| Popcorn has special expansion characteristics, but small kernel, short grain filling period and much low grain yield. Normal corn germplasm could be used to improve grain yield and broaden germplasm in popcorn. In this research, two hundred and fifty-eight F10 RILs were developed from a dent corn inbred line, Dan232, and an elite popcorn inbred line, N04. A high-density genetic map was constructed using SSR markers. Quantitative trait loci (QTL) were detected for 100-grain dry weight (GDW), 100-grain fresh weight (GFW), grain water content (WC), grain crude protein content (CP), crude starch content (CT), crude fat content (CF), lysine content (LS) at four development stages (10d, 20d, 30d and 40d) after pollination (DAP), and grain filling rate (GFR), fresh weight increasing rate (FWIR), water reducing rate (WC), net increased values of four kernel nutritive characters during six periods (10-20DAP, 10-30DAP, 10-40DAP, 20-30DAP, 20-40DAP and 30-40DAP), and the activities of three starch synthesis related enzymes (AGPP, GBSS and SSS) at 30DAP. Also, these results were compared with QTL detected for GDW and four kernel nutritive characters at harvest time using RIL, F2:3 and BC2F2 generations developed form the same two parents in our previous studies. Besides, integrated map was constructed from both RIL and F2:3 genetic maps. Consensus QTL were identified using meta-analysis method in Biomercator 2.1. Our main objective was to find major consistent QTL across different generations, development stages and environments, and their linked effective markers, and key chromosome regions on which those QTL were located. These results could provide more reliable theoretical basis marker-assisted selection and breeding for grain filling and kernel nutritive characters, and map-based cloning for important QTL and other related researches in future.The main results in this study were as follows:1. Variances for genotypes and interaction between genotypes and environments were significant for all traits. Except FWIR at different development stages, Dan232 had higher trait values than N04. Transgressive segregations were observed for all traits. The heritabilities for most traits were high. Except insignificant correlations between FWIR and other grain filling related traits, and negative correlations between CT and CP, CF, LS, all significant positive correlations were obtained among other traits. According to chosen RIL with different grain weight, the activities of three enzymes were all low at 10DAP, high at 20/30DAP, and then decreased lightly at 40DAP.2. One hundred and sixty-one QTL were detected for GDW, GFW at four developmental stages, GFR, FWIR during all developmental periods, and the activities of three enzymes at 30DAP under two years and in combined analysis. Contributions by a single QTL varied from 4.44% to 25.38%, with 88 QTL over 10% and 33 QTL over 15%. qGDW20-7-1, qGDW30-7-1, qGDW40-7-1, qGDW20-10-1, qGDW30-10-1, qGDW40-10-1, qGFW20-1-1, qGFW40-1-1, qGFW20-7-1, qGFW30-7-1, qGFW40-7-1, GFR12-7-1, qGFR13-7-1, qGFR14-7-1, qGFR23-7-1, qGFR12-10-1, qFWIR12-1-1, qFWIR13-1-1, qFWIR12-7-1, qFWIR13-7-1 were commonly detected under two environments and in combined analysis; qGDW10-7-1, qGDW10-10-1, qGFW10-7-1 were detected at all stages; qGFR12-1-1, qGFR12-7-1, qFWIR10-1-1 were detected only during early periods; qGDW20-1-1, qGDW40-1-1 and qGFW30-1-1, qGFR12-1-1, qGFR14-1-1 and qGFR23-1-1; qFWIR13-1-1 and qFWIR14-1-1 were all located in the same respective marker intervals across different environments, with contributions over 20%.3. Sixty-nine QTL were detected for WC at four stage, and WDR during all development periods under two environments and in combined analysis. Phenotypic variation explained by a single QTL varied from 4.33% to 18.69%, with 19 QTL over 10% and one QTL over 15%. Of these, qWC30-5-1 and qWC40-5-1 were commonly detected under two environments and in combined analysis; No QTL was detected at all stages; qWC10-1-1, qWC20-1-1, qWDR12-5-2, qWDR13-5-1 were detected only at early stages/periods. qWC20-5-1, qWC30-5-1, qWC40-5-1, qWDR24-2-1 