene misannotations and quantifies support for whether the genes should be merged into a single gene model. We demonstrated the utility of our method using gene annotations of three reference genomes from maize (B73, PH207, and W22), a difficult system from an annotation perspective due to the size and complexity of the genome. On average, we found several hundred of these potential split-gene misannotations in each pairwise comparison, corresponding to 3-5% of gene models across annotations. To determine which state (i.e. one gene or multiple genes) is biologically supported, we utilized RNAseq data from 10 tissues throughout development along with a novel metric and simulation framework. The methods we have developed require minimal human interaction and can be applied to future assemblies to aid in annotation efforts.

CONCLUSIONS

Split-gene misannotations occur at appreciable frequency in maize annotations. We have developed a method to easily identify and correct these misannotations. Importantly, this method is generic in that it can utilize any type of short-read expression data. Failure to account for split-gene misannotations has serious consequences for biological inference, particularly for expression-based analyses.

In silico analysis of maize HDACs with an emphasis on their response to biotic and abiotic stresses

Histone deacetylases (HDACs) are key epigenetic factors in regulating chromatin structure and gene expression in multiple aspects of plant growth, development, and response to abiotic or biotic stresses. Many studies on systematic analysis and molecular function of HDACs in Arabidopsis and rice have been conducted. However, systematic analysis of HDAC gene family and gene expression in response to abiotic and biotic stresses has not yet been reported. In this study, a systematic analysis of the HDAC gene family in maize was performed and 18 ZmHDACs distributed on nine chromosomes were identified. Phylogenetic analysis of ZmHDACs showed that this gene family could be divided into RPD3/HDA1, SIR2, and HD2 groups. Tissue-specific expression results revealed that ZmHDACs exhibited diverse expression patterns in different tissues, indicating that these genes might have diversified functions in growth and development. Expression pattern of ZmHDACs in hormone treatment and inoculation experiment suggested that several ZmHDACs might be involved in jasmonic acid or salicylic acid signaling pathway and defense response. Interestingly, HDAC genes were downregulated under heat stress, and immunoblotting results demonstrated that histones H3K9ac and H4K5ac levels were increased under heat stress. These results provide insights into ZmHDACs, which could help to reveal their functions in controlling maize development and responses to abiotic or biotic stresses.

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.

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis

Background

Systemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients.

Methods

An integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein–protein interaction (PPI) networks. Then, functional clusters in PPI networks were determined. Enrichr, a gene list enrichment analysis tool, was utilized for the functional enrichment of clusters.

Results

A total of 12, 2, and 4 functional clusters from 619, 52, and 119 DEGs were determined in the lung, peripheral blood mononuclear cell (PBMC), and skin tissues, respectively. Analysis revealed that the tumor necrosis factor (TNF) signaling pathway was enriched significantly in the three investigated tissues as a common pathway. In addition, clusters associated with inflammation and immunity were common in the three investigated tissues. However, clusters related to the fibrosis process were common in lung and skin tissues.

Conclusions

Analysis indicated that there were common pathological clusters that contributed to the pathogenesis of SSc in different tissues. Moreover, it seems that the common pathways in distinct tissues stem from a diverse set of genes.

A maize NAC transcription factor, ZmNAC34, negatively regulates starch synthesis in rice

ZmNAC34 might function as an important regulator of starch synthesis by decreasing total starch accumulation and soluble sugar content and increasing amylose fractions. Starch is a major component in endosperm and directly influences seed yield and the cooking quality of cereal grains. Starch is synthesized through a series of complex biological processes. Nevertheless, the mechanism by which starch biosynthesis is regulated in maize is still unclear. In this study, ZmNAC34, a NAC transcription factor related to starch synthesis, was screened based on transcriptome sequencing data. Subsequent qRT-PCR analysis showed that ZmNAC34 is specifically expressed in maize endosperm. Transactivation and subcellular localization assays revealed that ZmNAC34 possesses two characteristics of transcription factors: nuclear localization and transactivation activity. Overexpression of ZmNAC34 in rice decreased total starch accumulation and soluble sugar content, while increased amylose fractions. Meanwhile, the transgenic seeds exhibited alterant starch structure and abnormal morphology. In addition, compared with WT seeds, most of the 17 starch biosynthesis-related genes were significantly upregulated in transgenic seeds from 6 to 15 DAP (day after pollination). These data reveal that ZmNAC34 might function as an important regulator of starch synthesis, thus providing a new perspective on controlling seed yield and quality.

