Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias

The Zea mays PeptideAtlas: A New Maize Community Resource

This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.

Prioritizing Maize Metabolic Gene Regulators through Multi-Omic Network Integration

Elucidating gene regulatory networks is a major area of study within plant systems biology. Phenotypic traits are intricately linked to specific gene expression profiles. These expression patterns arise primarily from regulatory connections between sets of transcription factors (TFs) and their target genes. Here, we integrated 46 co-expression networks, 283 protein-DNA interaction (PDI) assays, and 16 million SNPs used to identify expression quantitative trait loci (eQTL) to construct TF-target networks. In total, we analyzed ∼4.6M interactions to generate four distinct types of TF-target networks: co-expression, PDI, trans -eQTL, and cis -eQTL combined with PDIs. To functionally annotate TFs based on their target genes, we implemented three different network integration strategies. We evaluated the effectiveness of each strategy through TF loss-of function mutant inspection and random network analyses. The multi-network integration allowed us to identify transcriptional regulators of several biological processes. Using the topological properties of the fully integrated network, we identified potential functionally redundant TF paralogs. Our findings retrieved functions previously documented for numerous TFs and revealed novel functions that are crucial for informing the design of future experiments. The approach here-described lays the foundation for the integration of multi-omic datasets in maize and other plant systems.

GRAPHICAL ABSTRACT

Whole-genome duplication in an algal symbiont bolsters coral heat tolerance

The algal endosymbiont Durusdinium trenchii enhances the resilience of coral reefs under thermal stress. D. trenchii can live freely or in endosymbiosis, and the analysis of genetic markers suggests that this species has undergone whole-genome duplication (WGD). However, the evolutionary mechanisms that underpin the thermotolerance of this species are largely unknown. Here, we present genome assemblies for two D. trenchii isolates, confirm WGD in these taxa, and examine how selection has shaped the duplicated genome regions using gene expression data. We assess how the free-living versus endosymbiotic lifestyles have contributed to the retention and divergence of duplicated genes, and how these processes have enhanced the thermotolerance of D. trenchii. Our combined results suggest that lifestyle is the driver of post-WGD evolution in D. trenchii, with the free-living phase being the most important, followed by endosymbiosis. Adaptations to both lifestyles likely enabled D. trenchii to provide enhanced thermal stress protection to the host coral.

Genome-wide identification of potassium channels in maize showed evolutionary patterns and variable functional responses to abiotic stresses

Potassium (K) channels are essential components of plant biology, mediating not only K ion (K+) homeostasis but also regulating several physiological processes and stress tolerance. In the current investigation, we identified 27 K+ channels in maize and deciphered the evolution and divergence pattern with four monocots and five dicot species. Chromosomal localization and expansion of K+ channel genes showed uneven distribution and were independent of genome size. The dispersed duplication is the major force in expanding K+ channels in the target genomes. The mean Ka/Ks ratio of <0.5 in paralogs and orthologs indicates horizontal and vertical expansions of K+ channel genes under strong purifying selection. The one-to-one K+ channel orthologs were prominent among the closely related species, with higher synteny between maize and the rest of the monocots. Comprehensive K+ channels promoter analysis revealed various cis-regulatory elements mediating stress tolerance with the predominance of MYB and STRE binding sites. The regulatory network showed AP2-EREBP TFs, miR164 and miR399 are prominent regulatory elements of K+ channels. The qRT-PCR analysis of K+ channels and regulatory miRNAs showed significant expressions in response to drought and waterlogging stresses. The present study expanded the knowledge on K+ channels in maize and will serve as a basis for an in-depth functional analysis.

