Feb 2017

Phenotypic and genetic dissection of water stress adaptations in pearl millet (Pennisetum glaucum) using QTL co-localization approachMurugesan Tharanya1,2, Jana Kholova1, Kaliamoorthy Sivasakthi1,2, Deepmala Seghal3, Charles Tom Hash4, Basker Raj1, Rekha Baddam1, Thiyagarajan Thirunalasundari2, Rattan Yadav3, Vincent Vadez1*1International Crops Research Institute for the Semi–Arid Tropics (ICRISAT), Crop Physiology Laboratory, Patancheru 502324, Telangana, India.2Bharathidasan University, Tiruchirappalli 620 024, Tamilnadu, India.3Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, AberystwythSY23 3EB, UK.4International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), ICRISAT Sahelian Center, Pearl Millet Breeding, BP 1204, Niamey, Niger.

About ICRISAT: www.icrisat.orgICRISAT’s scientific information: http://EXPLOREit.icrisat.org

IntroductionCrop yield is a consequence of several plant biological functions and its interactions with environment. Here we focus on some of basic plant functions related to i) water-use ii) canopy development and iii) agronomic traits and investigate on the relationship of these traits for crop production in different water-stress scenarios using the QTL co-localization approach.

Figure 1. APSIM generic template model developed by Graeme L. Hammer

Figure 2. Different phenotypic environments: a) Pot culture, b) High throughput phenotyping platform (LeasyScan), c) Lysimeter and d) Field

Figure 3. Range of variation obtained – Transpiration rate (Tr), 3dimensional leaf area (3DLA), transpiration (T) and grain yield (GY) from various phenotyping environments.

Figure 5 Selective principal component analysis (PCA) done for a) Grain yield (GY) from field under well-watered (WW) conditions and traits (canopy development and water-use related) from LeasyScan under WW b) GY from field under WW and traits (water-use and biomass related) from pot culture under WW c) GY from field under severe stress (SS) and traits (water-use and yield related) from Lysimeter under SS d) early water extraction from Lysimeter (SS) and canopy development related traits from LeasyScan (SS). CS represents canopy structure; RDW represents root dry weight; T represents transpiration and DAS represents days after sowing.

APSIM Generic Crop Template from Graeme L. Hammer

Grain Yield

Grain Number Grain Size

D BiomassRadiation

Transpiration Efficiency

Transpiration Radiation use efficiency

Radiation intercept (Rint)

Vapour pressure deficit

Leaf hydraulic conductance (kl)

Leaf area indexSpecific leaf nitrogen

Roots ExtinctionCoefficient (k)

“building blocks”=CAUSE of GxE

Yield = CONSEQUENCEOf Genotype x Environment (GxE)

Fig. 1

Nitrogen content

Leaf number

Objectivesi) Mapping of QTLs underlying traits related to i) water use ii) canopy development and iii) agronomy

which have been assessed at various phenotyping systems.ii) Infer the associations between the investigated traits and its importance for crop production through

QTL co-localization approach and principal component analysis (PCA).

Materials and MethodsA fine mapping population (FMP) population (162 lines) based on the cross between ICMR01004 x ICMR01029 segregating within LG02 for terminal water stress adaptation (Yadav et al., 2010). Genotypic data included of 17 polymorphic markers on LG02 (gene-based markers, RFLP, SNP, Seghal et al., 2012)Phenotyping was done at different levels of plant organization using four different environments • Pot culture (water-use related traits)• High throughput phenotyping platform: LeasyScan (canopy development related traits)• Lysimeter (water-use, agronomy-related traits)• Precision field (agronomy-related traits)

a) Pot culture b) High throughput phenotyping system: LeasyScan

c) Lysimeter d) Field

Conclusion• The phenotyping facilities at ICRISAT are highly relevant to identify the traits underlying agronomic

performance of crops in environments with various in-season water availability and so support the crop-improvement program.

• The gained knowledge provides the power to combine the alleles from LG02 and construct the plant ideotype for specific regions according to the prevailing conditions.

Selected referenceVadez et al (2015). J. Exp. Bot. (2015) 66 (18): 5581-5593.Kholova et al (2012). Mol Breed. 30, 1337-1353.

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Figure 4. Colocalisation of water-use, canopy development and agronomy related traits within 191-254cM of LG02.

Water-use and agronomy related traits

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Results• Terminal water stress adaptation locus (LG02; 191-254cM) was further dissected into four separate

QTL regions - R1 (191-205cM), R2 (229-233cM), R3 (236-239cM) and R4 (251-259cM) associated with water-use, canopy development and agronomy related traits.

• The loci harboring water-use and canopy development related traits co-localized with agronomic traits assessed in the field pointing out their functional linkages. These relations were also confirmed by PCA analysis across phenotyping environments.

AcknowledgementsThe authors thank for the funds from the USAID grant -Feed the Future Innovation Lab – Development of Abiotic Stress Tolerant Millet for Africa and South Asia

For more details contact v.vadez@cgiar.org