Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants

Genome-wide identification of kiwifruit K+ channel Shaker family members and their response to low-K+ stress

BACKGROUND

'Hongyang' kiwifruit (Actinidia chinensis cv 'Hongyang') is a high-quality variety of A. chinensis with the advantages of high yield, early ripening, and high stress tolerance. Studies have confirmed that the Shaker K+ genes family is involved in plant uptake and distribution of potassium (K+).

RESULTS

Twenty-eight Shaker genes were identified and analyzed from the 'Hongyang' kiwifruit (A. chinensis cv 'Hongyang') genome. Subcellular localization results showed that more than one-third of the AcShaker genes were on the cell membrane. Phylogenetic analysis indicated that the AcShaker genes were divided into six subfamilies (I-VI). Conservative model, gene structure, and structural domain analyses showed that AcShaker genes of the same subfamily have similar sequence features and structure. The promoter cis-elements of the AcShaker genes were classified into hormone-associated cis-elements and environmentally stress-associated cis-elements. The results of chromosomal localization and duplicated gene analysis demonstrated that AcShaker genes were distributed on 18 chromosomes, and segmental duplication was the prime mode of gene duplication in the AcShaker family. GO enrichment analysis manifested that the ion-conducting pathway of the AcShaker family plays a crucial role in regulating plant growth and development and adversity stress. Compared with the transcriptome data of the control group, all AcShaker genes were expressed under low-K+stress, and the expression differences of three genes (AcShaker15, AcShaker17, and AcShaker22) were highly significant. The qRT-PCR results showed a high correlation with the transcriptome data, which indicated that these three differentially expressed genes could regulate low-K+ stress and reduce K+ damage in kiwifruit plants, thus improving the resistance to low-K+ stress. Comparison between the salt stress and control transcriptomic data revealed that the expression of AcShaker11 and AcShaker18 genes was significantly different and lower under salt stress, indicating that both genes could be involved in salt stress resistance in kiwifruit.

CONCLUSION

The results showed that 28 AcShaker genes were identified and all expressed under low K+ stress, among which AcShaker22 was differentially and significantly upregulated. The AcShaker22 gene can be used as a candidate gene to cultivate new varieties of kiwifruit resistant to low K+ and provide a reference for exploring more properties and functions of the AcShaker genes.

New whole-genome alignment tools are needed for tapping into plant diversity

Genome alignment is one of the most foundational methods for genome sequence studies. With rapid advances in sequencing and assembly technologies, these newly assembled genomes present challenges for alignment tools to meet the increased complexity and scale. Plant genome alignment is technologically challenging because of frequent whole-genome duplications (WGDs) as well as chromosome rearrangements and fractionation, high nucleotide diversity, widespread structural variation, and high transposable element (TE) activity causing large proportions of repeat elements. We summarize classical pairwise and multiple genome alignment (MGA) methods, and highlight techniques that are widely used or are being developed by the plant research community. We also outline the remaining challenges for precise genome alignment and the interpretation of alignment results in plants.

Genome-wide identification and expression analysis of the MADS gene family in sweet orange (Citrus sinensis) infested with pathogenic bacteria

The risk of pathogenic bacterial invasion in plantations has increased dramatically due to high environmental climate change and has seriously affected sweet orange fruit quality. MADS genes allow plants to develop increased resistance, but functional genes for resistance associated with pathogen invasion have rarely been reported. MADS gene expression profiles were analyzed in sweet orange leaves and fruits infested with Lecanicillium psalliotae and Penicillium digitatum, respectively. Eighty-two MADS genes were identified from the sweet orange genome, and they were classified into five prime subfamilies concerning the Arabidopsis MADS gene family, of which the MIKC subfamily could be subdivided into 13 minor subfamilies. Protein structure analysis showed that more than 93% of the MADS protein sequences of the same subfamily between sweet orange and Arabidopsis were very similar in tertiary structure, with only CsMADS8 and AG showing significant differences. The variability of MADS genes protein structures between sweet orange and Arabidopsis subgroups was less than the variabilities of protein structures within species. Chromosomal localization and covariance analysis showed that these genes were unevenly distributed on nine chromosomes, with the most genes on chromosome 9 and the least on chromosome 2, with 36 and two, respectively. Four pairs of tandem and 28 fragmented duplicated genes in the 82 MADS gene sequences were found in sweet oranges. GO (Gene Ontology) functional enrichment and expression pattern analysis showed that the functional gene CsMADS46 was strongly downregulated of sweet orange in response to biotic stress adversity. It is also the first report that plants' MADS genes are involved in the biotic stress responses of sweet oranges. For the first time, L. psalliotae was experimentally confirmed to be the causal agent of sweet orange leaf spot disease, which provides a reference for the research and control of pathogenic L. psalliotae.

Genome-wide comparative analysis of the valine glutamine motif containing genes in four Ipomoea species

BACKGROUND

Genes with valine glutamine (VQ) motifs play an essential role in plant growth, development, and resistance to biotic and abiotic stresses. However, little information on the VQ genes in sweetpotato and other Ipomoea species is available.

RESULTS

This study identified 55, 58, 50 and 47 VQ genes from sweetpotato (I. batatas), I.triflida, I. triloba and I. nil, respectively. The phylogenetic analysis revealed that the VQ genes formed eight clades (I-VII), and the members in the same group exhibited similar exon-intron structure and conserved motifs distribution. The distribution of the VQ genes among the chromosomes of Ipomoea species was disproportional, with no VQ genes mapped on a few of each species' chromosomes. Duplication analysis suggested that segmental duplication significantly contributes to their expansion in sweetpotato, I.trifida, and I.triloba, while the segmental and tandem duplication contributions were comparable in I.nil. Cis-regulatory elements involved in stress responses, such as W-box, TGACG-motif, CGTCA-motif, ABRE, ARE, MBS, TCA-elements, LTR, and WUN-motif, were detected in the promoter regions of the VQ genes. A total of 30 orthologous groups were detected by syntenic analysis of the VQ genes. Based on the analysis of RNA-seq datasets, it was found that the VQ genes are expressed distinctly among different tissues and hormone or stress treatments. A total of 40 sweetpotato differentially expressed genes (DEGs) refer to biotic (sweetpotato stem nematodes and Ceratocystis fimbriata pathogen infection) or abiotic (cold, salt and drought) stress treatments were detected. Moreover, IbVQ8, IbVQ25 and IbVQ44 responded to the five stress treatments and were selected for quantitative reverse-transcription polymerase chain reaction (qRT-PCR) analysis, and the results were consistent with the transcriptome analysis.

CONCLUSIONS

Our study may provide new insights into the evolution of VQ genes in the four Ipomoea genomes and contribute to the future molecular breeding of sweetpotatoes.

