Please wait a minute...
Journal of Integrative Agriculture  2015, Vol. 14 Issue (7): 1261-1268    DOI: 10.1016/S2095-3119(14)60958-8
Crop Genetics · Breeding · Germplasm Resources Advanced Online Publication | Current Issue | Archive | Adv Search |
QTL analysis of leaf photosynthesis rate and related physiological traits in Brassica napus
 YAN Xing-ying, QU Cun-min, LI Jia-na, CHEN Li, LIU Lie-zhao
1、College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, P.R.China
2、Biotechnology Research Center, Southwest University, Chongqing 400715, P.R.China
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  Rapeseed (Brassica napus L.) oil is the crucial source of edible oil in China. In addition, it can become a major renewable and sustainable feedstock for biodiesel production in the future. It is known that photosynthesis products are the primary sources for dry matter accumulation in rapeseed. Therefore, increasing the photosynthetic efficiency is desirable for the raise of rapeseed yield. The objective of the present study was to identify the genetic mechanism of photosynthesis based on the description of relationships between different photosynthetic traits and their quantitative trait loci (QTL) by using a recombinant inbred line (RIL) population with 172 lines. Specifically, correlation analysis in this study showed that internal CO2 concentration has negative correlations with other three physiological traits under two different stages. Totally, 11 and 12 QTLs of the four physiological traits measured at the stages 1 and 2 were detected by using a high-density single nucleotidepolymorphism (SNP) markers linkage map with composite interval mapping (CIM), respectively. Three co-localized QTLs on A03 were detected at stage 1 with 5, 5, and 10% of the phenotypic variation, respectively. Other two co-localized QTLs were located on A05 at stage 2, which explained up to 12 and 5% of the phenotypic variation, respectively. The results are beneficial for our understanding of genetic control of photosynthetic physiological characterizations and improvement of rapeseed yield in the future.

Abstract  Rapeseed (Brassica napus L.) oil is the crucial source of edible oil in China. In addition, it can become a major renewable and sustainable feedstock for biodiesel production in the future. It is known that photosynthesis products are the primary sources for dry matter accumulation in rapeseed. Therefore, increasing the photosynthetic efficiency is desirable for the raise of rapeseed yield. The objective of the present study was to identify the genetic mechanism of photosynthesis based on the description of relationships between different photosynthetic traits and their quantitative trait loci (QTL) by using a recombinant inbred line (RIL) population with 172 lines. Specifically, correlation analysis in this study showed that internal CO2 concentration has negative correlations with other three physiological traits under two different stages. Totally, 11 and 12 QTLs of the four physiological traits measured at the stages 1 and 2 were detected by using a high-density single nucleotidepolymorphism (SNP) markers linkage map with composite interval mapping (CIM), respectively. Three co-localized QTLs on A03 were detected at stage 1 with 5, 5, and 10% of the phenotypic variation, respectively. Other two co-localized QTLs were located on A05 at stage 2, which explained up to 12 and 5% of the phenotypic variation, respectively. The results are beneficial for our understanding of genetic control of photosynthetic physiological characterizations and improvement of rapeseed yield in the future.
Keywords:  Brassica napus       photosynthesis       quantitative trait loci (QTL)  
Received: 27 August 2014   Accepted:
Fund: 

This research was supported by the National Natural Science Foundation of China (31171584, 31371655), National Basic Research Program of China (973 Program, 2015CB150201), the Fundamental Research Funds for the Central Universities, China (XDJK2013B015) and the Earmarked Fund for Modern Agro-industry Technology Research System, China (CARS-13).

Corresponding Authors:  LIU Lie-zhao, Tel: +86-23-68251383,E-mail: liezhao2003@126.com     E-mail:  liezhao2003@126.com

Cite this article: 

YAN Xing-ying, QU Cun-min, LI Jia-na, CHEN Li, LIU Lie-zhao. 2015. QTL analysis of leaf photosynthesis rate and related physiological traits in Brassica napus. Journal of Integrative Agriculture, 14(7): 1261-1268.

