2. MATERIALS AND METHODS
2.1 Plant materials and light
regimens
The study was performed in two sequential growth cycles as complete
replicates. In the first growth cycle, we mainly counted the number of
floret primordia with different morphologies and the number of grains
(Figure S1); and in the second growth cycle, we monitored the growth,
development, and transcriptional dynamics of all floret primordia in the
spike.
Spring
wheat seeds (cv. longfumai1) were selected, washed, stratified, and
germinated. The germination seeds with similar radicle length were sown
in pots (volume 14.7 L, 30 seeds per pot) filled with a 2: 1: 1 (v/v/v)
mixture of garden soil, humus, and sand. The pots were transferred to a
fully enclosed plant factory (a type of controlled environment
agriculture), that was programmed to run at a temperature of 20-21oC during 06:00-18:00 and 15-16 oC
during 18:00-next day 06:00, with a relative humidity of 60-70% and a
CO2 level of 380-400 ppm. There were 30 pots, and plants
were watered every two days with the modified Hoagland’s nutrient
solution (Table S1).
The white light-emitting diodes (LEDs) were used to provide 12 h of
illumination per day (06:00-18:00) and the photosynthetic photon flux
density (PPFD) was adjusted to ~320 µmol
m−2 s−1 at the top of the plant
canopy. When plants reached the terminal spikelet stage, the pots were
divided into three groups for different light treatments. Light regimens
included: (i) SW (12 h short photoperiod supplemented with white LEDs,
light (06:00-18:00)/ dark (18:00-next day 06:00)); (ii) LW (22 h long
photoperiod supplemented with white LEDs, light (06:00-next day 04:00)/
dark (04:00-06:00)); (iii) LR (22 h long photoperiod supplemented with
red LEDs, light (06:00-next day 04:00)/ dark (04:00-06:00)). The
photoperiod extension was performed at low intensity (approximately 12
µmol m−2 s−1 PPFD). Photoperiod and
light spectral quality were measured with a portable spectroradiometer
(Plant Lighting Analyzer, v. 2.00, China) and were showed in Figure 1
and Table S2.
2.2 Floret primordia number and
morphology
measurements
Representative six main spikes per treatment were collected every three
days to count the number of total, fertile, and infertile floret
primordia per spike and per spikelet according to the different
morphologies (Figure S1b). Photomicrographs of each floret primordium
within a particular central spikelet were taken with a microscope
(MZ101, Mshot, China) equipped with a digital camera (MSX1, Mshot,
China).
2.3 Dry matter accumulation and
sugar measurement
Representative six plants per treatment were collected every three days
and dried (at 105 oC for 10 min and then at 70oC for 48 h) to a constant weight to determine the dry
matter accumulation and partitioning of plants and spikes. Dry spike
samples were used for soluble sugar extraction (Hanft & Jones, 1986).
Soluble sugar content was determined following the anthrone-sulfuric
acid method (Yemm & Willis, 1954). Glucose and fructose content were
determined by enzymatic analysis as described by Blunden & Wilson
(1985).
2.4 Samples preparation and RNA
sequencing
Pooled samples from at least three spikes every three or six days were
collected within two to five hours after the illuminate initiation, then
immediately frozen in liquid nitrogen and stored at -80oC
until further used for RNA extraction. Three biological replicates were
used for RNA sequencing.
Total RNA was isolated and purified using TRIzol reagent (Invitrogen,
Carlsbad, CA, USA) according to the manufacturer’s protocol. The RNA
purity and integrity were quantified and assessed using the NanoDrop
ND-1000 (NanoDrop, Wilmington, DE, USA) and the Bioanalyzer 2100
(Agilent, CA, USA), respectively. RNA-seq libraries were constructed
according to the manufacturer’s protocol of the NEBNext mRNA-seq library
preparation kit, and paired-end sequencing libraries with an insert size
of ~300 bp were sequenced on an Illumina Novaseq™ 6000
platform (LC-Bio Technology CO., Ltd., Hangzhou, China) following the
vendor’s recommended protocol. Clean reads were mapped to the
International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version
2.1 genome assembly using Hisat2-2.0.4 software (Kim et al. ,
2015). The expression level of each gene was normalized to fragments per
kilobase of exon model per million mapped reads (FPKM). Comparisons of
biological replicates showed that their expression levels were highly
correlated (R > 0.95; Figure S2). Hence, a gene was
considered expressed if it had an average FPKM ≥
1.
Differential expression analyses between treatments were performed using
the platform OmicStudio (https://www.omicstudio.cn) according to edgeR,
and the differentially expressed genes (DEGs) were selected with an
absolute log2 fold change (FC) ≥ 1, a statistical
significance
(false
discovery rate (FDR)-adjusted P < 0.05), and FPKM ≥ 2
in highly expressed groups. The principal component analysis (PCA),
hierarchical clustering, and Venn diagram were performed using the
anosim and prcomp function, the hclust function, and the vennDiagram
function, respectively, in R software. The Heat maps were drawn using
the TBtools (Chen et al. , 2020).
2.5 Gene coexpression and functional
enrichment
analysis
The k -means method in R software was used for coexpression
analysis of DEGs selected in LR versus LW. Functional category of
each coexpression module was performed using Gene Ontology (GO) analysis
in the platform OmicStudio (https://www.omicstudio.cn). Significantly
enriched GO terms met the condition of FDR < 0.05.
2.6 Identification of candidate key
genes
A web database, STRING (https://cn.string-db.org/) (Szklarczyk et
al. , 2019), was used for the protein-protein interaction (PPI)
analysis, specifying Triticum aestivum as the target organism
with a minimum required interaction score of 0.4. The PPI network was
then sent to Cytoscape (v. 3.8.2) (Shannon et al. , 2003), and the
Cytohubba module and Degree method were used to screen out the five hub
nodes. Genes encoding proteins with higher degree centrality scores were
regarded as more important hubs in the network.
2.7 Statistical
analysis
All experimental data was processed using Microsoft Excel 2010
(Microsoft Corporation, USA). One-way analysis of variance (ANOVA) and
LSD’s post hoc test (P < 0.05) were performed for
statistical analysis of the phenotypes. Figures were created using
OriginPro 2017 (OriginLab Corp., Northampton, MA, USA), R (v. 4.1.2),
and Adobe Illustrator CC 2019 (Adobe Inc., USA).