Developing a deep root system is an important strategy for avoiding drought stress in rice. Using the 'basket' method, the ratio of deep rooting (RDR; the proportion of total roots that elongated ...through the basket bottom) was calculated to evaluate deep rooting. A new major quantitative trait locus (QTL) controlling RDR was detected on chromosome 9 by using 117 recombinant inbred lines (RILs) derived from a cross between the lowland cultivar IR64, with shallow rooting, and the upland cultivar Kinandang Patong (KP), with deep rooting. This QTL explained 66.6% of the total phenotypic variance in RDR in the RILs. A BC 2 F 3 line homozygous for the KP allele of the QTL had an RDR of 40.4%, compared with 2.6% for the homozygous IR64 allele. Fine mapping of this QTL was undertaken using eight BC 2 F 3 recombinant lines. The RDR QTL Dro1 (Deeper rooting 1) was mapped between the markers RM24393 and RM7424, which delimit a 608.4 kb interval in the reference cultivar Nipponbare. To clarify the influence of Dro1 in an upland field, the root distribution in different soil layers was quantified by means of core sampling. A line homozygous for the KP allele of Dro1 (Dro1-KP) and IR64 did not differ in root dry weight in the shallow soil layers (0–25 cm), but root dry weight of Dro1-KP in deep soil layers (25–50 cm) was significantly greater than that of IR64, suggesting that Dro1 plays a crucial role in increased deep rooting under upland field conditions.
Heading date, a crucial factor determining regional and seasonal adaptation in rice (Oryza sativa L.), has been a major selection target in breeding programs. Although considerable progress has been ...made in our understanding of the molecular regulation of heading date in rice during last two decades, the previously isolated genes and identified quantitative trait loci (QTLs) cannot fully explain the natural variation for heading date in diverse rice accessions.
To genetically dissect naturally occurring variation in rice heading date, we collected QTLs in advanced-backcross populations derived from multiple crosses of the japonica rice accession Koshihikari (as a common parental line) with 11 diverse rice accessions (5 indica, 3 aus, and 3 japonica) that originate from various regions of Asia. QTL analyses of over 14,000 backcrossed individuals revealed 255 QTLs distributed widely across the rice genome. Among the detected QTLs, 128 QTLs corresponded to genomic positions of heading date genes identified by previous studies, such as Hd1, Hd6, Hd3a, Ghd7, DTH8, and RFT1. The other 127 QTLs were detected in different chromosomal regions than heading date genes.
Our results indicate that advanced-backcross progeny allowed us to detect and confirm QTLs with relatively small additive effects, and the natural variation in rice heading date could result from combinations of large- and small-effect QTLs. We also found differences in the genetic architecture of heading date (flowering time) among maize, Arabidopsis, and rice.
One way to use a crop germplasm collection directly to map QTLs without using line-crossing experiments is the whole genome association mapping. A major problem with association mapping is the ...presence of population structure, which can lead to both false positives and failure to detect genuine associations (i.e., false negatives). Particularly in highly selfing species such as Asian cultivated rice, high levels of population structure are expected and therefore the efficiency of association mapping remains almost unknown. Here, we propose an approach that combines a Bayesian method for mapping multiple QTLs with a regression method that directly incorporates estimates of population structure. That is, the effects due to both multiple QTLs and population structure were included in our statistical model. We evaluated the efficiency of our approach in simulated- and real-trait analyses of a rice germplasm collection. Simulation analyses based on real marker data showed that our model could suppress both false-positive and false-negative rates and the error of estimation of genetic effects over single QTL models, indicating that our model has statistically desirable attributes over single QTL models. As real traits, we analyzed the size and shape of milled rice grains and found significant markers that may be linked to QTLs reported previously. Association mapping should have good prospects in highly selfing species such as rice if proper methods are adopted. Our approach will be useful for the whole genome association mapping of various selfing crop species.
Root system architecture (RSA) determines unevenly distributed water and nutrient availability in soil. Genetic improvement of RSA, therefore, is related to crop production. However, RSA phenotyping ...has been carried out less frequently than above-ground phenotyping because measuring roots in the soil is difficult and labor intensive. Recent advancements have led to the digitalization of plant measurements; this digital phenotyping has been widely used for measurements of both above-ground and RSA traits. Digital phenotyping for RSA is slower and more difficult than for above-ground traits because the roots are hidden underground. In this review, we summarized recent trends in digital phenotyping for RSA traits. We classified the sample types into three categories: soil block containing roots, section of soil block, and root sample. Examples of the use of digital phenotyping are presented for each category. We also discussed room for improvement in digital phenotyping in each category.
roots of future rice harvests Ahmadi, Nourollah; Audebert, Alain; Bennett, Malcolm J ...
Rice (New York, N.Y.),
2014/12, Letnik:
7, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Rice production faces the challenge to be enhanced by 50% by year 2030 to meet the growth of the population in rice-eating countries. Whereas yield of cereal crops tend to reach plateaus and a yield ...is likely to be deeply affected by climate instability and resource scarcity in the coming decades, building rice cultivars harboring root systems that can maintain performance by capturing water and nutrient resources unevenly distributed is a major breeding target. Taking advantage of gathering a community of rice root biologists in a Global Rice Science Partnership workshop held in Montpellier, France, we present here the recent progresses accomplished in this area and focal points where an international network of laboratories should direct their efforts.