RoseAP: an analytical platform for gene function of Rosa rugosa

Rosa rugosa, a perennial shrub belonging to family Rosaceae, is a well-known ornamental plant. Its petals contain an abundance of essential oils and anthocyanins with enormous economic and health benefits when used as edible or cosmetic ingredients. The whole genome of R. rugosa was sequenced in 2021, which provided opportunities and challenges for gene regulation. However, many gene functions remain unknown. Therefore, an analytical platform named RoseAP (http://www.gzybioinformatics.cn/RoseAP/index.php) for the functional analysis of R. rugosa genes was constructed. It improved the gene annotation rate by integrating and analyzing genomic and transcriptomic datasets. First, 38,815 genes, covering 97.76% of the coding genes, were annotated functionally and structurally using a variety of algorithms and rules. Second, a total of 33 transcriptome samples were integrated, including 23 samples from our lab and 10 samples from the SRA database. A co-expression network containing approximately 29,657 positive or negative gene pairs, covering 74.7% of the coding genes, was constructed based on PCC and MR algorithms. Network analysis revealed that the DFR function was closely related to anthocyanin metabolism. It demonstrated the reliability of the network. Several SAUR genes of R. rugosa shared similar expression patterns. RoseAP was used to determine the sequence, structure, functional annotation, expression profile, regulatory network, and functional modules at the transcriptional and protein levels by inputting gene IDs. In addition, auxiliary analytical tools, including BLAST, gene set enrichment, orthologue conversion, gene sequence extraction, gene expression value extraction, and JBrowse, were utilized. Regular updates to RoseAP are expected to facilitate mining of gene function and promote genetic improvement in R. rugosa.

Tracing 100 million years of grass genome evolutionary plasticity

Grasses derive from a family of monocotyledonous plants that includes crops of major economic importance such as wheat, rice, sorghum and barley, sharing a common ancestor some 100 million years ago. The genomic attributes of plant adaptation remain obscure and the consequences of recurrent whole genome duplications (WGD) or polyploidization events, a major force in plant evolution, remain largely speculative. We conducted a comparative analysis of omics data from ten grass species to unveil structural (inversions, fusions, fissions, duplications, substitutions) and regulatory (expression and methylation) basis of genome plasticity, as possible attributes of plant long lasting evolution and adaptation. The present study demonstrates that diverged polyploid lineages sharing a common WGD event often present the same patterns of structural changes and evolutionary dynamics, but these patterns are difficult to generalize across independent WGD events as a result of non-WGD factors such as selection and domestication of crops. Polyploidy is unequivocally linked to the evolutionary success of grasses during the past 100 million years, although it remains difficult to attribute this success to particular genomic consequences of polyploidization, suggesting that polyploids harness the potential of genome duplication, at least partially, in lineage-specific ways. Overall, the present study clearly demonstrates that post-polyploidization reprogramming is more complex than traditionally reported in investigating single species and calls for a critical and comprehensive comparison across independently polyploidized lineages.

A pan-grass transcriptome reveals patterns of cellular divergence in crops

Different plant species within the grasses were parallel targets of domestication, giving rise to crops with distinct evolutionary histories and traits1. Key traits that distinguish these species are mediated by specialized cell types2. Here we compare the transcriptomes of root cells in three grass species-Zea mays, Sorghum bicolor and Setaria viridis. We show that single-cell and single-nucleus RNA sequencing provide complementary readouts of cell identity in dicots and monocots, warranting a combined analysis. Cell types were mapped across species to identify robust, orthologous marker genes. The comparative cellular analysis shows that the transcriptomes of some cell types diverged more rapidly than those of others-driven, in part, by recruitment of gene modules from other cell types. The data also show that a recent whole-genome duplication provides a rich source of new, highly localized gene expression domains that favour fast-evolving cell types. Together, the cell-by-cell comparative analysis shows how fine-scale cellular profiling can extract conserved modules from a pan transcriptome and provide insight on the evolution of cells that mediate key functions in crops.

The maize callose synthase SLM1 is critical for a normal growth by controlling the vascular development

Callose, mainly deposited at the cell plate and in the newly formed cell wall at a very low level, is critical for cell activity and growth in plants. The genetic control and function of callose synthases, responsible for the synthesis of callose, are largely unknown in maize. In this study, we cloned a maize callose synthase, SLM1 (Seedling Lethal Mutant1) encoding for a GLUCAN SYNTHASE-LIKE (GSL) gene, from a seedling lethal mutant. Three different point mutations confirmed the key role of SLM1 to maintain maize normal growth. SLM1 was specifically expressed in immature leaf vascular with an enrichment in phloem of developing vasculature. Consistently, slm1 had severe defects in vasculature and leaf development, and terminated growth about 2 weeks after germination. Thus, SLM1 is a key gene to maintain normal growth by controlling leaf vascular development and cell activities. Loss of SLM1 function interrupted severely the important signaling pathways in which cell cyclin and histone related genes are involved. Our study reveals the critical function of a maize GSL gene and also its downstream signaling to maintain a normal growth of maize.

