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Gene expression atlas of embryo development in Arabidopsis


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Gene expression atlas of embryo development in Arabidopsis

Gao, Peng; Xiang, Daoquan; Quilichini, Teagen D.; Venglat, Prakash;

Pandey, Prashant K.; Wang, Edwin; Gillmor, C. Stewart; Datla, Raju


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https://nrc-publications.canada.ca/eng/view/object/?id=38b5e1d4-6070-44b9-ae29-778718beb005 https://publications-cnrc.canada.ca/fra/voir/objet/?id=38b5e1d4-6070-44b9-ae29-778718beb005








Gene expression atlas of embryo development in Arabidopsis

Peng Gao1,5  · Daoquan Xiang1  · Teagen D. Quilichini1  · Prakash Venglat1,2 · Prashant K. Pandey1  · Edwin Wang3 · C. Stewart Gillmor4  · Raju Datla1,5

Received: 16 November 2018 / Accepted: 1 February 2019 © The Author(s) 2019


Embryogenesis represents a critical phase in the life cycle of lowering plants. Here, we characterize transcriptome landscapes associated with key stages of embryogenesis by combining an optimized method for the isolation of developing Arabidopsis embryos with high-throughput RNA-seq. The resulting RNA-seq datasets identify distinct overlapping patterns of gene expression, as well as temporal shifts in gene activity across embryogenesis. Network analysis revealed stage-speciic and multi-stage gene expression clusters and biological functions associated with key stages of embryo development. Methylation-related gene expression was associated with early- and middle-stage embryos, initiation of photosynthesis components with the late embryogenesis stage, and storage/energy-related protein activation with late and mature embryos. These results provide a comprehensive understanding of transcriptome programming in Arabidopsis embryogenesis and identify modules of gene expression corresponding to key stages of embryo development. This dataset and analysis are a unique resource to advance functional genetic analysis of embryo development in plants.

Keywords Embryogenesis · Embryo isolation · RNA-seq · Transcriptome · Bioinformatics · Arabidopsis


Embryogenesis begins with fusion of male and female gam-etes to form the single-cell zygote. In Arabidopsis, the irst division of the zygote is asymmetric and is followed by

precisely oriented cell divisions which generate the major tissue lineages of the adult plant within the irst ive days of embryogenesis (Goldberg et al. 1994; Xiang et al. 2011a). Landmark events of embryogenesis include establishment of shoot and root meristems and provascular and ground tissue in early stages; growth of the embryo in middle stages; and activation of seed storage protein and seed dormancy pro-grams in late embryogenesis (Braybrook and Harada 2008; Huh et al. 2007; Jenik et al. 2007; Moller et al. 2017; Yang et al. 2009).

Discovering the genetic mechanisms employed during plant embryogenesis requires accessing embryos at progres-sive stages of development. This is challenging due to their

Communicated by Dolf Weijers.

RNA sequencing raw data can be found in the Gene Expression Omnibus (GEO) under the accession number “GSE123010.”

Electronic supplementary material The online version of this article (https ://doi.org/10.1007/s0049 7-019-00364 -x) contains supplementary material, which is available to authorized users.

* Raju Datla


1 Aquatic and Crop Resource Development, National Research

Council Canada, 110 Gymnasium Place, Saskatoon, SK S7N 0W9, Canada


Department of Plant Sciences and Crop Development Centre, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada

3 Center for Health Genomics and Informatics, University

of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada

4 Laboratorio Nacional de Genómica para la Biodiversidad

(Langebio), Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV-IPN), Irapuato, Guanajuato, Mexico


Global Institute for Food Security, University of Saskatchewan, Saskatoon, SK S7N 4J8, Canada

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small size, their enclosure within maternal tissue, and their close association with the endosperm and surrounding seed coat tissues (Xiang et al. 2011a). Laser capture microdissec-tion (LCM), a technology to facilitate the precise excision of select tissues or cells, has been used to isolate embryos and larger embryonic tissue domains from Arabidopsis for transcriptional analysis (Belmonte et al. 2013; Casson et al. 2005; Kerk et al. 2003). To avoid contamination from adjoining cells, LCM requires high precision during tissue excision. In addition, transcript alterations or reductions due to damage caused by material ixation remain a concern for obtaining accurate transcriptome data from LCM iso-lates. Tools employing luorescence or ainity tagging with luorescence-activated cell/nuclei sorting (FACS/FANS), translating ribosome ainity puriication (TRAP), and the isolation of nuclei tagged in speciic cell types (INTACT), have the potential to aid embryo identiication and improve isolation accuracy (Bonner et al. 1972; Deal and Henikof

2010; Heiman et al. 2008; Zhang et al. 2008). These tag-labeling methods have been successfully applied in the sort-ing of protoplasts and select tissues in plants. For studies of embryogenesis, one disadvantage of FACS and INTACT analyses is that the ratio of maternal tissues to embryo target cells is enormous, making avoidance of maternal contamina-tion diicult. Another drawback of tag-labeling methods is the requirement of genetic manipulation and transformation protocols for the species of interest and the time to generate these lines.

