Reciprocal Introgression Lines Research Articles

Genetic regulation of volatile production in two melon introgression line collections with contrasting ripening behavior.

The importance of melon aroma in determining fruit quality has been highlighted in recent years. The fruit volatile profile is influenced by the type of fruit ripening. Non-climacteric fruits contain predominantly aldehydes, while climacteric fruits mainly produce esters. Several genes have been described to participate in volatile organic compounds (VOCs) biosynthesis pathways, but knowledge in this area is still incomplete. In this work we analysed the volatile profile of two reciprocal Introgression Line (IL) collections generated from a cross between 'Piel de Sapo' (PS) and 'Védrantais' (VED) melons, differing in their aroma profile and ripening behaviour. SPME GC-MS was performed to identify genes responsible for VOCs formation. More than 1000 QTLs for many volatiles were detected taken together both populations. Introgressions on chromosomes 3, 5, 6, 7 and 8 modified ester-aldehyde balance and were correlated to ripening changes in both genetic backgrounds. Some previously identified QTLs for fruit ripening might be involved in these phenotypes, such as ETHQV8.1 on chromosome 8 and ETHQV6.3 on chromosome 6. PS alleles on chromosomes 2, 6, 10 and 11 were found to increase ester content when introgressed in VED melons. Terpenes showed to be affected by several genomic regions not related to ripening. In addition, several candidate genes have been hypothesized to be responsible for some of the QTLs detected. The analysis of volatile compounds in two reciprocal IL collections has increased our understanding of the relationship between ripening and aroma and offers valuable plant material to improve food quality in melon breeding programs.

Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice

Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers’ final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines.

Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.

Genetic dissection of climacteric fruit ripening in a melon population segregating for ripening behavior

Melon is as an alternative model to understand fruit ripening due to the coexistence of climacteric and non-climacteric varieties within the same species, allowing the study of the processes that regulate this complex trait with genetic approaches. We phenotyped a population of recombinant inbred lines (RILs), obtained by crossing a climacteric (Védrantais, cantalupensis type) and a non-climcteric variety (Piel de Sapo T111, inodorus type), for traits related to climacteric maturation and ethylene production. Individuals in the RIL population exhibited various combinations of phenotypes that differed in the amount of ethylene produced, the early onset of ethylene production, and other phenotypes associated with ripening. We characterized a major QTL on chromosome 8, ETHQV8.1, which is sufficient to activate climacteric ripening, and other minor QTLs that may modulate the climacteric response. The ETHQV8.1 allele was validated by using two reciprocal introgression line populations generated by crossing Védrantais and Piel de Sapo and analyzing the ETHQV8.1 region in each of the genetic backgrounds. A Genome-wide association study (GWAS) using 211 accessions of the ssp. melo further identified two regions on chromosome 8 associated with the production of aromas, one of these regions overlapping with the 154.1 kb interval containing ETHQV8.1. The ETHQV8.1 region contains several candidate genes that may be related to fruit ripening. This work sheds light into the regulation mechanisms of a complex trait such as fruit ripening.

Identify QTLs and candidate genes underlying source-, sink-, and grain yield-related traits in rice by integrated analysis of bi-parental and natural populations.

The source-sink relationship determines the ultimate grain yield of rice. In this study, we used a set of reciprocal introgression lines (ILs) derived from Xuishui09 × IR2061 to map quantitative trait loci (QTLs) that were associated with sink-, source-, and grain yield-related traits. A total of 95 QTLs influencing eight measured traits were identified using 6181 high-quality single nucleotide polymorphism markers. Nine background-independent QTLs were consistently detected in seven chromosomal regions in different genetic backgrounds. Seven QTLs clusters simultaneously affected sink-, source-, and grain yield-related traits, probably due to the genetic basis of significant correlations of grain yield with source and sink traits. We selected 15 candidate genes in the four QTLs consistently identified in the two populations by performing gene-based association and haplotype analyses using 2288 accessions from the 3K project. Among these, LOC_Os03g48970 for qTSN3b, LOC_Os06g04710 for qFLL6a, and LOC_Os07g32510 for qTGW7 were considered as the most likely candidate genes based on functional annotations. These results provide a basis for further study of candidate genes and for the development of high-yield rice varieties by balancing source–sink relationships using marker-assisted selection.

Unraveling waterlogging tolerance-related traits with QTL analysis in reciprocal intervarietal introgression lines using genotyping by sequencing in rapeseed (Brassica napus L.)

