QTL underlying iron and zinc toxicity tolerances at seedling stage revealed by two sets of reciprocal introgression populations of rice ( Oryza sativa L.)

Liu, Huan; Soomro, Aijaz Ahmed; Yingguo, Zhu; Qiu, Xianjin; Chen, Kai; Zheng, Tianqing; Yang, Longwei; Xing, Danying; Xu, Jianlong

doi:10.1016/j.cj.2016.05.007

Cited by 18 publications

(17 citation statements)

References 40 publications

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“…qSdw11 affecting SDW on chromosome 11 colocated with qLBI11 which influences leaf bronzing index under ferrous iron stress toxicity condition [ 8 ]. qRdw3 and qRdw9 for RDW were colocated with qFRRDW3 and qFRRDW9–2 for FRRDW (Fe relative root dry weight), respectively [ 13 ]. qSwc11 affecting SWC colocated with qSWC for SWC [ 11 ].…”

Section: Discussionmentioning

confidence: 99%

“…Although many studies reported QTL for different traits associated to Fe or Zn toxicity at seedling stage in rice [ 9 , 13 , 17 , 18 ], no stable locus has been identified, fine-mapped or cloned so far [ 21 ]. The genetic mechanisms of rice tolerance to Fe and Zn toxicity seem to be complex.…”

Section: Discussionmentioning

confidence: 99%

“…Several genes responsible for the uptake, transport and accumulation of Fe and Zn have been identified in rice, which belong to five known protein families ( OsNRAMPs , OsFROs , OsZIPs , OsFERs and OsYSLs ) [ 12 ]. Many QTL for Fe or Zn toxicity tolerance in rice have been identified and mapped using DNA molecular markers in the populations derived from two parents [ 8 , 9 , 13 – 17 ]. These QTL are associated with some easily measurable traits like leaf bronzing index, shoot height, root length, shoot and root dry weight, tiller number under toxicity stress, because physiological process traits are difficult to measure and map at the whole population level [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

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QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

et al. 2017

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BackgroundFerrous iron (Fe) and zinc (Zn) at high concentration in the soil cause heavy metal toxicity and greatly affect rice yield and quality. To improve rice production, understanding the genetic and molecular resistance mechanisms to excess Fe and Zn in rice is essential. Genome-wide association study (GWAS) is an effective way to identify loci and favorable alleles governing Fe and Zn toxicty as well as dissect the genetic relationship between them in a genetically diverse population.ResultsA total of 29 and 31 putative QTL affecting shoot height (SH), root length (RL), shoot fresh weight (SFW), shoot dry weight (SDW), root dry weight (RDW), shoot water content (SWC) and shoot ion concentrations (SFe or SZn) were identified at seedling stage in Fe and Zn experiments, respectively. Five toxicity tolerance QTL (qSdw3a, qSdw3b, qSdw12 and qSFe5 / qSZn5) were detected in the same genomic regions under the two stress conditions and 22 candidate genes for 10 important QTL regions were also determined by haplotype analyses.ConclusionRice plants share partial genetic overlaps of Fe and Zn toxicity tolerance at seedling stage. Candidate genes putatively affecting Fe and Zn toxicity tolerance identified in this study provide valuable information for future functional characterization and improvement of rice tolerance to Fe and Zn toxicity by marker-assisted selection or designed QTL pyramiding.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4221-5) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

et al. 2017

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“…A number of studies have reported QTL for tolerance to a variety of metal. With regards to Fe toxicity in rice, a total of 197 QTL have been reported (Wu et al, 1997 , 1998 , 2014 ; Wan J. L. et al, 2003a ; Wan J. M. et al, 2003b ; Wan et al, 2005 ; Shimizu et al, 2005 ; Ouyang et al, 2007 ; Dufey et al, 2009 , 2012 , 2015 ; Fukuda et al, 2012 ; Zhang et al, 2013 ; Zhao et al, 2013 ; Matthus et al, 2015 ; Ruengphayak et al, 2015 ; Liu et al, 2016 ). A total of four chromosomal regions (CR), including CR1 on chromosome 1 between markers RM246 and RM443; CR2 on chromosome 2 between markers RM526 and R758; CR3 on chromosome 3 between markers C515 and C25; and CR4 on chromosome 7 between markers R1245 and RM429, have been found to be involved in the resistance of rice to Fe toxicity (Dufey et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Association Mapping of Ferrous, Zinc, and Aluminum Tolerance at the Seedling Stage in Indica Rice using MAGIC Populations

