Use of component analysis in QTL mapping of complex crop traits: a case study on yield in barley

Abstract

Genes contributing to the quantitative variation of a complex crop trait can be numerous. However, using existing approaches, the number of quantitative trait loci (QTL) detected for a trait is limited. Therefore, rather than looking for QTL for a complex trait itself, determining QTL for underlying component traits might give more information. In this study the potential of component analysis in QTL mapping of complex traits was examined using grain yield in spring barley as an example. Grain yield was divided into three components: number of spikes/m 2 , number of kernels/spike, and 1000-kernel weight. These traits were measured for individuals of a recombinant inbred-line population in field trials conducted over 2 years. By the use of an approximate multiple QTL model, one to eight QTL were detected for each trait in a year. Some QTL were mapped to similar positions in both years. Almost all QTL for yield were found at the position of or in close proximity to QTL for its component traits. A number of QTL for component traits were not detected when yield itself was subjected to QTL analysis. However, relative to the QTL for yield itself, all component-trait QTL did not explain the variation in yield better. The results in relation to the potential of using component analysis in studying complex crop traits are discussed.

Statistical analysis of wheat yield under drought conditions

“…A high correlation between PC1 and a variable indicates that the variable is associated with the direction of the maximum amount of variation in the data set. Similar results were reported by Yin et al (2002) who stated that the grain yield was divided into three components, namely number of spikes/m 2 , number of kernels/spike, and 1000-kernel weight.…”

Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit

“…Dividing a trait into multiple component traits unravels the underlying inherited complexity (Yin et al, 2002). We detected a higher number of genetic loci for root length classified on root thickness than for TRL across treatments (Supplemental Tables S3, S4, and S7).…”

Applying modelling experiences from the past to shape crop systems biology: the need to converge crop physiology and functional genomics

“… The correlations of three yield components (ears ha −1 , filled grains per ear, and filled‐grain weight) among barley recombinant inbred lines (based on the data of Yin et al ., 2002). …”

“…While the simple relationship outlined in Eqn 1 is very useful in identifying factors limiting yield formation, it is not Fig. 1 The correlations of three yield components (ears ha -1 , filled grains per ear, and filled-grain weight) among barley recombinant inbred lines (based on the data of Yin et al, 2002). sufficient to unravel the underlying physiology and feedback mechanisms of crop growth.…”