*2.1. Plant Materials*

A total of 195 spray cut chrysanthemum varieties were used in this study, including varieties developed by Nanjing Agricultural University and those collected from around the world. These varieties were maintained at the Chrysanthemum Germplasm Resource Preserving Centre of Nanjing Agricultural University, China (E118◦85 , N31◦95 ). The 195 varieties evaluated during the two years are listed in Table S1.

#### *2.2. Phenotypic Evaluation of Architectural Traits*

Seedlings were planted in seedbeds in June 2019 and June 2020. Vigorously growing and similarly appearing rooted seedlings were selected and transplanted into a greenhouse in July of the same year. Fifty seedlings of each variety were planted in accordance with a row spacing of 10 cm × 10 cm, and conventional field management practices were performed. Flowering occurred from late October to late November. The monthly average temperature, monthly precipitation and monthly average relative humidity of EN2019 and EN2020 in planting location, Jiangning District, Nanjing, China (E118◦85 , N31◦95 ) were shown in Table S2.

Nine phenotypic traits were measured. 1. For plant height, the height of the aboveground part of the plant was measured with a ruler, with a precision of 0.1 cm; 2. for number of leaf nodes, the number of leaf nodes on the trunk of the aboveground part of the plant was counted visually; 3. for total number of lateral buds, the number of nodes of all germinating buds or sprouted branches on the stem of the plant was counted visually; 4. for number of upper lateral branches, the number of all primary branches within 15 cm from the top of the plant was counted visually; 5. for number of lateral flower buds, the total number of flower buds on all primary branches was counted visually; 6. for stem diameter, the diameter at 40 cm below the top of the plant was measured with a digital Vernier caliper with precision of 0.01 mm; 7. for branch diameter, the diameter at 1/2 of the three nearest primary branches around the main bud was measured with a digital Vernier caliper with a precision of 0.01 mm; 8. for branch angle, the angle of the three nearest primary branches around the main bud was measured with a protractor; 9. for branch length, the length of all primary branches was measured with a ruler, with a precision of 0.1 cm. At the full-flowering stage, the measurement was performed on six plants for each variety, and the mean values were taken.

## *2.3. Phenotypic Data Analysis*

Microsoft Excel 2019 was used for basic descriptive statistical analysis of the 9 architecturerelated phenotypic traits of the 195 cut chrysanthemum varieties in EN2019 and EN2020 environments, and IBM SPSS 25.0 statistical software was used for correlation analysis of the EN2019 and EN2020 data. Significant differences (paired-sample t tests) were assessed and violin mapping and cluster analysis of two environmental data were conducted by R 4.0.4 (https://www.r-project.org/, accessed on 7 December 2021).

#### *2.4. GWAS and Candidate Gene Annotation*

In our previous study [31], 199 chrysanthemum accessions were sequenced, of which forty-four spray cut chrysanthemum varieties were also measured in our study and the list is shown in Table S3. In order to obtain more meaningful information, we performed GWAS using these raw sequencing data. SLAF-seq raw reads whose quality scores were <30 and separated by barcodes were discarded. The highest depth tag in each SLAF was chosen as a reference due to the lack of a reference genome sequence. The qualified sequencing data of the samples were aligned to the genome reference sequence of chrysanthemum using Burrow–Wheeler Aligner (BWA) V0.7 (http://bio-bwa.sourceforge.net/, accessed on 7 December 2021) [32], and then SNP sites were detected by SAMtools V1.4 (http: //samtools.sourceforge.net/, accessed on 7 December 2021) [33]. After removing the SNPs with a sequencing depth less than 3, a data loss percentage greater than 20%, and a minor allele frequency (MAF) less than 5%, 191,417 high-quality SNPs were ultimately identified for further analysis.

GCTA software V1.93 (https://yanglab.westlake.edu.cn/software/gcta/#Overview, accessed on 7 December 2021) [34] was used for principal component analysis (PCA) and construction of a kinship matrix, yielding an eigenvector principal component (PC) matrix of all the individuals and a kinship matrix comprising data between every pair of individuals. Combining the data of the nine phenotypic traits and the SNP sequencing data, a GWAS was conducted via the compressed mixed linear model (cMLM) of GAPIT software V3 (https://www.zzlab.net/GAPIT/, accessed on 7 December 2021) [35] and via the cMLM and mixed linear model (MLM) of TASSEL software V5.0 (https://www. maizegenetics.net/tassel, accessed on 7 December 2021) [36]. The mean values were used for the GWAS, and the significance threshold was set at *p* ≤ 0.001. As a result, the SNPs found to be significantly associated with the phenotypic data and the phenotypic variance explained (PVE) were identified for gene mining.

According to the significant SNP sites detected by cMLM model of TASSEL, candidate genes within 300 k of SNP sites were found. The function of genes was annotated via The Arabidopsis Information Resource (TAIR) website (https://www.arabidopsis.org/, accessed on 7 May 2022) by BLASTX [37]. Through the functional annotations of Arabidopsis and other function reported in other plants, the genes related to plant architecture, hormone signaling pathways or plant development regulation were further selected as final candidate functional genes.

#### **3. Results**