Identification of clade-wide putative cis-regulatory elements from conserved non-coding sequences in Cucurbitaceae genomes

Cis-regulatory elements regulate gene expression and play an essential role in the development and physiology of organisms. Many conserved non-coding sequences (CNSs) function as cis-regulatory elements. They control the development of various lineages. However, predicting clade-wide cis-regulatory elements across several closely related species remains challenging. Based on the relationship between CNSs and cis-regulatory elements, we present a computational approach that predicts the clade-wide putative cis-regulatory elements in 12 Cucurbitaceae genomes. Using 12-way whole-genome alignment, we first obtained 632 112 CNSs in Cucurbitaceae. Next, we identified 16 552 Cucurbitaceae-wide cis-regulatory elements based on collinearity among all 12 Cucurbitaceae plants. Furthermore, we predicted 3 271 potential regulatory pairs in the cucumber genome, of which 98 were verified using integrative RNA sequencing and ChIP sequencing datasets from samples collected during various fruit development stages. The CNSs, Cucurbitaceae-wide cis-regulatory elements, and their target genes are accessible at http://cmb.bnu.edu.cn/cisRCNEs_cucurbit/. These elements are valuable resources for functionally annotating CNSs and their regulatory roles in Cucurbitaceae genomes.

Genome-wide identification, characterization, and expression profile ofNBS-LRRgene family in sweet orange (Citrussinensis)

BACKGROUND

The NBS-LRR (nucleotide-binding site-leucine-rich repeat gene) gene family, known as the plant R (resistance) gene family with the most members, plays a significant role in plant resistance to various external adversity stresses. The NBS-LRR gene family has been researched in many plant species. Citrus is one of the most vital global cash crops, the number one fruit group, and the third most traded agricultural product world wild. However, as one of the largest citrus species, a comprehensive study of the NBS-LRR gene family has not been reported on sweet oranges.

METHODS

In this study, NBS-LRR genes were identified from the Citrus sinensis genome (v3.0), with a comprehensive analysis of this gene family performed, including phylogenetic analysis, gene structure, cis-acting element of a promoter, and chromosomal localization, among others. The expression pattern of NBS-LRR genes was analyzed when sweet orange fruits were infected by Penicillium digitatum, employing experimental data from our research group. It first reported the expression patterns of NBS-LRR genes under abiotic stresses, using three transcript data from NCBI (National Center for Biotechnology Information).

RESULTS

In this study, 111 NBS-LRR genes were identified in the C. sinensis genome (v3.0) and classified into seven subfamilies according to their N-terminal and C-terminal domains. The phylogenetic tree results indicate that genes containing only the NBS structural domain are more ancient in the sweet orange NBS-LRR gene family. The chromosome localization results showed that 111 NBS-LRR genes were distributed unevenly on nine chromosomes, with the most genes distributed on chromosome 1. In addition, we identified a total of 18 tandem duplication gene pairs in the sweet orange NBS-LRR gene family, and based on the Ka/Ks ratio, all of the tandem duplication genes underwent purifying selection. Transcriptome data analysis showed a significant number of NBS-LRR genes expressed under biotic and abiotic stresses, and some reached significantly different levels of expression. It indicates that the NBS-LRR gene family is vital in resistance to biotic and abiotic stresses in sweet oranges.

CONCLUSION

Our study provides the first comprehensive framework on the NBS-LRR family of genes, which provides a basis for further in-depth studies on the biological functions of NBS-LRR in growth, development, and response to abiotic stresses in sweet orange.

Exploiting Genomic Features to Improve the Prediction of Transcription Factor-Binding Sites in Plants

The identification of transcription factor (TF) target genes is central in biology. A popular approach is based on the location by pattern matching of potential cis-regulatory elements (CREs). During the last few years, tools integrating next-generation sequencing data have been developed to improve the performance of pattern matching. However, such tools have not yet been comprehensively evaluated in plants. Hence, we developed a new streamlined method aiming at predicting CREs and target genes of plant TFs in specific organs or conditions. Our approach implements a supervised machine learning strategy, which allows decision rule models to be learnt using TF ChIP-chip/seq experimental data. Different layers of genomic features were integrated in predictive models: the position on the gene, the DNA sequence conservation, the chromatin state and various CRE footprints. Among the tested features, the chromatin features were crucial for improving the accuracy of the method. Furthermore, we evaluated the transferability of predictive models across TFs, organs and species. Finally, we validated our method by correctly inferring the target genes of key TFs controlling metabolite biosynthesis at the organ level in Arabidopsis. We developed a tool-Wimtrap-to reproduce our approach in plant species and conditions/organs for which ChIP-chip/seq data are available. Wimtrap is a user-friendly R package that supports an R Shiny web interface and is provided with pre-built models that can be used to quickly get predictions of CREs and TF gene targets in different organs or conditions in Arabidopsis thaliana, Solanum lycopersicum, Oryza sativa and Zea mays.

Genome-wide identification and characterization of NBS-encoding genes in the sweet potato wild ancestor Ipomoea trifida (H.B.K.)

The most predominant type of resistance (R) genes contain nucleotide-binding sites and leucine-rich repeat (NBS-LRR) domains, characterization of which is helpful for plant resistance improvement. However, the NBS genes of Ipomoea trifida (H.B.K.) remain insufficient to date. In this study, a genome-wide analysis of the NBS-encoding gene in I. trifida (H.B.K.) was carried out. A total of 442 NBS encoding genes were identified, amounting to 1.37% of the total genes of I. trifida (H.B.K.). Based on the analysis of the domains, the identified ItfNBS genes were further classified into seven groups: CNL, NL, CN, N, TNL, TN, and RNL. Phylogenetic analysis showed that the I. trifida NBS genes clustered into three independent clades: RNL, TNL, and CNL. Chromosome location analysis revealed that the distribution of ItfNBS genes in chromosomes was uneven, with a number ranging from 3 to 45. Multiple stress-related regulatory elements were detected in the promoters of the NBS-encoding genes, and their expression profiles were obtained. The qRT-PCR analysis revealed that IbNBS10, IbNBS20, IbNBS258, and IbNBS88 responded to stem nematode infection. These results provide critical proof for further characterization and analysis of NBS-encoding genes with important functions.

Characterization of Nucleotide Binding -Site-Encoding Genes in Sweetpotato, Ipomoea batatas(L.) Lam., and Their Response to Biotic and Abiotic Stresses

Sweetpotato, Ipomoea batatas (L.) Lam., is an important and widely grown crop, yet its production is affected severely by biotic and abiotic stresses. The nucleotide binding site (NBS)-encoding genes have been shown to improve stress tolerance in several plant species. However, the characterization of NBS-encoding genes in sweetpotato is not well-documented to date. In this study, a comprehensive analysis of NBS-encoding genes has been conducted on this species by using bioinformatics and molecular biology methods. A total of 315 NBS-encoding genes were identified, and 260 of them contained all essential conserved domains while 55 genes were truncated. Based on domain architectures, the 260 NBS-encoding genes were grouped into 6 distinct categories. Phylogenetic analysis grouped these genes into 3 classes: TIR, CC (I), and CC (II). Chromosome location analysis revealed that the distribution of NBS-encoding genes in chromosomes was uneven, with a number ranging from 1 to 34. Multiple stress-related regulatory elements were detected in the promoters, and the NBS-encoding genes' expression profiles under biotic and abiotic stresses were obtained. According to the bioinformatics analysis, 9 genes were selected for RT-qPCR analysis. The results revealed that IbNBS75, IbNBS219, and IbNBS256 respond to stem nematode infection; Ib-NBS240, IbNBS90, and IbNBS80 respond to cold stress, while IbNBS208, IbNBS71, and IbNBS159 respond to 30% PEG treatment. We hope these results will provide new insights into the evolution of NBS-encoding genes in the sweetpotato genome and contribute to the molecular breeding of sweetpotato in the future.