Basten C J, Weir B S, Zeng Z B. 1999. QTL Cartographer,Version 2.5: Programme in Statistical Genetics. NorthCarolina State University, Raleigh.Cao S Q, Zhai H Q, Yang T N, Zhang R X, Kuang T Y. 2001.Studies on photosynthetic rate and function duration of ricegermplasm. Chinese Journal of Rice Science, 15, 29-34 (in Chinese)

Chen W F, Xu Z J, Zhang B L, Yang S R. 1990. Comparativestudies on stomatal dendity and its relations to gas diffusionresistance and net photosynthetic rate in rice leaf. ChineseJournal of Rice Science, 4,163-168 (in Chinese)

Chen G Y, Chen J, Xu D Q. 2010. Thinking about relationshipbetween net photosynthesis rate and inter-cellular CO2concentration. Plant Physiology Communications, 46,64-66

Cui S Y, Yu D Y. 2007. QTL mapping of photosynthetic rate insoybean. Soybean Science, 26, 6-10 (in Chinese)

Czyczy?o-Mysza I, Marcińska I, Skrzypek E, Chrupek M,Grzesiak S, Hura T, Stoja?owski S, Mys´ków B, MilczarskiP,Quarrie S. 2011. Mapping QTLs for yield components andchlorophyll a fluorescence parameters in wheat underthree levels of water availability. Plant Genet Research,9, 291-295

Dellaporta S L, Wood J, Hicks J B. 1983. A plant DNA minipreparation: Version II. Plant Molecular Biology Report,1, 19-21

Fischer R A, Rees D, Sayre K D, Lu Z M, Condon A G, Saavedra A L. 1998. Wheat yield progress associated with higherstomatal conductance and photosynthetic rate and coolercanopies. Crop Science, 38, 1467-1475

Herve D, Fabre F, Berrios E F, Leroux N, Chaarani G A,Planchon C, Sarrafi A, Gentzbittel L. 2001. QTL analysisof photosynthesis and water status traits in sunflower(Helianthus annuus L.) under greenhouse conditions.Journal of Experimental Botany, 52, 1857-1864

Hu M L, Zhang Y X, Kong L N, Yang Q H, Wang C M, Zhai H Q,Wan J M. 2007. Quantitative trait locus for photosynthesisand its related physiological traits in rice (Oryza sativa L).Acta Agronomica Sinica, 33, 183-188(in Chinese)

Hu X Y, Mandy S G, Gupta M, Thompson S. 2006. Mappingof the loci controlling oleic and linolenic acid contentsand development of fad2 and fad3 allele-specific markersin canola (Brassica napus L.). Theoretical and AppliedGenetics, 113, 497-507

Hua W, Li R J, Zhan G M, Liu J, Li J, Wang X F, Liu G H, WangH Z. 2012. Maternal control of seed oil content in Brassicanapus: The role of silique wall photosynthesis. Plant Journal,69, 432- 444.

Jian H J, Wei L J, Li J N, Xu X F, Chen L, Liu L Z. 2014a.Quantitative traits loci analysis of seed glucosinolate contentin Brassica napus using high-density SNP map. ActaAgronomica Sinica, 40, 1386-1391 (in Chinese)

Jian H J, Xiao Y, Li J N, Ma Z Z, Wei L J, Liu L Z. 2014b. Mappingof QTLs for oilseed germination rate under stresses of salinityand drought in Brassica napus L. based on SNP genetic map.Acta Agronomica Sinica, 40, 629–635. (in Chinese)

Juenger T E, Mckay J K, Hausmann N, Keurentjes J J B, SenS, Stowe K A, Dawson T E, Simms E L, Richards J H. 2005.Identification and characterization of QTL underlying wholeplant physiology in Arabidopsis thaliana: σ13C, stomatalconductance and transpiration efficiency. Plant, Cell andEnvironment, 28, 697-708

Liu Z Y, Liu Z Q. 1984. Genetics and Breeding Study onPhotosynthesis. Guizhou People’s Publishing Company,Guiyang, China. (in Chinese)Liu L Z, Li J N. 2014. QTL Mapping of oleic acid, linolenic acidand erucic acid content in Brassica napus by using the highdensity SNP genetic map. China Agriculture Science, 47,24-32 (in Chinese)

Liu L Z, Qu C M, Wittkop B, Yi B, Xiao Y, He Y J, SonwdonR J, Li J N. 2013. A high-density SNP map for accuratemapping of seed fibre QTL in Brassica napus L. PLOSONE, 8, e83052.

McCouch S R, Cho Y G, Yano M, Paul E, Blinstrub M, MorishimaH, Kinoshita T. 1997. Report on QTL nomenclature. RiceGenetic Newsletter, 14, 11-13

Mönke G, Michael S, Jens K, Michaela M, Ivo G, Urs H, AstridJ, Bernd W, Udo C, Helmut B, Lothar A. 2012. Toward theidentification and regulation of the Arabidopsis thaliana ABI3regulon. Nucleic Acids Research, 40, 8240-8254

Ohno Y. 1976. Varietal differences of photosynthetic efficiencyand dry matter production in Indian rice. Tropical AgricultureResearch Center Technology Bulletin, 53, 115-123