Supplementary information

The online version contains supplementary material available at 10.1007/s11032-022-01350-4.

A multi-omics integrative network map of maize

Networks are powerful tools to uncover functional roles of genes in phenotypic variation at a system-wide scale. Here, we constructed a maize network map that contains the genomic, transcriptomic, translatomic and proteomic networks across maize development. This map comprises over 2.8 million edges in more than 1,400 functional subnetworks, demonstrating an extensive network divergence of duplicated genes. We applied this map to identify factors regulating flowering time and identified 2,651 genes enriched in eight subnetworks. We validated the functions of 20 genes, including 18 with previously unknown connections to flowering time in maize. Furthermore, we uncovered a flowering pathway involving histone modification. The multi-omics integrative network map illustrates the principles of how molecular networks connect different types of genes and potential pathways to map a genome-wide functional landscape in maize, which should be applicable in a wide range of species.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome

BACKGROUND

With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes.

RESULTS

To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network.

CONCLUSIONS

Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.

Spatio-temporal transcriptome profiling and subgenome analysis in Brassica napus

Brassica napus is an important oil crop and an allotetraploid species. However, the detailed analysis of gene function and homoeologous gene expression in all tissues at different developmental stages was not explored. In this study, we performed a global transcriptome analysis of 24 vegetative and reproductive tissues at six developmental stages (totally 111 tissues). These samples were clustered into eight groups. The gene functions of silique pericarp were similar to roots, stems and leaves. In particular, glucosinolate metabolic process was associated with root and silique pericarp. Genes involved in protein phosphorylation were often associated with stamen, anther and the early developmental stage of seeds. Transcription factor (TF) genes were more specific than structural genes. A total of 17 100 genes that were preferentially expressed in one tissue (tissue-preferred genes, TPGs), including 889 TFs (5.2%), were identified in the 24 tissues. Some TPGs were identified as hub genes in the co-expression network analysis, and some TPGs in different tissues were involved in different hormone pathways. About 67.0% of the homoeologs showed balanced expression, whereas biased expression of homoeologs was associated with structural divergence. In addition, the spatiotemporal expression of homoeologs was related to the presence of transposable elements (TEs) and regulatory elements (REs); more TEs and fewer REs in the promoters resulted in divergent expression in different tissues. This study provides a valuable transcriptional map for understanding the growth and development of B. napus, for identifying important genes for future crop improvement, and for exploring gene expression patterns in the B. napus.

Predicting Tissue-Specific mRNA and Protein Abundance in Maize: A Machine Learning Approach

Machine learning and modeling approaches have been used to classify protein sequences for a broad set of tasks including predicting protein function, structure, expression, and localization. Some recent studies have successfully predicted whether a given gene is expressed as mRNA or even translated to proteins potentially, but given that not all genes are expressed in every condition and tissue, the challenge remains to predict condition-specific expression. To address this gap, we developed a machine learning approach to predict tissue-specific gene expression across 23 different tissues in maize, solely based on DNA promoter and protein sequences. For class labels, we defined high and low expression levels for mRNA and protein abundance and optimized classifiers by systematically exploring various methods and combinations of k-mer sequences in a two-phase approach. In the first phase, we developed Markov model classifiers for each tissue and built a feature vector based on the predictions. In the second phase, the feature vector was used as an input to a Bayesian network for final classification. Our results show that these methods can achieve high classification accuracy of up to 95% for predicting gene expression for individual tissues. By relying on sequence alone, our method works in settings where costly experimental data are unavailable and reveals useful insights into the functional, evolutionary, and regulatory characteristics of genes.

