Identification of QTLs with main, epistatic and QTL?×?environment interaction effects for salt tolerance in rice seedlings under different salinity conditions

Salt tolerance of rice (Oryza sativa L.) at the seedling stage is one of the major determinants of its stable establishment in saline soil. One population of recombinant inbred lines (RILs, F (2:9)) derived from a cross between the salt-tolerant variety Jiucaiqing and the salt-sensitive variety IR26 was used to determine the genetic mechanism of four salt tolerance indices, seedling height (SH), dry shoot weight (DSW), dry root weight (DRW) and Na/K ratios (Na/K) in roots after 10 days in three salt concentrations (0.0, 0.5 and 0.7 % NaCl). The main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) were detected by QTL IciMapping program using single environment phenotypic values. Eleven M-QTLs and 11 E-QTLs were identified for the salt tolerance indices. There were six M-QTLs and two E-QTLs identified for SH, three M-QTLs and five E-QTLs identified for DSW, two M-QTLs and one E-QTL identified for DRW, and three E-QTLs identified for Na/K. The phenotypic variation explained by each M-QTL and E-QTL ranged from 7.8 to 23.9 % and 13.3 to 73.7 %, respectively. The QTL-by-environment interactions were detected by QTLNetwork program in the joint analyses of multi-environment phenotypic values. Six M-QTLs and five E-QTLs were identified. The phenotypic variation explained by each QTL and QTL × environment interaction ranged from 0.95 to 6.90 % and 0.02 to 0.50 %, respectively. By comparing chromosomal positions of these M-QTLs with those previously identified, five M-QTLs qSH1.3, qSH12.1, qSH12.2, qDSW12.1 and qDRW11 might represent novel salt tolerance genes. Five selected RILs with high salt tolerance had six to eight positive alleles of the M-QTLs, indicating that pyramiding by marker-assisted selection (MAS) of M-QTLs can be applied in rice salt tolerance breeding programs.     

Comparison of molecular linkage maps and QTLs for morphological traits in two reciprocal backcross populations of rice

Comparison of maps and QTLs between populations may provide us with a better understanding of molecular maps and the inheritance of traits. We developed and used two reciprocal BC1F1 populations, IP/DS//IP and IP/DS//DS, for QTL analysis. DS (Dasanbyeo) is a Korean tongil-type cultivar (derived from an indica x japonica cross and similar to indica in its genetic make-up) and IP (Ilpumbyeo) is a Korean japonica cultivar. We constructed two molecular linkage maps corresponding to each backcross population using 196 markers for each map. The length of each chromosome was longer in the IP/DS//IP population than in the IP/DS//DS population, indicating that more recombinants were produced in the IP/DS//IP population. Distorted segregation was observed for 44 and 19 marker loci for the IP/DS//IP and IP/DS//DS populations, respectively; these were mostly skewed in favor of the indica alleles. A total of 36 main effect QTLs (M-QTLs) and 15 digenic epistatic interactions (E-QTLs) were detected for the seven traits investigated. The phenotypic variation explained (PVE) by M-QTLs ranged from 3.4% to 88.2%. Total PVE of the M-QTLs for each trait was significantly higher than that of the E-QTLs. The total number of M-QTLs identified in the IP/DS//IP population was higher than in the IP/DS//DS population. However, the total PVE by the M-QTLs and E-QTLs together for each trait was similar in the two populations, suggesting that the two BC1F1 populations are equally useful for QTL analysis. Maps and QTLs in the two populations were compared. Eleven new QTLs were identified for SN, SF, GL, and GW in this study, and they will be valuable in marker-assisted selection, particularly for improving grain traits in tongil-type varieties.     

QTLs influencing panicle size detected in two reciprocal introgressive line (IL) populations in rice (Oryza sativa L.)

Two sets of reciprocal introgression line (IL) populations, i.e., ILs with Lemont as recurrent parent (IL_LT) and ILs with Teqing as recurrent parent (IL_TQ), were developed and evaluated for traits representing panicle size, including primary branch number (PBN), secondary branch number (SBN), and spikelet number per panicle (SNP). Together with the regression to recurrent parent by advanced backcross, transgressive segregations were observed for all traits. Correlation and regression analysis showed that SBN had much higher contribution to SNP than PBN. It was confirmed by the QTL analysis that many common loci were detected between SBN and SNP, in comparison with single common locus between PBN and SNP. One and three main effect QTLs (M-QTLs) were detected for PBN in IL_LT and IL_TQ, respectively. Six M-QTLs per trait per populations were associated with SBN and SNP. Less number and lower contribution of epistasis were detected in IL populations in comparison with mapping result from F ₂ or RI population. There were only four QTLs in fourteen loci (near 30%) commonly detected in both reciprocal IL populations implying the large impact of genetic background on QTLs expression. H. W. Mei and J. L. Xu contributed equally to this work.     

