Identification of Sex-Specific and Sex-Biased Transcripts for Genetic Sexing

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Sex-specific transcripts reveal molecular and physiological differences between sexes.
• Accurate sex determination is crucial for agriculture, conservation, and entomology.
• Existing methods may lack efficiency or applicability across species.

Purpose of the Study:

• To develop a versatile bioinformatic framework for identifying sex-specific transcripts.
• To enable genetic sexing in eukaryotic species, with or without a reference genome.
• To support advancements in livestock management, ecological monitoring, and pest control.

Main Methods:

• Utilized RNA-sequencing (RNA-seq) data.
• Developed a computational framework for transcript analysis.
• Applied the framework to eukaryotic species, accommodating both reference-based and reference-free approaches.

Main Results:

• Successfully identified sex-specific transcripts using the developed framework.
• Demonstrated the framework's utility across different eukaryotic species.
• Provided a robust method for genetic sex determination.

Conclusions:

• The bioinformatic framework offers a powerful tool for discovering sex-specific transcripts.
• This approach facilitates the development of precise genetic sexing methods.
• The findings have broad implications for biological research and applied sciences.