Gene expression evolution in pattern-triggered immunity within Arabidopsis thaliana and across Brassicaceae species

Plants recognize surrounding microbes by sensing microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). Despite their significance for microbial control, the evolution of PTI responses remains largely uncharacterized. Here, by employing comparative transcriptomics of six Arabidopsis thaliana accessions and three additional Brassicaceae species to investigate PTI responses, we identified a set of genes that commonly respond to the MAMP flg22 and genes that exhibit species-specific expression signatures. Variation in flg22-triggered transcriptome responses across Brassicaceae species was incongruent with their phylogeny, while expression changes were strongly conserved within A. thaliana. We found the enrichment of WRKY transcription factor binding sites in the 5'-regulatory regions of conserved and species-specific responsive genes, linking the emergence of WRKY-binding sites with the evolution of gene expression patterns during PTI. Our findings advance our understanding of the evolution of the transcriptome during biotic stress.

Ultra-conserved sequences in the genomes of highly diverse Anopheles mosquitoes, with implications for malaria vector control

DNA sequences that are exactly conserved over long evolutionary time scales have been observed in a variety of taxa. Such sequences are likely under strong functional constraint and they have been useful in the field of comparative genomics for identifying genome regions with regulatory function. A potential new application for these ultra-conserved elements (UCEs) has emerged in the development of gene drives to control mosquito populations. Many gene drives work by recognizing and inserting at a specific target sequence in the genome, often imposing a reproductive load as a consequence. They can therefore select for target sequence variants that provide resistance to the drive. Focusing on highly conserved, highly constrained sequences lowers the probability that variant, gene drive-resistant alleles can be tolerated. Here, we search for conserved sequences of 18 bp and over in an alignment of 21 Anopheles genomes, spanning an evolutionary timescale of 100 million years, and characterize the resulting sequences according to their location and function. Over 8000 UCEs were found across the alignment, with a maximum length of 164 bp. Length-corrected gene ontology analysis revealed that genes containing Anopheles UCEs were over-represented in categories with structural or nucleotide-binding functions. Known insect transcription factor binding sites were found in 48% of intergenic Anopheles UCEs. When we looked at the genome sequences of 1142 wild-caught mosquitoes, we found that 15% of the Anopheles UCEs contained no polymorphisms. Our list of Anopheles UCEs should provide a valuable starting point for the selection and testing of new targets for gene-drive modification in the mosquitoes that transmit malaria.

PlantRegMap: charting functional regulatory maps in plants

With the goal of charting plant transcriptional regulatory maps (i.e. transcription factors (TFs), cis-elements and interactions between them), we have upgraded the TF-centred database PlantTFDB (http://planttfdb.cbi.pku.edu.cn/) to a plant regulatory data and analysis platform PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) over the past three years. In this version, we updated the annotations for the previously collected TFs and set up a new section, ‘extended TF repertoires’ (TFext), to allow users prompt access to the TF repertoires of newly sequenced species. In addition to our regular TF updates, we are dedicated to updating the data on cis-elements and functional interactions between TFs and cis-elements. We established genome-wide conservation landscapes for 63 representative plants and then developed an algorithm, FunTFBS, to screen for functional regulatory elements and interactions by coupling the base-varied binding affinities of TFs with the evolutionary footprints on their binding sites. Using the FunTFBS algorithm and the conservation landscapes, we further identified over 20 million functional TF binding sites (TFBSs) and two million functional interactions for 21 346 TFs, charting the functional regulatory maps of these 63 plants. These resources are publicly available at PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) and a cloud-based mirror (http://plantregmap.gao-lab.org/), providing the plant research community with valuable resources for decoding plant transcriptional regulatory systems.

Inferring biosynthetic and gene regulatory networks from Artemisia annua RNA sequencing data on a credit card-sized ARM computer

Prediction of gene function and gene regulatory networks is one of the most active topics in bioinformatics. The accumulation of publicly available gene expression data for hundreds of plant species, together with advances in bioinformatical methods and affordable computing, sets ingenuity as one of the major bottlenecks in understanding gene function and regulation. Here, we show how a credit card-sized computer retailing for <50 USD can be used to rapidly predict gene function and infer regulatory networks from RNA sequencing data. To achieve this, we constructed a bioinformatical pipeline that downloads and allows quality-control of RNA sequencing data; and generates a gene co-expression network that can reveal enzymes and transcription factors participating and controlling a given biosynthetic pathway. We exemplify this by first identifying genes and transcription factors involved in the biosynthesis of secondary cell wall in the plant Artemisia annua, the main natural source of the anti-malarial drug artemisinin. Networks were then used to dissect the artemisinin biosynthesis pathway, which suggest potential transcription factors regulating artemisinin biosynthesis. We provide the source code of our pipeline (https://github.com/mutwil/LSTrAP-Lite) and envision that the ubiquity of affordable computing, availability of biological data and increased bioinformatical training of biologists will transform the field of bioinformatics. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

Enhanced Maps of Transcription Factor Binding Sites Improve Regulatory Networks Learned from Accessible Chromatin Data

Determining where transcription factors (TFs) bind in genomes provides insight into which transcriptional programs are active across organs, tissue types, and environmental conditions. Recent advances in high-throughput profiling of regulatory DNA have yielded large amounts of information about chromatin accessibility. Interpreting the functional significance of these data sets requires knowledge of which regulators are likely to bind these regions. This can be achieved by using information about TF-binding preferences, or motifs, to identify TF-binding events that are likely to be functional. Although different approaches exist to map motifs to DNA sequences, a systematic evaluation of these tools in plants is missing. Here, we compare four motif-mapping tools widely used in the Arabidopsis (Arabidopsis thaliana) research community and evaluate their performance using chromatin immunoprecipitation data sets for 40 TFs. Downstream gene regulatory network (GRN) reconstruction was found to be sensitive to the motif mapper used. We further show that the low recall of Find Individual Motif Occurrences, one of the most frequently used motif-mapping tools, can be overcome by using an Ensemble approach, which combines results from different mapping tools. Several examples are provided demonstrating how the Ensemble approach extends our view on transcriptional control for TFs active in different biological processes. Finally, a protocol is presented to effectively derive more complete cell type-specific GRNs through the integrative analysis of open chromatin regions, known binding site information, and expression data sets. This approach will pave the way to increase our understanding of GRNs in different cellular conditions.

TF2Network: predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidopsis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75–92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response.

Bringing numerous methods for expression and promoter analysis to a public cloud computing service

Summary

Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project.

Availability and implementation

The integrated apps can be found at http://www.cyverse.org/discovery-environment, while the raw code is available at https://github.com/cyversewarwick and the corresponding Docker images are housed at https://hub.docker.com/r/cyversewarwick/.