Stop CRYing! Inhibition of cryptochrome function by small proteins

Plants can detect the presence of light using specialised photoreceptor proteins. These photoreceptors measure the intensity of light, but they can also respond to different spectra of light and thus ‘see' different colours. Cryptochromes, which are also present in animals, are flavin-based photoreceptors that enable plants to detect blue and ultraviolet-A (UV-A) light. In Arabidopsis, there are two cryptochromes, CRYPTOCHROME 1 (CRY1) and CRYPTOCHROME 2 (CRY2) with known sensory roles. They function in various processes such as blue-light mediated inhibition of hypocotyl elongation, photoperiodic promotion of floral initiation, cotyledon expansion, anthocyanin production, and magnetoreception, to name a few. In the dark, the cryptochromes are in an inactive monomeric state and undergo photochemical and conformational change in response to illumination. This results in flavin reduction, oligomerisation, and the formation of the ‘cryptochrome complexome'. Mechanisms of cryptochrome activation and signalling have been extensively studied and found to be conserved across phylogenetic lines. In this review, we will therefore focus on a far lesser-known mechanism of regulation that is unique to plant cryptochromes. This involves inhibition of cryptochrome activity by small proteins that prevent its dimerisation in response to light. The resulting inhibition of function cause profound alterations in economically important traits such as plant growth, flowering, and fruit production. This review will describe the known mechanisms of cryptochrome activation and signalling in the context of their modulation by these endogenous and artificial small inhibitor proteins. Promising new applications for biotechnological and agricultural applications will be discussed.

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

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

Hepatic transcriptome perturbations in dairy cows fed different forage resources

Background

Forage plays critical roles in milk performance of dairy. However, domestic high-quality forage such as alfalfa hay is far from being sufficient in China. Thus, more than 1 million tons of alfalfa hay were imported in China annually in recent years. At the same time, more than 10 million tons of corn stover are generated annually in China. Thus, taking full advantage of corn stover to meet the demand of forage and reduce dependence on imported alfalfa hay has been a strategic policy for the Chinese dairy industry. Changes in liver metabolism under different forage resources are not well known. Thus, the objective of the present study was to investigate the effect of different forage resources on liver metabolism using RNAseq and bioinformatics analyses.

Results

The results of this study showed that the cows fed a diet with corn stover (CS) as the main forage had lower milk yield, DMI, milk protein content and yield, milk fat yield, and lactose yield than cows fed a mixed forage (MF) diet (P <  0.01). KEGG analysis for differently expressed genes (DEG) in liver (81 up-regulated and 423 down-DEG, Padj ≤0.05) showed that pathways associated with glycan biosynthesis and metabolism and amino acid metabolism was inhibited by the CS diet. In addition, results from DAVID and ClueGO indicated that biological processes related to cell-cell adhesion, multicellular organism growth, and amino acid and protein metabolism also were downregulated by feeding CS. Co-expression network analysis indicated that FAM210A, SLC26A6, FBXW5, EIF6, ZSCAN10, FPGS, and ARMCX2 played critical roles in the network. Bioinformatics analysis showed that genes within the co-expression network were enriched to “pyruvate metabolic process”, “complement activation, classical pathway”, and “retrograde transport, endosome to Golgi”.

Conclusions

Results of the present study indicated that feeding a low-quality forage diet inhibits important biological functions of the liver at least in part due to a reduction in DMI. In addition, the results of the present study provide an insight into the metabolic response in the liver to different-quality forage resources. As such, the data can help develop favorable strategies to improve the utilization of corn stover in China.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07332-0.

Soybean TILLING-by-Sequencing+ reveals the role of novel GmSACPD members in unsaturated fatty acid biosynthesis while maintaining healthy nodules

Developing soybean lines with high levels of stearic acid is a primary goal of the soybean industry. Most high-stearic-acid soybeans carry different GmSACPD-C mutated alleles. However, due to the dual role of GmSACPD-C in seeds and nodule development, all derived deleterious GmSACPD-C mutant alleles are of extremely poor agronomic value because of defective nodulation. The soybean stearoyl-acyl carrier protein desaturase (GmSACPD) gene family is composed of five members. Comparative genomics analysis indicated that SACPD genes were duplicated and derived from a common ancestor that is still present in chlorophytic algae. Synteny analysis showed the presence of segment duplications between GmSACPD-A/GmSACPD-B, and GmSACPD-C/GmSACPD-D. GmSACPD-E was not contained in any duplicated segment and may be the result of tandem duplication. We developed a TILLING by Target Capture Sequencing (Tilling-by-Sequencing+) technology, a versatile extension of the conventional TILLING by sequencing, and successfully identified 12, 14, and 18 ethyl methanesulfonate mutants at the GmSACPD-A, GmSACPD-B, and GmSACPD-D genes, respectively. Functional analysis of all identified mutants revealed an unprecedented role of GmSACPD-A, GmSACPD-B, and GmSACPD-D in unsaturated fatty acid biosynthesis without affecting nodule development and structure. This discovery will positively impact the development of high-stearic-acid lines to enhance soybean nutritional value without potential developmental tradeoffs.