While the techniques mentioned above offer unique advantages and disadvantages for the isolation of embryos for transcriptome studies, isolation of embryos by precise hand dissection in conditions that maintain RNA integrity is a valuable approach with signiicantly lower cost (Xiang et al. 2011a, b). The use of living materials in manual dis-sections is minimally invasive and does not create ixation artifacts, making this method conducive to capturing the native transcriptome landscape. Furthermore, manual dis-section does not require genetic manipulation of the species under study, making it an eicient and afordable approach to accessing embryo transcriptome data in a broad range of species.

Transcriptome analyses of embryo development in Arabi-dopsis have been conducted using Afymetrix Gene Chip and Arabidopsis oligonucleotide microarrays (Belmonte et al. 2013; Palovaara et al. 2017; Slane et al. 2014; Xiang et al. 2011a) and RNA-seq (Autran et al. 2011; Hsieh et al.

2011; Nodine and Bartel 2012; Pignatta et al. 2014). In comparison with microarray assays, RNA-seq ofers sev-eral advantages, including improved sensitivity, access to alternative splicing information, and accurate detection of a broad range of expression data. In the present study, high-throughput RNA-seq analysis was performed using Arabi-dopsis embryos, from zygote to maturity, that were isolated

by an optimized hand dissection method. Comprehensive transcriptome analysis across all key stages of embryogen-esis revealed gene expression clusters associated with dif-ferent stages of embryo development. Functional interroga-tion of these gene clusters identiied characteristic biological pathways involved in the early, middle, late, and mature stages of embryo development. These results deine gene expression patterns and coexpression networks associated with embryogenesis in Arabidopsis and provide a framework for hypothesis generation and functional validation of the molecular mechanisms governing embryogenesis.

Materials and methods

Plant growth and embryo isolation

Arabidopsis (Arabidopsis thaliana, ecotype Col-0) seeds were placed on ½ Murashige and Skoog (MS) plates for 4 days at 4 °C in the dark and then transferred to 24-hour light for 10 days. Seedlings were transferred to soil and grown under long-day conditions (16-h light and 8-h dark) with a constant temperature of 22 °C and 120–150 µmol m−2 s−1 light intensity. Timed and controlled self-pollinations were performed to ensure synchronized development of early-stage embryos in the ovules. For each pollination, the main inlorescence was pruned to remove all lowers and buds, except for the two oldest lower buds. The remaining lower buds were pollinated 4 h after emascula-tion using pollen from an open lower of the same plant.

Embryo isolation by hand dissection

Embryo isolation was performed as described in Xiang et al. (2011a, b), with some modiications and additional details outlined below. The approximate number of embryos harvested for each of the seven stages of embryo develop-ment deined by this study, was as follows: 100 zygote and 2 cell embryos (Z), 200 octant (O), 100 globular (G), 100 heart (H), 60 torpedo (T), 30 bent (B), and 30 mature (M) embryos. Z-, O-, and G-stage embryos were isolated at approximately 24, 60, and 72 h after pollination, respec-tively. The H- to M-stage embryos were isolated based on their morphology.

Contamination of the embryo mRNA with seed coat- and endosperm-derived mRNA in the early-stage embryos (Z and O stages) is a major concern. To ensure that clean embryos were obtained for mRNA extraction, we performed the isolation of embryos from ovules in mini-petri dishes containing isolation bufer (4.8% sucrose solution + 0.1% RNAlater, Ambion Cat# AM7020). Two precise incisions were made at the micropylar end with needles (Fine Sci-ence Tools Cat. 10130-05) (Xiang et al. 2011a, b). This

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approach enabled the separation of the micropylar region that houses the early-stage embryo from the seed coat and the subsequent isolation of the embryo within the micropyle from the maternal ovule tissue and endosperm cells. Isolated embryos from early stages were inspected under a micro-scope (Leica DMR), and only samples with no visible con-tamination from the ovule tissue or early endosperm nuclei/ cells were collected for RNA isolation. Since the ovule soon after fertilization contains very few endosperm cells/nuclei, the risk of endosperm contamination is greater at later stages (after globular) which usually has dense endosperm cells associated with the embryos. Therefore, embryos at early and later stages of development (after globular) were care-fully washed several times in isolation bufer to avoid con-tamination from surrounding tissues such as the endosperm. The washing steps were performed using mini-petri dishes illed with freshly prepared isolation bufer. After one sin-gle embryo was isolated from the ovule, it was transferred using pipette to a mini-petri dish, followed by gentle agita-tion to separate any attached debris. To remove remaining debris, each embryo was transferred to fresh isolation bufer in a mini-petri dish for at least three rounds of sequential washing steps. All washing steps were performed on ice and inspected with a dissecting Leica microscope. After all washing steps, embryos were transferred to Eppendorf tubes on dry ice using ine glass pipettes. Due to their diminutive size and slight variation in the timing of irst division, pre-cisely diferentiating and separating was diicult for single-celled zygotes from zygotes which had divided to produce 2-cell embryos (i.e., with an apical embryo and basal sus-pensor cell), and the isolated zygote stage samples may also contain few 2-cell embryos.

To test the eicacy of our isolation procedure for obtain-ing clean embryos (without a signiicant contaminatobtain-ing endosperm or seed coat tissues), embryos were placed on a glass slide in large droplet of water, within the conines of a well (created by a Mini PAP pen, Invitrogen Cat# 008877) and coverslip and imaged using a Leica DMR equipped with a Microire camera (Optronics, California).

