Genealogical and evolutionary inference with the human Y chromosome

Area of Science:

• Population genetics
• Human evolutionary studies
• Genetic genealogy

Background:

• Y-chromosome DNA variation is crucial for understanding human history.
• Current data analysis methods for Y-chromosome genealogical inference face ambiguities and inaccuracies.
• Advancements in the field are hindered by analytical challenges.

Purpose of the Study:

• To review and compare methods for genealogical inference using Y-chromosome data.
• To highlight the strengths and weaknesses of model-based and model-free approaches.
• To discuss the impact of mutation processes on genealogical inference accuracy.

Main Methods:

• Review of existing Y-chromosome data analysis methodologies.
• Categorization of approaches into model-based and model-free.
• Coalescent simulations to assess genealogical inference accuracy with modified mutation models.

Main Results:

• Model-based and model-free approaches have distinct biases and limitations.
• Generalizations of mutation processes significantly improve microsatellite locus genealogical inference.
• Both analytical approaches are valuable for robust genealogical inference.

Conclusions:

• Continued use of both model-based and model-free methods is beneficial for Y-chromosome genealogical inference.
• Addressing mutation process complexities enhances analytical accuracy.
• Improved analytical strategies are key to advancing population genetics and human history research.