Data from: Subgenome-informed statistical modeling of transcriptomes in 25 common wheat accessions reveals cis- and trans- regulation architectures
Abstract
Common wheat is allohexaploid, where it is difficult to obtain homoeolog-distinguished transcriptome data. Lasy-Seq, a type of 3’ RNA-seq, is a technology efficient at obtaining homoeolog-distinguished transcriptomes. Here we applied Lasy-Seq to obtain transcriptome data from the seedlings, second leaves, and root tips of 25 common wheat lines mainly from East Asia. Roots and seedlings were similar to each other in transcriptome profiles, but they were different from the leaves. We then asked how three homoeologous genes from different subgenomes (i.e., triads) show different levels of expression. Specifically, we examined the effects of subgenomes, lines, and their interaction on the expression levels of each homoeolog triad, separately in each tissue. Of the 19,805 homoeolog triads, 51–55% showed significant effect of subgenome, suggesting cis-regulation, whereas 24–30% showed significant effect line, suggesting trans-regulation. We also found that 7.7–9.0% triads showed significant effects of the interaction. Hierarchical clustering and co-trans regulation network analysis of homoeolog triads revealed that the patterns of expression polymorphisms among the lines were shared in different genes. Our results also implied that expression variation between lines is caused by changes in a smaller number of common trans-factors. We performed GO term enrichment analysis using newly annotated and substantially improved reference, which revealed that GO terms related to each tissue type function were enriched in genes expressed in the leaves and roots. Our information provides fundamental knowledge for the future breeding of plants possessing complex gene regulatory networks such as common wheat.
README: Dataset: Subgenome-informed statistical modeling of transcriptomes in 25 common wheat accessions reveals cis- and trans- regulation architectures
https://doi.org/10.5061/dryad.fqz612jzq
This study obtained transcriptome data from seedlings, second leaves, and root tips of four replications of 25 NAM parental lines using Lasy-Seq. Roots and seedlings were similar transcriptome profiles to each other and different from leaves. We determined the effects of subgenomes, lines, and their interactions by leaves, roots and seedlings on expression levels for each homoeolog triads. Of the 19,805 homoeolog triads, the percentages of homoeolog triads with significant subgenome, line and interaction effects were 50.9–55.4%, 24.2–29.5% and 7.7–9.0%, respectively. GO term enrichment analysis showed that GO terms related to each tissue type function were enriched in expressed genes in leaves and roots.
Description of the data and file structure
File structure
script.zip
|- Step1_MakeDescriptionFile.R
|- Step2_MakeRPMFile.R
|- Step3_MakeUlgFile.R
|- Step4_ModelingEdgeR_organs.R
|- Step5_ModelingEdgeR_terms.R
|- Step6_GOanalysisOrgans.R
|- Step7_GOanalysisTerms.R
|- Step8_D_genome_error.R
|- Step9_GeneticDistance_TranscriptomeDistance.R
|- Step10_Step10_WGCNA_with_Fig6A.R
|- Step11_GOanaylsis_of_WGCNA_module.R
|- Fig1C.R
|- Fig1D.R
|- Fig1E.R
|- Fig2.R
|- Fig4A.R
|- Fig4BC.R
|- Fig5.R
|- Fig6B.R
|- Fig6C.R
|- Fig6D.R
|- FigS1.R
|- FigS2.R
|- FigS4_5.R
|- FigS6.R
function.zip
|- 220920_GOanalysis_functions_modified.R
|- PrepareRPM_20220625.R
data.zip
|- Allotetraploid/
| |- rsem_output/
| | |- Allotetraploid/
| | | |- Index805.genes.results
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| | | |- Index810.genes.results
| |- 231004_Sample-IndexPrimer_Allotetraploid.txt
| |- count_mapped_reads.tsv
|- TaeNAM6/
| |- rsem_output/
| | |- TaeNAM6/
| | | |- Index009.genes.results
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| | | |- Index126.genes.results
| | | |- Index127.genes.results
| | | |- Index128.genes.results
| |- 220221_Sample-IndexPrimer_TaeNAM6.txt
| |- count_mapped_reads.tsv
|- TaeNAM7/
| |- rsem_output/
| | |- TaeNAM7/
| | | |- Index209.genes.results
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| | | |- Index326.genes.results
| | | |- Index327.genes.results
| | | |- Index328.genes.results
| |- 220221_Sample-IndexPrimer_TaeNAM7.txt
| |- count_mapped_reads.tsv
|- TaeNAM8/
| |- rsem_output/
| | |- TaeNAM8/
| | | |- Index009.genes.results
| | | |- Index010.genes.results
| | | |- Index011.genes.results
| | | |- Index012.genes.results
