Transposable element polymorphisms improve prediction of complex agronomic traits in rice

Area of Science:

• Plant genetics
• Genomics
• Agricultural science

Background:

• Transposon insertion polymorphisms (TIPs) represent a key source of genetic variation in rice.
• Previous studies indicated TIPs' potential in identifying causative loci for agronomic traits.

Purpose of the Study:

• To quantify the genetic variance explained by TIPs versus single nucleotide polymorphisms (SNPs).
• To evaluate if TIPs improve genomic prediction of complex agronomic traits in rice.

Main Methods:

• Analysis of eleven agronomic traits across five rice population groups (738 accessions).
• Application of data split validation in within- and across-population scenarios.
• Comparison of prediction models including Bayes C and Bayesian reproducible kernel Hilbert space regression.

Main Results:

• TIPs explain a substantial fraction of total genetic variance in rice.
• TIPs improved genomic prediction accuracy, outperforming SNPs in nine of eleven traits in the across-population scenario.
• For traits like leaf senescence and grain width, TIPs increased predictive correlation by 30-50%.

Conclusions:

• TIP genotyping enhances prediction of complex agronomic traits in rice.
• The benefit of TIPs is most pronounced when predicting accessions distantly related to the training set.