Abstract Background and Aims Root system architecture (RSA) plays a key role in plant adaptation to drought because deep rooting enables better water uptake than shallow rooting under terminal ...drought. Understanding RSA during early plant development is essential for improving crop yields, as early drought can affect subsequent shoot growth. Herein, we demonstrate that root distribution in the topsoil significantly impacts shoot growth during the early stages of rice (Oryza sativa) development under drought, as assessed through three-dimensional (3D) image analysis. Methods We used 109 F12 recombinant inbred lines (RILs) obtained from a cross between shallow-rooting lowland rice and deep-rooting upland rice, representing a population with diverse RSA. We applied a moderate drought during the early development of rice grown in a plant pot (25 cm height) by stopping irrigation 14 days after sowing (DAS). Time-series RSA at 14, 21, and 28 DAS was visualized by X-ray computed tomography, and subsequently compared between drought and well-watered conditions. Following this analysis, we further investigated drought-avoidant RSA by testing 20 randomly selected RILs under drought conditions. Key Results We inferred the root location that most influences shoot growth using a hierarchical Bayes approach: the root segment depth, which positively impacted shoot growth, ranged between 1.7–3.4 cm under drought conditions and between 0.0–1.7 cm under well-watered conditions. Drought-avoidant RILs had a higher root density in the lower layers of the topsoil compared to the others. Conclusions Fine classification of soil layers using 3D image analysis revealed that increasing root density in the lower layers of the topsoil, rather than in the subsoil, is advantageous for drought avoidance during the early growth stage of rice.
Abstract
Field-grown rice plants are exposed to various stresses at different stages of their life cycle, but little is known about the effects of stage-specific stresses on phenomes and ...transcriptomes. In this study, we performed integrated time-course multiomics on rice at 3-d intervals from seedling to heading stage under six drought conditions in a well-controlled growth chamber. Drought stress at seedling and reproductive stages reduced yield performance by reducing seed number and setting rate, respectively. High temporal resolution analysis revealed that drought response occurred in two steps: a rapid response via the abscisic acid (ABA) signaling pathway and a slightly delayed DEHYDRATION-RESPONSIVE ELEMENT-BINDING PROTEIN (DREB) pathway, allowing plants to respond flexibly to deteriorating soil water conditions. Our long-term time-course multiomics showed that temporary drought stress delayed flowering due to prolonged expression of the flowering repressor gene GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (Ghd7) and delayed expression of the florigen genes HEADING DATE 3a (Hd3a) and RICE FLOWERING LOCUS T 1 (RFT1). Our life-cycle multiomics dataset on rice shoots under drought conditions provides a valuable resource for further functional genomic studies to improve crop resilience to drought stress.
Asian cultivated rice (Oryza sativa L.) has genetic diversification of root characteristics, but this variation has not been elucidated fully with reference to the genetic background. To clarify the ...differences in root anatomical and morphological traits among different varietal groups of cultivated rice, we analyzed four anatomical traits (root thickness, stele transversal area, total transversal area and number of late metaxylem vessels) and two morphological traits (root length index and ratio of deep rooting) in 59 accessions. A previous principal-coordinate analysis study using data on 179 restriction fragment length polymorphisms classified these accessions into three varietal groups: 13 japonica, 21 indica-I, and 25 indica-II. Based on a principal-components analysis of the six traits, the japonica group had wide variation in root anatomy compared to the two indica groups. In particular, japonica upland rice was characterized by a larger stele and xylem structures. By contrast, the two indica groups had wide variation in root morphology compared to the japonica group. Of the two indica groups, on average, the indica-I accessions had deeper, thicker roots than the indica-II accessions. Our results demonstrate that the japonica and indica groups contain different genetic diversity with respect to their root characteristics.
BACKGROUND: Root system architecture is an important trait affecting the uptake of nutrients and water by crops. Shallower root systems preferentially take up nutrients from the topsoil and help ...avoid unfavorable environments in deeper soil layers. We have found a soil-surface rooting mutant from an M₂ population that was regenerated from seed calli of a japonica rice cultivar, Nipponbare. In this study, we examined the genetic and physiological characteristics of this mutant. RESULTS: The primary roots of the mutant showed no gravitropic response from the seedling stage on, whereas the gravitropic response of the shoots was normal. Segregation analyses by using an F₂ population derived from a cross between the soil-surface rooting mutant and wild-type Nipponbare indicated that the trait was controlled by a single recessive gene, designated as sor1. Fine mapping by using an F₂ population derived from a cross between the mutant and an indica rice cultivar, Kasalath, revealed that sor1 was located within a 136-kb region between the simple sequence repeat markers RM16254 and 2935-6 on the terminal region of the short arm of chromosome 4, where 13 putative open reading frames (ORFs) were found. We sequenced these ORFs and detected a 33-bp deletion in one of them, Os04g0101800. Transgenic plants of the mutant transformed with the genomic fragment carrying the Os04g0101800 sequence from Nipponbare showed normal gravitropic responses and no soil-surface rooting. CONCLUSION: These results suggest that sor1, a rice mutant causing soil-surface rooting and altered root gravitropic response, is allelic to Os04g0101800, and that a 33-bp deletion in the coding region of this gene causes the mutant phenotypes.
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