RNA extraction, antisense RNA ampliication, and high-throughput sequencing

Total RNA was extracted from embryos corresponding to the seven developmental stages described above, for two biological replicates at each stage, following the RNAque-ous-Micro kit protocol (Ambion, Catalog# 1927). The iso-lated embryos’ homogenization was performed using poly-propylene pestles in 1.5-ml Eppendorf tubes after adding lysis bufer. The whole homogenization process was oper-ated on ice. The quantity of RNA isoloper-ated from early-stage embryos was insuicient for direct library preparation and RNA-seq experiments. Therefore, the mRNA of all stages

was similarly subjected to ampliication and the resulting antisense RNA (aRNA) was used for RNA-seq experiments. The mRNA ampliication was conducted according to the protocol provided in the MessageAmp aRNA kit (Ambion, Catalog# 1750). For RNA-seq proile analysis, Illumina mRNA-seq libraries were prepared using the TruSeq RNA kit (ver. 1, rev A) according to the manufacturer’s instruc-tions. For Illumina HiSeq 2000 sequencing (with an Illumina GA II instrument), four indexed libraries were pooled per sequencing lane, paired-end reads were aligned to the refer-ence genome (TAIR10), and the reads for each gene were summarized for further analysis.

Diferential gene expression (DEG) analysis

High-quality reads were iltered using the Trimmomatic tool (Bolger et al. 2014) with default parameters to remove sequencing adapters and low-quality reads. A quality check was performed with FastQC (Andrews 2010), and the il-tered reads were mapped to the Arabidopsis genome TAIR10 using STAR (Dobin et al. 2013). Read counting was carried out with HTSeq (Anders et al. 2015). Analysis of diferen-tial expression genes (DEGs) was performed with DESeq 2 to normalize the raw reads and identify DEGs in pairwise comparisons between each stage of embryo development (Love et al. 2014). An experimental design based on the DESeq 2 R package was applied to raw read counts for all libraries with p value (adjusted) < 0.05, log2FoldChange > 1 and < − 1 to relect transcriptional regulation across all seven developmental stages, as shown in Supplementary Data S1. Raw data counts were normalized by library size and it to a negative binomial model. Principal component analysis (PCA) was calculated with the built-in plotPCA function provided by the DESeq 2 tool. All DEGs were annotated by querying the open reading frame (ORF) sequences against the non-redundant protein database (with BLAST) using an e-value cutof of 10−5 and reporting the maximum “hit” sequence per query. Diferential expression of genes was determined to be signiicant if a log2 (fold change) of > 1 or < − 1 and p value (adjusted) < 0.05 was obtained.

Gene coexpression analysis and heatmap generation

To identify genes that exhibit similar expression across all seven stages of embryo development, raw counts were nor-malized to the log2 scale, using the rlog function in DESeq 2. Sample-to-sample distance was calculated based on rlog matrix using the R package dist function. Unrooted hierar-chical trees were generated using SplitsTree4 software with the R package hclust function “complete” method. Counts with rlog < 3 across all samples were removed. Groups of closely connected genes were identiied by weighted

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gene coexpression network analysis (WGCNA) with a soft thresholding power of 9 (Langfelder and Horvath 2008) and “unsigned” network model. Hierarchical clustering was performed based on the topological overlap matrix and cutting the resulting dendrogram with the dynamicTreeCut program with deepslipt = 4, minModuleSize = 30, MaxMod-uleSize = 5000 to obtain maximum dynamic gene clusters. Initial clusters with similar expression proiles were merged at cutheight = 0.25. Gene modules with stage-speciic pat-terns of gene expression (speciically, patpat-terns where gene expression was relatively high in one stage and low in the other six) were correlated with the stage-speciic expres-sion patterns in diferent embryo samples, based on signii-cantly high Pearson’s correlation coeicient values (r > 0.8, p value < 0.001; Fig. 2b). Based on the resulting adjacency matrix, we calculated the topological overlap, a concept deined for weighted networks, which is a robust and bio-logically meaningful measure of network interconnectedness (Langfelder and Horvath 2008). Heatmaps were generated by the R pheatmap package using rlog values with Z-score transformation.

Functional classiication of transcripts based on gene ontology, KEGG, and MapMan pathway enrichment

Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments were performed using the topGO and KEGGproile R packages, respec-tively. REVIGO analysis (http://revig o.irb.hr) was used to slim the enriched GO terms based on the “medium simi-larity” parameter. The MapMan tool (Thimm et al. 2004) was used to facilitate the assignment of identiied DEGs into functional categories (bins). A MapMan mapping ile that mapped the genes into bins via hierarchical ontologies through the searching of a variety of reference databases was generated using the Mercator tool (http://mapma n.gabip d.org/web/guest /app/merca tor). DEGs associated with seed development pathways from the seven stages of embryo development were categorized and visualized in ImageAn-notator module. GO term interact graphs were generated by Cytoscape software.