Additive and over-dominant effects resulting from epistatic loci are the primary genetic basis of heterosis in rice

A set of 148 F9 recombinant inbred lines (RILs) was developed from the cross of an indica cultivar 93-11 and japonica cultivar DTT13,showing strong F1 heterosis.Subsequently,two backcross F1 (BCF1) populations were constructed by backcrossing these 148 RILs to two parents,93-11 and DT713.These three related populations (281BCF1 lines,148 RILs) were phenotyped for six yield-related traits in two locations.Significant inbreeding depression was detected in the population of RILS and a high level of heterosis was observed in the two BCF1 populations.A total of 42 main-effect quantitative trait loci (M-QTLs) and 109 epistatic effect QTL pairs (E-QTLs) were detected in the three related populations using the mixed model approach.By comparing the genetic effects of these QTLs detected in the RILs,BCF1 performance and mid-parental heterosis (HMp),we found that,in both BCF1 populations,the QTLs detected could be classified into two predominant types:additive and over-domlnant loci,which indicated that the additive and over-dominant effect were more important than complete or partially dominance for M-QTLs and E-QTLs.Further,we found that the E-QTLs detected collectively explained a larger portion of the total phenotypic variation than the M-QTLs in both RILs and BCF1 populations.All of these results suggest that additive and over-dominance resulting from epistatic loci might be the primary genetic basis of heterosis in rice.     

Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachis hypogaea L.)

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 x ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2-3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48-33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3-15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54-44.72% PVE) and 63 (7.11-21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7-8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2-9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut.     

Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two testcross populations

To understand the types of gene action controlling seven quantitative traits in rice, QTL mapping was performed to dissect the main effect (M-QTLs) and digenic epistatic (E-QTLs) QTLs responsible for the trait performance of 254 recombinant inbred lines (RILs) of "Lemont/Teqing", and two testcross (TC) F(1) populations derived from these RILs. The correlation analyses reveal a general pattern, i.e. trait heritability in the RILs was negatively correlated to trait heterosis in the TC hybrids. A large number of M-QTLs and E-QTLs affecting seven traits, including heading date (HD), plant height (PH), flag leaf length (FLL), flag leaf width (FLW), panicle length (PL), spikelet number per panicle (SN) and spikelet fertility (SF), were identified and could be classified into two predominant groups, additive QTLs detected primarily in the RILs, and overdominant QTLs identified exclusively in the TC populations. There is little overlap between QTLs identified in the RILs and in the TC populations. This result implied that additive gene action is largely independent from non-additive gene action in the genetic control of quantitative traits of rice. The detected E-QTLs collectively explained a much greater portion of the total phenotypic variation than the M-QTLs, supporting prior findings that epistasis has played an important role in the genetic control of quantitative traits in rice. The implications of these results to the development of inbred and hybrid cultivars were discussed.     

Genetic basis of pre-harvest sprouting tolerance using single-locus and two-locus QTL analyses in bread wheat

Quantitative trait loci (QTL) analysis for pre-harvest sprouting tolerance (PHST) in bread wheat was conducted following single-locus and two-locus analyses, using data on a set of 110 recombinant inbred lines (RILs) of the International Triticeae Mapping Initiative population grown in four different environments. Single-locus analysis following composite interval mapping (CIM) resolved a total of five QTLs with one to four QTLs in each of the four individual environments. Four of these five QTLs were also detected following two-locus analysis, which resolved a total of 14 QTLs including 8 main effect QTLs (M-QTLs), 8 epistatic QTLs (E-QTLs) and 5 QTLs involved in QTL × environment (QE) or QTL × QTL × environment (QQE) interactions, some of these QTLs being common. The analysis revealed that a major fraction (76.68%) of the total phenotypic variation explained for PHST is due to M-QTLs (47.95%) and E-QTLs (28.73%), and that only a very small fraction of variation (3.24%) is due to QE and QQE interactions. Thus, more than three-quarters of the genetic variation for PHST is fixable and would contribute directly to gains under selection. Two QTLs that were detected in more than one environment and at LOD scores above the threshold values were located on 3BL and 3DL presumably in the vicinity of the dormancy gene TaVp1. Another QTL was found to be located on 3B, perhaps in close proximity to the R gene for red grain colour. However, these associations of QTLs for PHST with genes for dormancy and grain colour are only suggestive. The results obtained in the present study suggest that PHST is a complex trait controlled by large number of QTLs, some of them interacting among themselves or with the environment. These QTLs can be brought together through marker-aided selection, leading to enhanced PHST.     

Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two backcross populations

To understand the types of gene action controlling seven quantitative traits in rice, we carried out quantitative trait locus (QTL) mapping in order to distinguish between the main-effect QTLs (M-QTLs) and digenic epistatic QTLs (E-QTLs) responsible for the trait performance of 254 recombinant inbred lines (RILs) from rice varieties Lemont/Teqing and two backcross hybrid (BCF₁) populations derived from these RILs. We identified 44 M-QTL and 95 E-QTL pairs in the RI and BCF₁ populations as having significant effects on the mean values and mid-parental heterosis of heading date, plant height, flag leaf length, flag leaf width, panicle length, spikelet number and spikelet fertility. The E-QTLs detected collectively explained a larger portion of the total phenotypic variation than the M-QTLs in both the RI and BCF₁ populations. In both BCF₁ populations, over-dominant (or under-dominant) loci were more important than additive and complete or partially dominant loci for M-QTLs and E-QTL pairs, thereby supporting prior findings that overdominance resulting from epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice.     

Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein content

In hexaploid wheat, single-locus and two-locus quantitative trait loci (QTL) analyses for grain protein content (GPC) were conducted using two different mapping populations (PI and PII). Main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL x environment interactions (QE, QQE) were detected using two-locus analyses in both the populations. Only a few QTLs were common in both the analyses, and the QTLs and the interactions detected in the two populations differed, suggesting the superiority of two-locus analysis and the need for using several mapping populations for QTL analysis. A sizable proportion of genetic variation for GPC was due to interactions (28.59% and 54.03%), rather than to M-QTL effects (7.24% and 7.22%), which are the only genetic effects often detected in the majority of QTL studies. Even E-QTLs made a marginal contribution to genetic variation (2.68% and 6.04%), thus suggesting that the major part of genetic variation is due to changes in gene networks rather than the presence or absence of specific genes. This is in sharp contrast to the genetic dissection of pre-harvest sprouting tolerance conducted by us earlier, where interaction effects were not substantial, suggesting that the nature of genetic variation also depends on the nature of the trait.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

Identification of quantitative trait loci associated with salt tolerance at seedling stage from Oryza rufipogon

Soil salinity is one of the major abiotic stresses affecting plant growth and crop production.In the present study,salt tolerance at rice seedling stage was evaluated using 87 introgression lines (ILs),which were derived from a cross between an elite indica cultivar Teqing and an accession of common wild rice (Oryza rufipogon Griff.).Substantial variation was observed for four traits including salt tolerance score (STS),relative root dry weight (RRW),relative shoot dry weight (RSW) and relative total dry weight (RTW).STS was significantly positively correlated with all other three traits.A total of 15 putative quantitative trait loci (QTLs) associated with these four traits were detected using single-point analysis,which were located on chromosomes 1,2,3,6,7,9 and 10 with 8％-26％ explaining the phenotypic variance.The O.rufipogon-derived alleles at 13 QTLs (86.7％) could improve the salt tolerance in the Teqing background.Four QTL clusters affecting RRW,RSW and RTW were found on chromosomes 6,7,9 and 10,respectively.Among these four QTL clusters,a major cluster including three QTLs (qRRW10,qRSW10 and qRTW10) was found near the maker RM271 on the long arm of chromosome 10,and the O.rufipogon-derived alleles at these three loci increased RRW,RSW and RTW with additive effects of 22.7％,17.3％ and 18.5％,respectively,while the phenotypic variance explained by these three individual QTLs for the three traits varied from 19％ to 26％.In addition,several salt tolerant ILs were selected and could be used for identifying and utilizing favorable salt tolerant genes from common wild rice and used in the salt tolerant rice breeding program.     