Soil waterlogging is a major environmental stress that suppresses the growth and productivity of rapeseed (Brassica napus L.). Natural genetic variations in waterlogging tolerance (WT) were observed but no QTL mapping has been done for WT related traits in rapeseed. In this study, QTL associated with three WT related traits including relative root length (RRL), relative hypocotyl length (RHL) and relative fresh weight (RFW) were dissected using a set of reciprocal introgression lines (ILs) derived from the cross GH01×ZS9, which showed significant difference in WT. Genotyping-by-sequencing (GBS) of the populations were performed, totally 1 468 and 1 450 binned SNPs were identified for GIL (GH01 as the recurrent parent) and ZIL (ZS9 as the recurrent parent) population, respectively. A total of 66 distinct QTLs for WT at the seedling establishment stage including 31 for RRL, 17 for RHL and 18 for RFW were detected. Among the 66 QTLs, 20 (29.4%) QTLs were detected in both genetic backgrounds and then they were integrated into six QTL clusters, which can be targeted in rapeseed breeding for improvement of WT through marker-assisted selection (MAS). Based on the physical positions of SNPs and the functional annotation of the Arabidopsis thaliana genome, 56 genes within the six QTL cluster regions were selected as preliminary candidate genes, then the resequencing and transcriptome information about parents were applied to narrow the extent of candidate genes. Twelve genes were determined as candidates for the six QTL clusters, some of them involved in RNA/protein degradation, most of them involved in oxidation-reduction process. These findings provided genetic resources, candidate genes to address the urgent demand of improving WT in rapeseed breeding.

Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.)

Key messageA novel QTL cluster for appearance quality on Chr07 was identified using reciprocal introgression populations in different locations in China. Two secondary F2populations validated QTL with significant effect on appearance quality.Appearance quality (AQ) is the main determinants of market value of rice. Identification of QTL affecting AQ is the prerequisite for efficient improvement of AQ through marker-assisted selection (MAS). Two sets of reciprocal introgression lines derived from indica Minghui 63 and japonica 02428 were used to dissect the stability of QTL affecting five AQ traits, including grain length, grain width, length to width ratio, percentage of grains with chalkiness, and degree of endosperm chalkiness using 4568 bin genotype produced from 58,000 SNPs across five different environments. A total of 41 and 30 main-effect QTL were identified in MH63 and 02428 backgrounds, respectively. Among them, 9 background-independent QTL (BI-QTL) were found. There were also 13 and 10 stable-expressed QTL (SE-QTL) across at least two environments in MH63 and 02428 backgrounds, respectively. Two important BI- and SE-QTL regions (BISERs) including BISER-I harboring qPGWC5, qDEC5, qGW5.1, and qLWR5 on chromosome 5 and BISER-II harboring qGL7, qLWR7, qPGWC7, and qDEC7 on chromosome 7 were identified. The BISER-II was newly reported and validated by two secondary F2 populations in the reciprocal backgrounds. Among 59 epistatic QTL (E-QTL) detected in this study, there were only four SE- but no BI-E-QTL detected in different environments, indicating that genetic background has stronger effect on AQ traits than the environmental factors, especially for percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC) with lower heritability. BISER-I and BISER-II harboring many BI- and SE-QTL with favorable alleles from slender grain rice are much important for improvement of rice AQ by MAS.

QTL underlying iron and zinc toxicity tolerances at seedling stage revealed by two sets of reciprocal introgression populations of rice (Oryza sativa L.)

Iron and zinc are two trace elements that are essential for rice. But they are toxic at higher concentrations, leading to severe rice yield losses especially in acid soils and inland valleys. In this study, two reciprocal introgression line (IL) populations sharing the same parents were used with high-density SNP bin markers to identify QTL tolerant to iron and zinc toxicities. The results indicated that the japonica variety 02,428 had stronger tolerance to iron and zinc toxicities than the indica variety Minghui 63. Nine and ten QTL contributing to iron and zinc toxicity tolerances, respectively, were identified in the two IL populations. The favorable alleles of most QTL came from 02,428. Among them, qFRRDW2, qZRRDW3, and qFRSDW11 appeared to be independent of genetic background. The region C11S49–C11S60 on chromosome 11 harbored QTL affecting multiple iron and zinc toxicity tolerance-related traits, indicating partial genetic overlap between the two toxicity tolerances. Our results provide essential information and materials for developing excellent rice cultivars with iron and/or zinc tolerance by marker-assisted selection (MAS).