Comprehensive Stress-Based De Novo Transcriptome Assembly and Annotation of Guar (Cyamopsis tetragonoloba (L.) Taub.): An Important Industrial and Forage Crop

The forage crop Guar (Cyamopsis tetragonoloba (L.) Taub.) has the ability to endure heat, drought, and mild salinity. A complete image on its genic architecture will promote our understanding about gene expression networks and different tolerance mechanisms at the molecular level. Therefore, whole mRNA sequence approach on the Guar plant was conducted to provide a snapshot of the mRNA information in the cell under salinity, heat, and drought stresses to be integrated with previous transcriptomic studies. RNA-Seq technology was employed to perform a 2 × 100 paired-end sequencing using an Illumina HiSeq 2500 platform for the transcriptome of leaves of C. tetragonoloba under normal, heat, drought, and salinity conditions. Trinity was used to achieve a de novo assembly followed by gene annotation, functional classification, metabolic pathway analysis, and identification of SSR markers. A total of 218.2 million paired-end raw reads (~44 Gbp) were generated. Of those, 193.5M paired-end reads of high quality were used to reconstruct a total of 161,058 transcripts (~266 Mbp) with N50 of 2552 bp and 61,508 putative genes. There were 6463 proteins having >90% full-length coverage against the Swiss-Prot database and 94% complete orthologs against Embryophyta. Approximately, 62.87% of transcripts were blasted, 50.46% mapped, and 43.50% annotated. A total of 4715 InterProScan families, 3441 domains, 74 repeats, and 490 sites were detected. Biological processes, molecular functions, and cellular components comprised 64.12%, 25.42%, and 10.4%, respectively. The transcriptome was associated with 985 enzymes and 156 KEGG pathways. A total of 27,066 SSRs were gained with an average frequency of one SSR/9.825 kb in the assembled transcripts. This resulting data will be helpful for the advanced analysis of Guar to multi-stress tolerance.

SWEET Transporters for the Nourishment of Embryonic Tissues during Maize Germination

In maize seed germination, the endosperm and the scutellum nourish the embryo axis. Here, we examined the mRNA relative amount of the SWEET protein family, which could be involved in sugar transport during germination since high [¹⁴-C]-glucose and mainly [¹⁴-C]-sucrose diffusional uptake were found in embryo tissues. We identified high levels of transcripts for SWEETs in the three phases of the germination process: ZmSWEET4c, ZmSWEET6b, ZmSWEET11, ZmSWEET13a, ZmSWEET13b, ZmSWEET14b and ZmSWEET15a, except at 0 h of imbibition where the abundance of each ZmSWEET was low. Despite the major sucrose (Suc) biosynthesis capacity of the scutellum and the high level of transcripts of the Suc symporter SUT1, Suc was not found to be accumulated; furthermore, in the embryo axis, Suc did not decrease but hexoses increased, suggesting an efficient Suc efflux from the scutellum to nourish the embryo axis. The influx of Glc into the scutellum could be mediated by SWEET4c to take up the large amount of transported sugars due to the late hydrolysis of starch. In addition, sugars regulated the mRNA amount of SWEETs at the embryo axis. These results suggest an important role for SWEETs in transporting Suc and hexoses between the scutellum and the embryo axis, and differences in SWEET transcripts between both tissues might occur because of the different sugar requirements and metabolism.

Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize

Premature senescence in annual crops reduces yield, while delayed senescence, termed stay-green, imposes positive and negative impacts on yield and nutrition quality. Despite its importance, scant information is available on the genetic architecture of senescence in maize (Zea mays) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and coexpression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by genome-wide association study (GWAS), and 14 of these genes are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a coexpression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding Cys protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggests a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.

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.

Genome-Wide Identification of Long Non-Coding RNAs and Their Regulatory Networks Involved in Apis mellifera ligustica Response to Nosema ceranae Infection

