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Mapping of quantitative trait loci in pearl millet (Pennisetum glaucum (L.) R. Br.) and relating to the water stress environments
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Mapping of quantitative trait loci in pearl millet (Pennisetum glaucum (L.) R. Br.) and relating to the water stress environments

  1. Feb 2017 Mapping of quantitative trait loci in pearl millet (Pennisetum glaucum (L.) R. Br.) and relating to the water stress environments Aparna Kakkera1 , Rekha Baddam1 , Jana Kholova1 , Vincent Vadez1 * 1 International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, India About ICRISAT: www.icrisat.org ICRISAT’s scientific information: http://EXPLOREit.icrisat.org Table 1. Details of the experiments conducted at Patancheru under well-water and severe water stress conditions Year Treatment Rainfall (mm) Stage of crop during rain Irrigation interval Total irrigation (mm) Yield (gm-2 ) Mean flowering time (DAE) Harvest time (DAE) 2013 Well- water 7 days 420 328 38 77 Mild stress 60 49 DAE 15 days (from 15 DAS) 180 217 37 76 Severe stress Weekly irrigation till flowering and later on no irrigation 220 256 38 74 2014 Well- water 7 days 290 300 37 78 13 25 DAE Mild stress 42 65 DAE 15 days (from 20 DAS) 210 258 36 72 43 75 DAE Severe stress Weekly irrigation till flowering and later on no irrigation 175 168 38 70 Introduction • One well-watered and three different water stress patterns were designed based on the mean seasonal rain fall variations (460, 305, and 139 mm in 1988) observed during cropping season, in dry environments of Rajasthan, to identify the genomic regions associated with the traits related to stover and grain yield under these varied water stress patterns. Objectives • To identify the traits that impart yield advantage under different water stress treatments and QTLs associated with these traits. • To interpret the functional relations of the QTL interactions affecting grain yield under various water stress treatments. Figure 1: Traits associated with LG 2 Figure 2: Principal component analysis (PCA) projections on axes 1 and 2 for 113 RILs, estimating the relationship of traits a) account for 64% of total variance under well-water and b) account for 63 % of total variance under severe water stress Figure 3: QTL interactions from GMM analysis under a) well- water b) mild water stress and c) severe water stress Figure 4: Traits associated with LG 4 (Fig 4a) and LG 6 (Fig 4b) PgPb89840.0 PgPb1059413.8 PgPb860729.8 PgPb908145.5 PgPb1143363.9 PgPb968165.5 PgPb9143100.8 PgPb11732113.3 PgPb10852132.1 PgPb9167142.0 PgPb10902155.6 Xctm03167.7 PgPb7431178.4 PgPb12731188.5 PgPb7979191.8 Xpsmp2237193.1 PgPb8512196.3 PgPb10563198.8 PgPb11193200.7 PgPb6613 PgPb6558201.2 PgPb6013204.5 PgPb8369205.8 PgPb8177206.6 PgPb6628 PgPb7120207.0 PgPb7413211.7 Xipes0007218.4 PgPb6184219.5 PgPb11036221.1 PgPb10525222.1 PgPb6471222.6 Xicmp3056223.1 PgPb10361224.5 Xipes0117225.0 PgPb8259226.0 PgPb8902231.8 PgPb12641240.3 PgPb6880242.2 PgPb8268248.8 PgPb9046255.2 PgPb9970256.1 PgPb8464 PgPb10086258.7 PgPb8139260.7 