Contact

info@cyverse.warwick.ac.uk or D.L.Wild@warwick.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-scale examination of NBS-encoding genes in blueberry

Blueberry is an important crop worldwide. It is, however, susceptible to a variety of diseases, which can lead to losses in yield and fruit quality. Although screening studies have identified resistant germplasm for some important diseases, still little is known about the molecular basis underlying that resistance. The most predominant type of resistance (R) genes contains nucleotide binding site and leucine rich repeat (NBS-LRR) domains. The identification and characterization of such a gene family in blueberry would enhance the foundation of knowledge needed for its genetic improvement. In this study, we searched for and found a total of 106 NBS-encoding genes (including 97 NBS-LRR) in the current blueberry genome. The NBS genes were grouped into eleven distinct classes based on their domain architecture. More than 22% of the NBS genes are present in clusters. Ten genes were mapped onto seven linkage groups. Phylogenetic analysis grouped these genes into two major clusters based on their structural variation, the first cluster having toll and interleukin-1 like receptor (TIR) domains and most of the second cluster containing a coiled-coil domain. Our study provides new insight into the NBS gene family in blueberry and is an important resource for the identification of functional R-genes.

Conserved noncoding sequences conserve biological networks and influence genome evolution

Comparative genomics approaches have identified numerous conserved cis-regulatory sequences near genes in plant genomes. Despite the identification of these conserved noncoding sequences (CNSs), our knowledge of their functional importance and selection remains limited. Here, we used a combination of DNA methylome analysis, microarray expression analyses, and functional annotation to study these sequences in the model tree Populus trichocarpa. Methylation in CG contexts and non-CG contexts was lower in CNSs, particularly CNSs in the 5'-upstream regions of genes, compared with other sites in the genome. We observed that CNSs are enriched in genes with transcription and binding functions, and this also associated with syntenic genes and those from whole-genome duplications, suggesting that cis-regulatory sequences play a key role in genome evolution. We detected a significant positive correlation between CNS number and protein interactions, suggesting that CNSs may have roles in the evolution and maintenance of biological networks. The divergence of CNSs indicates that duplication-degeneration-complementation drives the subfunctionalization of a proportion of duplicated genes from whole-genome duplication. Furthermore, population genomics confirmed that most CNSs are under strong purifying selection and only a small subset of CNSs shows evidence of adaptive evolution. These findings provide a foundation for future studies exploring these key genomic features in the maintenance of biological networks, local adaptation, and transcription.

Engineering Quantitative Trait Variation for Crop Improvement by Genome Editing

Major advances in crop yields are needed in the coming decades. However, plant breeding is currently limited by incremental improvements in quantitative traits that often rely on laborious selection of rare naturally occurring mutations in gene-regulatory regions. Here, we demonstrate that CRISPR/Cas9 genome editing of promoters generates diverse cis-regulatory alleles that provide beneficial quantitative variation for breeding. We devised a simple genetic scheme, which exploits trans-generational heritability of Cas9 activity in heterozygous loss-of-function mutant backgrounds, to rapidly evaluate the phenotypic impact of numerous promoter variants for genes regulating three major productivity traits in tomato: fruit size, inflorescence branching, and plant architecture. Our approach allows immediate selection and fixation of novel alleles in transgene-free plants and fine manipulation of yield components. Beyond a platform to enhance variation for diverse agricultural traits, our findings provide a foundation for dissecting complex relationships between gene-regulatory changes and control of quantitative traits.

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.

GC Content Heterogeneity Transition of Conserved Noncoding Sequences Occurred at the Emergence of Vertebrates

Conserved non-coding sequences (CNSs) of Eukaryotes are known to be significantly enriched in regulatory sequences. CNSs of diverse lineages follow different patterns in abundance, sequence composition, and location. Here, we report a thorough analysis of CNSs in diverse groups of Eukaryotes with respect to GC content heterogeneity. We examined 24 fungi, 19 invertebrates, and 12 non-mammalian vertebrates so as to find lineage specific features of CNSs. We found that fungi and invertebrate CNSs are predominantly GC rich as in plants we previously observed, whereas vertebrate CNSs are GC poor. This result suggests that the CNS GC content transition occurred from the ancestral GC rich state of Eukaryotes to GC poor in the vertebrate lineage due to the enrollment of GC poor transcription factor binding sites that are lineage specific. CNS GC content is closely linked with the nucleosome occupancy that determines the location and structural architecture of DNAs.

A method for identification of highly conserved elements and evolutionary analysis of superphylum Alveolata

Background

Perfectly or highly conserved DNA elements were found in vertebrates, invertebrates, and plants by various methods. However, little is known about such elements in protists. The evolutionary distance between apicomplexans can be very high, in particular, due to the positive selection pressure on them. This complicates the identification of highly conserved elements in alveolates, which is overcome by the proposed algorithm.

Results

A novel algorithm is developed to identify highly conserved DNA elements. It is based on the identification of dense subgraphs in a specially built multipartite graph (whose parts correspond to genomes). Specifically, the algorithm does not rely on genome alignments, nor pre-identified perfectly conserved elements; instead, it performs a fast search for pairs of words (in different genomes) of maximum length with the difference below the specified edit distance. Such pair defines an edge whose weight equals the maximum (or total) length of words assigned to its ends. The graph composed of these edges is then compacted by merging some of its edges and vertices. The dense subgraphs are identified by a cellular automaton-like algorithm; each subgraph defines a cluster composed of similar inextensible words from different genomes. Almost all clusters are considered as predicted highly conserved elements. The algorithm is applied to the nuclear genomes of the superphylum Alveolata, and the corresponding phylogenetic tree is built and discussed.

Conclusion

We proposed an algorithm for the identification of highly conserved elements. The multitude of identified elements was used to infer the phylogeny of Alveolata.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1257-5) contains supplementary material, which is available to authorized users.

Computational inference of gene regulatory networks: Approaches, limitations and opportunities

Gene regulatory networks lie at the core of cell function control. In E. coli and S. cerevisiae, the study of gene regulatory networks has led to the discovery of regulatory mechanisms responsible for the control of cell growth, differentiation and responses to environmental stimuli. In plants, computational rendering of gene regulatory networks is gaining momentum, thanks to the recent availability of high-quality genomes and transcriptomes and development of computational network inference approaches. Here, we review current techniques, challenges and trends in gene regulatory network inference and highlight challenges and opportunities for plant science. We provide plant-specific application examples to guide researchers in selecting methodologies that suit their particular research questions. Given the interdisciplinary nature of gene regulatory network inference, we tried to cater to both biologists and computer scientists to help them engage in a dialogue about concepts and caveats in network inference. Specifically, we discuss problems and opportunities in heterogeneous data integration for eukaryotic organisms and common caveats to be considered during network model evaluation. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

A Collection of Conserved Noncoding Sequences to Study Gene Regulation in Flowering Plants

Transcription factors (TFs) regulate gene expression by binding cis-regulatory elements, of which the identification remains an ongoing challenge owing to the prevalence of large numbers of nonfunctional TF binding sites. Powerful comparative genomics methods, such as phylogenetic footprinting, can be used for the detection of conserved noncoding sequences (CNSs), which are functionally constrained and can greatly help in reducing the number of false-positive elements. In this study, we applied a phylogenetic footprinting approach for the identification of CNSs in 10 dicot plants, yielding 1,032,291 CNSs associated with 243,187 genes. To annotate CNSs with TF binding sites, we made use of binding site information for 642 TFs originating from 35 TF families in Arabidopsis (Arabidopsis thaliana). In three species, the identified CNSs were evaluated using TF chromatin immunoprecipitation sequencing data, resulting in significant overlap for the majority of data sets. To identify ultraconserved CNSs, we included genomes of additional plant families and identified 715 binding sites for 501 genes conserved in dicots, monocots, mosses, and green algae. Additionally, we found that genes that are part of conserved mini-regulons have a higher coherence in their expression profile than other divergent gene pairs. All identified CNSs were integrated in the PLAZA 3.0 Dicots comparative genomics platform (http://bioinformatics.psb.ugent.be/plaza/versions/plaza_v3_dicots/) together with new functionalities facilitating the exploration of conserved cis-regulatory elements and their associated genes. The availability of this data set in a user-friendly platform enables the exploration of functional noncoding DNA to study gene regulation in a variety of plant species, including crops.

