DOI: 10.5061/dryad.4288j
title: Data from: Root architecture shaping by the environment is orchestrated by dynamic gene expression in space and time

description: Shaping of root architecture is a quintessential developmental response
 that involves the concerted action of many different cell types, is highly
 dynamic and underpins root plasticity. To determine to what extent the
 environmental regulation of lateral root development is a product of cell
 type preferential activities, we tracked transcriptomic responses to two
 different treatments that both change root development in Arabidopsis
 thaliana, at an unprecedented level of temporal detail. We found that
 individual transcripts are expressed with a very high degree of temporal
 and spatial specificity, yet biological processes are commonly regulated,
 in a mechanism we term response non-redundancy. Using causative gene
 network inference to compare the genes regulated in different cell types
 and during responses to nitrogen and a biotic interaction we found that
 common transcriptional modules often regulate the same gene families, but
 control different individual members of these families, specific to
 response and cell type. This reinforces that the activity of a gene cannot
 be defined simply as molecular function; rather, it is a consequence of
 spatial location, expression timing and environmental responsiveness.
description: Supplemental Dataset
 1Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961.Supplemental Dataset
 1. RMA-normalised Nimblegen microarray data for all transcripts measured.
 The table lists the TAIR10 Arabidopsis Genome Initiative (AGI) gene IDs
 represented on the array (for design see GEO record GPL18735 for Nimblegen
 probe design) and their expression values in all 6 time series, averaged
 (“Mean”) for each replicate set; see GEO GSE91379 for complete raw and
 normalised individual replicate values. Gene symbols and gene descriptions
 are listed according to the TAIR10 annotation. If significantly
 differentially expressed within a time series (BATS), the cluster number
 is listed. If significantly differentially expressed between treated and
 untreated time series (CN GP2S etc), the cluster number is listed. Cluster
 numbers described in the manuscript text always refer to the within-CU/PU
 or N/Rhizobia vs. U clusters (orange columns). Empty cells indicate no
 evidence of DE within/between time series. Transcripts associated with
 genes that have previously been found to be affected by the protoplast
 generation treatment or FACS (as [18]) are marked (Proto-flagged) but not
 removed from the analysis.Supplemental Dataset
 2Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961.Supplemental Dataset
 2. Cluster designations for differentially expressed transcripts. The
 table lists the TAIR10 AGI IDs and descriptions (as Supplemental Dataset
 1), whether these are classed as transcriptional regulators for network
 analysis (‘TF category’) and the cluster numbers for DE transcripts. In
 addition, transcripts that are differentially expressed in both CU and PU
 (‘Core CU/PU’), are ‘N-response’ marker genes, clock genes or are CTSEs in
 cortex or pericycle are indicated (as referred to in the
 text).Supplemental Dataset
 3Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 3. Phenotypic analysis. (A) Average (ave) and standard error (SE)
 root trait values measured from 9 day old Col0 seedlings and for the same
 seedlings after 4 days of N, rhizobial or control/mock treatment with
 T-test values comparing phenotype values (bold=P&lt;0.01). (B-C) Average
 (ave) and standard error (SE) root trait values measured from 12 day old
 wrky15 (B) and nlp8 (C) mutant plants on replete and deplete N with T-test
 values comparing phenotype values in mutant and silbling WT
 (bold=P&lt;0.01); LR = lateral root, PR = primary root. (D) Average and SE
 (n=3 biological replicates) of qPCR measurement, qPCR primer sequences and
 qPCR product lengths.Supplemental Dataset
 4Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 4. GO term overrepresentation analysis. GO terms (biological
 process/molecular function/cellular component) found to be overrepresented
 within CN/PN/CR/PR clusters (according to GOrilla [79] with hypergeometric
 test correction) or within core N-response groups (Figure 6C) (according
 to BioMaps implemented in VirtualPlant [80] using a Fisher exact test with
 FDR correction) are listed, together with the corrected P value and gene
 membership; x=number of genes with GO term in test cluster/group; X=total
 number of genes in test cluster/group; n=number of genes with GO term in
 background; N=total number of genes in background.Supplemental Dataset
 5Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 5. Network edge designations with validation information. For each
 causal regulatory network (A) CU, (B) CN, (C) CR, (D) PU, (E) PN, (F) PR,
 edges between regulator and target are listed with their posterior
 probability (pp), regulation type (induce or repress), and whether they
 are validated according to the O'Malley et al 2016 ampDAP-Seq data or
 DAP-seq data [42] (1=validated, 0=not validated, NT=not
 tested).Supplemental Dataset
 6Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 6. Network statistics and module annotation and characteristics
 .(A) For each causal regulatory network 8 statistics are shown: number of
 edges, number of nodes, the node/edge ratio, number of connected TFs,
 number of targets of those TFs (including TFs that are targets), average
 targets per TF, the network clustering coefficient and the characteristic
 path length as given in Cytoscape. (B) Comparison of TF module size and
 timing response category for CN and PN networks. (C) Network statistics
 for major modules in each experiment are shown with a cut off of &gt;=10
 targets in at least one experiment. The status of each TF in the network
 in each experiment is shown (DE (0 not DE, 1 DE), indegree, outdegree).
