*2.7. QTL Analysis and Candidate Genes Prediction*

QTL analysis was performed with composite interval mapping (CIM) to map the QTLs involving pepper bacterial wilt resistance using the Windows QTL Cartographer v. 2.5 program [62]. The CIM was operated at a 1.0-cM walk speed using the model 6 parameters (standard model) and the forward and backward regression model. The LOD threshold level for significance of each QTL was determined as 1000 permutations of *p* < 0.05. To identify candidate genes, the positions of highly significant QTLs regions on the genetic map were compared with their physical positions on the *C. annuum* cv. CM334 reference genome (ver. 1.55, http://www.sgn.cornell.edu/ (accessed on 19 November 2019), and 1 Mb left and right sequences were mined for candidate genes from respective corresponding marker. Putative functions of the candidate genes were further annotated with an application of sequence alignment using CM334 reference genome (ver. 1.55, https://solgenomics.net/ (accessed on 21 December 2021), Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.genome.jp/kegg/ (accessed on 21 December 2021), SwissProt (https://www.uniprot.org/ (accessed on 21 December 2021), Gene Ontology (GO) (https://www.geneontology.org/ (accessed on 23 December 2021), and the NCBI non-redundant protein (NR) (https://ncbi.nih.gov/blast/db/ (accessed on 23 December 2021) with default values.

#### *2.8. Data Analysis*

The Tukey's HSD/Kramer test (*p* < 0.05) and the descriptive statistics of disease index were analyzed using SPSS program (IBM SPSS v27.0, Chicago, IL, USA). The Pearson's correlation coefficients were calculated using the R statistical Software (ver. 4.0.1, https: //www.r-project.org (accessed on 3 January 2022)).