Purifying selection acts on coding and non-coding sequences of paralogous genes in Arabidopsis thaliana

Background

Whole-genome duplications in the ancestors of many diverse species provided the genetic material for evolutionary novelty. Several models explain the retention of paralogous genes. However, how these models are reflected in the evolution of coding and non-coding sequences of paralogous genes is unknown.

Results

Here, we analyzed the coding and non-coding sequences of paralogous genes in Arabidopsis thaliana and compared these sequences with those of orthologous genes in Arabidopsis lyrata. Paralogs with lower expression than their duplicate had more nonsynonymous substitutions, were more likely to fractionate, and exhibited less similar expression patterns with their orthologs in the other species. Also, lower-expressed genes had greater tissue specificity. Orthologous conserved non-coding sequences in the promoters, introns, and 3′ untranslated regions were less abundant at lower-expressed genes compared to their higher-expressed paralogs. A gene ontology (GO) term enrichment analysis showed that paralogs with similar expression levels were enriched in GO terms related to ribosomes, whereas paralogs with different expression levels were enriched in terms associated with stress responses.

Conclusions

Loss of conserved non-coding sequences in one gene of a paralogous gene pair correlates with reduced expression levels that are more tissue specific. Together with increased mutation rates in the coding sequences, this suggests that similar forces of purifying selection act on coding and non-coding sequences. We propose that coding and non-coding sequences evolve concurrently following gene duplication.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2803-2) contains supplementary material, which is available to authorized users.

Identification of plant transcription factor target sequences

Regulation of gene expression depends on specific cis-regulatory sequences located in the gene promoter regions. These DNA sequences are recognized by transcription factors (TFs) in a sequence-specific manner, and their identification could help to elucidate the regulatory networks that underlie plant physiological responses to developmental programs or to environmental adaptation. Here we review recent advances in high throughput methodologies for the identification of plant TF binding sites. Several approaches offer a map of the TF binding locations in vivo and of the dynamics of the gene regulatory networks. As an alternative, high throughput in vitro methods provide comprehensive determination of the DNA sequences recognized by TFs. These advances are helping to decipher the regulatory lexicon and to elucidate transcriptional network hierarchies in plants in response to internal or external cues. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand

The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, even when no such gene is present. This capability means that synteny-based methods are far more effective than sequence similarity-based methods in identifying true-negatives, a necessity for studying gene loss and gene transposition. However, the identification of syntenic regions requires complex analyses which must be repeated for pairwise comparisons between any two species. Therefore, as the number of published genomes increases, there is a growing demand for scalable, simple-to-use applications to perform comparative genomic analyses that cater to both gene family studies and genome-scale studies. We implemented SynFind, a web-based tool that addresses this need. Given one query genome, SynFind is capable of identifying conserved syntenic regions in any set of target genomes. SynFind is capable of reporting per-gene information, useful for researchers studying specific gene families, as well as genome-wide data sets of syntenic gene and predicted gene locations, critical for researchers focused on large-scale genomic analyses. Inference of syntenic homologs provides the basis for correlation of functional changes around genes of interests between related organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic data from over 15,000 organisms from all domains of life as well as supporting multiple releases of the same organism. SynFind makes use of a powerful job execution framework that promises scalability and reproducibility. SynFind can be accessed at http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc.

Transcriptional Dynamics Driving MAMP-Triggered Immunity and Pathogen Effector-Mediated Immunosuppression in Arabidopsis Leaves Following Infection with Pseudomonas syringae pv tomato DC3000

Transcriptional reprogramming is integral to effective plant defense. Pathogen effectors act transcriptionally and posttranscriptionally to suppress defense responses. A major challenge to understanding disease and defense responses is discriminating between transcriptional reprogramming associated with microbial-associated molecular pattern (MAMP)-triggered immunity (MTI) and that orchestrated by effectors. A high-resolution time course of genome-wide expression changes following challenge with Pseudomonas syringae pv tomato DC3000 and the nonpathogenic mutant strain DC3000hrpA- allowed us to establish causal links between the activities of pathogen effectors and suppression of MTI and infer with high confidence a range of processes specifically targeted by effectors. Analysis of this information-rich data set with a range of computational tools provided insights into the earliest transcriptional events triggered by effector delivery, regulatory mechanisms recruited, and biological processes targeted. We show that the majority of genes contributing to disease or defense are induced within 6 h postinfection, significantly before pathogen multiplication. Suppression of chloroplast-associated genes is a rapid MAMP-triggered defense response, and suppression of genes involved in chromatin assembly and induction of ubiquitin-related genes coincide with pathogen-induced abscisic acid accumulation. Specific combinations of promoter motifs are engaged in fine-tuning the MTI response and active transcriptional suppression at specific promoter configurations by P. syringae.

Analysis of 5' gene regions reveals extraordinary conservation of novel non-coding sequences in a wide range of animals

Background

Phylogenetic footprinting is a comparative method based on the principle that functional sequence elements will acquire fewer mutations over time than non-functional sequences. Successful comparisons of distantly related species will thus yield highly important sequence elements likely to serve fundamental biological roles. RNA regulatory elements are less well understood than those in DNA. In this study we use the emerging model organism Nasonia vitripennis, a parasitic wasp, in a comparative analysis against 12 insect genomes to identify deeply conserved non-coding elements (CNEs) conserved in large groups of insects, with a focus on 5’ UTRs and promoter sequences.

Results

We report the identification of 322 CNEs conserved across a broad range of insect orders. The identified regions are associated with regulatory and developmental genes, and contain short footprints revealing aspects of their likely function in translational regulation. The most ancient regions identified in our analysis were all found to overlap transcribed regions of genes, reflecting stronger conservation of translational regulatory elements than transcriptional elements. Further expanding sequence analyses to non-insect species we also report the discovery of, to our knowledge, the two oldest and most ubiquitous CNE’s yet described in the animal kingdom (700 MYA). These ancient conserved non-coding elements are associated with the two ribosomal stalk genes, RPLP1 and RPLP2, and were very likely functional in some of the earliest animals.

Conclusions

We report the identification of the most deeply conserved CNE’s found to date, and several other deeply conserved elements which are without exception, part of 5’ untranslated regions of transcripts, and occur in a number of key translational regulatory genes, highlighting translational regulation of translational regulators as a conserved feature of insect genomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0499-6) contains supplementary material, which is available to authorized users.