Detecting major QTL associated with resistance to bacterial blight using a set of rice reciprocal introgression lines with high density SNP markers

AbstractBacterial blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is a worldwide rice disease. QTL providing BB resistance were identified using a set of introgression lines (ILs) derived from a cross between Teqing and Lemont, and 3924 evenly distributed SNP markers developed from the two parents. After inoculating three Xoo pathotypes, CII, CIV and CV, seven major BB resistance‐associated QTL were detected. The alleles at all loci with improved BB resistance were from the Teqing background. Four QTL resistance to CII and CIV were identified in the reciprocal backgrounds across 2 years. Six QTL conferring resistance to CV identified in Teqing background were not detected in Lemont background, indicating that genetic background had a strong effect on the BB resistance‐associated QTL. Based on the interactions of 27 significant digenic QTL pairs among the seven main‐effect QTL, the QTL were divided into three strain‐specific groups. Genotype analyses of resistant ILs suggest that rice lines with a high level of resistance to BB can be achieved by pyramiding R gene(s) and QTL that interact with R gene(s).

Genetic background effects on QTL and QTL × environment interaction for yield and its component traits as revealed by reciprocal introgression lines in rice

QTLs for quantitative traits are influenced by genetic background (GB) and environment. Identification of QTL with GB independency and environmental stability is prerequisite for effective marker-assisted selection (MAS). In this study, QTLs and QTL×environment interactions affecting grain yield per plant (GY) and its component traits, filled grain number per panicle (FGN), panicle number per plant (PN) and 1000-grain weight (TGW) across six environments were dissected using two sets of reciprocal introgression lines (ILs) derived from the cross Lemont×Teqing and SNP genotypic data. ANOVA indicated that the differences among genotypes and environments within each set of ILs were highly significant for all traits. A total of 72 distinct QTLs for GY and its component traits including 15 for GY, 25 for FGN, 18 for PN, and 29 for TGW were detected over the six environments. Most QTLs (87.4%) showed significant QTL×environment interactions (QEIs) and appeared to be more or less environment-specific. Among 72 QTLs, 15 (20.8%) QTLs and 12 (16.7%) QEIs were commonly identified in both backgrounds, indicating QTL especially QEI for yield and its component traits had strong GB effects. Four QTL regions affecting GY and its component traits, including S1269707–S4288071, S16661497–S17511092, and S35861863–S36341768 on chromosome 3, and S4134205–S7643153 on chromosome 5, were detected in both backgrounds and coincided with cloned genes for yield-related traits. These regions can be the targeted in rice breeding for high yield potential through MAS. Application of QTL main effects and their environmental interaction effects in MAS was discussed in detail.

Drought-tolerance QTLs commonly detected in two sets of reciprocal introgression lines in rice

Drought is one of the major abiotic stresses limiting rice (Oryza sativa L.) production. Quantitative trait loci (QTLs) for drought tolerance (DT) at the reproductive stage were identified with two sets of reciprocal introgression lines derived from Lemont × Teqing. In total, 29 and 23 QTLs were identified in the Teqing and Lemont backgrounds, respectively, during the reproductive stage under drought and irrigated conditions for spikelet number per panicle, seed fertility, filled grain weight per panicle, plant height, and grain yield per plant. Most of these QTLs showed obvious differential expressions in response to drought stress. Another 21 QTLs were detected by the ratio of trait values under drought stress relative to the normal irrigation conditions in the two backgrounds. For 28 DT QTLs, the Teqing alleles at 23 loci had increased trait values and could improve DT under drought stress. Only five (17.9%) DT QTLs (QSnp1b, QSnp3a, QSnp11, QSf8, and QGyp2a) were consistently detected in the two backgrounds, clearly suggesting overwhelming genetic background effects on QTL detection for DT. Seven of the DT QTL regions identified were found to share the same genomic regions with previously reported DT-related genes. Introgressing or pyramiding of favourable alleles from Teqing at the validated QTLs (QSnp3a, QSnp11 and QGyp2a) into Lemont background may improve DT level of Lemont.

