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Genome-wide analysis of root hair-preferential genes in rice.

ABSTRACT: BACKGROUND:Root hairs are valuable in taking up nutrients and water from the rhizosphere and serving as sites of interactions with soil microorganisms. By increasing the external surface area of the roots or interacting with rhizobacteria, root hairs directly and indirectly promote plant growth and yield. Transcriptome data can be used to understand root-hair development in rice. RESULT:We performed Agilent 44 K microarray experiments with enriched root-hair samples and identified 409 root hair-preferential genes in rice. The expression patterns of six genes were confirmed using a GUS reporter system and quantitative RT-PCR analysis. Gene Ontology (GO) analysis demonstrated that 13 GO terms, including oxygen transport and cell wall generation, were highly over-represented in those genes. Although comparative analysis between rice and Arabidopsis revealed a large proportion of orthologous pairs, their spatial expression patterns were not conserved. To investigate the molecular network associated with root hair-preferential genes in rice, we analyzed the PPI network as well as coexpression data. Subsequently, we developed a refined network consisting of 24 interactions between 10 genes and 18 of their interactors. CONCLUSION:Identification of root hair-preferential genes and in depth analysis of those genes will be a useful reference to accelerate the understanding of root-hair development in rice.

SUBMITTER: Moon S

PROVIDER: S-EPMC6115326 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Genome-wide analysis of root hair-preferential genes in rice.

Moon Sunok S Chandran Anil Kumar Nalini AKN An Gynheung G Lee Chanhui C Jung Ki-Hong KH

Rice (New York, N.Y.) 20180829 1

<h4>Background</h4>Root hairs are valuable in taking up nutrients and water from the rhizosphere and serving as sites of interactions with soil microorganisms. By increasing the external surface area of the roots or interacting with rhizobacteria, root hairs directly and indirectly promote plant growth and yield. Transcriptome data can be used to understand root-hair development in rice.<h4>Result</h4>We performed Agilent 44 K microarray experiments with enriched root-hair samples and identified ...[more]

PMID: 30159808

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Project description:Root system architecture (RSA) is an important agronomic trait with vital roles in plant productivity under water stress conditions. A deep and branched root system may help plants to avoid water stress by enabling them to acquire more water and nutrient resources. Nevertheless, our knowledge of the genetics and molecular control mechanisms of RSA is still relatively limited. In this study, we analyzed the transcriptome response of root tips to water stress in two well-known genotypes of rice: IR64, a high-yielding lowland genotype, which represents a drought-susceptible and shallow-rooting genotype; and Azucena, a traditional, upland, drought-tolerant and deep-rooting genotype. We collected samples from three zones (Z) of root tip: two consecutive 5 mm sections (Z1 and Z2) and the following next 10 mm section (Z3), which mainly includes meristematic and maturation regions. Our results showed that Z1 of Azucena was enriched for genes involved in cell cycle and division and root growth and development whereas in IR64 root, responses to oxidative stress were strongly enriched. While the expansion of the lateral root system was used as a strategy by both genotypes when facing water shortage, it was more pronounced in Azucena. Our results also suggested that by enhancing meristematic cell wall thickening for insulation purposes as a means of confronting stress, the sensitive IR64 genotype may have reduced its capacity for root elongation to extract water from deeper layers of the soil. Furthermore, several members of gene families such as NAC, AP2/ERF, AUX/IAA, EXPANSIN, WRKY, and MYB emerged as main players in RSA and drought adaptation. We also found that HSP and HSF gene families participated in oxidative stress inhibition in IR64 root tip. Meta-quantitative trait loci (QTL) analysis revealed that 288 differentially expressed genes were colocalized with RSA QTLs previously reported under drought and normal conditions. This finding warrants further research into their possible roles in drought adaptation. Overall, our analyses presented several major molecular differences between Azucena and IR64, which may partly explain their differential root growth responses to water stress. It appears that Azucena avoided water stress through enhancing growth and root exploration to access water, whereas IR64 might mainly rely on cell insulation to maintain water and antioxidant system to withstand stress. We identified a large number of novel RSA and drought associated candidate genes, which should encourage further exploration of their potential to enhance drought adaptation in rice.