Evolution of DNA-Binding Sites of a Floral Master Regulatory Transcription Factor

Flower development is controlled by the action of key regulatory transcription factors of the MADS-domain family. The function of these factors appears to be highly conserved among species based on mutant phenotypes. However, the conservation of their downstream processes is much less well understood, mostly because the evolutionary turnover and variation of their DNA-binding sites (BSs) among plant species have not yet been experimentally determined. Here, we performed comparative ChIP (chromatin immunoprecipitation)-seq experiments of the MADS-domain transcription factor SEPALLATA3 (SEP3) in two closely related Arabidopsis species: Arabidopsis thaliana and A. lyrata which have very similar floral organ morphology. We found that BS conservation is associated with DNA sequence conservation, the presence of the CArG-box BS motif and on the relative position of the BS to its potential target gene. Differences in genome size and structure can explain that SEP3 BSs in A. lyrata can be located more distantly to their potential target genes than their counterparts in A. thaliana. In A. lyrata, we identified transposition as a mechanism to generate novel SEP3 binding locations in the genome. Comparative gene expression analysis shows that the loss/gain of BSs is associated with a change in gene expression. In summary, this study investigates the evolutionary dynamics of DNA BSs of a floral key-regulatory transcription factor and explores factors affecting this phenomenon.

Advances in understanding cis regulation of the plant gene with an emphasis on comparative genomics

The plant gene model remains largely an extrapolation from animals, with the cis functional unit, the gene, cast as a dynamic looping structure. Molecular genetics with model plants continues to make advances; highlighted here are quantitative-occupancy results from the Arabidopsis thaliana (Arabidopsis) Phytochrome-Interacting bHLH transcription Factors (PIF) quartet. Compared to this complex snapshot, results from chromatin occupancy and other Encyclopedia of DNA Elements (ENCODE)-like approaches increase our transcription factor-motif cognate library, but regulation cannot by itself be inferred from binding. Complementary published Arabidopsis conserved noncoding sequence lists are compared, evaluated, merged, and released. Comparative genomic approaches have identified a cis modifier of a gene's expression-hypothetically, a transposon-based 'rheostat'-that works in all cells, times and places.

CNMS: The preferred genic markers for comparative genomic, molecular phylogenetic, functional genetic diversity and differential gene regulatory expression analyses in chickpea

The intra/inter-genomic comparative mapping-based phylogenetic footprinting identified 5 paralogous and 656 orthologous genome-wide CNMS markers in the upstream sequences of chickpea genes. These CNMS markers revealed a high-degree of gene-based syntenic relationship between chickpea and Medicago genomes while minimum between chickpea and Vitis genomes. The time of divergence and duplication estimated using CNMS markers highlight the expected phylogenetic relationships between chickpea and six dicot (legume) species as well as occurrence of ancient genome (approximately 53 Mya) with small-scale recent segmental (approximately 10 Mya) duplication events in chickpea. A wider level of functional molecular diversity (14 to 88 percent) and admixed population genetic structure was detected among desi, kabuli and wild genotypes by genic CNMS markers at a genome-wide scale suggesting their utility in large-scale genetic analysis in chickpea. The subfunctionalization at the cis-regulatory element region and TFBS (transcription factor binding site) motif levels in the upstream sequences of CNMS marker-associated orthologous genes than the paralogues was predominant. Functional constraint might have considerable effect on these CNMScontaining regulatory elements controlling consistent orthologous gene expression in dicots. A rapid subfunctionalization based on diverge differential expression of paralogous CNMS marker-associated genes particularly those that underwent recent small-scale segmental duplication events in chickpea was apparent. The differential regulation of expression and subfunctionalization potential of Ultra CNMS marker-associated genes suggest their utility in deciphering the complex gene regulatory function as well as identification and targeted mapping of potential genes/QTLs governing vital agronomic traits in chickpea. The gene-based CNMS markers with desirable inherent genetic attributes like higher degree of comparative genome mapping, functional genetic diversity and differential gene regulatory expression potential can significantly propel the genomics-assisted chickpea crop improvement.

Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea

Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5'-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea.

Improving crop disease resistance: lessons from research on Arabidopsis and tomato

One of the great challenges for food security in the 21st century is to improve yield stability through the development of disease-resistant crops. Crop research is often hindered by the lack of molecular tools, growth logistics, generation time and detailed genetic annotations, hence the power of model plant species. Our knowledge of plant immunity today has been largely shaped by the use of models, specifically through the use of mutants. We examine the importance of Arabidopsis and tomato as models in the study of plant immunity and how they help us in revealing a detailed and deep understanding of the various layers contributing to the immune system. Here we describe examples of how knowledge from models can be transferred to economically important crops resulting in new tools to enable and accelerate classical plant breeding. We will also discuss how models, and specifically transcriptomics and effectoromics approaches, have contributed to the identification of core components of the defense response which will be key to future engineering of durable and sustainable disease resistance in plants.

The histone modification H3K27me3 is retained after gene duplication and correlates with conserved noncoding sequences in Arabidopsis

The histone modification H3K27me3 is involved in repression of transcription and plays a crucial role in developmental transitions in both animals and plants. It is deposited by PRC2 (Polycomb repressive complex 2), a conserved protein complex. In Arabidopsis thaliana, H3K27me3 is found at 15% of all genes. These tend to encode transcription factors and other regulators important for development. However, it is not known how PRC2 is recruited to target loci nor how this set of target genes arose during Arabidopsis evolution. To resolve the latter, we integrated A. thaliana gene families with five independent genome-wide H3K27me3 data sets. Gene families were either significantly enriched or depleted of H3K27me3, showing a strong impact of shared ancestry to H3K27me3 distribution. To quantify this, we performed ancestral state reconstruction of H3K27me3 on phylogenetic trees of gene families. The set of H3K27me3-marked genes changed less than expected by chance, suggesting that H3K27me3 was retained after gene duplication. This retention suggests that the PRC2-recruiting signal could be encoded in the DNA and also conserved among certain duplicated genes. Indeed, H3K27me3-marked genes were overrepresented among paralogs sharing conserved noncoding sequences (CNSs) that are enriched with transcription factor binding sites. The association of upstream CNSs with H3K27me3-marked genes represents the first genome-wide connection between H3K27me3 and potential regulatory elements in plants. Thus, we propose that CNSs likely function as part of the PRC2 recruitment in plants.

Lineage-specific conserved noncoding sequences of plant genomes: their possible role in nucleosome positioning

Many studies on conserved noncoding sequences (CNSs) have found that CNSs are enriched significantly in regulatory sequence elements. We conducted whole-genome analysis on plant CNSs to identify lineage-specific CNSs in eudicots, monocots, angiosperms,and vascular plants based on the premise that lineage-specific CNSs define lineage-specific characters and functions in groups of organisms. We identified 27 eudicot, 204 monocot, 6,536 grass, 19 angiosperm, and 2 vascular plant lineage-specific CNSs(lengths range from 16 to 1,517 bp) that presumably originated in their respective common ancestors. A stronger constraint on the CNSs located in the untranslated regions was observed. The CNSs were often flanked by genes involved in transcription regulation. A drop of A+T content near the border of CNSs was observed and CNS regions showed a higher nucleosome occupancy probability. These CNSs are candidate regulatory elements, which are expected to define lineage-specific features of various plant groups.