Hepatic transcriptomic adaptation from prepartum to postpartum in dairy cows

The transition from pregnancy to lactation is the most challenging period for high-producing dairy cows. The liver plays a key role in biological adaptation during the peripartum. Prior works have demonstrated that hepatic glucose synthesis, cholesterol metabolism, lipogenesis, and inflammatory response are increased or activated during the peripartum in dairy cows; however, those works were limited by a low number of animals used or by the use of microarray technology, or both. To overcome such limitations, an RNA sequencing analysis was performed on liver biopsies from 20 Holstein cows at 7 ± 5d before (Pre-P) and 16 ± 2d after calving (Post-P). We found 1,475 upregulated and 1,199 downregulated differently expressed genes (DEG) with a false discovery rate adjusted P-value < 0.01 between Pre-P and Post-P. Bioinformatic analysis revealed an activation of the metabolism, especially lipid, glucose, and amino acid metabolism, with increased importance of the mitochondria and a key role of several signaling pathways, chiefly peroxisome proliferators-activated receptor (PPAR) and adipocytokines signaling. Fatty acid oxidation and gluconeogenesis, with a likely increase in amino acid utilization to produce glucose, were among the most important functions revealed by the transcriptomic adaptation to lactation in the liver. Although gluconeogenesis was induced, data indicated decrease in expression of glucose transporters. The analysis also revealed high activation of cell proliferation but inhibition of xenobiotic metabolism, likely due to the liver response to inflammatory-like conditions. Co-expression network analysis disclosed a tight connection and coordination among genes driving biological processes associated with protein synthesis, energy and lipid metabolism, and cell proliferation. Our data confirmed the importance of metabolic adaptation to lipid and glucose metabolism in the liver of early Post-P cows, with a pivotal role of PPAR and adipocytokines.

3D genome architecture coordinates trans and cis regulation of differentially expressed ear and tassel genes in maize

BACKGROUND

Maize ears and tassels are two separate types of inflorescence which are initiated by similar developmental processes but gradually develop distinct architectures. However, coordinated trans and cis regulation of differentially expressed genes determining ear and tassel architecture within the 3D genome context is largely unknown.

RESULTS

We identify 56,055 and 52,633 open chromatin regions (OCRs) in developing maize ear and tassel primordia using ATAC-seq and characterize combinatorial epigenome features around these OCRs using ChIP-seq, Bisulfite-seq, and RNA-seq datasets. Our integrative analysis of coordinated epigenetic modification and transcription factor binding to OCRs highlights the cis and trans regulation of differentially expressed genes in ear and tassel controlling inflorescence architecture. We further systematically map chromatin interactions at high-resolution in corresponding tissues using in situ digestion-ligation-only Hi-C (DLO Hi-C). The extensive chromatin loops connecting OCRs and genes provide a 3D view on cis- and trans-regulatory modules responsible for ear- and tassel-specific gene expression. We find that intergenic SNPs tend to locate in distal OCRs, and our chromatin interaction maps provide a potential mechanism for trait-associated intergenic SNPs that may contribute to phenotypic variation by influencing target gene expression through chromatin loops.

CONCLUSIONS

Our comprehensive epigenome annotations and 3D genome maps serve as valuable resource and provide a deep understanding of the complex regulatory mechanisms of genes underlying developmental and morphological diversities between maize ear and tassel.

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

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

Co-expression networks for plant biology: why and how

Co-expression network analysis is one of the most powerful approaches for interpretation of large transcriptomic datasets. It enables characterization of modules of co-expressed genes that may share biological functional linkages. Such networks provide an initial way to explore functional associations from gene expression profiling and can be applied to various aspects of plant biology. This review presents the applications of co-expression network analysis in plant biology and addresses optimized strategies from the recent literature for performing co-expression analysis on plant biological systems. Additionally, we describe the combined interpretation of co-expression analysis with other genomic data to enhance the generation of biologically relevant information.