et al. 2017

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Excessive amounts of metal are toxic and severely affect plant growth and development. Understanding the genetic control of metal tolerance is crucial to improve rice resistance to Fe, Zn, and Al toxicity. The multi-parent advanced generation inter-cross (MAGIC) populations were genotyped using a 55 K rice SNP array and screened at the seedling stage for Fe, Zn, and Al toxicity using a hydroponics system. Association analysis was conducted by implementing a mixed linear model (MLM) for each of the five MAGIC populations double cross DC1 (founders were SAGC-08, HHZ5-SAL9-Y3-Y1, BP1976B-2-3-7-TB-1-1, PR33282-B-8-1-1-1-1-1), double cross DC2 (founders of double cross were FFZ1, CT 16658-5-2-2SR-2-3-6MP, IR 68, IR 02A127), eight parents population 8way (founders were SAGC-08, HHZ5-SAL9-Y3-Y1, BP1976B-2-3-7-TB-1-1, PR33282-B-8-1-1-1-1-1, FFZ1, CT 16658-5-2-2SR-2-3-6MP, IR 68, IR 02A127), DC12 (DC1+DC2) and rice multi-parent recombinant inbred line population RMPRIL (DC1+DC2+8way). A total of 21, 30, and 21 QTL were identified for Fe, Zn, and Al toxicity tolerance, respectively. For multi tolerance (MT) as Fe, Zn, and Al tolerance-related traits, three genomic regions, MT1.1 (chr.1: 35.4–36.3 Mb), MT1.2 (chr.1: 35.4–36.3 Mb), and MT3.2 (chr.3: 35.4-36.2 Mb) harbored QTL. The chromosomal regions MT2.1 (chr.2: 2.4–2.8 Mb), MT2.2 (chr.2: 24.5–25.8 Mb), MT4 (chr.4: 1.2 Mb Mb), MT8.1 (chr.8: 0.7–0.9 Mb), and MT8.2 (chr.8: 2.2–2.4 Mb) harbored QTL for Fe and Zn tolerance, while MT2.3 (chr.2: 30.5–31.6 Mb), MT3.1 (chr.3: 12.5–12.8 Mb), and MT6 (chr.6: 2.0–3.0 Mb) possessed QTL for Al and Zn tolerance. The chromosomal region MT9.1 (chr.9: 14.2–14.7 Mb) possessed QTL for Fe and Al tolerance. A total of 11 QTL were detected across different MAGIC populations and 12 clustered regions were detected under different metal conditions, suggesting that these genomic regions might constitute valuable regions for further marker-assisted selection (MAS) in breeding programs.

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“…There is a need to exploit genetic variability available among the different accessions. Recently, a unique QTL, qFRSDW11 associated with Iron and zinc toxicity tolerance was identified [78]. Therefore, pyramiding of genes/QTLs from different sources could result in higher level of tolerance in new varieties.…”

Section: Methods Of Developmentmentioning

confidence: 99%

Effect of Climate Change on Rice

Dabi¹,

Khanna²

2018

Agrotechnology

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Climate change has evolved from a subject of future speculation to an inconvenient reality of the present. Given the inseparable link of agriculture with climatic variables, impact of climate change on agriculture and food security has been at the forefront of the research and policy agenda in recent times. Climatic alteration in India is becoming fairly perceptible, and the changes are far more evident than in other parts of the country. As a result of climate change, extreme abiotic factors like high and low temperatures, droughts, salinity, osmotic stress, heavy rains, floods and frost damages are posing serious threats to rice production and also are detrimental for the farmers earning livelihood from rice cultivation. There is a dire need to frame strategies against these stresses, so that in order to cope with such impacts crop improvement will help in finding the sustainable and effective solution against the negative impact of climate change. Advancement in Molecular breeding will help in utilizing the inherent potential of wild species by generating abiotic tolerant lines through introgression. Large screening of tolerance in wild genotypes should be done with the help of molecular markers to identify the underlying QTLs/genes. With the development in the field of bioinformatics, DNA microarrays, mass spectrometry, RNA-Sequencing or other modern high-throughput genomic techniques, it is now feasible to decipher the underlying metabolic pathways through top down approach. The present paper provides an overview of the recent evidences, potential impacts of climate change on rice and also offers its mitigation strategy through crop improvement with special reference to northeast India.

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QTL underlying iron and zinc toxicity tolerances at seedling stage revealed by two sets of reciprocal introgression populations of rice ( Oryza sativa L.)

Cited by 18 publications

References 40 publications

QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study

Association Mapping of Ferrous, Zinc, and Aluminum Tolerance at the Seedling Stage in Indica Rice using MAGIC Populations

Effect of Climate Change on Rice

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