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| | | |- Index127.genes.results
| | | |- Index128.genes.results
| |- 220221_Sample-IndexPrimer_TaeNAM8.txt
| |- count_mapped_reads.tsv
|- 220804_CS_refseq_FunctionalAnnotation_IDv2.1_CS_description
|- StrainID_Name_ID.csv
|- Sun_2023_homeolog_triads.csv
|- ulg.IWGSC_homeolog_220825
|- ulg.TAIR_190903
|- Wheat_Ara_reciprocalBLAST.csv
Description
script.zip
Step1_MakeDescriptionFile.R: Make gene description file of wheat genes using IWGSC data and reciprocal BLAST data between wheat and Arabidopsis
Step2_MakeRPMFile.R: Calculate read per million from RSEM data
Step3_MakeUlgFile.R: Make GO list file using for GO enrichment analysis
Step4_ModelingEdgeR_organs.R: Script of tests of differential expression genes among tissue types using edgeR
Step5_ModelingEdgeR_terms.R: Script of tests of differential expression genes among statistical terms (subgenome, line and interaction) using edgeR
Step6_GOanalysisOrgans.R: Script of GO enrichment analysis among tissue types
Step7_GOanalysisTerms.R: Script of GO enrichment analysis among statistical terms
Step8_D_genome_error.R: Calculate percentage of mapped reads on D genome
Step9_GeneticDistance_TranscriptomeDistance.R: MRQAP tests on genetic and transcriptomic distance
Step10_Step10_WGCNA_with_Fig6A.R: Script of WGCNA and drawing Figure 6A
Step11_GOanaylsis_of_WGCNA_module.R: Script of GO enrichment analysis among WGCNA modules\
Fig1C.R: Make figure of PCA of transcriptome of leaf, root and seedling
Fig1D.R: Make figure of heatmap of transcriptome correlation of leaf, root and seedling
Fig1E.R: Make figure of Venn diagram of DEGs among tissue types
Fig2.R: Make figure of GI and LHCB gene expression
Fig4A.R: Make figure of Venn diagram of DEGs among statistical terms
Fig4BC.R: Make figure of representative gene expression
Fig5.R: Make figure of heatmap of GO terms of statistical terms
Fig6B.R: Make figure of heatmap of standardized expression level
Fig6C.R: Make figure of WGCNA modules
Fig6D.R: Make figure of RPS6S gene expression
FigS1.R: Make figure of histogram of read counts\
FigS2.R: Make figure of relationship of the number of GO terms in wheat and Arabidopsis\
FigS4_5.R: Make figure of Venn diagram of DEGs among tissue types and representative gene expression\
FigS6.R: Make figure of histogram of P value of edgeR results
function.zip
220920_GOanalysis_functions_modified.R: Using for GO term analysis
PrepareRPM_20220625.R: Using for calculate read per million
data.zip
Allotetraploid/
rsem_output/
Allotetraploid/
IndexXXX.genes.results: Read counts of allotetraploid wheats from RSEM
231004_Sample-IndexPrimer_Allotetraploid.txt: File description of allotetraploid wheats
count_mapped_reads.tsv: Summary of read counts of allotetraploid wheats from RSEM
TaeNAM6/
rsem_output
TaeNAM6/
IndexXXX.genes.results: Read counts of wheat seedlings of 25 lines from RSEM
220221_Sample-IndexPrimer_TaeNAM6.txt: File description of wheat seedlings of 25 lines
count_mapped_reads.tsv: Summary of read counts of wheat seedlings of 25 lines from RSEM
TaeNAM7/
rsem_output/
TaeNAM7/
IndexXXX.genes.results: Read counts of wheat leaves of 25 lines from RSEM
220221_Sample-IndexPrimer_TaeNAM7.txt: File description of wheat leaves of 25 lines
count_mapped_reads.tsv: Summary of read counts of wheat leaves of 25 lines from RSEM
TaeNAM8/
rsem_output/
TaeNAM8/
IndexXXX.genes.results: Read counts of wheat roots of 25 lines from RSEM
220221_Sample-IndexPrimer_TaeNAM8.txt: File description of wheat roots of 25 lines
count_mapped_reads.tsv: Summary of read counts of wheat roots of 25 lines from RSEM
220804_CS_refseq_FunctionalAnnotation_IDv2.1_CS_description: Annotation files of wheat (Chinese Spring) genes from IWGSC (gene description file) (R object). You can load in R using load function.
StrainID_Name_ID.csv: Description file of samples
Sun_2023_homeolog_triads.csv: Homoeolog triads data based on Sun et al. (2023) NAR Genomics and Bioinformatics
ulg.IWGSC_homeolog_220825: GO term list of wheat (Chinese Spring) from IWGSC data (R object). You can load in R using load function.
ulg.TAIR_190903: GO term list of Arabidopsis thaliana from TAIR (R object). You can load in R using load function.
Wheat_Ara_reciprocalBLAST.csv: Result of reciprocal BLAST between wheat and Arabidopsis
Sharing/Access information
None.
Code/Software
All scripts can be run using R.
Methods
This study obtained transcriptome data from seedlings, second leaves, and root tips of four replications of 25 NAM parental lines using Lasy-Seq.