Identification of Stably Expressed Quantitative Trait Loci for Grain Yield and Protein Content Using Recombinant Inbred Line and Reciprocal Introgression Line Populations in Rice

ABSTRACTImprovements of rice (Oryza sativa L.) grain yield and protein content are important breeding objectives. Two hundred forty recombinant inbred lines (RILs) derived from a cross between japonica cultivar Xiushui09 and indica breeding line IR2061‐520‐6‐9 were used to identify quantitative trait loci (QTLs) affecting grain yield per plant (GYP) and protein content (PC) in rice. A total of five main‐effect QTLs (M‐QTLs) were identified on chromosomes 2, 4, 7, 10, and 12, which collectively explained 50.06% of the total phenotypic variance. As for PC, a total of four M‐QTLs were identified on chromosomes 2, 5, 10, and 11, which explained 41.44% of the total phenotypic variance. A total six pairs of epistatic QTLs (E‐QTLs) were identified. Furthermore, the M‐QTLs for GYP and PC detected in the RIL population were confirmed by two sets of BC2F6 reciprocal introgression lines (ILs) derived from the same parents and tested in Sanya and Hangzhou. The results indicated that four M‐QTLs (qGYP‐7 and qGYP‐12 for GYP and qPC‐10 and qPC‐11 for PC) showed stable expressions and consistent pyramiding effects across different environments under different genetic backgrounds. The ILs with pyramided nonallelic alleles at M‐QTLs for GYP from Xiushui09 in IR2061‐520‐6‐9 genetic background or the alleles of M‐QTLs for PC from IR2061‐520‐6‐9 in Xiushui09 genetic background provided some useful information on marker‐assisted selection (MAS) for developing either higher GYP or higher PC cultivars. Two lines, XS‐198 and IR146, with favorable alleles at four M‐QTLs from the two parents showed high GYP and PC and thus could be directly used in production.

Mapping of QTL for Iron and Zinc Toxicity Tolerance at Seedling Stage Using a Set of Reciprocal Introgression Lines of Rice

Ferrum and zinc are essential microelements for rice.However,rice growing in lowland or acid soil is easily subjected to ferrous iron and zinc toxicities which harm plant growth and finally result in deduction of biomass and yield in production.The aim of this study was to identify quantitative trait locus(QTL)underlying ferrous iron toxicity tolerance(FTT)and zinc toxicity tolerance(ZTT)of rice using a reciprocal advanced backcross introgression lines,which was derived from the cross between Lemont(japonica)and Teqing(indica),and 308 evenly distributed single nucleotide polymorphism(SNP)markers developed from the two parents.A total of 42 putative QTLs affecting shoot height(SH),shoot dry weight(SDW),and root dry weight(RDW)under control and stress conditions and for the relative value of the stress to the control were detected,the alleles at most loci improving the tolerance of ferrous and zinc toxicities were from Lemont.Among them,only four QTLs(9.5%)were detected under the two backgrounds,indicating the expression of most QTLs is specific to genetic background.Nine QTLs were detected from the same genetic background affecting the tolerance of both ferrous and zinc toxicities,in which QSdw5 was expressed under the two backgrounds with the same direction and similar quantity of gene additive effect,suggesting that there is a genetic overlap between FTT and ZTT at seedling stage in rice.It is likely,therefore,to improve Teqing's FTT and ZTT by introgressing and pyramiding Lemont favorable alleles at the overlapping QTLs via marker-assisted selection.

Identification of stably expressed QTL for heading date using reciprocal introgression line and recombinant inbred line populations in rice

Two sets of reciprocal introgression lines (ILs) and a population of recombinant inbred lines (RILs) derived from the cross between japonica cultivar Xiushui09 and indica breeding line IR2061-520-6-9 (abbreviated as IR2061) were used to identify QTL for heading date (HD). Phenotyping was conducted in Hainan Island for two winter seasons (2007 and 2009). Nine QTLs were detected in the ILs with Xiushui09 background (XS-ILs), and four of which were repeatedly mapped across 2 years. Five QTLs were identified in the ILs with IR2061 background (IR-ILs), and three of which were commonly detected in 2 years. All commonly detected QTL had the same direction of gene effect. Seven QTL for HD were identified in the RILs in 2009. Only three (25%) QTLs were commonly detected using all the three populations (XS-ILs, IR-ILs and RILs). The number of commonly identified QTLs among populations was related to degree of similarity of their genetic backgrounds, suggesting that the genetic background effect is important for detecting HD QTL. QHd7 and QHd10b stably expressed in different populations and across years thus would be exploited in rice breeding programme. Moreover, lines with both of QHd7 and QHd10b resulted in at least 3 days earlier than lines with only one of them QTL, showing evident pyramiding effect.

Novel loci for field resistance to black-streaked dwarf and stripe viruses identified in a set of reciprocal introgression lines of rice (Oryza sativa L.)

