STATISTICAL COMPARISONS OF CHROMOSOMAL SHAPE POPULATIONS.

Area of Science:

• Genomics
• Statistical Genetics
• Computational Biology

Background:

• Chromosome structure is crucial for genome stability and function.
• Gene knockouts (KO) can alter chromosome organization.
• Quantifying these alterations requires advanced statistical methods.

Purpose of the Study:

• To develop and apply statistical tools for detecting shape differences in chromosomes.
• To compare chromosomes from RIF1 gene KO (RKO) and RAD21 gene KO (CKO) with wild type (WT).
• To identify specific chromosomal regions affected by these gene KOs.

Main Methods:

• Utilized a two-sample test for comparing chromosome shapes.
• Employed elastic shape metrics for 3D curve analysis.
• Performed shape comparisons at two levels: coarse (whole/large parts) and fine (TAD-based segments).

Main Results:

• Statistically significant shape differences were observed between KO and WT chromosomes.
• Differences were detected at both coarse and fine shape analysis levels.
• The framework successfully highlighted localized regions of significant shape alteration.

Conclusions:

• The developed statistical framework effectively identifies chromosome shape changes due to gene KOs.
• RIF1 and RAD21 gene knockouts induce distinct and detectable alterations in chromosome structure.
• This approach provides insights into the functional impact of specific gene disruptions on chromosome organization.