Transcriptome proiling of Arabidopsis embryogenesis

To obtain a comprehensive view of transcriptome proiles during embryogenesis in Arabidopsis, RNA-seq analysis was performed using isolated embryos at seven key stages of embryogenesis, referred to herein as the zygote (Z), octant

(O), globular (G), heart (H), torpedo (T), bent (B), and mature (M) embryo. Embryo poly(A) + transcripts were used to generate libraries for Illumina high-throughput sequenc-ing. In total, 257 million sequenced reads were obtained and aligned to the Arabidopsis TAIR 10 Genome. The cor-responding numbers of mapped, unmapped reads, unique mapped reads, and multiple mapped reads from each sample are presented in Figure S1. Given the large number of sam-ples in this study, relative relatedness and reproducibility among the two biological replicates were examined by prin-cipal component analysis (PCA) (Fig. 1a), which displayed a clear clustering of replicate samples isolated from the same stage of embryogenesis. Sample-to-sample distances were calculated based on a normalized read count transformed rlog matrix from all samples as shown in Fig. 1b. All rep-licate samples had highly correlated Pearson’s coeicients demonstrating accurate isolation of embryos representing the speciic stage of their development as well as the reproduc-ibility of the corresponding RNA isolation and library prep-aration procedures. Moreover, the analysis showed higher degrees of correlation in neighboring stages of embryo development (i.e., Z to O, G to H, and T to B), except for the M stage, which was more distant (Fig. 1b). With replicates combined, the unrooted hierarchical tree showed the same trend as the sample-to-sample distance analysis, with four discrete groupings of related expression patterns across the seven stages of embryo development (Fig. 1c). Thus, four groupings for embryo development emerged, termed them as the early (Z and O), middle (G and H), late (T and B), and mature (M) embryo groups (Fig. 1c). These groupings are consistent with indings described in a previous microarray study by Xiang et al. (2011a, b) using comparable samples from similar embryo stages. Both studies revealed a clear separation of four distinct expression patterns from early to late embryogenesis.

DEG identiication across whole embryo developmental stages

The study of diferential gene expression provides insight into the putative activation and repression of pathways and processes associated with the complex process of embry-ogenesis. In total, 15,912 diferentially expressed genes (DEGs) were identified through pairwise comparisons between consecutive stages of development with p value (adjusted) < 0.05, log2FoldChange > 1 and < − 1. Each pairwise comparison identiied a large proportion of DEGs, including 8436 in Z versus O; 5568 in O versus G; 4836 in G versus H; 4638 in H versus T; 3550 in T versus B; and 10,339 in B versus M. Among the DEGs identiied, 101 genes appeared in six comparisons across all seven stages of embryo development (Data S2). Gene ontology (GO) analysis of these 101 genes revealed enrichment of the GO

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terms “post-embryonic development,” “seed development,” and “fruit development,” suggesting fundamental roles for these gene products in diferent developmental phases of embryogenesis (Table 1).

Stage-speciic gene coexpression networks

Since the 15,912 DEGs represent diverse functionalities in an array of biological processes, weighted gene coexpres-sion network analysis (WGCNA) and dynamic hierarchical clustering approaches were used to deine clusters, called modules, of coexpressed genes that follow speciic patterns of expression (Fig. 2). By including genes with expres-sion levels greater than or equal to ten counts in at least one sample from all seven developmental stages, a total of 26 modules were identiied (Fig. 2a). We irst deined the module eigengene (ME), a single value that represents the highest percent of variance in expression values for all module genes in a stage. Thus, the expression proiles of module genes among diferent stages can be summarized as the expression proile of MEs. Pearson’s correlation coef-icient values (r) between MEs and each stage were then used to determine the relationship between a module and a developmental stage (Fig. 2b). Collectively, we identiied six “stage-speciic” modules (see asterisks, Fig. 2b), deined as modules that signiicantly correlated with one stage of embryo development (r > 0.8 and p value < 0.001), corre-lating “MEblack” to zygote, “MEtan” to octant, “MElight-green” to heart, “MEdarkgray” to torpedo, “MEdarkred” to bent, and “MEmagenta” to mature. No stage-speciic mod-ule was identiied for the globular stage, suggesting this important transition stage connecting early and late embryo development may be distinguished by an overlap of biologi-cal processes. Besides the stage-speciic modules, we also identiied seven “multi-stage” modules (see dashed outlines, Fig. 2b), deined by a constant dominant expression pattern in two or more consecutive stages of embryogenesis (r of each stage > 0.2, sum(r) > 0.8), including “MElightcyan,” “MEgreenyellow,” “MEsalmon,” “MEyellow,” “MEblue,”

Fig. 1 Hierarchical clusters of embryo transcriptomes in diferent developmental stages. a Principal component analysis (PCA) of the transcriptomes for seven stages of embryo development. Biological replicates from the same embryo stage are represented by the same color. Arrows indicate the direction of embryo development. b Heat-map of sample distance from seven diferent embryo stages, with two replicates (numbered 1 and 2) per stage. The grayscale spectrum rep-resents sample distance calculated by R dist function ranging from 0 (black) to 400 (white), indicating high to low correlations, respec-tively. Embryo stages include Z, zygote; O, octant; G, globular; H, heart; T, torpedo; B, bent; and M, mature. c Unrooted hierarchical tree generated with combined sample replicates using SplitsTree4 software. The node distance was calculated with the R hclust package “complete” method. The length of lines connecting stages of embryo development are proportional to relatedness

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“MEred,” and “MEgreen.” We combined these thirteen mod-ules and named them M1–M13, based on their respective dominant expression stages during the sequential develop-mental progression from zygote to mature embryo. The color modules and corresponding module numbers are listed in Supplemental Data S3. An updated eigengene adjacency heatmap generated using the thirteen MEs and seven stages of embryo development highlights the association between development stages and the stage-speciic (M1, 2, 5, 6, 9, 11) or multi-stage modules (M3, 4, 7, 8, 10, 12, 13) (Fig. 3a).