PgPb11702263.8 PgPb8214266.5 PgPb8035271.1 PgPb9474274.9 PgPb13146277.9 PgPb8457287.0 PgPb8244295.6 PgPb9338299.1 Xipes0003303.5 PgPb11641304.9 PgPb6117305.4 PgPb9306307.5 PgPb7336309.6 PgPb11469315.3 Xctm21318.7 PgPb10526320.5 PgPb8443322.3 PgPb6665322.7 PgPb13198324.4 PgPb11611327.1 Xpsmp2059327.5 PgPb12897328.5 PgPb8694331.9 PgPb7330335.9 Xipes0210 Xipes0218341.5 PgPb6669344.6 PgPb8856349.3 PgPb12598351.6 PgPb7028355.3 PgPb7861355.7 PgPb7019 PgPb13134363.1 PgPb10206365.4 Xipes0118370.3 Locus introgressed to NILs Hash et al. 1999 Grain mass_WW Grain mass_MS Grain number_WW Grain number_WW Grain number_MS Grain mass_MS PHI_SS Tiller number_MS Tiller number_WW LG 2 Figure 1: Traits associated with LG 2 Allele from H 77/833–2 parent_unadapted to terminal water stress Allele from PRLT 2/89–33 parent_adapted to terminal water stress PgPb89840.0 PgPb1059413.8 PgPb860729.8 PgPb908145.5 PgPb1143363.9 PgPb968165.5 PgPb9143100.8 PgPb11732113.3 PgPb10852132.1 PgPb9167142.0 PgPb10902155.6 Xctm03167.7 PgPb7431178.4 PgPb12731188.5 PgPb7979191.8 Xpsmp2237193.1 PgPb8512196.3 PgPb10563198.8 PgPb11193200.7 PgPb6613 PgPb6558201.2 PgPb6013204.5 PgPb8369205.8 PgPb8177206.6 PgPb6628 PgPb7120207.0 PgPb7413211.7 Xipes0007218.4 PgPb6184219.5 PgPb11036221.1 PgPb10525222.1 PgPb6471222.6 Xicmp3056223.1 PgPb10361224.5 Xipes0117225.0 PgPb8259226.0 PgPb8902231.8 PgPb12641240.3 PgPb6880242.2 PgPb8268248.8 PgPb9046255.2 PgPb9970256.1 PgPb8464 PgPb10086258.7 PgPb8139260.7 PgPb11702263.8 PgPb8214266.5 PgPb8035271.1 PgPb9474274.9 PgPb13146277.9 PgPb8457287.0 PgPb8244295.6 PgPb9338299.1 Xipes0003303.5 PgPb11641304.9 PgPb6117305.4 PgPb9306307.5 PgPb7336309.6 PgPb11469315.3 Xctm21318.7 PgPb10526320.5 PgPb8443322.3 PgPb6665322.7 PgPb13198324.4 PgPb11611327.1 Xpsmp2059327.5 PgPb12897328.5 PgPb8694331.9 PgPb7330335.9 Xipes0210 Xipes0218341.5 PgPb6669344.6 PgPb8856349.3 PgPb12598351.6 PgPb7028355.3 PgPb7861355.7 PgPb7019 PgPb13134363.1 PgPb10206365.4 Xipes0118370.3 Locus introgressed to NILs Hash et al. 1999 Grain mass_WW Grain mass_MS Grain number_WW Grain number_WW Grain number_MS Grain mass_MS PHI_SS Tiller number_MS Tiller number_WW LG 2 Figure 1: Traits associated with LG 2 Allele from H 77/833–2 parent_unadapted to terminal water stress Allele from PRLT 2/89–33 parent_adapted to terminal water stress b) Fig 4a PgPb101840.0 PgPb113257.5 PgPb1171118.1 PgPb1316123.8 PgPb1029233.9 PgPb990341.0 PgPb663741.9 PgPb989450.2 PgPb978852.1 PgPb1000552.5 PgPb1103155.2 PgPb993359.8 PgPb1094663.6 PgPb623066.2 PgPb1074671.2 PgPb710172.1 PgPb791073.8 PgPb771179.9 PgPb1136790.9 PgPb1011094.8 PgPb795895.8 PgPb1260897.5 PgPb647898.1 PgPb13415100.1 Xipes0186101.5 PgPb6893102.4 PgPb9293103.8 Xicmp3029105.4 PgPb10768106.4 PgPb13178107.4 Xipes0066 PgPb7832 PgPb13377 108.3 PgPb7642109.1 Xpsmp2084109.9 PgPb10141111.2 PgPb10598112.0 PgPb7545112.9 Xipes0076113.8 PgPb12205114.7 PgPb10552118.3 PgPb9450123.0 PgPb8656127.1 PgPb7528134.4 PgPb8208143.1 PgPb7311155.2 PgPb6639156.1 FT, SV_ WW, MS HI_ WW, MS, SS LG 4 Fig 4b LG 6 PgPb130620.0 Xicmp30024.7 PgPb69476.2 PgPb708212.3 PgPb801813.7 PgPb5969 PgPb8664 PgPb10715 14.2 PgPb8306 