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Diego M Peralta1,2, Juan I Túnez1,3, Ulises E Rodríguez Cruz4

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This study presents a new bioinformatic framework for accurate sex identification in animals using genomic data. The method reliably determines sex, even with low-quality sequencing data, aiding molecular ecology studies.

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Area of Science:

  • Molecular Ecology
  • Genomics
  • Bioinformatics

Background:

  • Sex identification is crucial in molecular ecology, but challenging in species lacking distinct phenotypes or when using non-invasive methods.
  • DNA analysis offers a valuable tool for sex determination and validation, especially when phenotypic traits are ambiguous.
  • Existing methods may struggle with varying data quality and non-invasive sampling.

Purpose of the Study:

  • To develop a robust bioinformatic framework for sex assignment using genomic data (GBS).
  • To create novel indexes based on mammalian sex chromosome properties for accurate sex determination.
  • To assess the framework's reliability across different sequencing coverage depths.

Main Methods:

  • Developed a bioinformatic framework utilizing two ad hoc indexes based on heteromorphic sex chromosome properties.
  • Mapped RAD-seq loci to a closely related, chromosome-level reference genome.
  • Analyzed missingness and coverage depth of autosomes and sex chromosomes (X and Y) for each individual.
  • Evaluated index accuracy with varying average coverage depths.

Main Results:

  • Successfully determined the sex of 165 phenotypically sexed fur seals and 40 non-invasively sampled sea lions.
  • Index Y demonstrated superior reliability and robustness for sex assignment in individuals with low-depth coverage.
  • The framework proved effective across a range of GBS sequencing data qualities.

Conclusions:

  • The developed bioinformatic framework provides a reliable method for sex identification using genomic data.
  • The approach is adaptable to various animal taxa with known heteromorphic sex chromosome systems (XY/ZW).
  • This method enhances the utility of GBS data for sex determination in molecular ecology research, even with suboptimal data quality.