Long non-coding RNAs (lncRNAs) are a diverse class of transcripts that structurally resemble mRNAs but do not encode proteins, and lncRNAs have been proven to play pivotal roles in a wide range of biological processes in animals and plants. However, knowledge of expression patterns and potential roles of honeybee lncRNA response to Nosema ceranae infection is completely unknown. Here, we performed whole transcriptome strand-specific RNA sequencing of normal midguts of Apis mellifera ligustica workers (Am7CK, Am10CK) and N. ceranae-inoculated midguts (Am7T, Am10T), followed by comprehensive analyses using bioinformatic and molecular approaches. A total of 6353 A. m. ligustica lncRNAs were identified, including 4749 conserved lncRNAs and 1604 novel lncRNAs. These lncRNAs had minimal sequence similarities with other known lncRNAs in other species; however, their structural features were similar to counterparts in mammals and plants, including shorter exon and intron length, lower exon number, and lower expression level, compared with protein-coding transcripts. Further, 111 and 146 N. ceranae-responsive lncRNAs were identified from midguts at 7-days post-inoculation (dpi) and 10 dpi compared with control midguts. Twelve differentially expressed lncRNAs (DElncRNAs) were shared by Am7CK vs. Am7T and Am10CK vs. Am10T comparison groups, while the numbers of unique DElncRNAs were 99 and 134, respectively. Functional annotation and pathway analysis showed that the DElncRNAs may regulate the expression of neighboring genes by acting in cis and trans fashion. Moreover, we discovered 27 lncRNAs harboring eight known miRNA precursors and 513 lncRNAs harboring 2257 novel miRNA precursors. Additionally, hundreds of DElncRNAs and their target miRNAs were found to form complex competitive endogenous RNA (ceRNA) networks, suggesting that these DElncRNAs may act as miRNA sponges. Furthermore, DElncRNA-miRNA-mRNA networks were constructed and investigated, the results demonstrated that a portion of the DElncRNAs were likely to participate in regulating the host material and energy metabolism as well as cellular and humoral immune host responses to N. ceranae invasion. Our findings revealed here offer not only a rich genetic resource for further investigation of the functional roles of lncRNAs involved in the A. m. ligustica response to N. ceranae infection, but also a novel insight into understanding the host-pathogen interaction during honeybee microsporidiosis.

Genome-wide identification, expression profiling, and network analysis of AT-hook gene family in maize

AT-hook motif nuclear localized (AHL) genes have diverse but poorly understood biological functions. We identified and analyzed 37 AHL genes in maize. We also discovered four and one additional AHLs in rice and sorghum, respectively, besides those reported earlier. The maize AHLs were classified into two clades (A and B) and three distinct types (I, II, and III) as also reported in Arabidopsis. Phylogenetic and ortholog analyses showed that, while the evolutionary classification was conserved in plants, expansion of the AHL gene family in maize was accompanied with new biological functions. Gene structure analysis showed that, while all but one Type-I AHLs lacked an intron, origin of Type-II and Type-III AHLs was associated with the gain of introns suggesting evolutionarily distinct temporal and spatial expression patterns and, likely, neofunctionalization. Gene duplication analysis revealed that AHLs in maize expanded via dispersive duplication further supporting their functional diversity. To discern these functions, we analyzed 71 transcriptomes from diverse tissues and developmental stages of maize and classified AHLs into eight groups with distinct temporal/spatial expression profiles. Coexpression analysis implicated 5 AHLs and 33 novel genes in networks specific to endosperm, seed, root, leaf, and reproductive tissues indicating their role in the development of these organs. Major processes coregulated by AHLs include pollen development, drought response, senescence, and wound response. We also identified interactions of AHL proteins in coregulating important processes including stress response. These novel insights into the role of AHLs in plant development provide a platform for functional analyses in maize and related grasses.

Comparative genome analysis of the SPL gene family reveals novel evolutionary features in maize

SPLs are plant-specific transcription factors that play important regulatory roles in plant growth and development. Systematic analysis of the SPL family has been performed in numerous plants, such as Arabidopsis, rice, and Populus. However, no comparative analysis has been performed across different species to examine evolutionary features. In this study, we present a comparative analysis of SPLs in different species. The results showed that 84 SPLs of the four species can be divided into six groups according to phylogeny. We found that most of the SPL-containing regions in maize showed extensive conservation with duplicated regions of rice and sorghum. A gene duplication analysis in maize indicated that ZmSPLs showed a significant excess of segmental duplication. The Ka/Ks analysis indicated that 9 out of 18 duplicated pairs in maize experienced positive selection, while SPL gene pairs of rice and sorghum mainly evolved under purifying selection, suggesting novel evolutionary features for ZmSPLs. The 31 ZmSPLs were further analyzed by describing their gene structure, phylogenetic relationships, chromosomal location, and expression, Among the ZmSPLs, 13 were predicated to be targeted by miR156s and involved in drought stress response. These results provide the foundation for future functional analyses of ZmSPLs.