Mapping of QTLs governing agronomic and yield traits in chickpea

Chickpea is one of the most important leguminous cool season food crops, cultivated prevalently in South Asia and Middle East. The main objective of this study was to identify quantitative trait loci (QTLs) associated with seven agronomic and yield traits in two recombinant inbred line populations of chickpea derived from the crosses JG62 × Vijay (JV population) and Vijay × ICC4958 (VI population) from at least three environments. Single locus QTL analysis involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated traits to detect pleiotropic QTLs. Two-locus analysis was conducted to identify the main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions. Through CIM analysis, a total of 106 significant QTLs (41 in JV and 65 in VI populations) were identified for the seven traits, of which one QTL each for plant height and days to maturity was common in both the populations. Six pleiotropic QTLs that were consistent over the environments were also identified. LG2 in JV and LG1a in VI contained at least one QTL for each trait. Hence, concentrating on these LGs in molecular breeding programs is most likely to bring simultaneous improvement in these traits.     

QTL mapping for quantities of protein fractions in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

One of the key targets of breeding programs in bread wheat is to improve the end-use quality. The relationships between quantities of protein fractions and dough rheological characters have been well established, but there is little information on the genetic control of quantities of protein fractions. Two hundred and forty F₆ recombinant inbred lines derived from a cross between two Chinese wheat cultivars, PH82-2 and Neixiang 188, were sown at Jiaozuo in Henan province in the 2005–2006 and 2006–2007 cropping seasons, and inclusive composite interval mapping was used to dissect main effect quantitative trait loci (M-QTLs) and digenic epistatic QTLs (E-QTLs) for quantities of protein fractions. A total of 55 M-QTLs and 77 pairs of E-QTLs affecting the quantities of protein fractions including GLU-A1 (QGA1), GLU-B1 (QGB1), GLU-D1 (QGD1), HMW-GS (QHMW), GLU-A3 (QGA3), GLU-B3 (QGB3), LMW-GS (QLMW), glutenin (QGLU) and the ratio of the quantity of glutenin to those of gliadin were identified, with M-QTLs contributing 39.3–95.6% of the phenotypic variance explained (PVE), and E-QTLs accounting for 1.4–33.5% of the PVE. Among the M-QTLs, 33 were consistent in two seasons and in the mean value of two seasons with similar effects in both magnitude and direction, including major genes on HMW and LMW glutenin loci linked to Sec1 and Glu-B1c, Glu-D1d, Glu-A3a, and grain hardness locus Ha, indicating that these genes were the most important determinants of gluten strength, and they might have significant effects on dough properties not only through effects on allelic composition, but also by influencing quantities of protein fractions. The effects of E-QTLs were more influenced by environments, compared with those of M-QTLs, with only two pairs of E-QTLs consistent in two seasons and in the mean value of two seasons. The M-QTLs were detected in 12 marker intervals, all of which involved E-QTLs on quantities of protein fractions, whereas only 40 of 77 pairs of E-QTLs involved intervals in which M-QTLs were detected. The results indicated that besides main effects, epistatic effects were also important factors in determining quantities of protein fractions in wheat.     

Quantitative trait loci for cold tolerance of rice recombinant inbred lines in low temperature environments

Low temperature is one of the major environmental stresses in rice cultivation in high-altitude and high-latitude regions. In this study, we cultivated a set of recombinant inbred lines (RIL) derived from Dasanbyeo (indica) / TR22183 (japonica) crosses in Yanji (high-latitude area), Kunming (high-altitude area), Chuncheon (cold water irrigation) and Suwon (normal) to evaluate the main effects of quantitative trait loci (QTL) and epistatic QTL (E-QTL) with regard to their interactions with environments for cold-related traits. Six QTLs for spikelet fertility (SF) were identified in three cold treatment locations. Among them, four QTLs on chromosomes 2, 7, 8, and 10 were validated by several near isogenic lines (NILs) under cold treatment in Chuncheon. A total of 57 QTLs and 76 E-QTLs for nine cold-related traits were identified as distributing on all 12 chromosomes; among them, 19 QTLs and E-QTLs showed significant interactions of QTLs and environments (QEIs). The total phenotypic variation explained by each trait ranged from 13.2 to 29.1% in QTLs, 10.6 to 29.0% in EQTLs, 2.2 to 8.8% in QEIs and 1.0% to 7.7% in E-QTL × environment interactions (E-QEIs). These results demonstrate that epistatic effects and QEIs are important properties of QTL parameters for cold tolerance at the reproductive stage. In order to develop cold tolerant varieties adaptable to wide-ranges of cold stress, a strategy facilitating marker-assisted selection (MAS) is being adopted to accumulate QTLs identified from different environments.     