Cluster analysis of coexpression gene modules

To investigate transcriptional regulation across embryo development, all the genes represented by the thirteen ules were analyzed. First, a heatmap of stage-speciic mod-ules associated with the developmental stages M1, M2, M5, M6, M9, and M11 was generated. As shown in Fig. 2c, genes enriched or absent in speciic stages of development were clustered with each corresponding module.

To investigate the putative functions associated with the stage-speciic and multi-stage modules, we performed gene ontology (GO) enrichment analysis (Ashburner et al. 2000). Top GO terms in the biological process (BP, Fig. 3b) and cellular component (CC, Figure S2) categories were gener-ated. No enrichment of BP GO terms was detected in M2, 3, 6, 9, 12 with a threshold setting of p value (adjusted) < 0.01, indicating no dominant biological process could be linked to these module-associated embryo stages. Gene lists and gene functional descriptions of all 13 modules are presented in Data S3. The majority of genes enriched in M1 are involved in developmental regulation and protein-targeting processes, supporting the importance of these genes and the associ-ated processes in the zygote and early embryo establishment phase. Genes in M4 are highly expressed in the zygote and octant stages (Fig. 3a) and show GO term enrichment in cell wall modiication and organism developmental processes.

Gene activities involved in developmental processes in M1 and M4 are closely related to the embryonic patterning events that occur in early stages of embryonic development, as highlighted in a previous study (Jenik et al. 2007). M7 and M8 are multi-stage modules where high gene expression was associated speciically with early and middle stages of embryo development, from O to T and from Z to T, respec-tively. GO terms associated with these two modules were predominantly related to cell development. Genes with GO term enrichment in methylation were also observed, particu-larly in M8, supporting a signiicant epigenetic programming and its inluence on early and middle stages of embryo devel-opment. M10 is a multi-stage module associated with late embryo stages of development, corresponding to T and B stages, in which GO enrichment analysis revealed the onset of the components associated with photosynthetic processes. M11 and M13, modules associated with late and mature embryo development, respectively, showed GO term enrich-ment in metabolic processes and storage reserve synthesis (storage proteins, lipids, fatty acid oxidation), suggesting that lipid metabolism is reprogrammed for seed dormancy before the formation of mature seeds. The interact graphs of GO terms in these modules were simulated (Fig. 3c–e, S4). Our results suggest that the top enriched GO terms from most gene modules are grouped to one cluster, indicating that stage-speciic genes in the same module are primarily involved in similar biological processes. One exception to this is gene module M1. The top enriched GO terms from M1 are clustered in three diferent groups (Fig. S4a), reveal-ing complex reprogrammreveal-ing after fertilization at the zygote stage of embryo development.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database resource for understanding the high-level func-tions of a biological system (Kanehisa and Goto 2000). The signiicantly enriched pathway ontology (PO) terms were phenylpropanoid biosynthesis in M1, ribosome in M8, pho-tosynthesis in M10, and lipid metabolism in M13 (Fig. S3).

Table 1 Gene ontology (GO) terms associated with selected 101 DEGs

For GO enrichment analysis, 101 DEGs identiied from comparisons between every two consecutive stages of embryo development (for a total of six comparisons) were selected. The top ive enriched GO terms and the corresponding gene ratio are indicated. Gene ratio is deined by the number of genes related to the GO term/the number of genes in the gene set. Bg_ratio (Background_ratio) is deined as the number of genes in Arabidopsis related to this GO term/total number of genes in Arabidopsis genome. GO_acc GO accession number. FDR false discovery rate, which is the rate of type I errors in null hypothesis testing when con-ducting multiple comparisons

GO_acc GO_term Gene_ratio Bg_ratio FDR

GO:0009791 Post-embryonic development 11/101 705/37767 0.00047

GO:0048316 Seed development 9/101 530/37767 0.001

GO:0010154 Fruit development 9/101 557/37767 0.001

GO:0009793 Embryonic development ending in seed dormancy

7/101 465/37767 0.0062

GO:0048608 Reproductive structure development 10/101 978/37767 0.0062

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These PO terms are similar to the results of GO term enrich-ment analysis, providing further support for the functional annotation of gene modules.