Identification of genes with universally upregulated or downregulated expressions in colorectal cancer

BACKGROUND AND AIM

Differentially expressed (DE) genes detected at the population-level through case-control comparison provide no information on the dysregulation frequencies of DE genes in a cancer. In this work, we aimed to identify the genes with universally upregulated or downregulated expressions in colorectal cancer (CRC).

METHODS

We firstly clarified that DE genes in an individual cancer tissue should be the disease-relevant genes, which are dysregulated in the cancer tissue in comparison with its own previously normal state. Then, we identified DE genes at the individual level for 2233 CRC samples collected from multiple data sources using the RankComp algorithm.

RESULTS

We found 26 genes that were upregulated or downregulated in almost all the 2233 CRC samples and validated the results using 124 CRC tissues with paired adjacent normal tissues. Especially, we found that two genes (AJUBA and EGFL6), upregulated universally in CRC tissues, were extremely lowly expressed in normal colorectal tissues, which were considered to be oncogenes in CRC oncogenesis and development. Oppositely, we found that one gene (LPAR1), downregulated universally in CRC tissues, was silenced in CRC tissues but highly expressed in normal colorectal tissues, which were considered to be tumor suppressor genes in CRC. Functional evidences revealed that these three genes may induce CRC through deregulating pathways for ribosome biogenesis, cell proliferation, and cell cycle.

CONCLUSIONS

In conclusion, the individual-level DE genes analysis can help us find genes dysregulated universally in CRC tissues, which may be important diagnostic biomarkers and therapy targets.

An updated gene atlas for maize reveals organ-specific and stress-induced genes

Maize (Zea mays L.), a model species for genetic studies, is one of the two most important crop species worldwide. The genome sequence of the reference genotype, B73, representative of the stiff stalk heterotic group was recently updated (AGPv4) using long-read sequencing and optical mapping technology. To facilitate the use of AGPv4 and to enable functional genomic studies and association of genotype with phenotype, we determined expression abundances for replicated mRNA-sequencing datasets from 79 tissues and five abiotic/biotic stress treatments revealing 36 207 expressed genes. Characterization of the B73 transcriptome across six organs revealed 4154 organ-specific and 7704 differentially expressed (DE) genes following stress treatment. Gene co-expression network analyses revealed 12 modules associated with distinct biological processes containing 13 590 genes providing a resource for further association of gene function based on co-expression patterns. Presence-absence variants (PAVs) previously identified using whole genome resequencing data from 61 additional inbred lines were enriched in organ-specific and stress-induced DE genes suggesting that PAVs may function in phenological variation and adaptation to environment. Relative to core genes conserved across the 62 profiled inbreds, PAVs have lower expression abundances which are correlated with their frequency of dispersion across inbreds and on average have significantly fewer co-expression network connections suggesting that a subset of PAVs may be on an evolutionary path to pseudogenization. To facilitate use by the community, we developed the Maize Genomics Resource website (maize.plantbiology.msu.edu) for viewing and data-mining these resources and deployed two new views on the maize electronic Fluorescent Pictograph Browser (bar.utoronto.ca/efp_maize).

The DOF-Domain Transcription Factor ZmDOF36 Positively Regulates Starch Synthesis in Transgenic Maize

Starch synthesis is a complex process that influences crop yield and grain quality in maize. Many key enzymes have been identified in starch biosynthesis; however, the regulatory mechanisms have not been fully elucidated. In this study, we identified a DOF family gene, ZmDOF36, through transcriptome sequencing analysis. Real-time PCR indicated that ZmDOF36 was highly expressed in maize endosperm, with lower expression in leaves and tassels. ZmDOF36 is a typical DOF transcription factor (TF) that is localized to the nucleus and possesses transcriptional activation activity, and its transactivation domain is located in the C-terminus (amino acids 227-351). Overexpression of ZmDOF36 can increase starch content and decrease the contents of soluble sugars and reducing sugars. In addition, abnormal starch structure in transgenic maize was also observed by scanning electron microscopy (SEM). Furthermore, the expression levels of starch synthesis-related genes were up-regulated in ZmDOF36-expressing transgenic maize. ZmDOF36 was also shown to bind directly to the promoters of six starch biosynthesis genes, ZmAGPS1a, ZmAGPL1, ZmGBSSI, ZmSSIIa, ZmISA1, and ZmISA3 in yeast one-hybrid assays. Transient expression assays showed that ZmDOF36 can activate the expression of ZmGBSSI and ZmISA1 in tobacco leaves. Collectively, the results presented here suggest that ZmDOF36 acts as an important regulatory factor in starch synthesis, and could be helpful in devising strategies for modulating starch production in maize endosperm.