Trait ontology analysis based on association mapping studies bridges the gap between crop genomics and Phenomics

BACKGROUND

Trait ontology (TO) analysis is a powerful system for functional annotation and enrichment analysis of genes. However, given the complexity of the molecular mechanisms underlying phenomes, only a few hundred gene-to-TO relationships in plants have been elucidated to date, limiting the pace of research in this "big data" era.

RESULTS

Here, we curated all the available trait associated sites (TAS) information from 79 association mapping studies of maize (Zea mays L.) and rice (Oryza sativa L.) lines with diverse genetic backgrounds and built a large-scale TAS-derived TO system for functional annotation of genes in various crops. Our TO system contains information for up to 18,042 genes (6345 in maize at the 25 k level and 11,697 in rice at the 50 k level), including gene-to-TO relationships, which covers over one fifth of the annotated gene sets for maize and rice. A comparison of Gene Ontology (GO) vs. TO analysis demonstrated that the TAS-derived TO system is an efficient alternative tool for gene functional annotation and enrichment analysis. We therefore combined information from the TO, GO, metabolic pathway, and co-expression network databases and constructed the TAS system, which is publicly available at http://tas.hzau.edu.cn . TAS provides a user-friendly interface for functional annotation of genes, enrichment analysis, genome-wide extraction of trait-associated genes, and crosschecking of different functional annotation databases.

CONCLUSIONS

TAS bridges the gap between genomic and phenomic information in crops. This easy-to-use tool will be useful for geneticists, biologists, and breeders in the agricultural community, as it facilitates the dissection of molecular mechanisms conferring agronomic traits in an easy, genome-wide manner.

New lncRNA annotation reveals extensive functional divergence of the transcriptome in maize

Long non-coding RNAs (lncRNAs), whose sequences are approximately 200 bp or longer and unlikely to encode proteins, may play an important role in eukaryotic gene regulation. Although the latest maize (Zea mays L.) reference genome provides an essential genomic resource, genome-wide annotations of maize lncRNAs have not been updated. Here, we report on a large transcriptomic dataset collected from 749 RNA sequencing experiments across different tissues and stages of the maize reference inbred B73 line and 60 from its wild relative teosinte. We identified 18,165 high-confidence lncRNAs in maize, of which 6,873 are conserved between maize and teosinte. We uncovered distinct genomic characteristics of conserved lncRNAs, non-conserved lncRNAs, and protein-coding transcripts. Intriguingly, Shannon entropy analysis showed that conserved lncRNAs are likely to be expressed similarly to protein-coding transcripts. Co-expression network analysis revealed significant variation in the degree of co-expression. Furthermore, selection analysis indicated that conserved lncRNAs are more likely than non-conserved lncRNAs to be located in regions subject to recent selection, indicating evolutionary differentiation. Our results provide the latest genome-wide annotation and analysis of maize lncRNAs and uncover potential functional divergence between protein-coding, conserved lncRNA, and non-conserved lncRNA genes, demonstrating the high complexity of the maize transcriptome.

Cis-trans controls and regulatory novelty accompanying allopolyploidization

Allopolyploidy is a prevalent process in plants, having important physiological, ecological and evolutionary consequences. Transcriptomic responses to genomic merger and doubling have been demonstrated in many allopolyploid systems, encompassing a diversity of phenomena including homoeolog expression bias, genome dominance, expression-level dominance and revamping of co-expression networks. Notwithstanding the foregoing, there remains a need to develop a conceptual framework that will stimulate a deeper understanding of these diverse phenomena and their mechanistic interrelationships. Here we introduce considerations relevant to this framework with a focus on cis-trans interactions among duplicated genes and alleles in hybrids and allopolyploids. By extending classic allele-specific expression analysis to the allopolyploid level, we distinguish the distinct effects of progenitor regulatory interactions from the novel intergenomic interactions that arise from genome merger and allopolyploidization. This perspective informs experiments designed to reveal the molecular genetic basis of gene regulatory control, and will facilitate the disentangling of genetic from epigenetic and higher-order effects that impact gene expression. Finally, we suggest that the extended cis-trans model may help conceptually unify several presently disparate hallmarks of allopolyploid evolution, including genome-wide expression dominance and biased fractionation, and lead to a new level of understanding of phenotypic novelty accompanying polyploidy.

