DOI: 10.5061/dryad.fqz612jzq
title: Data from: Subgenome-informed statistical modeling of transcriptomes in 25 common wheat accessions reveals cis- and trans- regulation architectures

description: 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.
description: This study obtained
 transcriptome data from seedlings, second leaves, and root tips of four
 replications of 25 NAM parental lines using
 Lasy-Seq. 
description: # 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](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 \| | | |- Index806.genes.results \| | | |- Index807.genes.results \| | | |- Index808.genes.results \| | | |- Index809.genes.results \| | | |- Index810.genes.results \| |- 231004_Sample-IndexPrimer_Allotetraploid.txt \| |- count_mapped_reads.tsv \|- TaeNAM6/ \| |- rsem_output/ \| | |- TaeNAM6/ \| | | |- Index009.genes.results \| | | |- Index010.genes.results \| | | |- Index011.genes.results \| | | |- Index012.genes.results \| | | |- Index013.genes.results \| | | |- Index014.genes.results \| | | |- Index015.genes.results \| | | |- Index016.genes.results \| | | |- Index017.genes.results \| | | |- Index018.genes.results \| | | |- Index019.genes.results \| | | |- Index020.genes.results \| | | |- Index021.genes.results \| | | |- Index022.genes.results \| | | |- Index023.genes.results \| | | |- Index024.genes.results \| | | |- Index025.genes.results \| | | |- Index026.genes.results \| | | |- Index027.genes.results \| | | |- Index028.genes.results \| | | |- Index029.genes.results \| | | |- Index030.genes.results \| | | |- Index031.genes.results \| | | |- 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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 \| | | |- Index013.genes.results \| | | |- Index014.genes.results \| | | |- Index015.genes.results \| | | |- Index016.genes.results \| | | |- Index017.genes.results \| | | |- Index018.genes.results \| | | |- Index019.genes.results \| | | |- Index020.genes.results \| | | |- Index021.genes.results \| | | |- Index022.genes.results \| | | |- Index023.genes.results \| | | |- Index024.genes.results \| | | |- Index025.genes.results \| | | |- Index026.genes.results \| | | |- Index027.genes.results \| | | |- Index028.genes.results \| | | |- Index029.genes.results \| | | |- Index030.genes.results \| | | |- Index031.genes.results \| | | |- Index032.genes.results \| | | |- Index033.genes.results \| | | |- 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Index114.genes.results \| | | |- Index115.genes.results \| | | |- Index116.genes.results \| | | |- Index117.genes.results \| | | |- Index118.genes.results \| | | |- Index119.genes.results \| | | |- Index120.genes.results \| | | |- Index121.genes.results \| | | |- Index122.genes.results \| | | |- Index123.genes.results \| | | |- Index124.genes.results \| | | |- Index125.genes.results \| | | |- Index126.genes.results \| | | |- 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.