DOI: 10.5061/dryad.0k6djhb59
title: The cacao gene atlas: A transcriptome developmental atlas reveals highly tissue-specific and dynamically-regulated gene networks in Theobroma cacao L

description: A large dataset of replicated transcriptomes was developed to accelerate
 Theobroma cocoa genomics research with the long-term goal of progressing
 breeding towards developing high-yielding elite varieties of cacao. RNAs
 were extracted and transcriptomes were sequenced from 123 different
 tissues and stages of development representing major organs and
 developmental stages of the cacao lifecycle. In addition, several
 experimental treatments and time courses were performed to measure gene
 expression in tissues responding to biotic and abiotic stressors. Samples
 were collected in replicates (3-5) to enable statistical analysis of gene
 expression levels for a total of 390 transcriptomes.  We describe
 the creation of the atlas,and its global characterization and define sets
 of genes co-regulated in highly organ- and temporally-specific manners. To
 promote wider use of these data, all raw sequencing data, expression read
 mapping matrices, scripts, and other information used to create the
 resource are freely available online. A gene expression browser with a
 graphical user interface was developed to display gene expression patterns
 and to provide easy access of raw data and statistical analyses.
description: RNA was extracted form about 400
 different tissues/treatments and replicates. Transcriptome sequencing was
 performed by Quant Seq (Lexogen). Raw QuantSeq reads were first examined
 with FASTQC (v0.11.9 https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to assess the overall data quality before processing. Reads were then processed using <em>bbduk</em> (BBMap tools v37.76; https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbduk-guide/) to trim the adapter sequences, poly-A tails, and low-quality bases and to discard fragments less than 20 bp in length after trimming. Trimmed reads were mapped to the CCN-51 and SCA6 <em>Theobroma cacao</em> genotype reference genomes using the STAR Aligner version 2.7.5b (Dobin et al. 2013). Expression quantification was performed with <em>featureCounts</em> from the Subread package version 2.0.1 (Liao et al. 2013) in a fractional read-counting mode to prop distribute muti-mapping reads among features using gene annotation GFF3 files modified with GenomeTools version 1.5.9 (Gremme et al. 2013) to include intron coordinates. The count matrices were normalized to counts per million (CPM) values using the default parameters of the <em>cpm</em> function in the <em>edgeR</em> Bioconductor package (Robinson et al. 2010). Annotations were performed as described in Winters (2023). Analysis commands utilized in the QuantSeq read processing are reported in Supplemental Data Set 3.
description: Excel or any text editor or spreadsheet program.
description: # The cacao gene atlas: A transcriptome developmental atlas reveals highly
 tissue-specific and dynamically-regulated gene networks in Theobroma cacao
 L ## Description of the Data and file structure 1. The first row lists all
 tissues, replicates and time points for each sample. The first column
 lists each cacao gene that was detected. All other cells contain the
 number of transcripts that were mapped for each gene/sample combination.
 2. CPM counts are normalized by counts per million, they are used on the
 BAR website 3. To compare values in the gene expression matrix with the
 BAR website, be sure to use the CPM read counts 4. Fractional reads are
 unnormalized raw reads to be used for downsteam analysis such as DESeq2,
 do not compare these counts with the counts on BAR 5. Genotype of the
 tissue is indicated in the metadata, the data was mapped to multiple
 genomes which may differ from the genotype of the tissue 6. Ex: CCN51
 tissues were mapped to the CCN51 genome AND SCA6 genome 7. The Leaf
 Development and Leaf Infection atlases were mapped to the Criollo v2.0
 genome 8. Note that gene accession numbers for identical genes are
 different across the different assemblies 9. To determine identical genes
 across assemblies, a reciprocal BLAST must be performed or reference
 additional file 11. ## Sharing/access Information Links to other publicly
 accessible locations of the data: NCBI Master Bioproject
 Guiltinan-Maximova
 Lab: [https://www.ncbi.nlm.nih.gov/bioproject/936437](https://www.ncbi.nlm.nih.gov/bioproject/936437) The Cacao SCA eFP Browser is at  [https://bar.utoronto.ca/efp_cacao_sca/cgi-bin/efpWeb.cgi](https://bar.utoronto.ca/efp_cacao_sca/cgi-bin/efpWeb.cgi)   The Cacao CCN eFP Browser is at [https://bar.utoronto.ca/efp_cacao_ccn/cgi-bin/efpWeb.cgi](https://bar.utoronto.ca/efp_cacao_ccn/cgi-bin/efpWeb.cgi)   The Cacao TC eFP Browser is at  [https://bar.utoronto.ca/efp_cacao_tc/cgi-bin/efpWeb.cgi](https://bar.utoronto.ca/efp_cacao_tc/cgi-bin/efpWeb.cgi) [Was](https://www.ncbi.nlm.nih.gov/bioproject/936437Was) data derived from another source? No If yes, list source(s) Original data produced in the Guiltinan-Maximova lab at Penn State.