Evaluation of experimental design and computational parameter choices affecting analyses of ChIP-seq and RNA-seq data in undomesticated poplar trees

Background

One of the great advantages of next generation sequencing is the ability to generate large genomic datasets for virtually all species, including non-model organisms. It should be possible, in turn, to apply advanced computational approaches to these datasets to develop models of biological processes. In a practical sense, working with non-model organisms presents unique challenges. In this paper we discuss some of these challenges for ChIP-seq and RNA-seq experiments using the undomesticated tree species of the genus Populus.

Results

We describe specific challenges associated with experimental design in Populus, including selection of optimal genotypes for different technical approaches and development of antibodies against Populus transcription factors. Execution of the experimental design included the generation and analysis of Chromatin immunoprecipitation-sequencing (ChIP-seq) data for RNA polymerase II and transcription factors involved in wood formation. We discuss criteria for analyzing the resulting datasets, determination of appropriate control sequencing libraries, evaluation of sequencing coverage needs, and optimization of parameters. We also describe the evaluation of ChIP-seq data from Populus, and discuss the comparison between ChIP-seq and RNA-seq data and biological interpretations of these comparisons.

Conclusions

These and other "lessons learned" highlight the challenges but also the potential insights to be gained from extending next generation sequencing-supported network analyses to undomesticated non-model species.

Inference of transcriptional networks in Arabidopsis through conserved noncoding sequence analysis

Transcriptional regulation plays an important role in establishing gene expression profiles during development or in response to (a)biotic stimuli. Transcription factor binding sites (TFBSs) are the functional elements that determine transcriptional activity, and the identification of individual TFBS in genome sequences is a major goal to inferring regulatory networks. We have developed a phylogenetic footprinting approach for the identification of conserved noncoding sequences (CNSs) across 12 dicot plants. Whereas both alignment and non-alignment-based techniques were applied to identify functional motifs in a multispecies context, our method accounts for incomplete motif conservation as well as high sequence divergence between related species. We identified 69,361 footprints associated with 17,895 genes. Through the integration of known TFBS obtained from the literature and experimental studies, we used the CNSs to compile a gene regulatory network in Arabidopsis thaliana containing 40,758 interactions, of which two-thirds act through binding events located in DNase I hypersensitive sites. This network shows significant enrichment toward in vivo targets of known regulators, and its overall quality was confirmed using five different biological validation metrics. Finally, through the integration of detailed expression and function information, we demonstrate how static CNSs can be converted into condition-dependent regulatory networks, offering opportunities for regulatory gene annotation.

Expression-based network biology identifies immune-related functional modules involved in plant defense

Background

Plants respond to diverse environmental cues including microbial perturbations by coordinated regulation of thousands of genes. These intricate transcriptional regulatory interactions depend on the recognition of specific promoter sequences by regulatory transcription factors. The combinatorial and cooperative action of multiple transcription factors defines a regulatory network that enables plant cells to respond to distinct biological signals. The identification of immune-related modules in large-scale transcriptional regulatory networks can reveal the mechanisms by which exposure to a pathogen elicits a precise phenotypic immune response.

Results

We have generated a large-scale immune co-expression network using a comprehensive set of Arabidopsis thaliana (hereafter Arabidopsis) transcriptomic data, which consists of a wide spectrum of immune responses to pathogens or pathogen-mimicking stimuli treatments. We employed both linear and non-linear models to generate Arabidopsis immune co-expression regulatory (AICR) network. We computed network topological properties and ascertained that this newly constructed immune network is densely connected, possesses hubs, exhibits high modularity, and displays hallmarks of a “real” biological network. We partitioned the network and identified 156 novel modules related to immune functions. Gene Ontology (GO) enrichment analyses provided insight into the key biological processes involved in determining finely tuned immune responses. We also developed novel software called OCCEAN (One Click Cis-regulatory Elements ANalysis) to discover statistically enriched promoter elements in the upstream regulatory regions of Arabidopsis at a whole genome level. We demonstrated that OCCEAN exhibits higher precision than the existing promoter element discovery tools. In light of known and newly discovered cis-regulatory elements, we evaluated biological significance of two key immune-related functional modules and proposed mechanism(s) to explain how large sets of diverse GO genes coherently function to mount effective immune responses.

Conclusions

We used a network-based, top-down approach to discover immune-related modules from transcriptomic data in Arabidopsis. Detailed analyses of these functional modules reveal new insight into the topological properties of immune co-expression networks and a comprehensive understanding of multifaceted plant defense responses. We present evidence that our newly developed software, OCCEAN, could become a popular tool for the Arabidopsis research community as well as potentially expand to analyze other eukaryotic genomes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-421) contains supplementary material, which is available to authorized users.

The most deeply conserved noncoding sequences in plants serve similar functions to those in vertebrates despite large differences in evolutionary rates

In vertebrates, conserved noncoding elements (CNEs) are functionally constrained sequences that can show striking conservation over >400 million years of evolutionary distance and frequently are located megabases away from target developmental genes. Conserved noncoding sequences (CNSs) in plants are much shorter, and it has been difficult to detect conservation among distantly related genomes. In this article, we show not only that CNS sequences can be detected throughout the eudicot clade of flowering plants, but also that a subset of 37 CNSs can be found in all flowering plants (diverging ∼170 million years ago). These CNSs are functionally similar to vertebrate CNEs, being highly associated with transcription factor and development genes and enriched in transcription factor binding sites. Some of the most highly conserved sequences occur in genes encoding RNA binding proteins, particularly the RNA splicing-associated SR genes. Differences in sequence conservation between plants and animals are likely to reflect differences in the biology of the organisms, with plants being much more able to tolerate genomic deletions and whole-genome duplication events due, in part, to their far greater fecundity compared with vertebrates.

PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

With the aim to provide a resource for functional and evolutionary study of plant transcription factors (TFs), we updated the plant TF database PlantTFDB to version 3.0 (http://planttfdb.cbi.pku.edu.cn). After refining the TF classification pipeline, we systematically identified 129 288 TFs from 83 species, of which 67 species have genome sequences, covering main lineages of green plants. Besides the abundant annotation provided in the previous version, we generated more annotations for identified TFs, including expression, regulation, interaction, conserved elements, phenotype information, expert-curated descriptions derived from UniProt, TAIR and NCBI GeneRIF, as well as references to provide clues for functional studies of TFs. To help identify evolutionary relationship among identified TFs, we assigned 69 450 TFs into 3924 orthologous groups, and constructed 9217 phylogenetic trees for TFs within the same families or same orthologous groups, respectively. In addition, we set up a TF prediction server in this version for users to identify TFs from their own sequences.

Network modeling to understand plant immunity

Deciphering the networks that underpin complex biological processes using experimental data remains a significant, but promising, challenge, a task made all the harder by the added complexity of host-pathogen interactions. The aim of this article is to review the progress in understanding plant immunity made so far by applying network modeling algorithms and to show how this computational/mathematical strategy is facilitating a systems view of plant defense. We review the different types of network modeling that have been used, the data required, and the type of insight that such modeling can provide. We discuss the current challenges in modeling the regulatory networks that underlie plant defense and the future developments that may help address these challenges.