Consensus Coexpression Network Analysis Identifies Key Regulators of Flower and Fruit Development in Wild Strawberry

The diploid strawberry, Fragaria vesca, is a developing model system for the economically important Rosaceae family. Strawberry fleshy fruit develops from the floral receptacle and its ripening is nonclimacteric. The external seed configuration of strawberry fruit facilitates the study of seed-to-fruit cross tissue communication, particularly phytohormone biosynthesis and transport. To investigate strawberry fruit development, we previously generated spatial and temporal transcriptome data profiling F. vesca flower and fruit development pre- and postfertilization. In this study, we combined 46 of our existing RNA-seq libraries to generate coexpression networks using the Weighted Gene Co-Expression Network Analysis package in R. We then applied a post-hoc consensus clustering approach and used bootstrapping to demonstrate consensus clustering's ability to produce robust and reproducible clusters. Further, we experimentally tested hypotheses based on the networks, including increased iron transport from the receptacle to the seed postfertilization and characterized a F. vesca floral mutant and its candidate gene. To increase their utility, the networks are presented in a web interface (www.fv.rosaceaefruits.org) for easy exploration and identification of coexpressed genes. Together, the work reported here illustrates ways to generate robust networks optimized for the mining of large transcriptome data sets, thereby providing a useful resource for hypothesis generation and experimental design in strawberry and related Rosaceae fruit crops.

Gene co-expression analysis for functional classification and gene-disease predictions

Gene co-expression networks can be used to associate genes of unknown function with biological processes, to prioritize candidate disease genes or to discern transcriptional regulatory programmes. With recent advances in transcriptomics and next-generation sequencing, co-expression networks constructed from RNA sequencing data also enable the inference of functions and disease associations for non-coding genes and splice variants. Although gene co-expression networks typically do not provide information about causality, emerging methods for differential co-expression analysis are enabling the identification of regulatory genes underlying various phenotypes. Here, we introduce and guide researchers through a (differential) co-expression analysis. We provide an overview of methods and tools used to create and analyse co-expression networks constructed from gene expression data, and we explain how these can be used to identify genes with a regulatory role in disease. Furthermore, we discuss the integration of other data types with co-expression networks and offer future perspectives of co-expression analysis.

Comparative analysis of the male inflorescence transcriptome profiles of an ms22 mutant of maize

In modern agricultural production, maize is the most successful crop utilizing heterosis. 712C-ms22 is an important male sterile material in maize. In this study, we performed transcriptome sequencing analysis of the V10 stage of male inflorescence. Through this analysis, 27.63 million raw reads were obtained, and trimming of the raw data revealed 26.63 million clean reads, with an average match rate of 94.64%. Using Tophat software, we matched these clean reads to the maize reference genome. The abundance of 39,622 genes was measured, and 35,399 genes remained after filtering out the non-expressed genes across all the samples. These genes were classified into 19 categories by clusters of orthologous groups of protein annotation. Transcriptome sequencing analysis of the male sterile and fertile 712C-ms22 maize revealed some key DEGs that may be related to metabolic pathways. qRT-PCR analysis validated the gene expression patterns identified by RNA-seq. This analysis revealed some of the essential genes responsible for pollen development and for pollen tube elongation. Our findings provide useful markers of male sterility and new insights into the global mechanisms mediating male sterility in maize.

Genome-wide identification and comparative analysis of phosphate starvation-responsive transcription factors in maize and three other gramineous plants

The present study identified several important candidate Pi regulation genes of maize and provides a better understanding on the generation of PHR genes in gramineous plants. Plants have evolved adaptive responses to cope with low phosphate (Pi) soils. The previous studies have indicated that phosphate starvation response (PHR) genes play central roles in regulating plant Pi starvation responses. However, the investigation of PHR family in gramineous plants is limited. In this study, we identified 64 PHR genes in four gramineous plants, including maize, rice, sorghum, and brachypodium, and conducted systematical analyses on phylogenetic, structure, collinearity, and expression pattern of these PHR genes. Genome synteny analysis revealed that a number of PHR genes were present in the corresponding syntenic blocks of maize, rice, sorghum, and brachypodium, indicating that large-scale duplication events contributed significantly to the expansion and evolution of PHR genes in these gramineous plants. Gene expression analysis showed that many PHR genes were expressed in various tissues, suggesting that these genes are involved in Pi redistribution and allocation. In addition, the expression levels of PHR genes from maize and rice under low Pi stress conditions revealed that some PHRs may play an important role in Pi starvation response. Our results provided a better understanding on the generation of PHR genes in gramineous plants and identified several important candidate Pi regulation genes of maize.