DEGs associated with seed developmental networks

In this study, an ImageAnnotator module from the MapMan visualization tool was used to deine hierarchical functional

Fig. 2 Stage-speciic gene modules identiied by weighted gene coexpression network analysis (WGCNA). a Hierarchical cluster tree showing modules of coexpressed genes, with a total of 26 coex-pressed gene modules identiied by WGCNA dendrograms. The height (y-axis) indicates level of correlation. Colors represent the 26 diferent modules, with gray color indicating genes that could not be assigned to any module. b Heatmap of correlations between coexpressed gene modules and stages of embryo development, with numerical Pearson’s correlation coeicient (top) and correspond-ing p values (bottom). The color scheme, from red through white

to green, indicates the level of correlation, from high to low. Stage-speciic modules (*) are identiied by r > 0.8, p < 0.001. Associated consecutive stages in multi-stage modules are identiied by r of each stage > 0.2, sum (r) > 0.8, and grouped in dashed boxes. c Heatmap of expression dynamics of gene members in six stage-speciic modules, M1, 2, 5, 6, 9, 11. Genes in each module are associated with a color on the left of the heatmap. Z-score was applied for each row. Each module contains high expression (red) and low expression (green) genes in corresponding stages

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categories (bins) for all DEGs associated with embryogen-esis. This module was downloaded from the MapManStore server including known Arabidopsis seed development-related genes and their assignment to corresponding bins. The outline of this module is shown in Figure S5. DEGs in diferent embryo developmental stages were assigned to diferent bins in this module, and their expression levels in comparison with the previous embryonic stage were visual-ized (Fig. S5a–f). The progression from Z to O was accom-panied by an upregulation of most of the genes in this mod-ule. In the O and G stages, downregulation of almost all bins was observed, whereas from the G to T stage, the majority of genes in this module were predominantly upregulated. Finally, the majority of the seed development-associated

genes are downregulated in the B and M stages. Altogether, the DEGs involved in this module followed this signiicant developmental stage-dependent expression pattern. Two typ-ical examples representing this pattern include a hormone regulation signaling pathway and transcriptional factors involved in embryo development (Fig. S5). High expres-sion peaks of most members in these two pathways are in O and T stages, which are closely connected to major events in embryogenesis, embryo patterning, and embryonic body plan establishment and elaboration.

In contrast to most categories in the seed development molecular networks listed above, DEGs from six pathway bins showed distinct expression patterns (Fig. S5, Data S4). A heatmap of related genes’ dynamic expression across

Fig. 3 Cluster analysis and functional annotation of stage-associated gene modules. a Eigengene adjacency heatmap of the consensus eigengene network that includes thirteen stage-associated modules and seven embryo development stages. The color scheme, from red through white to blue, indicates the level of correlation, from high to low. M1–13 represent thirteen stage-speciic modules (purple text). Zygote—Z, octant—O, globular—G, heart—H, torpedo—T, bent— B, and mature—M represent the seven developmental stages (orange text). Related stage-speciic gene modules and embryo development stages are grouped by a dashed black box. b A visual representation of GO enrichment for the DEGs with enriched GO terms in the

bio-logical process category (on the y-axis) plotted against each module (x-axis). No signiicant GO terms were enriched in M2, 3, 6, 9, 12. The GO terms with a signiicant p (< 0.01) are shown. Dot size repre-sents related gene count number. c–e Interact graphs of enriched GO terms in diferent modules. GO terms with p value (corrected) < 0.01 were selected and applied to Cytoscape software to generate GO interact graphs. c M8 (zygote to torpedo), d M10 (heart and torpedo), e M13 (torpedo, bent, and mature). Colors from red to yellow indi-cate p value from low to high. Thickness of lines indiindi-cates the relative strength of the association between two GO terms

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embryo development was generated (Figs. 4b–d, S5). Pho-tosynthesis and Calvin Cycle category BIN genes exhibited high expression in T and B stages, which is identical to the GO and KEGG enrichment analysis results for the M10 gene module (Figs. 3b, 4b, S6a). The other four pathway bins, including most seed storage proteins, late embryogen-esis abundant (LEA) proteins, triacylglycerol (TAG), and fermentation-related genes, were signiicantly upregulated in B and M stages (Figs. 4c, d, S6b, c). Associated genes in these four pathways are suggested to play important roles in regulating seed maturation processes such as seed dormancy and storage reserve accumulation.

The observations from seed development networks revealed unique gene expression enrichment proiles involved in late and mature embryo development stages. Similar enrich-ment, such as methylation-related pathways, was observed in early and middle stages of embryo development. A list of histone methylation-related genes in Arabidopsis was estab-lished (Data S5), and a heatmap of their expression patterns in embryo development was generated (Fig. 4a). Like the GO enrichment analysis, most of these genes were enriched in early and middle stages of embryo development, suggesting epigenetic reprogramming during these stages of embryogen-esis. Stringent regulation of the transcript levels of these genes from methylation, photosynthesis, and storage protein-related pathways reveals their key roles in embryogenesis.


Due to the small size of early embryos, and the potential for contamination of embryo samples by surrounding seed coat and endosperm tissues, transcriptomic analysis of early

plant embryogenesis has been challenging. In this study, we optimized and validated a method for hand dissection of Arabidopsis embryos from zygotes to mature stages. Our protocol ofers an afordable, reliable, and precise approach to obtaining plant embryos for transcriptome analysis. The embryo isolation method we developed has been success-fully adopted in diferent species and applied in several studies (Armenta-Medina et al. 2017; Moller et al. 2017; Quint et al. 2012; Venglat et al. 2011; Xiang et al. 2011a,

b). Previous transcriptome studies of the full developmen-tal time course of Arabidopsis embryogenesis have used microarray-based technologies (Belmonte et  al. 2013; Xiang et al. 2011a), which are not as quantitative for gene expression as RNA-seq studies, and have the disadvantage that transcript isoform variants like diferent mRNA splice products cannot be detected. Other studies of embryo tran-scriptomes have used RNA-seq, but focused only on a few stages of embryogenesis (Autran et al. 2011; Hsieh et al.