The mystery of extreme non-coding conservation

Regions of several dozen to several hundred base pairs of extreme conservation have been found in non-coding regions in all metazoan genomes. The distribution of these elements within and across genomes has suggested that many have roles as transcriptional regulatory elements in multi-cellular organization, differentiation and development. Currently, there is no known mechanism or function that would account for this level of conservation at the observed evolutionary distances. Previous studies have found that, while these regions are under strong purifying selection, and not mutational coldspots, deletion of entire regions in mice does not necessarily lead to identifiable changes in phenotype during development. These opposing findings lead to several questions regarding their functional importance and why they are under strong selection in the first place. In this perspective, we discuss the methods and techniques used in identifying and dissecting these regions, their observed patterns of conservation, and review the current hypotheses on their functional significance.

Making open data work for plant scientists

Despite the clear demand for open data sharing, its implementation within plant science is still limited. This is, at least in part, because open data-sharing raises several unanswered questions and challenges to current research practices. In this commentary, some of the challenges encountered by plant researchers at the bench when generating, interpreting, and attempting to disseminate their data have been highlighted. The difficulties involved in sharing sequencing, transcriptomics, proteomics, and metabolomics data are reviewed. The benefits and drawbacks of three data-sharing venues currently available to plant scientists are identified and assessed: (i) journal publication; (ii) university repositories; and (iii) community and project-specific databases. It is concluded that community and project-specific databases are the most useful to researchers interested in effective data sharing, since these databases are explicitly created to meet the researchers' needs, support extensive curation, and embody a heightened awareness of what it takes to make data reuseable by others. Such bottom-up and community-driven approaches need to be valued by the research community, supported by publishers, and provided with long-term sustainable support by funding bodies and government. At the same time, these databases need to be linked to generic databases where possible, in order to be discoverable to the majority of researchers and thus promote effective and efficient data sharing. As we look forward to a future that embraces open access to data and publications, it is essential that data policies, data curation, data integration, data infrastructure, and data funding are linked together so as to foster data access and research productivity.

The fate of Arabidopsis thaliana homeologous CNSs and their motifs in the Paleohexaploid Brassica rapa

Following polyploidy, duplicate genes are often deleted, and if they are not, then duplicate regulatory regions are sometimes lost. By what mechanism is this loss and what is the chance that such a loss removes function? To explore these questions, we followed individual Arabidopsis thaliana–A. thaliana conserved noncoding sequences (CNSs) into the Brassica ancestor, through a paleohexaploidy and into Brassica rapa. Thus, a single Brassicaceae CNS has six potential orthologous positions in B. rapa; a single Arabidopsis CNS has three potential homeologous positions. We reasoned that a CNS, if present on a singlet Brassica gene, would be unlikely to lose function compared with a more redundant CNS, and this is the case. Redundant CNSs go nondetectable often. Using this logic, each mechanism of CNS loss was assigned a metric of functionality. By definition, proved deletions do not function as sequence. Our results indicated that CNSs that go nondetectable by base substitution or large insertion are almost certainly still functional (redundancy does not matter much to their detectability frequency), whereas those lost by inferred deletion or indels are approximately 75% likely to be nonfunctional. Overall, an average nondetectable, once-redundant CNS more than 30 bp in length has a 72% chance of being nonfunctional, and that makes sense because 97% of them sort to a molecular mechanism with “deletion” in its description, but base substitutions do cause loss. Similarly, proved-functional G-boxes go undetectable by deletion 82% of the time. Fractionation mutagenesis is a procedure that uses polyploidy as a mutagenic agent to genetically alter RNA expression profiles, and then to construct testable hypotheses as to the function of the lost regulatory site. We show fractionation mutagenesis to be a “deletion machine” in the Brassica lineage.

Ancient cis-regulatory constraints and the evolution of genome architecture

The order of genes along metazoan chromosomes has generally been thought to be largely random, with few implications for organismal function. However, two recent studies, reporting hundreds of pairs of genes that have remained linked in diverse metazoan species over hundreds of millions of years of evolution, suggest widespread functional implications for gene order. These associations appear to largely reflect cis-regulatory constraints, with either (i) multiple genes sharing transcriptional regulatory elements, or (ii) regulatory elements for a developmental gene being found within a neighboring 'bystander' gene (known as a genomic regulatory block). We discuss implications, questions raised, and new research directions arising from these studies, as well as evidence for similar phenomena in other eukaryotic groups.

Chromatin and epigenetic features of long-range gene regulation

The precise regulation of gene transcription during metazoan development is controlled by a complex system of interactions between transcription factors, histone modifications and modifying enzymes and chromatin conformation. Developments in chromosome conformation capture technologies have revealed that interactions between regions of chromatin are pervasive and highly cell-type specific. The movement of enhancers and promoters in and out of higher-order chromatin structures within the nucleus are associated with changes in expression and histone modifications. However, the factors responsible for mediating these changes and determining enhancer:promoter specificity are still not completely known. In this review, we summarize what is known about the patterns of epigenetic and chromatin features characteristic of elements involved in long-range interactions. In addition, we review the insights into both local and global patterns of chromatin interactions that have been revealed by the latest experimental and computational methods.

A temporal switch model for estimating transcriptional activity in gene expression

Motivation: The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription–polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states.

Results: The model is flexible enough to capture a variety of observed transcriptional dynamics, including oscillatory behaviour, in a way that is compatible with the demands imposed by the quality, time-resolution and quantity of the data. We show that the timing and number of switch events in transcriptional activity can be estimated alongside individual gene mRNA stability with the help of a Bayesian reversible jump Markov chain Monte Carlo algorithm. To demonstrate the methodology, we focus on modelling the wild-type behaviour of a selection of 200 circadian genes of the model plant Arabidopsis thaliana. The results support the idea that using a mechanistic model to identify transcriptional switch points is likely to strongly contribute to efforts in elucidating and understanding key biological processes, such as transcription and degradation.

Contact:B.F.Finkenstadt@Warwick.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Automated conserved non-coding sequence (CNS) discovery reveals differences in gene content and promoter evolution among grasses

Conserved non-coding sequences (CNS) are islands of non-coding sequence that, like protein coding exons, show less divergence in sequence between related species than functionless DNA. Several CNSs have been demonstrated experimentally to function as cis-regulatory regions. However, the specific functions of most CNSs remain unknown. Previous searches for CNS in plants have either anchored on exons and only identified nearby sequences or required years of painstaking manual annotation. Here we present an open source tool that can accurately identify CNSs between any two related species with sequenced genomes, including both those immediately adjacent to exons and distal sequences separated by >12 kb of non-coding sequence. We have used this tool to characterize new motifs, associate CNSs with additional functions, and identify previously undetected genes encoding RNA and protein in the genomes of five grass species. We provide a list of 15,363 orthologous CNSs conserved across all grasses tested. We were also able to identify regulatory sequences present in the common ancestor of grasses that have been lost in one or more extant grass lineages. Lists of orthologous gene pairs and associated CNSs are provided for reference inbred lines of arabidopsis, Japonica rice, foxtail millet, sorghum, brachypodium, and maize.