Van Ooijen J, Voorrips R. 2006. JoinMap 4.0. Software forthe Calculation of Genetic Linkage Maps in ExperimentalPopulations.Poonam S N, Ghildiyal M C. 2005. Potential targets forimproving photosynthesis and crop yield. Current Science,88,1918-1928

Price A H, Steele K A, Moore B J, Jones R G W. 2002. Uplandrice grown in soil-filled chambers and exposed to contrastingwater-deficit regimes II. Mapping quantitative trait loci for rootmorphology and distribution. Field Crop Research, 76, 25-43

Prioul J L, Quarrie S, Causse M, Vienne D. 1997. Dissectingcomplex physiological functions through the use ofmolecular quantitative genetics. Journal of ExperimentalBotany, 48, 1151-1163

Ramana S, Ghildiyal M C. 1997. Contribution of leafphotosynthesis towards seed yield in Brassica species.Journal of Agronomy and Crop Science, 178, 185-187

Ramana S, Sharma-Natu P, Ghildiyal M C. 2002. Cytoplasmiceffects on photosynthesis and ribulose-1,5-bisphosphatecarboxylase activity in Brassica species Euphytica, 123,361-365

Rawson H M, Constable G A. 1982. Photosyntheticcharacteristics of mesophyll cells isolated from sunflower(Helianthus annuus L.) leaves. Photosynthesis Research,3, 59-67

Teng S, Qian Q, Zeng D L, Kunihiro Y, Fujimoto K, Huang DN, Zhu L H. 2004. QTL analysis of leaf photosynthetic rateand related physiological traits in rice (Oryza sativa L.).Euphytica, 135, 1-7

Thomas J A, Jeffrey A C, Atsuko K, David M K. 2005.Regulating the proton budget of higher plant photosynthesis.Proceedings of the National Academy of Sciences of theUnited States of America, 102, 9709-9713

Tu Z P, Feng M Y, Cai W J, Chen G H, Lin X Z. 1980. Study onrice high photosynthetic efficiency breeding, I. Genetics ofsingle leaf net photosynthetic rate. Guangdong AgricultureScience, 5, 8-13 (in Chinese)

Ulloa M, Cantrell R G, Percy R G, Zeiger E, Lu Z M. 2000.QTL analysis of stomatal conductance and relationship tolint yield in an interspecific cotton. The Journal of CottonScience, 4, 10-18 (in Chinese)

Wu Y, Bhat P R, Close T J, Lonardi S. 2008. Efficient andaccurate construction of genetic linkage maps from theminimum spanning tree of a graph. PLoS Genetics, 4,e1000212.

Xu D Q, Shen Y G. 1994. Progress on Physiology of CropHigh Production and High Efficiency. Science PublishingCompany, Beijing, China. pp. 17-23

Xu D Q. 1990. Ecology, physiology and biochemistry ofmidday depression of photosynthesis. Plant PhysiologyCommunication, 26, 5-10