2011; Nodine and Bartel 2012; Pignatta et al. 2014). For these reasons, our RNA-seq analysis of the complete time course of Arabidopsis embryogenesis is comprehensive and a valuable resource for studies of embryogenesis in the widely studied model plant Arabidopsis and has potential to aid embryogenesis studies in other plant species. This dataset has already allowed us to discover gene expres-sion patterns correlated with stage transitions throughout embryo development. Furthermore, through our application of RNA-seq technology to embryogenesis, the transcrip-tomic reprogramming associated with embryo development is presented in a high-throughput and quantitative manner. This study revealed novel gene expression patterns and their correlation with stage transitions in embryo development. This comprehensive description of gene activities during

Fig. 4 Distinct expression trends of DEGs. Heatmaps of DEGs gen-erated with the R pheatmap package. Rlog value of a histone meth-ylation, b photosynthesis, c triacylglycerol (TAG), and d late embry-ogenesis abundant protein (LEA)-related DEGs were extracted, and the heatmaps were generated based on the Z-score transformed rlog

value. Gene names are indicated to the right of the heatmap. Genes with similar expression patterns were clustered, and hierarchical trees were generated on the top of the heatmaps. The color scheme, from magenta through gray to cyan, indicates the level of correlation, from high to low 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539

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embryo development and the identiication of stage-speciic and multi-stage modules ofer new insights and resources for future plant embryogenesis research.

Based on our DEG analysis, the transitions between every two consecutive stages of embryo development deined by this study are characterized by a signiicant transcriptome reprogramming (Data S1). The early and middle stages of embryo development are associated with embryonic pat-terning events (Jenik et al. 2007; Moller and Weijers 2009; Venglat et al. 2011), so the large shifts observed in expres-sion and transcriptional regulation at these stages are not surprising. Consistent with our indings (Fig. S5, Data S1), previous reports indicated that early embryo patterning pro-cesses are promoted by auxin, the SHORT SUSPENSOR (SSP)/YODA (YDA)/WUSCHEL-LIKE HOMEOBOX (WOX) cascade, and miRNAs (Armenta-Medina et al. 2017; Bayer et al. 2009; Breuninger et al. 2008; Moller and Weijers

2009; Moller et al. 2017; Musielak and Bayer 2014; Nodine and Bartel 2010, 2012; Robert et al. 2018; Seefried et al.

2014; Ueda et al. 2011, 2017).

Studies in mammalian and plant systems have revealed an important role for epigenetic factors such as DNA methyla-tion in regulating early development (Garcia-Aguilar et al.

2010; Rose and Klose 2014). Based on our DEG analysis of transcriptome datasets, DNA methylation is an impor-tant epigenetic factor observed in early and middle stages of embryo development, providing another proof for this con-clusion (Fig. 3b). In mammals, the absence of DNA replica-tion maintenance caused by methylareplica-tion has been implicated in the developmental regulation of early embryos (Rose and Klose 2014). In this study, GO terms including DNA rep-lication, RNA methylation, and histone 3 lysine 9 (H3-K9) methylation were enriched in gene module M8 (Fig. 3b, c), which represent the Z to T stages of embryo development (Fig. 3a), indicating that methylation-associated changes likely occur soon after fertilization. In plants, DNA meth-ylation is found in three diferent sequence contexts: CG, CHG, and CHH. CHH methylation occurs through two pathways, the H3K9me2-dependent DNA methyltransferase CHROMOMETHYLASE 2 (CMT2) and RNA-directed DNA methylation (RdDM) (Jullien et al. 2012). Both CHH methylation pathways were enriched in M8 gene modules, which implicates a key role for this epigenetic modiication in early and middle stages of embryo development, and is supported by a previous study that detected increasing CHH methylation in Arabidopsis embryo development (Jullien et al. 2012).

Many angiosperm seeds contain chlorophyllous embryos (called chloroembryos) (Yakovlev and Zhukova

1980) that contain components of the photosynthetic machinery, despite being embedded in ovule tissues within a highly osmotic environment (Puthur and Sara-dhi 2004). Our study revealed a signiicant enrichment of

photosynthesis-related genes and pathways in M10 gene modules, representing late-stage H, T, and B embryos (Figs. 3b, d, 4b). In the M10 module, genes with anno-tated roles in plastid membrane organization were also enriched and are likely to be related to chloroplast bio-genesis (Fig. 3b). These findings are consistent with recent research on LEAFY COTYLEDON 1 (LEC1). At early stages of seed development, LEC1 regulates dis-tinct gene sets to mediate the temporal transition between chloroplast biogenesis and photosynthesis (Pelletier et al. 2017). In our study, we also observed late embryo-enriched expression of CHLOROPLAST STEM-LOOP BINDING PROTEIN 41 kDa (CSP41B, AT1G09340) and GERANYL(GERANYL)DIPHOSPHATE SYNTHASE 11 (GGPPS11, AT4G36810), two genes involved in photo-synthesis and the Calvin Cycle (Figs. 4b, S5a, Data S1). Previous functional analysis of these genes has shown that they are expressed during late stages of embryo devel-opment and are required for chlorophyll production and embryo development (Ruiz-Sola et al. 2016). Thus, our transcriptome-based observations complement functional analysis of the importance of photosynthesis in late stages of embryo development.