Distinct tissue-specific transcriptional regulation revealed by gene regulatory networks in maize

BACKGROUND

Transcription factors (TFs) are proteins that can bind to DNA sequences and regulate gene expression. Many TFs are master regulators in cells that contribute to tissue-specific and cell-type-specific gene expression patterns in eukaryotes. Maize has been a model organism for over one hundred years, but little is known about its tissue-specific gene regulation through TFs. In this study, we used a network approach to elucidate gene regulatory networks (GRNs) in four tissues (leaf, root, SAM and seed) in maize. We utilized GENIE3, a machine-learning algorithm combined with large quantity of RNA-Seq expression data to construct four tissue-specific GRNs. Unlike some other techniques, this approach is not limited by high-quality Position Weighed Matrix (PWM), and can therefore predict GRNs for over 2000 TFs in maize.

RESULTS

Although many TFs were expressed across multiple tissues, a multi-tiered analysis predicted tissue-specific regulatory functions for many transcription factors. Some well-studied TFs emerged within the four tissue-specific GRNs, and the GRN predictions matched expectations based upon published results for many of these examples. Our GRNs were also validated by ChIP-Seq datasets (KN1, FEA4 and O2). Key TFs were identified for each tissue and matched expectations for key regulators in each tissue, including GO enrichment and identity with known regulatory factors for that tissue. We also found functional modules in each network by clustering analysis with the MCL algorithm.

CONCLUSIONS

By combining publicly available genome-wide expression data and network analysis, we can uncover GRNs at tissue-level resolution in maize. Since ChIP-Seq and PWMs are still limited in several model organisms, our study provides a uniform platform that can be adapted to any species with genome-wide expression data to construct GRNs. We also present a publicly available database, maize tissue-specific GRN (mGRN, https://www.bio.fsu.edu/mcginnislab/mgrn/ ), for easy querying. All source code and data are available at Github ( https://github.com/timedreamer/maize_tissue-specific_GRN ).

Gene retention, fractionation and subgenome differences in polyploid plants

All natural plant species are evolved from ancient polyploids. Polyloidization plays an important role in plant genome evolution, species divergence and crop domestication. We review how the pattern of polyploidy within the plant phylogenetic tree has engendered hypotheses involving mass extinctions, lag-times following polyploidy, and epochs of asexuality. Polyploidization has happened repeatedly in plant evolution and, we conclude, is important for crop domestication. Once duplicated, the effect of purifying selection on any one duplicated gene is relaxed, permitting duplicate gene and regulatory element loss (fractionation). We review the general topic of fractionation, and how some gene categories are retained more than others. Several explanations, including neofunctionalization, subfunctionalization and gene product dosage balance, have been shown to influence gene content over time. For allopolyploids, genetic differences between parental lines immediately manifest as subgenome dominance in the wide-hybrid, and persist and propagate for tens of millions of years. While epigenetic modifications are certainly involved in genome dominance, it has been difficult to determine which came first, the chromatin marks being measured or gene expression. Data support the conclusion that genome dominance and heterosis are antagonistic and mechanically entangled; both happen immediately in the synthetic wide-cross hybrid. Also operating in this hybrid are mechanisms of 'paralogue interference'. We present a foundation model to explain gene expression and vigour in a wide hybrid/new allotetraploid. This Review concludes that some mechanisms operate immediately at the wide-hybrid, and other mechanisms begin their operations later. Direct interaction of new paralogous genes, as measured using high-resolution chromatin conformation capture, should inform future research and single cell transcriptome sequencing should help achieve specificity while studying gene sub- and neo-functionalization.

