Comparison of QTLs for rice seedling morphology under different water supply conditions

Pinpointing genomic regions associated with root system architecture in rice through an integrative meta-analysis approach

Applying an integrated meta-analysis approach led to identification of meta-QTLs/ candidate genes associated with rice root system architecture, which can be used in MQTL-assisted breeding/ genetic engineering of root traits. Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA-related MQTLs were detected and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance-associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA), and lignification (e.g. C4H, PAL, PRX and CAD). The genes located within both the SNP peak positions and the QTL-overview peaks for RSA are suggested as novel candidate genes for further functional analysis. The promising candidate genes and MQTLs can be used as basis for genetic engineering and MQTL-assisted breeding of root phenotypes to improve yield potential, stability and performance in a water-stressed environment.

Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.)

Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.

Dynamics of cell wall structure and related genomic resources for drought tolerance in rice

Cell wall plasticity plays a very crucial role in vegetative and reproductive development of rice under drought and is a highly potential trait for improving rice yield under drought. Drought is a major constraint in rice (Oryza sativa L.) cultivation severely affecting all developmental stages, with the reproductive stage being the most sensitive. Rice plants employ multiple strategies to cope with drought, in which modification in cell wall dynamics plays a crucial role. Over the years, significant progress has been made in discovering the cell wall-specific genomic resources related to drought tolerance at vegetative and reproductive stages of rice. However, questions remain about how the drought-induced changes in cell wall made by these genomic resources potentially influence the vegetative and reproductive development of rice. The possibly major candidate genes underlying the function of quantitative trait loci directly or indirectly associated with the cell wall plasticization-mediated drought tolerance of rice might have a huge promise in dissecting the putative genomic regions associated with cell wall plasticity under drought. Furthermore, engineering the drought tolerance of rice using cell wall-related genes from resurrection plants may have huge prospects for rice yield improvement. Here, we review the comprehensive multidisciplinary analyses to unravel different components and mechanisms involved in drought-induced cell wall plasticity at vegetative and reproductive stages that could be targeted for improving rice yield under drought.

Integration of Phenotype and Hormone Data during Adventitious Rooting in Carnation (Dianthus caryophyllus L.) Stem Cuttings

The rooting of stem cuttings is a highly efficient procedure for the vegetative propagation of ornamental plants. In cultivated carnations, an increased auxin level in the stem cutting base produced by active auxin transport from the leaves triggers adventitious root (AR) formation from the cambium. To provide additional insight into the physiological and genetic basis of this complex trait, we studied AR formation in a collection of 159 F1 lines derived from a cross between two hybrid cultivars (2003 R 8 and 2101-02 MFR) showing contrasting rooting performances. In three different experiments, time-series for several stem and root architectural traits were quantified in detail in a subset of these double-cross hybrid lines displaying extreme rooting phenotypes and their parental genotypes. Our results indicate that the water content and area of the AR system directly contributed to the shoot water content and shoot growth. Moreover, morphometric data and rooting quality parameters were found to be associated with some stress-related metabolites such as 1-aminocyclopropane-1-carboxylic acid (ACC), the ethylene precursor, and the conjugated auxin indol-3-acetic acid-aspartic acid (IAA-Asp).