Yan X Y, Li J N, Jin M Y, Chen L, Wang J F, Qu C M, Liu L Z.2009. QTL analysis of chlorophyll content in silique wall inBrassica napus L. Chinese Journal of Oil Crop Sciences,31, 269-273 (in Chinese)
[1] WANG Xing-long, ZHU Yu-peng, YAN Ye, HOU Jia-min, WANG Hai-jiang, LUO Ning, WEI Dan, MENG Qing-feng, WANG Pu. Irrigation mitigates the heat impacts on photosynthesis during grain filling in maize [J]. >Journal of Integrative Agriculture, 2023, 22(8): 2370-2383.
[2] XU Yan-xia, ZHANG Jing, WAN Zi-yun, HUANG Shan-xia, DI Hao-chen, HE Ying, JIN Song-heng. Physiological and transcriptome analyses provide new insights into the mechanism mediating the enhanced tolerance of melatonin-treated rhododendron plants to heat stress[J]. >Journal of Integrative Agriculture, 2023, 22(8): 2397-2411.
[3] DING Yong-gang, ZHANG Xin-bo, MA Quan, LI Fu-jian, TAO Rong-rong, ZHU Min, Li Chun-yan, ZHU Xin-kai, GUO Wen-shan, DING Jin-feng. Tiller fertility is critical for improving grain yield, photosynthesis and nitrogen efficiency in wheat[J]. >Journal of Integrative Agriculture, 2023, 22(7): 2054-2066.
[4] JIANG Hui, GAO Ming-wei, CHEN Ying, ZHANG Chao, WANG Jia-bao, CHAI Qi-chao, WANG Yong-cui, ZHENG Jin-xiu, WANG Xiu-li, ZHAO Jun-sheng. Effect of the L-D1 alleles on leaf morphology, canopy structure and photosynthetic productivity in upland cotton (Gossypium hirsutum L.)[J]. >Journal of Integrative Agriculture, 2023, 22(1): 108-119.
[5] WU Han-yu, QIAO Mei-yu, ZHANG Wang-feng, WANG Ke-ru, LI Shao-kun, JIANG Chuang-dao. Systemic regulation of photosynthetic function in maize plants at graining stage under vertically heterogeneous light environment[J]. >Journal of Integrative Agriculture, 2022, 21(3): 666-676.
[6] WANG Yi-bo, HUANG Rui-dong, ZHOU Yu-fei. Effects of shading stress during the reproductive stages on photosynthetic physiology and yield characteristics of peanut (Arachis hypogaea Linn.)[J]. >Journal of Integrative Agriculture, 2021, 20(5): 1250-1265.
[7] MA Ming-yang, LIU Yang, ZHANG Yao-wen, QIN Wei-long, WANG Zhi-min, ZHANG Ying-hua, LU Cong-ming, LU Qing-tao. In situ measurements of winter wheat diurnal changes in photosynthesis and environmental factors reveal new insight into photosynthesis improvement by super-high-yield cultivation[J]. >Journal of Integrative Agriculture, 2021, 20(2): 527-539.
[8] ZHU Mei-chen, HU Ran, ZHAO Hui-yan, TANG Yun-shan, SHI Xiang-tian, JIANG Hai-yan, ZHANG Zhi-yuan, FU Fu-you, XU Xin-fu, TANG Zhang-lin, LIU Lie-zhao, LU Kun, LI Jia-na, QU Cun-min. Identification of quantitative trait loci and candidate genes controlling seed pigments of rapeseed[J]. >Journal of Integrative Agriculture, 2021, 20(11): 2862-2879.
[9] Iram SHAFIQ, Sajad HUSSAIN, Muhammad Ali RAZA, Nasir IQBAL, Muhammad Ahsan ASGHAR, Ali RAZA, FAN Yuan-fang, Maryam MUMTAZ, Muhammad SHOAIB, Muhammad ANSAR, Abdul MANAF, YANG Wen-yu, YANG Feng. Crop photosynthetic response to light quality and light intensity[J]. >Journal of Integrative Agriculture, 2021, 20(1): 4-23.
[10] JIA Teng-jiao, LI Jing-jing, WANG Li-feng, CAO Yan-yong, MA Juan, WANG Hao, ZHANG Deng-feng, LI Hui-yong. Evaluation of drought tolerance in ZmVPP1-overexpressing transgenic inbred maize lines and their hybrids[J]. >Journal of Integrative Agriculture, 2020, 19(9): 2177-2187.
[11] YE Yu-xiu, WEN Zhang-rong, YANG Huan, LU Wei-ping, LU Da-lei. Effects of post-silking water deficit on the leaf photosynthesis and senescence of waxy maize[J]. >Journal of Integrative Agriculture, 2020, 19(9): 2216-2228.
[12] DING Xiao-yu, XU Jin-song, HUANG He, QIAO Xing, SHEN Ming-zhen, CHENG Yong, ZHANG Xue-kun. Unraveling waterlogging tolerance-related traits with QTL analysis in reciprocal intervarietal introgression lines using genotyping by sequencing in rapeseed (Brassica napus L.)[J]. >Journal of Integrative Agriculture, 2020, 19(8): 1974-1983.
[13] ZOU Jie, ZHOU Cheng-bo, XU Hong, CHENG Rui-feng, YANG Qi-chang, LI Tao. The effect of artificial solar spectrum on growth of cucumber and lettuce under controlled environment[J]. >Journal of Integrative Agriculture, 2020, 19(8): 2027-2034.
[14] Tahmina SHAR, SHENG Zhong-hua, Umed ALI, Sajid FIAZ, WEI Xiang-jin, XIE Li-hong, JIAO Gui-ai, Fahad ALI, SHAO Gao-neng, HU Shi-kai, HU Pei-song, TANG Shao-qing. Mapping quantitative trait loci associated with starch paste viscosity attributes by using double haploid populations of rice (Oryza sativa L.)[J]. >Journal of Integrative Agriculture, 2020, 19(7): 1691-1703.
[15] Dong Yun, Wang Yi, Jin Feng-wei, Xing Li-juan, Fang Yan, Zhang Zheng-ying, ZOU Jun-jie, Wang Lei, Xu Miao-yun. Differentially expressed miRNAs in anthers may contribute to the fertility of a novel Brassica napus genic male sterile line CN12A[J]. >Journal of Integrative Agriculture, 2020, 19(7): 1731- 1742.
No Suggested Reading articles found!