Mapping Covariation Quantitative Trait Loci That Control Organ Growth and Whole-Plant Biomass

Abstract

Covariation between organ growth and biomass accumulation plays an important role in plants. Plant to capture optimal fitness in nature, which depend coordinate and interact for distinct organs such as leaves, stems, and roots. Although many studies have focused on plant growth or biomass allocation, detailed information on the genetic mechanism of coordinated variation is lacking. Here, we expand a new mapping model based on functional mapping to detect covariation quantitative trait loci (QTLs) that govern development of plant organs and whole biomass, which, via a series of hypothesis tests, allows quantification of how QTLs regulate covariation between organ growth and biomass accumulation. The model was implemented to analyze leaf number data and the whole dry weight of recombinant inbred lines (RILs) of Arabidopsis . Two key QTLs related to growth and biomass allocation that reside within biologically meaningful genes, CRA1 and HIPP25 , are characterized. These two genes may control covariation between two traits. The new model will enable the elucidation of the genetic architecture underlying growth and biomass accumulation, which may enhance our understanding of fitness development in plants.

A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth of Catalpa bungei

“…The genetic basis of coordinated growth and trade-off strategies among growth traits have since attracted great interest among biologists. However, the conventional QTL mapping method focusing on genetic variation at a single trait may fail to reveal the genetic architecture underlying trait-trait balanced growth ( Gan et al, 2019 ; Zhang et al, 2020b ). Currently, there are two statistical approaches for QTL mapping, namely the mixture model for sparse molecular markers and the multiplicative model for dense markers.…”

“…The binary covariate genetic mapping analysis model was used to genetically analyse the unequal growth relationships between organs and phenotypes, in an attempt to better interpret the biological significance of cov QTLs ( Gan et al, 2019 ). Various members in these gene families were involved in plant development, carboxylic acid metabolism, cell division and substance transportation.…”

“…Utilising a dynamic allometric QTL mapping model, Li et al (2007) further analysed the genetic mechanism of ontogenetic C allocation in soybean RIL populations. Based on the statistical and/or dynamic models, the QTLs related to biomass distribution and balanced growth between plant organs or traits were subsequently identified for the aboveground-underground growth of Populus euphratica ( Zhang et al, 2017 ), leaf number and whole dry weight of Arabidopsis ( Gan et al, 2019 ) as well as for the leaf area-leaf dry weight of common bean ( Zhang et al, 2020b ). Despite these advances, genetic analyses of C allocation have focused mainly on annual herbs and crops.…”

Functional Mapping of Phenotypic Plasticity of Staphylococcus aureus Under Vancomycin Pressure

“…The majority of phenotypic plasticity studies using the GWAS method so far have modeled static phenotypic data measured at a single point in time ( Gan et al, 2019 ). Phenotypes are developmental and changes over time; however, GWAS can only be used to identify phenotypic correlations at a specific time and quantitative trait locus (QTL), without considering dynamic phenotypic development information ( Wang et al, 2014 ; Jiang et al, 2019 ).…”

DataSheet1.docx

“…The binary covariate genetic mapping analysis model was used to genetically analyse the unequal growth relationships between organs and phenotypes, in an attempt to better interpret the biological significance of covQTLs (Gan et al, 2019). Various members in these gene families were involved in plant development, carboxylic acid metabolism, cell division and substance transportation.…”