Journal of Experimental BotanyGeneticsPeer-reviewed journal article
Integrative k-mer and Transcriptomic Analysis Reveals Putative Sex-Determining Genes in Spinacia turkestanica
Shoaib Muhammad, Shuyu Liang, Tongyu Zhou, Xinrong Liu, Liang YangiD, Ameer Ahmed MirbahariD, Ning LiiD, Chuan‐Liang DengiD
Abstract
Deciphering the regulation of sex-determining gene/s in dioecious crops is crucial for molecular breeding. However, the identification of sex-determining gene/s in Spinacia is challenging due to incomplete genome assemblies, high genomic similarity between males and females, and the limitations of transcriptome-only analyses, which may miss unannotated or novel genes in poorly assembled or absent genomic regions. To overcome these limitations, we employed a reference-genome-free k-mer approach to identify candidate sex-determining genes in Spinacia turkestanica, the closest evolutionary relative of cultivated spinach (S. oleracea). Male-specific reads were de novo assembled into contigs, revealing 21.5 Mb of the sex-determining region (SDR). Using the MAKER pipeline, which integrates transcriptomic and proteomic evidence, we predicted 226 protein-coding genes within the SDR, including nine previously unannotated. Transcriptomic profiling combined with weighted gene co-expression network analysis identified eight SDR DEGs, including two newly annotated genes, co-expressing during early male flower development. qPCR validation confirmed three SDR genes as candidate sex-determining factors, including TU_SDR00087 (bZIP domain), TU_SDR000168 (RNA-binding splicing factor domain), and TU_SDR000174 (MYB domain). Together, these findings provide a foundation for functional characterization of sex determination in Spinacia. HighlightA k-mer based analysis uncovered male-specific regions and candidate sex-determining genes in Spinacia turkestanica, advancing understanding of sex regulation and spinach breeding.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 1
- FWCI
- 4.05
- Field percentile
- top 11%
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