Influence of Epistasis and QTL×Environment Interaction on Heading Date of Rice(Oryza sativa L.)

QTLs for heading date of rice （Oryza sativa L.） with additive, epistatic, and QTL × environment （QE） interaction effects were studied using a mixed-model-based composite interval mapping （MCIM） method and a double haploid （DH） population derived from IR64/Azucena in two crop seasons. Fourteen QTLs conferring heading date in rice, which were distributed on ten chromosomes except for chromosomes 5 and 9, were detected. Among these QTLs, eight had single-locus effects, five pairs had double-locus interaction effects, and two single-loci and one pair of double-loci showed QTL × environment interaction effects. All predicted values of QTL effects varied from 1.179 days to 2.549 days, with corresponding contribution ratios of 1.04%-4.84%. On the basis of the effects of the QTLs, the total genetic effects on rice heading date for the two parents and the two superior lines were predicted, and the putative reasons for discrepancies between predicted values and observed values, and the genetic potentiality in the DH population for improvement of heading date were discussed. These results are in agreement with previous results for heading date in rice, and the results provide further information, which indicate that both epistasis and QE interaction are important genetic basis for determining heading date in rice.

Mapping QTLs with epistatic effects and QTL×environment interactions for plant height using a doubled haploid population in cultivated wheat

Quantitative trait loci （QTLs） for plant height in wheat （Triticum aestivum L.） were studied using a set of 168 doubled haploid （DH） lines, which were derived from the cross Huapei 3/Yumai 57. A genetic linkage map was constructed using 283 SSR and 22 EST-SSR markers. The DH population and the parents were evaluated for wheat plant height in 2005 and 2006 in Tai＇an and 2006 in Suzhou. QTL analyses were performed using the software of QTLNetwork version 2.0 based on the mixed linear model. Four additive QTLs and five pairs of epistatic effects were detected, which were distributed on chromosomes 3A, 4B, 4D, 5A, 6A, 7B, and 7D. Among them, three additive QTLs and three pairs of epistatic QTLs showed QTL×environment interactions （QEs）. Two major QTLs, Qph4B and Qph4D, which accounted for 14.51% and 20.22% of the phenotypic variation, were located similar to the reported locations of the dwarfing genes Rhtl and Rht2, respectively. The Qph3A-2 with additive effect was not reported in previous linkage mapping studies. The total QTL effects detected for the plant height explained 85.04% of the phenotypic variation, with additive effects 46.07%, epistatic effects 19.89%, and QEs 19.09%. The results showed that both additive effects and epistatic effects were important genetic bases of wheat plant height, which were subjected to environmental modifications, and caused dramatic changes in phenotypic effects. The information obtained in this study will be useful for manipulating the QTLs for wheat plant height by molecular marker-assisted selection （MAS）.

QTL Mapping of Chlorophyll Contents in Rice

The objectives of this study were to investigate the genetic factors controlling the chlorophyll content of rice leaf using QTL analysis. A linkage map consisting of 207 DNA markers was constructed by using 247 recombinant inbred lines （RILs） derived from an indica-indica rice cross of Zhenshan97B×Milyang 46. In 2002 and 2003, the contents of chlorophyll a and b of the parents and the 247 RILs were measured on the top first leaf, top second leaf, and top third leaf, respectively. The software QTLMapper 1.6 was used to detect quantitative trait loci （QTLs）, additive by environment （AE） interactions, and epistatic by environment （AAE） interactions. A total of eight QTLs in four intervals were detected to have significant additive effects on chlorophyll a and b contents at different leaf positions, with 1.96-9.77% of phenotypic variation explained by a single QTL, and two QTLs with significant AE interactions were detected. Epistasis analysis detected nine significant additive-by-additive interactions on chlorophyll a and b contents, and one pair of QTLs with significant AAE interactions was detected. On comparison with QTLs for yield traits detected in the same population, it was found in many cases that the QTLs for chlorophyll a and b contents and those for yield traits were located in the same chromosome intervals.

Identification of a major QTL for flag leaf glaucousness using a high-density SNP marker genetic map in hexaploid wheat

Cuticular wax plays an important role in protecting land plant against biotic and abiotic stresses. Cuticular wax production on plant surface is often visualized by a characteristic glaucous appearance. This study identified quantitative trait loci （QTLs） for wheat （Triticum aestivum L.） flag leaf glaucousness （FLG） using a high-density genetic linkage map developed from a recombinant inbred line （RIL） population derived from the cross HeynexLakin by single-seed descent. The map consisted of 2 068 single nucleotide polymorphism （SNP） markers and 157 simple sequence repeat （SSR） markers on all 21 wheat chromosomes and covered a genetic distance of 2 381.19 cM, with an average marker interval of 1.07 cM. Two additive QTLs for FLG were identified on chromosomes 3AL and 2DS with the increasing FLG allele contributed from Lakin. The major QTL on 3AL, QFIg.hwwgr-3AL, explained 17.5-37.8% of the phenotypic variation in different environments. QFIg.hwwgr-3AL was located in a 4.4-cM interval on chromosome 3AL that was flanked by two markers IWA1831 and IWA8374. Another QTL for FLG on 2DS, designated as QFIg.hwwgr-2DS which was identified only in Yangling in 2014 （YL14）, was flanked by IWA1939 and Xgwm261 and accounted for 11.3% of the phenotypic variation for FLG. QFIg.hww- gr-3AL and QFIg.hwwgr-2DS showed Additive×Environment （AE） interactions, explaining 3.5 and 4.4% of the phenotypic variance, respectively. Our results indicated that different genes/QTLs may contribute different scores of FLG in a cultivar and that the environment may play a role in FLG.