Active photosynthesis in late-stage embryos contributes oxygen and energy supplies (ATP/NADPH), which might be an important resource supporting subsequent seed develop-ment and lipid synthesis (Ohlrogge and Browse 1995). The storage of lipids and fatty acids in the inal stages of seed development is critical for supporting the energy demands of germination (Baud and Lepiniec 2010; Borek and Ratajc-zak 2010), and recent metabolic and transcriptional analysis demonstrated the importance of the embryo and endosperm in lipid and fatty acid biosynthesis (Han et al. 2017; Tron-coso-Ponce et al. 2016). We observed that genes associated with lipid synthesis were enriched in the late embryogen-esis (the M13 gene module) (Fig. 3b). Functional analysis of genes in this module should reveal the diferent roles of the embryo in storage of lipids and fatty acids during late embryonic development. The enrichment of triacylglycerols (TAGs), one of the main forms of energy storage in liv-ing organisms, was supported by gene expression patterns in B- and M-stage embryos (Fig. 4c). Similar trends were observed in other energy-related gene categories, such as fermentation-related genes (Fig. S6c). Late embryogenesis abundant (LEA) proteins accumulate at high levels during late stages of embryo development and are associated with dehydration tolerance (Dure and Galau 1981; Tunnaclife and Wise 2007). In this study, most LEA proteins belong to mature-stage-speciic gene modules and showed enrichment speciically in the mature-stage embryos (Fig. 4d).

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This study presents an optimized method for characterizing the transcriptome of developing Arabidopsis embryos from zygote to maturity. RNA-seq analysis supported a signii-cant transcriptional reprogramming during embryogenesis. A comprehensive examination of gene activities deined stage-speciic and multi-stage gene modules and coexpres-sion gene networks. Methylation, initiation of photosyn-thesis, and storage/energy-related protein activation were identiied as three signature gene activities associated with early/middle, late, and mature stages of embryo develop-ment, respectively. The dynamic transcriptome and genes associated with diferent metabolic pathways in embryogen-esis were revealed, providing a landscape of gene expression for ongoing eforts to unravel the genetic regulation of plant embryogenesis.

Author contribution statement RD and DX designed and coordinated the study. DX performed experiments. PG, DX, and TDQ performed data analysis, prepared the igures, and wrote the manuscript. EW participated in bioinformatics data analysis. PV and PKP assisted with data analysis. CSG edited the manuscript and contributed to interpretation of results. All authors read and approved the inal manuscript.

Acknowledgements This work was funded by the Aquatic and Crop Resource Development Research Division of the National Research Council of Canada (ACRD manuscript #56424). We thank Dr. Wentao Zhang for reviewing the manuscript and providing suggestions for its improvement.

Compliance with ethical standards

Conflict of interest The authors declare that they have no conlict of interest.


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Fig. 1   Hierarchical clusters of embryo transcriptomes in diferent  developmental stages
Table 1   Gene ontology (GO)  terms associated with selected  101 DEGs
Fig. 2   Stage-speciic gene modules identiied by weighted gene  coexpression network analysis (WGCNA)
Fig. 3   Cluster analysis and functional annotation of stage-associated  gene modules


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The ionic conductivity is about 10 {sup-4}-10 {sup-5} S cm {sup-1}; for the activation energy, a typical value of 0.32 eV is obtained for x= 0.6 composition whereas

Nous avons retenu le schéma réactionnel proposé par Broido-Shafizadeh et modifié par Varhegyi, c’est-à-dire la décomposition thermique de la cellulose représentée par

Inzi-a qqaren-t ɣef lmut ara yeṭṭfen yal amdan, maca yiwen deg-neɣ ur yeẓri amek ara yemmet, acku aṭas n ssebbat i yellan.. Ixleq imdanen, yal yiwen d acu i

(B) Quantification of NP distribution in percentage inside the basolateral compartment as a function of the surface charge of the NP, in white SiO 2 -FITC-NP and in.. black SiO

L’accès à ce site Web et l’utilisation de son contenu sont assujettis aux conditions présentées dans le site LISEZ CES CONDITIONS ATTENTIVEMENT AVANT D’UTILISER CE SITE WEB.

Access and use of this website and the material on it are subject to the Terms and Conditions set forth at Regulated and controlled direct current electrical supply for

However, when focusing on the target genes analysed by 3D DNA FISH, we observed a general decrease in the degree value, meaning that IGF2, DLK1, MEG3, RPL32, MEST, DCN and MYH3

The approach was to convert the EMAGE data into a formal context, mine the context for concepts satisfying a specified minimum size and then approximate the results using FCA

The results of the present experiment show no interaction between visual information and “at the ear” loudness estimates for white noise bursts displayed by a loudspeaker in anechoic

To cite this version: Le, Nguyen Tuan Thanh and Hanachi, Chihab and Stinckwich, Serge and Ho, Tuong Vinh Discovering crisis models to help assess coordination plans: a case study