RUFUS

RUFUS detects de novo mobile element insertions (MEIs) from pedigree-based whole-genome sequencing (WGS) to estimate germline retrotransposition rates in humans.

Key Features:

• Targeted elements: Targets mobile element insertions (MEIs) arising from L1, Alu, and SVA retrotransposons.
• Input data: Processes pedigree-based whole-genome sequencing (WGS) data from multi-generation pedigrees.
• De novo detection: Identifies de novo MEIs across generations within pedigrees.
• Comparative use: Was used alongside MELT and TranSurVeyor for MEI detection in comparative analyses.
• Empirical discovery: Detected 26 novel MEI events in 437 births from 599 CEPH individuals spanning 33 three-generation pedigrees.
• Alu retrotransposition rate: Estimated an Alu rate of approximately one in 40 births, about half the rate predicted by phylogenetic analyses.
• L1 retrotransposition rate: Estimated an L1 rate of approximately one in 63 births, consistent with prior estimates of one in 20 to one in 200 births.
• SVA retrotransposition rate: Estimated an SVA rate of approximately one in 63 births, higher than an earlier estimate of one in 900 births.
• Parent-of-origin analysis: Revealed a statistically significant paternal bias for Alu retrotransposition, suggesting insertions predominantly occur during spermatogenesis or early embryonic development.

Scientific Applications:

• Germline mutation rate estimation: Estimating germline retrotransposition rates for human mobile elements such as L1, Alu, and SVA.
• Retrotransposon dynamics: Investigating activity and dynamics of active human retrotransposons within pedigrees.
• Parent-of-origin and timing analyses: Assessing parent-of-origin effects and timing of insertion events (spermatogenesis versus oogenesis/early embryogenesis).
• Comparative validation: Comparing empirical retrotransposition rate estimates against phylogenetic and previous population-based estimates.

Methodology:

Processes pedigree-based whole-genome sequencing (WGS) data from large multi-generation pedigrees to identify de novo MEIs across generations and was applied alongside MELT and TranSurVeyor in the analysis of 599 CEPH individuals across 33 three-generation pedigrees.