Proliferation of Regulatory DNA Elements Derived from Transposable Elements in the Maize Genome

Genomic regions free of nucleosomes, which are hypersensitive to DNase I digestion, are known as DNase I hypersensitive sites (DHSs) and frequently contain cis-regulatory DNA elements. To investigate their prevalence and characteristics in maize (Zea mays), we developed high-resolution genome-wide DHS maps using a modified DNase-seq technique. Maize DHSs exhibit depletion of nucleosomes and low levels of DNA methylation and are enriched with conserved noncoding sequences (CNSs). We developed a protoplast-based transient transformation assay to assess the potential gene expression enhancer and/or promoter functions associated with DHSs, which showed that more than 80% of DHSs overlapping with CNSs showed an enhancer function. Strikingly, nearly 25% of maize DHSs were derived from transposable elements (TEs), including both class I and class II transposons. Interestingly, TE-derived DHSs (teDHSs) homologous to retrotransposons were enriched with sequences related to the intrinsic cis-regulatory elements within the long terminal repeats of retrotransposons. We demonstrate that more than 80% of teDHSs can drive transcription of a reporter gene in protoplast assays. These results reveal the widespread occurrence of TE-derived cis-regulatory sequences and suggest that teDHSs play a major role in transcriptional regulation in maize.

Control of Maize Vegetative and Reproductive Development, Fertility, and rRNAs Silencing by HISTONE DEACETYLASE 108

Histone deacetylases (HDACs) catalyze the removal of acetyl groups from acetylated histone tails that consequently interact more closely with DNA, leading to chromatin state refractory to transcription. Zea mays HDA108 belongs to the Rpd3/HDA1 HDAC family and is ubiquitously expressed during development. The newly isolated hda108/hda108 insertional mutant exhibited many developmental defects: significant reduction in plant height, alterations of shoot and leaf development, and alterations of inflorescence patterning and fertility. Western blot analyses and immunolocalization experiments revealed an evident increase in histone acetylation, accompanied by a marked reduction in H3K9 dimethylation, in mutant nuclei. The DNA methylation status, in the CHG sequence context, and the transcript level of ribosomal sequences were also affected in hda108 mutants, while enrichment in H3 and H4 acetylation characterizes both repetitive and nonrepetitive transcriptional up-regulated loci. RNA-Seq of both young leaf and anthers indicated that transcription factor expression is highly affected and that the pollen developmental program is disrupted in hda108 mutants. Crosses between hda108/hda108 and epiregulator mutants did not produce any double mutant progeny indicating possible genetic interactions of HDA108 with distinct epigenetic pathways. Our findings indicate that HDA108 is directly involved in regulation of maize development, fertility, and epigenetic regulation of genome activity.

Comparative phylogenetic and expression analysis of small GTPases families in legume and non-legume plants

BACKGROUND

Small monomeric GTPases act as molecular switches in several processes that involve polar cell growth, participating mainly in vesicle trafficking and cytoskeleton rearrangements. This gene superfamily has largely expanded in plants through evolution as compared with other Kingdoms, leading to the suggestion that members of each subfamily might have acquired new functions associated to plant-specific processes. Legume plants engage in a nitrogen-fixing symbiotic interaction with rhizobia in a process that involves polar growth processes associated with the infection throughout the root hair. To get insight into the evolution of small GTPases associated with this process, we use a comparative genomic approach to establish differences in the Ras GTPase superfamily between legume and non-legume plants.

RESULTS

Phylogenetic analyses did not show clear differences in the organization of the different subfamilies of small GTPases between plants that engage or not in nodule symbiosis. Protein alignments revealed a strong conservation at the sequence level of small GTPases previously linked to nodulation by functional genetics. Interestingly, one Rab and three Rop proteins showed conserved amino acid substitutions in legumes, but these changes do not alter the predicted conformational structure of these proteins. Although the steady-state levels of most small GTPases do not change in response to rhizobia, we identified a subset of Rab, Rop and Arf genes whose transcript levels are modulated during the symbiotic interaction, including their spatial distribution along the indeterminate nodule.