Rice black-streaked dwarf virus (RBSDV) and stripe virus (RSV) are the two chronic viral diseases causing great damage to rice (Oryza sativa L.) production in China, and both are transmitted by the small brown planthopper (SBPH, Laodelphaxstriatellus Fallen). Quantitative trait loci (QTL) affecting field resistance to these two viral diseases were identified using QTL mapping software in a set of reciprocal introgression lines derived from the cross between Lemont and Teqing. A panel of 119 landraces was used for marker confirmation and allele mining. A total of 17 quantitative resistance loci (QRL) for the infection incidences of RBSDV and RSV were discovered and belong to 16 regions on all chromosomes except chromosome 12. Among them, 12 QRL were confirmed by association mapping, and many novel alleles at these loci were mined from the set of landraces. Only one region was found to be responsible for the genetic overlap between the field resistance against RBSDV and RSV, which was reported to be associated with SBPH resistance. The favorable alleles at the above novel and/or overlapping loci should be effective for marker-assisted selection breeding for resistance against the two diseases and the insect. Different strategies of varietal development and effective deployment against the two viral diseases are also discussed.

Identification of salt-tolerant QTLs with strong genetic background effect using two sets of reciprocal introgression lines in rice

Effect of genetic background on detection of quantitative trait locus (QTL) governing salinity tolerance (ST) was studied using two sets of reciprocal introgression lines (ILs) derived from a cross between a moderately salinity tolerant japonica variety, Xiushui09 from China, and a drought tolerant but salinity susceptible indica breeding line, IR2061-520-6-9 from the Philippines. Salt toxicity symptoms (SST) on leaves, days to seedling survival (DSS), and sodium and potassium uptake by shoots were measured under salinity stress of 140mmol/L of NaCl. A total of 47 QTLs, including 26 main-effect QTLs (M-QTLs) and 21 epistatic QTLs (E-QTLs), were identified from the two sets of reciprocal ILs. Among the 26M-QTLs, only four (15.4%) were shared in the reciprocal backgrounds while no shared E-QTLs were detected, indicating that ST QTLs, especially E-QTLs, were very specific to the genetic background. Further, 78.6% of the M-QTLs for SST and DSS identified in the reciprocal ILs were also detected in the recombinant inbred lines (RILs) from the same cross, which clearly brings out the background effect on ST QTL detection and its utilization in ST breeding. The detection of ILs with various levels of pyramiding of nonallelic M-QTL alleles for ST from Xiushui09 into IR2061-520-6-9 allowed us to further improve the ST in rice.

Genetic Effects of Background‐Independent Loci for Grain Weight and Shape Identified using Advanced Reciprocal Introgression Lines from Lemont × Teqing in Rice

ABSTRACTGenetic background effect and environmental sensitivity are two major obstacles for marker‐assisted breeding (MAB) of complex traits. Background‐independent (BI) loci for 1000‐grain weight (TGW) and grain shape (GS) were detected over three seasons using a set of reciprocal introgression lines (ILs) from Lemont × Teqing cross with parents having distinctive GS but equal TGW. Reciprocal ILs in advanced (F11–13) generations were genotyped using 142 polymorphic simple sequence repeat (SSR) markers on 64 chromosome bins. Nineteen bins of BI loci significantly associated with TGW and/or GS that were identified consistently over multiple seasons and additive effects were in the opposite directions at the same loci between two backgrounds. These 19 bins could be classified into three types: Type I includes four genetic overlapping bins affecting both TGW and GS, Type II includes nine genetic overlapping bins controlling GS component traits, and Type III includes six bins for single GS component. Among them, five stably expressed BI loci (bins 2.2, 2.5, and 3.7 for grain length [GL] and bins 5.2 and 7.4 for grain width [GW]) found consistently over three seasons would be the first choice for MAB. Secondary choice would be the loci that expressed over at least over two seasons and include bins 1.2, 3.3, 4.3 for GL and bins 7.1 and 11.5 for GW. Two related key traits, one for yield (TGW) and the other for grain quality (GS), can now be fully utilized through marker‐aided transfer or pyramiding of the identified BI loci in rice (Oryza sativa L.) improvement programs.

