A general statistical framework for dissecting parent-of-origin effects underlying endosperm traits in flowering plants

TL;DR

This paper introduces a comprehensive statistical framework for identifying imprinted genes affecting endosperm traits in flowering plants, addressing a key challenge in understanding seed development and crop improvement.

Contribution

It develops a novel variance components method utilizing sex-specific allelic sharing to map imprinted QTLs in triploid endosperm, including extensions for multiple loci and maternal effects.

Findings

Method shows high power in simulations

Effective in real data analysis

Accounts for maternal cytoplasmic effects

Abstract

Genomic imprinting has been thought to play an important role in seed development in flowering plants. Seed in a flowering plant normally contains diploid embryo and triploid endosperm. Empirical studies have shown that some economically important endosperm traits are genetically controlled by imprinted genes. However, the exact number and location of the imprinted genes are largely unknown due to the lack of efficient statistical mapping methods. Here we propose a general statistical variance components framework by utilizing the natural information of sex-specific allelic sharing among sibpairs in line crosses, to map imprinted quantitative trait loci (iQTL) underlying endosperm traits. We propose a new variance components partition method considering the unique characteristic of the triploid endosperm genome, and develop a restricted maximum likelihood estimation method in an interval scan for estimating and testing genome-wide iQTL effects. Cytoplasmic maternal effect which is thought to have primary influences on yield and grain quality is also considered when testing for genomic imprinting. Extension to multiple iQTL analysis is proposed. Asymptotic distribution of the likelihood ratio test for testing the variance components under irregular conditions are studied. Both simulation study and real data analysis indicate good performance and powerfulness of the developed approach.