DOI: 10.5061/dryad.2rbnzs7w3
title: Leaf and shoot apical meristem transcriptomes of quinoa (Chenopodium quinoa Willd.) in response to photoperiod and plant development

description: Our study focused on identifying key genes regulating flowering time and
 photoperiod response in quinoa. We examined the timing of
 photoperiod-induced floral transition and analyzed transcriptomes in
 photoperiod-sensitive and -insensitive quinoa accessions' leaf and
 shoot apical meristems. Histological analysis showed that floral
 transition in quinoa initiates two to three weeks after sowing. We found
 four groups of differentially expressed genes annotated in the QQ74-V2
 reference genome that responded to plant development and floral
 transition, (i) 222 genes responsive to photoperiod in leaves, (ii) 1,812
 genes differentially expressed between accessions under long-day
 conditions in leaves, (iii) 57 genes responding to developmental changes
 between weeks under short-day conditions in leaves, and (iv) 911 genes
 responding to floral transition within the shoot apical meristem.
 Interestingly, among numerous candidate genes, two putative FT orthologues
 and others (e.g., SOC1, COL, AP1) have been reported as key regulators of
 flowering time in other species. Additionally, we used co-expression
 networks to associate novel transcripts to a putative biological process
 based on the annotated genes within the same co-expression cluster. The
 candidate genes in this study would benefit quinoa breeding by identifying
 and integrating their beneficial haplotypes in crossing programs to
 develop adapted cultivars to diverse environmental conditions. We examined
 the timing of photoperiod-induced floral transition and analyzed
 transcriptomes in photoperiod-sensitive and -insensitive quinoa
 accessions' leaf and shoot apical meristems. Histological analysis
 revealed floral transition initiating two to three weeks after sowing.
 Differentially expressed genes were categorized in the QQ74-V2 reference
 genome, encompassing 222 genes responsive to photoperiod in leaves, 1,812
 genes under long-day conditions, 57 genes during short-day conditions, and
 911 genes during floral transition in shoot apical meristems. Notably,
 among numerous candidates, two putative FT orthologues and others (e.g.,
 SOC1, COL, AP1) implicated in flowering time regulation in various species
 were identified. Co-expression networks associated novel transcripts with
 putative biological processes based on annotated genes in the same
 cluster. The candidate genes identified have potential applications in
 quinoa breeding, facilitating the incorporation of beneficial haplotypes
 in crossbreeding programs to develop cultivars adapted to diverse
 environmental conditions.
description: We analyzed the development of the Shoot Apical Meristem (SAM) in
 two quinoa accessions differentially responding to day length. Studying
 leaf and SAM transcriptomes from plants grown under Short Days (SD) and
 Long Days (LD) conditions resulted in thousands of differentially
 expressed genes. Our study provides new insight into quinoa’s flowering
 time and photoperiod regulation.
description: # Leaf and shoot apical meristem transcriptomes of quinoa (Chenopodium
 quinoa Willd.) in response to photoperiod and plant development
 Here we release the raw
 read count data allowing the reproduction of the transcriptomic analysis
 performed in the linked study. This is a matrix of CPM (count per million
 mapped reads) resulting from the mapping of 72 RNA-seq samples of quinoa
 against a transcriptome of 132,965 gene models (including previously
 annotated genes from the reference genome, and newly annotated transcripts
 supported by the current RNA-seq dataset). The RNA-seq samples correspond
 to the transcriptome sequencing of 48 leaf and 24 SAM cDNA libraries from
 two quinoa cultivars contrasting by their daylength sensitivity grown
 under short- and long-days conditions. This dataset allows to explore the
 mechanisms of quinoa’s flowering time and photoperiod regulation at the
 transcriptomic level. ## Description of the data and file structure
 \##List of files for Statistical analyses:
 \--&gt;RNA-seq_Sample-Description.xlsx : a table describing the name,
 accession, tissue, condition, developmental stage, and replication of each
 RNA-seq library sample used in this study. \--&gt;gene_matrix_leaf.txt :
 gene matrix of 'expected counts' (estimate maximum likelihood
 expression levels) produced by rsem for the RNA-seq samples from leaf
 tissue. \--&gt;gene_matrix_meristem.txt : gene matrix of 'expected
 counts' (estimate maximum likelihood expression levels) produced by
 rsem for the RNA-seq samples from meristem tissue. \##List of files for
 Bioinformatics analyses: \--&gt;gene2transcript.txt : table matching gene
 and transcript IDs \--&gt;merged_assembly.gff : coordinates of each
 transcript/gene on the reference genome QQ74_V2 \--&gt;transcripts.fa.tar
 : transcripts assembly including known (from QQ74_V2 reference genome
 annotation) and newly assembled transcripts using the rna-seq dataset
 generated for this study. ## Code/Software \##List of files compiling the
 codes to reproduce bioinformatics and statistical analyses
 \--&gt;R_Script_DEG_analysis_and_MDS_plots.R : the R script used to
 perform the statistical analysis from the matrix of counts.
 \--&gt;Bioinformatic_pipeline.docx : code for read mapping against the
 reference genome, transcripts assembly, and mapping of reads against the
 transcriptome.