PMSeeker: A Scheme Based on the Greedy Algorithm and the Exhaustive Algorithm to Screen Low-Redundancy Marker Sets...

Area of Science:

• Genetics
• Aquaculture
• Bioinformatics

Background:

• Parentage assignment is crucial for commercial fish farming, requiring extensive genetic data.
• Accurate parentage assignment relies on comprehensive genotypes within a parentage marker set (PMS).
• Reducing the number of markers in a PMS can significantly decrease experimental costs.

Purpose of the Study:

• To establish an efficient scheme for screening low-redundancy parentage marker sets (PMSs).
• To reduce the number of genetic markers required for accurate parentage assignment.
• To conserve resources and facilitate the implementation of parentage assignment in economic species breeding.

Main Methods:

• Utilized exhaustive and greedy algorithms to screen for low-redundancy PMSs.
• Employed a novel metric, the parental dispersity index (PDI), for marker selection.
• Validated the scheme through random sample experiments across three distinct groups.

Main Results:

• Developed a scheme to screen for PMSs with reduced marker redundancy.
• The greedy algorithm, using PDI, proved effective in marker selection.
• Achieved over 99.7% accuracy in solvable cases using the developed non-redundant PMSs.
• Demonstrated that low-redundancy PMSs can be composed from multiple non-redundant sets.

Conclusions:

• The proposed scheme effectively reduces the number of markers needed for parentage assignment.
• This approach conserves human and experimental resources.
• Lays the foundation for broader application of parentage assignment technology in aquaculture breeding programs.