Project description:BackgroundClpB-cyt/HSP100 protein acts as chaperone, mediating disaggregation of denatured proteins. Previous studies have shown that ClpB-cyt/HSP100 gene belongs to the group class I Clp ATPase proteins and ClpB-cyt/HSP100 transcript is regulated by heat stress and developmental cues.ResultsNine ORFs were noted to constitute rice class I Clp ATPases in the following manner: 3 ClpB proteins (ClpB-cyt, Os05g44340; ClpB-m, Os02g08490; ClpB-c, Os03g31300), 4 ClpC proteins (ClpC1, Os04g32560; ClpC2, Os12g12580; ClpC3, Os11g16590; ClpC4, Os11g16770) and 2 ClpD proteins (ClpD1, Os02g32520; ClpD2, Os04g33210). Using the respective signal sequences cloned upstream to GFP/CFP reporter proteins and transient expression studies with onion epidermal cells, evidence is provided that rice ClpB-m and Clp-c proteins are indeed localized to their respective cell locations mitochondria and chloroplasts, respectively. Associated with their diverse cell locations, domain structures of OsClpB-c, OsClpB-m and OsClpB-cyt proteins are noted to possess a high-level conservation. OsClpB-cyt transcript is shown to be enriched at milk and dough stages of seed development. While expression of OsClpB-m was significantly less as compared to its cytoplasmic and chloroplastic counterparts in different tissues, this transcript showed highest heat-induced expression amongst the 3 ClpB proteins. OsClpC1 and OsClpC2 are predicted to be chloroplast-localized as is the case with all known plant ClpC proteins. However, the fact that OsClpC3 protein appears mitochondrial/chloroplastic with equal probability and OsClpC4 a plasma membrane protein reflects functional diversity of this class. Different class I Clp ATPase transcripts were noted to be cross-induced by a host of different abiotic stress conditions. Complementation assays of Deltahsp104 mutant yeast cells showed that OsClpB-cyt, OsClpB-m, OsClpC1 and OsClpD1 have significantly positive effects. Remarkably, OsClpD1 gene imparted appreciably high level tolerance to the mutant yeast cells.ConclusionsRice class I Clp ATPase gene family is constituted of 9 members. Of these 9, only 3 belonging to ClpB group are heat stress regulated. Distribution of ClpB proteins to different cell organelles indicates that their functioning might be critical in different cell locations. From the complementation assays, OsClpD1 appears to be more effective than OsClpB-cyt protein in rescuing the thermosensitive defect of the yeast ScDeltahsp104 mutant cells.

Project description:Root system architecture plays a crucial role in nutrient and water absorption during rice production. Genetic improvement of the rice root system requires elucidating its genetic control. Genome-wide association studies (GWASs) have identified genomic regions responsible for rice root phenotypes. However, candidate gene prioritization around the peak region often suffers from low statistical power and resolution. Transcriptomics enables other statistical mappings, such as transcriptome-wide association study (TWAS) and expression GWAS (eGWAS), which improve candidate gene identification by leveraging the natural variation of the expression profiles. To explore the genes responsible for root phenotypes, we conducted GWAS, TWAS, and eGWAS for 12 root phenotypes in 57 rice accessions using 427,751 single nucleotide polymorphisms (SNPs) and the expression profiles of 16,901 genes expressed in the roots. The GWAS identified three significant peaks, of which the most significant peak responsible for seven root phenotypes (crown root length, crown root surface area, number of crown root tips, lateral root length, lateral root surface area, lateral root volume, and number of lateral root tips) was detected at 6,199,732 bp on chromosome 8. In the most significant GWAS peak region, OsENT1 was prioritized as the most plausible candidate gene because its expression profile was strongly negatively correlated with the seven root phenotypes. In addition to OsENT1, OsEXPA31, OsSPL14, OsDEP1, and OsDEC1 were identified as candidate genes responsible for root phenotypes using TWAS. Furthermore, a cis-eGWAS peak SNP was detected for OsDjA6, which showed the eighth strongest association with lateral root volume in the TWAS. The cis-eGWAS peak SNP for OsDjA6 was in strong linkage disequilibrium (LD) with a GWAS peak SNP on the same chromosome for lateral root volume and in perfect LD with another SNP variant in a putative cis-element at the 518 bp upstream of the gene. These candidate genes provide new insights into the molecular breeding of root system architecture.

Dataset Information

Genome-wide analysis of root hair-preferential genes in rice.

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Genome-wide analysis of root hair-preferential genes in rice.

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