Characterization of introgression lines with an Indica-type rice (Oryza sativa L.) variety IR64 genetic background M N Uddin1, M Obara2, S　Yanagihara2, N Kobayashi3, T Ishimaru4, Y　Fukuta2 Correspond person: uddinnashir575@gmail.com 　　1 Graduate school of life and Environmental Sciences, University of Tsukuba, Japan 　　2 Japan International Research Center for Agricultural Sciences (JIRCAS), Tsukuba, Japan 　　3 National Institute of Crop Science (NICS), Tsukuba, Japan 　　4 International Rice Research Institute (IRRI), Los Banos, Laguna, the Philippines Background & Rationale IR64 has been cultivated widly as an Indica-type elite rice variety (Oryza sativa L.) in Tropical regions, and well-known for its wide acceptance by the farmers (Ballini et al. 2007). but the performance of IR64 was limited (Wade et al. 1999, Lafitte et al. 2006, and Namai et al. 2009). Therefore, Fujita et al. 2009, have developed the introgression lines with chromosome segments from Japonica-type varieties, such as New Plant types (NTPs), to improve the yield potential of IR64. The objective of this study was to characterize the introgression lines (INLs) under different cultivated conditions. Materials & Methods A total of 339 introgression lines (INLs, BC3F9) with IR64 genetic background (Fujita et al. 2009) were used INLs were grown in two different cultivated conditions (irrigated lowland and upland) at Tsukuba, Japan, and all standard agricultural practices were performed A total of 13 agronomic traits related to yield components (YP) and dry matter production (DMP) were measured following IRRI-IBPGRI standard descriptors for rice, and average value of 10 individuals per lNLs were used to calculate each trait Results & Discussions An improved performance were observed among the INLs grown in both conditions compared with IR64, and upland conditions showed superior performance to irrigated lowland (Figure 1) Fujita et al. (2009) & Kobayashi et al. (2010) reported about the unique agronomic traits among these INLs, and current study results revealed the uniqueness in the traits related to YC & DMP compared with IR64. Developed INLs were classified into 8 based on 13 trait’s data for YC and DMP groups by cluster analysis (Figure 2) Group AI was characterized as the early heading and high panicle numbers Group AII was short plant type and low spikelet numbers of panicle and fertilities. Group AIV was late heading and high sterile seeds, where Group BI showed the high harvest index and fertility seeds, and BII was short plant type and short panicle. Group BIII was characterized by highest plant length, DMP, and fertile seeds and total spikelet. And this group showed the best performance and higher DMPs than those of IR64 in both conditions Groups, AIII and BIV, showed the intermediate values between BIII and AII. The performance of IR64 is close to the cluster group AII Donor parents of the CG BIII might possess high yield potential factors (genetic) among all the donor parents Upland IV (n =53) I (n =166) III (n =100) II (n =20) Linkage distance Irrigated lowland A (n =143) B (n =196) Linkage distance Fig. 2 Classification of 339 INLs. Cluster analysis was carried out with 13 agronomic traits following Ward`s hierarchical analysis (Ward 1963) using JMP7.0 (SAS institute Inc., Cary, NC, USA) Table 2. Relationship between irrigated lowland and upland conditions for INLs performance Table 3. Yield components and dry matter production of IR64 and INLs within the