 The combined outdegree is the sum of the shown out degrees across the six
 experiments, the number of experiments where outdegree is &gt;7 is also
 shown. Maximum module size was in part dictated by the number of genes in
 the network, while the mean number of targets per TF was larger in CU and
 CN. This indicates that the pericycle and cortex networks have
 statistically different structures and this was confirmed by analysis of
 the network connectivity using size independent statistics; specifically
 there were differing levels of clustering, CN was the least clustered
 whereas PN had the longest path length while still being highly clustered.
 This indicates that the cortex is dominated by a few large modules, while
 the pericycle is more distributed amongst a larger number of modules, in
 fact extending to very large sizes. (D) Corroborated interactions based on
 the presence of cis-acting TF family binding sites for networks. Data
 derived from Franco-Zorrilla et al 2014 [83]. Source contains TFs that
 interact with a putative regulated gene (Target) and the type of
 interaction (activation/inhibition) is shown.Supplemental Dataset
 7Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 7. Glutathione S-transferase gene family expression is highly
 variable. All members of the GST family the time series within which
 differential expression was found are indicated (or not DE), together with
 the cluster number for that time series. Genes shown on Figure 6 are
 highlighted in yellow and the time series that has been shown is
 indicated.Supplemental Dataset
 8Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961. Supplemental
 Dataset 8. Gene family regulation across cell types and treatments. (A)
 Summary of gene family regulation: number DE/non-DE, in which timeseries
 they are regulated and if transcripts are DE in one or both cell types.
 (B) Lists of the genes in each family together with cluster numbers if
 differentially expressed in a timeseries.Supplemental Dataset
 9Supplemental Data.
 Walker et al. (2017). Plant Cell 10.1105/tpc.16.00961.Supplemental Dataset
 9. Gene model analysis. 1547 differentially expressed transcripts that
 measure the expression of 711 genes, with each gene represented between
 2-6 times. Cluster numbers, the transcript count per gene and a summary of
 whether expression of transcripts are “identical”, ”similar” or
 “different” based on the location, response and timing of differential
 expression for each gene are given (see text for explanation of
 analysis).Supplemental File
 1CU
 full network sessionSupplemental File
 2CN
 full network sessionSupplemental File
 3CR
 full network sessionSupplemental File
 4PU
 full network sessionSupplemental File
 5PN
 full network sessionSupplemental File
 6PR
 full network sessionSupplemental File
 7CU
 backbone network sessionSupplemental File
 8CN
 backbone network sessionSupplemental File
 9CR
 backbone network sessionSupplemental File
 10PU
 backbone network sessionSupplemental File
 11PN
 backbone network sessionSupplemental File
 12PR
 backbone network sessionSupplemental File
 13CN
 backbone network session with shared TFs in middleSupplemental File
 14PN
 backbone network session with shared TFs in middle