Functional Divergence between Subgenomes and Gene Pairs after Whole Genome Duplications

Gene loss following whole genome duplication (WGD) is often biased, with one subgenome retaining more ancestral genes and the other sustaining more gene deletions. While bias toward the greater expression of gene copies on one subgenome can explain bias in gene loss, this raises the question to what drives differences in gene expression levels between subgenomes. Differences in chromatin modifications and epigenetic markers between subgenomes in several model species are now being identified, providing an explanation for bias in gene expression between subgenomes. WGDs can be classified into duplications with higher, biased gene loss and bias in gene expression between subgenomes versus those with lower, unbiased rates of gene loss and an absence of detectable bias between subgenomes; however, the originally proposed link between these two classes and whether WGD results from an allo- or autopolyploid event is inconsistent with recent data from the allopolyploid Capsella bursa-pastoris. The gene balance hypothesis can explain bias in the functional categories of genes retained following WGD, the difference in gene loss rates between unbiased and biased WGDs, and how plant genomes have avoided being overrun with genes encoding dose-sensitive subunits of multiprotein complexes. Comparisons of gene expression patterns between retained transcription factor pairs in maize suggest the high degree of retention for WGD-derived pairs of transcription factors may instead be explained by the older duplication-degeneration-complementation model.

Largely unlinked gene sets targeted by selection for domestication syndrome phenotypes in maize and sorghum

The domestication of diverse grain crops from wild grasses was a result of artificial selection for a suite of overlapping traits producing changes referred to in aggregate as 'domestication syndrome'. Parallel phenotypic change can be accomplished by either selection on orthologous genes or selection on non-orthologous genes with parallel phenotypic effects. To determine how often artificial selection for domestication traits in the grasses targeted orthologous genes, we employed resequencing data from wild and domesticated accessions of Zea (maize) and Sorghum (sorghum). Many 'classic' domestication genes identified through quantitative trait locus mapping in populations resulting from wild/domesticated crosses indeed show signatures of parallel selection in both maize and sorghum. However, the overall number of genes showing signatures of parallel selection in both species is not significantly different from that expected by chance. This suggests that while a small number of genes will extremely large phenotypic effects have been targeted repeatedly by artificial selection during domestication, the optimization part of domestication targeted small and largely non-overlapping subsets of all possible genes which could produce equivalent phenotypic alterations.

Differentially Regulated Orthologs in Sorghum and the Subgenomes of Maize

Identifying interspecies changes in gene regulation, one of the two primary sources of phenotypic variation, is challenging on a genome-wide scale. The use of paired time-course data on cold-responsive gene expression in maize (Zea mays) and sorghum (Sorghum bicolor) allowed us to identify differentially regulated orthologs. While the majority of cold-responsive transcriptional regulation of conserved gene pairs is species specific, the initial transcriptional responses to cold appear to be more conserved than later responses. In maize, the promoters of genes with conserved transcriptional responses to cold tend to contain more micrococcal nuclease hypersensitive sites in their promoters, a proxy for open chromatin. Genes with conserved patterns of transcriptional regulation between the two species show lower ratios of nonsynonymous to synonymous substitutions. Genes involved in lipid metabolism, known to be involved in cold acclimation, tended to show consistent regulation in both species. Genes with species-specific cold responses did not cluster in particular pathways nor were they enriched in particular functional categories. We propose that cold-responsive transcriptional regulation in individual species may not be a reliable marker for function, while a core set of genes involved in perceiving and responding to cold stress are subject to functionally constrained cold-responsive regulation across the grass tribe Andropogoneae.

STAG-CNS: An Order-Aware Conserved Noncoding Sequences Discovery Tool for Arbitrary Numbers of Species

One method for identifying noncoding regulatory regions of a genome is to quantify rates of divergence between related species, as functional sequence will generally diverge more slowly. Most approaches to identifying these conserved noncoding sequences (CNSs) based on alignment have had relatively large minimum sequence lengths (≥15 bp) compared with the average length of known transcription factor binding sites. To circumvent this constraint, STAG-CNS that can simultaneously integrate the data from the promoters of conserved orthologous genes in three or more species was developed. Using the data from up to six grass species made it possible to identify conserved sequences as short as 9 bp with false discovery rate ≤0.05. These CNSs exhibit greater overlap with open chromatin regions identified using DNase I hypersensitivity assays, and are enriched in the promoters of genes involved in transcriptional regulation. STAG-CNS was further employed to characterize loss of conserved noncoding sequences associated with retained duplicate genes from the ancient maize polyploidy. Genes with fewer retained CNSs show lower overall expression, although this bias is more apparent in samples of complex organ systems containing many cell types, suggesting that CNS loss may correspond to a reduced number of expression contexts rather than lower expression levels across the entire ancestral expression domain.