Skip to content
naulon
Not checkedNot checked for notices yet.

PolyReco: A Method to Automatically Label Collinear Regions and Recognize Polyploidy Events Based on the KS Dotplot

Fushun Wang, Fushun Wang, Kang Zhang and 8 more

Frontiers in Genetics · 2022

doi:10.3389/fgene.2022.842387 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Polyploidization plays a critical role in producing new gene functions and promoting species evolution. Effective identification of polyploid types can be helpful in exploring the evolutionary mechanism. However, current methods for detecting polyploid types have some major limitations, such as being time-consuming and strong subjectivity, etc. In order to objectively and scientifically recognize collinearity fragments and polyploid types, we developed PolyReco method, which can automatically label collinear regions and recognize polyploidy events based on the KS dotplot. Combining with whole-genome collinearity analysis, PolyReco uses DBSCAN clustering method to cluster KS dots. According to the distance information in the x-axis and y-axis directions between the categories, the clustering results are merged based on certain rules to obtain the collinear regions, automatically recognize and label collinear fragments. According to the information of the labeled collinear regions on the y-axis, the polyploidization recognition algorithm is used to exhaustively combine and obtain the genetic collinearity evaluation index of each combination, and then draw the genetic collinearity evaluation index graph. Based on the inflection point on the graph, polyploid types and related chromosomes with polyploidy signal can be detected. The validation experiments showed that the conclusions of PolyReco were consistent with the previous study, which verified the effectiveness of this method. It is expected that this approach can become a reference architecture for other polyploid types classification methods.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.