PgPb913919.7 Xipes017620.2 PgPb1026421.1 PgPb1194721.6 PgPb1232222.5 PgPb9775 PgPb1076723.4 PgPb836826.5 PgPb1047030.4 PgPb10723 PgPb10580 Xipes0071 31.5 PgPb1311332.0 PgPb693137.0 PgPb891942.2 PgPb751644.0 PgPb923544.9 PgPb12466 Xicmp305046.9 Xipes008747.5 PgPb860148.0 PgPb893550.8 PgPb1316451.2 Xpsmp227054.1 PgPb1060364.0 PgPb11645 PgPb1156366.8 PgPb641669.4 PgPb989877.1 PgPb1139781.7 FT Grain yield_SS PHI_MS, SS Grain yield_WW, MS Grain no_MS a) b) Results • Grain mass, grain number and tiller number were linked to terminal drought tolerant region of LG 2 under all the moisture treatments (Fig 1). • Grain number showed very close relationship with grain yield under well-water conditions (Fig 2a) • Tiller number comapped with grain number and also showed a close relationship with grain yield under well-water conditions. • Grain mass has its importance as the water stress becomes severe (Fig 2b) • Under severe water stress, grain mass, grain number and PHI showed a close relationship with grain yield Epistatic interactions for grain yield: • A combination of tiller number, PHI and SY alleles showed 17-21% increase in grain yield under well- water conditions (Fig 3a) • Under mild water stress conditions also a combination of tiller number, HI and SY alleles showed 29% increase in grain yield (Fig 3b) • Under severe stress a combination of grain mass, HI and PHI alleles showed 8% increase in grain yield (Fig 3c) a) For more details contact v.vadez@cgiar.org b)a) 17% Well-water (19.7 cM, p_8306) FT, PHI Tillers21% a) Mild water stress 29% (76.78 cM, p_12113) (286.98 cM, p_8457) (51.48 cM, p_13164) b) Severe water stress 8% (101.97 cM, p_9343) (31.46 cM, p_10723) (24.39 cM, p_8170) c) c) Materials and Methods • Phenotypic evaluation was carried out on 113 F7 progenies of RIL cross H 77/833-2 X PRLT 2/89-33. Test cross hybrids of this cross were grown under well-water (WW), mild stress (MS) and severe water stress (SS) environments in the fields of ICRISAT- Patancheru during 2013 and 2014 (Table 1). • The genotyping of F6 plants of the RIL cross H 77/833–2 x PRLT 2/89–33 was used for construction of linkage map. The linkage map consists of 321 markers distributed across seven linkage groups (LG), with an average marker interval length 3.7cM. Phenotyping and genotyping data was subjected to QTL mapping through composite interval mapping approach of PLABQTL. Conclusions • Terminal drought tolerant region identified on LG 2 was associated with grain yield components i.e. grain mass, grain number of all the moisture treatments, tiller number (mild water stress) and PHI (severe water stress). • Stover yield (SY) and flowering time (FT) were majorly associated with LG 4 and LG 6 (mild water stress). • Under well-water and mild water stress, grain number and tiller number were favourable for retaining grain yield. • Grain mass is more favourable for retaining grain yield under severe water stress, i.e. alleles favouring the ability of filling grains would be the choice of selection under severe water stress environments.
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