and qWDR34-2-1 were detected at middle and late stages. The contributions of qWC20-5-1, q08WDR14-2-1, qcWDR14-2-2 were high, 18.69%,14.97% and 14.11%, respectively.4. One hundred and eight QTL were detected for all kernel nutritive characters at four stages under two environments and in combined analysis. Phenotypic variations explained by a single QTL varied from 4.57% to 24.38%, with 33 QTL over 10% and 10 over 15%. qCP30-3-1, qCT10-1-1, qCT20-1-1, qCT30-1-1, qCT30-4-1, qCT30-5-1 and qLS40-4-2 were commonly detected under two environments and in combined analysis, which showed consistency across different environments; qCP20-3-1, qCT10-1-1, qCF10-9-1, qLS10-1-1 and qLS20-1-1 were detected only at early stages; qCP20-3-1, qCT20-5-1, qCT30-3-1, qLS20-5-1, qLS40-3-1 and qLS30-4-1 were detected at middle and late stages; q08CT10-2-1, qcCT10-2-1, and qCT20-1-1 located in marker interval bnlg1017-umc1776, and qCT40-1-1, qCT10-1-1, q08CT20-1-1, qcCT20-1-1 in marker interval umc1976-bnlg1803 were major QTL, with contributions from 15.30% to 24.38%.5. One hundred and seventeen QTL were detected for net increased values of four kernel nutritive characters during all developmental stages under two environments and in combined analysis. Phenotypic variations explained by a single QTL varied from 3.41% to 23.55%, with 43 QTL over 10% and 7 QTL over 15%. qCP13-4-1, qCT12-5-1, qCT13-5-1, qCT12-1-1 and qCT13-1-1 were commonly detected under two environments and in combined analysis; qCP12-3-1, qCP13-3-1, qCT12-1-1, qCT13-1-1, qCF13-3-1, qLS12-5-2 and qLS13-5-1 were detected only during early periods; CP23-4-1, qCP24-4-1, qCT14-5-1, qCT23-5-1, qCF24-8-2, qCF34-8-2, qLS14-4-2 and qLS24-4-2 were detected at middle and later periods; The contributions of CP13-4-1, qCP34-4-1, qCT12-4-1, qCT23-4-1, qCF14-2-1, qLS12-5-1 and qLS13-5-1 were high (15.85% to 23.55%). They had consistency across different environments.6. Comparing with QTL detected for grain filling related traits and kernel nutritive characters at harvest time using RIL, F2:3 and BC2F2 populations in our previous studies, QTL for GDW in marker intervals phi001-umc2227, umc1478-bnlg565, umc2057-umc1567, umc1677-umc2122, umc1478-bnlg565, and QTL for kernel nutritive characters in marker intervals umc1976-bnlg1803, bnlg1452-umc1773, umc1389-umc1162, phi072-umc1757 and phi299852-phi364545, were consistently detected across different generations. Totally, 73"consensus"QTL were obtained, 13"consensus"QTL for 161 QTL associated with four grain filling related traits in this study, 14"consensus"QTL for 197 QTL associated with six grain filling related traits in this study and GDW at harvest time in RIL, F2:3 and BC2F2 populations, 22"consensus"QTL for 225 static and dynamic QTL associated with kernel nutritive characters, and 24"Consensus"QTL for 308 QTL associated with all kernel nutritive characters in this study and those at harvest time using RIL, F2:3 and BC2F2 populations. Each"consensus"QTL integrated 2 to 54 QTL, with an average of 10 QTL, and related with 15 traits. Most QTL for related traits were distributed in the same chromosome regions in clusters. For example, phi001-umc2227, umc1906-umc2083 on chromosomes 1, umc1502-umc1941 on chromosomes 5, umc2057-umc1567 on chromosomes 7 and umc1677-umc2122 on chromosomes 10 were all major regions for grain filling related traits, and bnlg1452-umc1025 on chromosomes 3, phi072-umc1757 on chromosomes 4 and umc1389-umc1162 on chromosomes 5 were for kernel nutritive characters. True QTL for relate traits might gather in these marker intervals.7. Among 563 detected QTL, 197 pairs of QTL or marker intervals had digenic interactions, but their effects were small. The favorable alleles of 395 QTL for six grain filling related traits and four kernel nutritive characters contributed by dent corn inbred Dan232, while those of 168 QTL for other grain filling related traits, the activities of three enzyme and other kernel nutritive characters were from popcorn inbred N04. |
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