Traits-related QTLs and genes and their potential applications in rice improvement under low phosphorus condition

<p>The genetic improvement of rice over past decades has led to the loss of several genes which are responsible for nutrient acquisition and soil-related stresses. Phosphorus (P) is a non-renewable resource and inevitable element of metabolic functions in plants. By pedogenesis process, organic matter contributes to renewing soil P in lesser extent. Therefore, improvement of the P use efficiency is one of the most imperative traits in rice breeding program, which is governed by quantitative trait loci (QTLs). QTLs controlling low P associated morphological and physiological traits in rice were investigated mostly during last one and half decade by using diverse mapping populations. Comprehensive and meticulous survey from literature, we found that to date 133 P associated QTLs of morpho-physiological traits were reported to be distributed on twelve chromosomes and majority of these QTLs localized on chromosome 1, 2 and 12. For the first time, a complete figure is presented in this review on chromosome wise with respective QTLs associated with low P for easy understanding and selecting markers for future prospect. Further, it is necessary to understand the molecular mechanisms and regulation of genes and traits associated with low P to develop tolerant rice cultivars using functional marker-assisted selection.</p

Population structure group of accessions based on inferred ancestry values.

<p>Population structure group of accessions based on inferred ancestry values.</p

Quantile-Quantile (QQ) plot and distribution of marker-trait association from MLM analysis.

<p>Quantile-Quantile (QQ) plot and distribution of marker-trait association from MLM analysis.</p

Details of SSR loci used for genotyping a set of 60 rice genotypes and their genetic diversity parameters.

<p>Details of SSR loci used for genotyping a set of 60 rice genotypes and their genetic diversity parameters.</p

Association of marker alleles with phenotypic traits under high temperature stress using GLM and MLM analysis in 60 rice genotypes.

<p>Association of marker alleles with phenotypic traits under high temperature stress using GLM and MLM analysis in 60 rice genotypes.</p

Information on the selected linked molecular markers used for high temperature stress tolerance.

<p>Information on the selected linked molecular markers used for high temperature stress tolerance.</p

Population structure of a panel of 60 landraces and breeding lines arranged based on inferred ancestry.

<p>The membership fractions, the genotypes with the probability of ≥ 80% were assigned to corresponding subgroups with others categorized as admixture.</p

Population Structure, Genetic Diversity and Molecular Marker-Trait Association Analysis for High Temperature Stress Tolerance in Rice

<div><p>Rice exhibits enormous genetic diversity, population structure and molecular marker-traits associated with abiotic stress tolerance to high temperature stress. A set of breeding lines and landraces representing 240 germplasm lines were studied. Based on spikelet fertility percent under high temperature, tolerant genotypes were broadly classified into four classes. Genetic diversity indicated a moderate level of genetic base of the population for the trait studied. Wright’s F statistic estimates showed a deviation of Hardy-Weinberg expectation in the population. The analysis of molecular variance revealed 25 percent variation between population, 61 percent among individuals and 14 percent within individuals in the set. The STRUCTURE analysis categorized the entire population into three sub-populations and suggested that most of the landraces in each sub-population had a common primary ancestor with few admix individuals. The composition of materials in the panel showed the presence of many QTLs representing the entire genome for the expression of tolerance. The strongly associated marker RM547 tagged with spikelet fertility under stress and the markers like RM228, RM205, RM247, RM242, INDEL3 and RM314 indirectly controlling the high temperature stress tolerance were detected through both mixed linear model and general linear model TASSEL analysis. These markers can be deployed as a resource for marker-assisted breeding program of high temperature stress tolerance.</p></div

AMOVA between sub-populations and germplasm lines and fixation indices (GenAlEx 6.5 software).

<p>AMOVA between sub-populations and germplasm lines and fixation indices (GenAlEx 6.5 software).</p

Environmental settings for high temperature treatment in the indoor growth chamber.

<p>Environmental settings for high temperature treatment in the indoor growth chamber.</p