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Multi-Tissue Transcriptomic Profiling Identifies Anther Preferentially Expressed Candidate Genes in Cotton
Juanjuan Feng1, Hexuan Zhang1, Xuexian Zhang1
1State Key Laboratory of Cotton Bio-breeding and Integrated Utilization, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, 38 Huanghe Dadao, Anyang 455000, China.
Abstract:
Anther development is a complex and highly regulated process essential for pollen formation and reproductive development. However, systematic identification of genes exhibiting anther-preferential expression patterns through multi-tissue transcriptomic comparisons remains limited in cotton. In this study, comparative transcriptome analysis was performed using root, stem, leaf, and anther tissues of the cotton D8R line to identify candidate genes associated with anther development. Transcriptomic comparisons revealed extensive transcriptional differences between anthers and vegetative tissues, with 11,255 differentially expressed genes commonly identified among the three pairwise comparisons. Through stringent expression filtering, 843 putative anther-preferentially expressed candidate genes were identified, showing predominant expression in anthers and minimal expression in vegetative tissues. Nine representative genes, including GhGDSLA08, GhGDSLD08 esterase/lipase, GhPRX (class III peroxidase), GhAGL (MADS-box transcription factor), and GhTKPR1-like reductase genes, were further validated by qRT-PCR, confirming their anther-preferential expression patterns. Promoter analysis of the nine validated genes identified three recurrent sequence motifs among seven selected promoters, including CG-rich and G-rich sequences, which showed similarity to reported binding motifs of CAMTA, bHLH, and TCP transcription factors. Collectively, this study provides a valuable transcriptomic resource of anther-preferentially expressed candidate genes and potential cis-regulatory features, offering genetic resources for further investigation of cotton anther development and related reproductive processes.
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