CONCLUSIONS

This study provides a comprehensive study of the small GTPase superfamily in several plant species. The genetic program associated to root nodule symbiosis includes small GTPases to fulfill specific functions during infection and formation of the symbiosomes. These GTPases seems to have been recruited from members that were already present in common ancestors with plants as distant as monocots since we failed to detect asymmetric evolution in any of the subfamily trees. Expression analyses identified a number of legume members that can have undergone neo- or sub-functionalization associated to the spatio-temporal transcriptional control during the onset of the symbiotic interaction.

Control of Maize Vegetative and Reproductive Development, Fertility, and rRNAs Silencing by HISTONE DEACETYLASE 108

Histone deacetylases (HDACs) catalyze the removal of acetyl groups from acetylated histone tails that consequently interact more closely with DNA, leading to chromatin state refractory to transcription. Zea mays HDA108 belongs to the Rpd3/HDA1 HDAC family and is ubiquitously expressed during development. The newly isolated hda108/hda108 insertional mutant exhibited many developmental defects: significant reduction in plant height, alterations of shoot and leaf development, and alterations of inflorescence patterning and fertility. Western blot analyses and immunolocalization experiments revealed an evident increase in histone acetylation, accompanied by a marked reduction in H3K9 dimethylation, in mutant nuclei. The DNA methylation status, in the CHG sequence context, and the transcript level of ribosomal sequences were also affected in hda108 mutants, while enrichment in H3 and H4 acetylation characterizes both repetitive and nonrepetitive transcriptional up-regulated loci. RNA-Seq of both young leaf and anthers indicated that transcription factor expression is highly affected and that the pollen developmental program is disrupted in hda108 mutants. Crosses between hda108/hda108 and epiregulator mutants did not produce any double mutant progeny indicating possible genetic interactions of HDA108 with distinct epigenetic pathways. Our findings indicate that HDA108 is directly involved in regulation of maize development, fertility, and epigenetic regulation of genome activity.

The Sorghum bicolor reference genome: improved assembly, gene annotations, a transcriptome atlas, and signatures of genome organization

Sorghum bicolor is a drought tolerant C4 grass used for the production of grain, forage, sugar, and lignocellulosic biomass and a genetic model for C4 grasses due to its relatively small genome (approximately 800 Mbp), diploid genetics, diverse germplasm, and colinearity with other C4 grass genomes. In this study, deep sequencing, genetic linkage analysis, and transcriptome data were used to produce and annotate a high-quality reference genome sequence. Reference genome sequence order was improved, 29.6 Mbp of additional sequence was incorporated, the number of genes annotated increased 24% to 34 211, average gene length and N50 increased, and error frequency was reduced 10-fold to 1 per 100 kbp. Subtelomeric repeats with characteristics of Tandem Repeats in Miniature (TRIM) elements were identified at the termini of most chromosomes. Nucleosome occupancy predictions identified nucleosomes positioned immediately downstream of transcription start sites and at different densities across chromosomes. Alignment of more than 50 resequenced genomes from diverse sorghum genotypes to the reference genome identified approximately 7.4 M single nucleotide polymorphisms (SNPs) and 1.9 M indels. Large-scale variant features in euchromatin were identified with periodicities of approximately 25 kbp. A transcriptome atlas of gene expression was constructed from 47 RNA-seq profiles of growing and developed tissues of the major plant organs (roots, leaves, stems, panicles, and seed) collected during the juvenile, vegetative and reproductive phases. Analysis of the transcriptome data indicated that tissue type and protein kinase expression had large influences on transcriptional profile clustering. The updated assembly, annotation, and transcriptome data represent a resource for C4 grass research and crop improvement.

A Brief History of Promoter Development for Use in Transgenic Maize Applications

Promoters regulate gene expression, and are essential biotechnology tools. Since its introduction in the mid-1990s, biotechnology has greatly enhanced maize productivity primarily through the development of insect control and herbicide tolerance traits. Additional biotechnology applications include improving seed nutrient composition, industrial protein production, therapeutic production, disease resistance, abiotic stress resistance, and yield enhancement. Biotechnology has also greatly expanded basic research into important mechanisms that govern plant growth and reproduction. Many novel promoters have been developed to facilitate this work, but only a few are widely used. Transgene optimization includes a variety of strategies some of which effect promoter structure. Recent reviews examine the state of the art with respect to transgene design for biotechnology applications. This chapter examines the use of transgene technology in maize, focusing on the way promoters are selected and used. The impact of new developments in genomic technology on promoter structure is also discussed.