Genetic Background Effect on QTL Expression of Heading Date and Plant Height and Their Interaction with Environment in Reciprocal Introgression Lines of Rice

Expression of quantitative trait is affected by genetic background and environment.Genetic background effect on QTL mapping and QTL by environment interaction for heading date(HD)and plant height(PH)in Beijing and Hainan environments were dissected using a large set of reciprocal introgression lines(ILs)derived from a japonica variety"Lemont"and indica variety"Teqing".The two sets of ILs showed transgressive segregation for the two traits.Total 16 and 17 main-effect QTLs were identified for HD and PH in the two environments,respectively.Among them,only five main-effect QTLs(QHd2,QHd8a,QPh3, QPh5,and QPh12)were detected under the two backgrounds,indicating expression of most main-effect QTLs are specific to genetic background.Three main-effect QTLs(QHd8a,QHd9,and QHd10b)by environment interactions for HD were significantly detected under the two backgrounds,of which that of QHd8a had earlier heading for 2–3 days in Hainan,but delayed heading for 2–3 days in Beijing.Therefore,QHd8a could be considered as an important main-effect QTL for HD.By comparison with the QTL mapping results previously identified in the seven different mapping populations derived from the same parents indifferent environments,some stably expressed main-effect QTLs including QHd3,QHd8a,QPh3,and QPh4 were identified under different backgrounds and environments,suggesting these QTLs could be used in marker-assisted breeding for HD and PH. On the basis of the mapping information,marker-assisted improvement of HD for a rice variety under different environments was deeply discussed.

Effect of Genetic Background on QTLs for Heading Date and Plant Height and Interactions Between QTL and Environment Using Reciprocal Introgression Lines in Rice

Expression of quantitative trait locus (QTL) is affected by genetic background (GB) and environment. The GB effect on QTL mapping and QTL by environment interaction for heading date (HD) and plant height (PH) were studied in Beijing and Hainan environments using a large set of reciprocal introgression lines (ILs) derived from a japonica rice ( Oryza sativa L.) variety Lemont and an indica variety Teqing. In both environments, the 2 IL populations showed transgressive segregation for HD and PH traits. A total of 16 and 17 main-effect QTLs (M-QTLs) were identified for HD and PH, respectively. Among them, only 5 M-QTLs were detected under the 2 GBs, indicating that the expressions of most M-QTLs are specific to GB. Under both GBs, significant interactions between QTLs and environment responsible for HD were observed at 3 M-QTLs, of which QHd8a antedated heading for 2–3 d in Hainan but delayed heading for 2–3 d in Beijing. Therefore, QHd8a could be considered as an important M-QTL for HD. By comparing with the previous results on QTL mapping using another 7 populations derived from the same parents, a few M-QTLs were found to express stably under different GBs in various environments, such as QHd3, QHd8a, QPh3, and QPh4. These QTLs show applicable potential in marker-assisted breeding for HD and PH in rice.

Genetic Background Effect on QTL Mapping for Salt Tolerance Revealed by a Set of Reciprocal Introgression Line Populations in Rice

QTLs for salt tolerance (ST) related traits including score of salt toxicity of leaves (SST), survival days of seedlings (SDS), shoot K+ concentration (SKC) and shoot Na+ concentration (SNC) were detected using the reciprocal introgression lines (ILs) derived from a cross between japonica variety "Lemont" and indica variety "Teqing" under salt stress treatment with the concentration of 140 mmol L?1 NaCl in green house and phytotron. Both genetic backgrounds of the two sets of ILs were similar to their respective parents. On the average, Lemont genome accounted for 83.8% in Lemont background-ILs whereas 88.9% of Teqing genome in Teqing background-ILs. Continuous variation and transgressive segregation for all ST-related traits were ob-served in the two IL populations with overlaps of frequency distributions for most traits, suggesting the gene effect of reciprocal introgression of the two parents on each ST-related trait was almost equivalent. Eighteen QTLs for all ST-related traits were iden-tified for each of the two IL populations. No any a common QTL for the same trait was detected in the reciprocal IL populations, indicating there was a strong genetic background effect on expression of ST-QTLs, and also suggesting these ST-QTLs had rela-tively small phenotypic effect. Only one common QTL affecting SKC was identified in Teqing background-ILs under green house and phototron environments, indicating there was a strong interaction of ST-QTL with environment. Although the two parents are moderately susceptible to salt stress, QTL mapping results indicated that some favorable alleles beneficial to improvement of ST-related traits do exist in the parents. Therefore, it is possible to develop a new variety with improved ST by identifying and mining this kind of "hidden" ST-genes existed in the modern varieties through molecular marker technology and further pyramid-ing these non-allelic alleles via marker-assisted selection.