cluster groups (CG) in irrigated lowland (upper line) and Upland conditions(lower line); red & purple color indicates the higher & lower values Traits   Introgression lines IR64 AI AII AIII AIV BI BII BIII BIV DTH 86.00-122.00 84.49-112.65 83.56-114.44 85.57-113.67 89.61-121.11 84.59-112.86 85.25-119.00 86.25-115.30 87.29-120.57 CW 78.33-40.78 76.10-51.90 76.84-42.71 79.45-60.16 80.42-46.49 79.19-54.08 82.68-42.40 83.22-61.37 83.22-51.27 PW 24.67-24.67 24.42-24.84 24.09-22.73 25.69-26.59 27.33-25.54 25.63-26.14 25.64-22.80 26.93-27.80 27.46-26.98 TW 103.00-65.44 100.51-76.73 100.93-65.44 105.14-86.75 107.75-72.03 104.82-80.23 108.32-65.20 110.15-89.18 110.68-78.25 P/C 0.19- 0.13 0.32-0.46 0.30-0.36 0.30-0.44 0.27-0.25 0.41-0.47 0.35-0.28 0.41- 0.46 0.39- 0.29 CL 61.28-69.33 47.92-41.44 50.58-20.14 50.86-57.47 55.57-54.68 44.35-42.22 44.50-16.02 46.14-53.19 46.80-51.11 PL 14.44-10.63 22.89-35.41 21.26-10.79 22.06-45.18 20.73-18.45 30.47-37.15 24.31-6.12 32.45-45.73 30.32-21.40 TL 75.72-79.97 70.88-76.78 71.62-31.32 72.92-102.39 76.30-73.14 74.79-79.33 68.81-22.14 78.57-99.00 77.13-72.50 PN 26.56-20.11 19.76-21.12 18.94-10.23 16.66-23.51 15.70-18.00 16.02-20.19 14.16-7.33 14.43-21.89 14.28-18.09 FS 20.44-24.67 64.51-115.70 57.24-63.02 70.02-139.91 58.96-63.02 99.32-128.78 80.68-55.65 108.86-161.07 105.42-89.65 SS 109.67-141.56 78.73-25.10 66.61-33.48 94.07-51.16 96.52-100.48 52.19-24.92 55.66-49.23 62.00-41.35 63.89-106.32 TS 130.11-166.22 143.24-140.80 123.86-96.50 164.09-191.07 155.49-163.50 151.51-153.71 136.34-104.88 170.86-202.42 169.30-195.96 FS/TS 0.16- 0.15 0.46-0.82 0.46-0.63 0.43-0.73 0.39-0.37 0.66-0.84 0.60-0.54 0.64- 0.80 0.62- Cluster No. of lines in each cluster groups Irrigated lowland A B Total Upland I 88 78 166 II 16 4 20 III 21 79 100 IV 18 35 53 143 196 339 ↧ ⇣ ▾ ▿ ↧ ⇣ ↧ ▿ ▾ ▿ ↧ ⇣ ▾ ⇣ ▿ ↧ ▿ ⇣ ▾ ▾               ⇣ ↧ ↧ ⇣ ⇣ ↧ ↧ ⇣ ▿ ▾ No. of lines ▿ ▾ ▾ ▿ ▿ DTH; Days to heading, CL; Culm length, PL; Panicle length, TL; Total length, CW; Culm weight, PW; Panicle weight, TW; Total weight, P/C; Harvest index (P/C), PN; Panicle number, FS; Fertile seed, SS; Sterile seed, TS; Total spikelet and FS/TS; Ratio of fertile seed and total seed. ▿ ▾ ↧ ⇣ ▾           ⇣ ↧ ⇣ ▾ ▿ ↧ ▿ ▾ ▿ ↧ ▾ ⇣       Fig. 1　Variation of Introgression lines (INLs) for agronomic traits in irrigated lowland (Black bar) and upland (White bar) conditions Triangle (▿,▾)indicate the average value of IR64 and arrows (↧,⇣) indicate the average values of INLs in both environmental conditions respectively. Conclusion & Perspectives These results indicated that IR64 was improved genetically by through introgressions of chromosome segments where were harboring the useful morphological and physiological genetic factors from Japonica-type varieties, and further studies are needed to be confirmed These INLs will be used as genetic materials for identifying and favorable gene sources from NTPs. References Fujita D, Santos RE, Ebron LA, Telebanco-Yanoria MJ,Kato H, Kobayashi S, Uga Y, Araki E, Takai T, Tsunematsu H, Imbe T, Khush GS, Brar DS, Fukuta Y and Kobayashi N (2009). Field Crops Research, Vol. 114:244-254 Kobayashi N, Fukuta Y and Ito O (2010). JIRCAS Working Report No.66: 13 Lafitte HR, Yongsheng G, Shi Y and Li z-k (2006).Journal of Experimental Botany, Vol.58: 169-175 Wade LJ, McLaren CG, Quintana L, Harnpichitvitaya D, Rajatasereekul S, Sarawgi AK (1999). Field Crops Research, Vol.64,pp.35–50 Namai S, Toriyama K and Fukuta K(2009). Breeding Science, Vol.59:269-276