Highly interwoven communities of a gene regulatory network unveil topologically important genes for maize seed development

The complex interactions between transcription factors (TFs) and their target genes in a spatially and temporally specific manner are crucial to all cellular processes. Reconstruction of gene regulatory networks (GRNs) from gene expression profiles can help to decipher TF-gene regulations in a variety of contexts; however, the inevitable prediction errors of GRNs hinder optimal data mining of RNA-Seq transcriptome profiles. Here we perform an integrative study of Zea mays (maize) seed development in order to identify key genes in a complex developmental process. First, we reverse engineered a GRN from 78 maize seed transcriptome profiles. Then, we studied collective gene interaction patterns and uncovered highly interwoven network communities as the building blocks of the GRN. One community, composed of mostly unknown genes interacting with opaque2, brittle endosperm1 and shrunken2, contributes to seed phenotypes. Another community, composed mostly of genes expressed in the basal endosperm transfer layer, is responsible for nutrient transport. We further integrated our inferred GRN with gene expression patterns in different seed compartments and at various developmental stages and pathways. The integration facilitated a biological interpretation of the GRN. Our yeast one-hybrid assays verified six out of eight TF-promoter bindings in the reconstructed GRN. This study identified topologically important genes in interwoven network communities that may be crucial to maize seed development.

Patterns and Consequences of Subgenome Differentiation Provide Insights into the Nature of Paleopolyploidy in Plants

Polyploidy is an important feature of plant genomes, but the nature of many polyploidization events remains to be elucidated. Here, we demonstrate that the evolutionary fates of the subgenomes in maize (Zea mays) and soybean (Glycine max) have followed different trajectories. One subgenome has been subject to relaxed selection, lower levels of gene expression, higher rates of transposable element accumulation, more small interfering RNAs and DNA methylation around genes, and higher rates of gene loss in maize, whereas none of these features were observed in soybean. Nevertheless, individual gene pairs exhibit differentiation with respect to these features in both species. In addition, we observed a higher number of chromosomal rearrangements and higher frequency of retention of duplicated genes in soybean than in maize. Furthermore, soybean "singletons" were found to be more frequently tandemly duplicated than "duplicates" in soybean, which may, to some extent, counteract the genome imbalance caused by gene loss. We propose that unlike in maize, in which two subgenomes were distinct prior to the allotetraploidization event and thus experienced global differences in selective constraints, in soybean, the two subgenomes were far less distinct prior to polyploidization, such that individual gene pairs, rather than subgenomes, experienced stochastic differences over longer periods of time, resulting in retention of the majority of duplicates.

LSTrAP: efficiently combining RNA sequencing data into co-expression networks

BACKGROUND

Since experimental elucidation of gene function is often laborious, various in silico methods have been developed to predict gene function of uncharacterized genes. Since functionally related genes are often expressed in the same tissues, conditions and developmental stages (co-expressed), functional annotation of characterized genes can be transferred to co-expressed genes lacking annotation. With genome-wide expression data available, the construction of co-expression networks, where genes are nodes and edges connect significantly co-expressed genes, provides unprecedented opportunities to predict gene function. However, the construction of such networks requires large volumes of high-quality data, multiple processing steps and a considerable amount of computation power. While efficient tools exist to process RNA-Seq data, pipelines which combine them to construct co-expression networks efficiently are currently lacking.

RESULTS

LSTrAP (Large-Scale Transcriptome Analysis Pipeline), presented here, combines all essential tools to construct co-expression networks based on RNA-Seq data into a single, efficient workflow. By supporting parallel computing on computer cluster infrastructure, processing hundreds of samples becomes feasible as shown here for Arabidopsis thaliana and Sorghum bicolor, which comprised 876 and 215 samples respectively. The former was used here to show how the quality control, included in LSTrAP, can detect spurious or low-quality samples. The latter was used to show how co-expression networks are able to group known photosynthesis genes and imply a role in this process of several, currently uncharacterized, genes.

CONCLUSIONS

LSTrAP combines the most popular and performant methods to construct co-expression networks from RNA-Seq data into a single workflow. This allows large amounts of expression data, required to construct co-expression networks, to be processed efficiently and consistently across hundreds of samples. LSTrAP is implemented in Python 3.4 (or higher) and available under MIT license from https://github.molgen.mpg.de/proost/LSTrAP.