Identification of main effect and epistatic quantitative trait loci for morphological and yield-related traits in peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

An effort was made in the present study to identify the main effect and epistatic quantitative trait locus (QTL) for the morphological and yield-related traits in peanut. A recombinant inbred line (RIL) population derived from TAG 24 × GPBD 4 was phenotyped in seven environments at two locations. QTL analysis with available genetic map identified 62 main-effect QTLs (M-QTLs) for ten morphological and yield-related traits with the phenotypic variance explained (PVE) of 3.84–15.06%. Six major QTLs (PVE >?10%) were detected for PLHT, PPP, YPP, and SLNG. Stable M-QTLs appearing in at least two environments were detected for PLHT, LLN, YPP, YKGH, and HSW. Five M-QTLs governed two traits each, and 16 genomic regions showed co-localization of two to four M-QTLs. Intriguingly, a major QTL reported to be linked to rust resistance showed pleiotropic effect for yield-attributing traits like YPP (15.06%, PVE) and SLNG (13.40%, PVE). Of the 24 epistatic interactions identified across the traits, five interactions involved six M-QTLs. Three interactions were additive × additive and remaining two involved QTL × environment (QE) interactions. Only one major M-QTL governing PLHT showed epistatic interaction. Overall, this study identified the major M-QTLs for the important productivity traits and also described the lack of epistatic interactions for majority of them so that they can be conveniently employed in peanut breeding.     

Detection and verification of malting quality QTLs using wild barley introgression lines

A malting quality quantitative trait locus (QTL) study was conducted using a set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs). Each S42IL harbors a single marker-defined chromosomal segment from the wild barley accession ‘ISR 42-8’ (Hordeum vulgare ssp. spontaneum) within the genetic background of the elite spring barley cultivar ‘Scarlett’ (Hordeum vulgare ssp. vulgare). The aim of the study was (1) to verify genetic effects previously identified in the advanced backcross population S42, (2) to detect new QTLs, and (3) to identify S42ILs exhibiting multiple QTL effects. For this, grain samples from field tests in three different environments were subjected to micro malting. Subsequently, a line × phenotype association study was performed with the S42ILs in order to localize putative QTL effects. A QTL was accepted if the trait value of a particular S42IL was significantly (P < 0.05) different from the recurrent parent as a control, either across all tested environments or in a particular environment. For eight malting quality traits, altogether 40 QTLs were localized, among which 35 QTLs (87.5%) were stable across all environments. Six QTLs (15.0%) revealed a trait improving wild barley effect. Out of 36 QTLs detected in a previous advanced backcross QTL study with the parent BC₂DH population S42, 18 QTLs (50.0%) could be verified with the S42IL set. For the quality parameters α-amylase activity and Hartong 45°C, all QTLs assessed in population S42 were verified by S42ILs. In addition, eight new QTL effects and 17 QTLs affecting two newly investigated traits were localized. Two QTL clusters harboring simultaneous effects on eight and six traits, respectively, were mapped to chromosomes 1H and 4H. In future, fine-mapping of these QTL regions will be conducted in order to shed further light on the genetic basis of the most interesting QTLs.     

Individual QTLs controlling quantitative variation in blood pressure inherited in a Mendelian mode

We studied three possible genotypes at 10 well-defined blood pressure (BP) QTLs using congenic rat lines. The central question was whether the hypertensive or normotensive allele is dominant, or whether there is partial dominance. The congenic strains were employed to investigate the BP effects of alleles originating from normotensive rats in the background of hypertensive Dahl salt-sensitive (DSS) rats. The normotensive alleles at eight QTLs were fully dominant over DSS alleles, which we tentatively interpreted as indicating that DSS rats incurred a loss of function at these loci and that the QTLs produced BP-reducing agents. In contrast, the normotensive allele of only one QTL was recessive over its DSS counterpart, implying a gain of function at this QTL or a null allele involved in generating a BP-elevating agent. Only one locus, C17QTL, had alleles exhibiting partial dominance. These estimates of dominance differ considerably from those obtained by QTL analysis in a F2 cross. This disagreement demonstrates the importance of establishing a cause-effect relationship between a QTL and its phenotypic effect via congenic strains. The dominance relationships suggest pertinent strategies for gene identification and pharmaceutical intervention.     

Introgression of dual abiotic stress tolerance QTLs (Saltol QTL and Sub1 gene) into Rice (Oryza sativa L.) variety Aiswarya through marker assisted backcross breeding

Salinity and submergence are two very prominent abiotic stress conditions affecting rice yield adversely in the coastal agro ecosystem. Marker Assisted Backcross Breeding (MABB) is an efficient and fast track molecular tool to incorporate a desired stress tolerant QTL/gene into an improved cultivar. The present study was carried out for the introgression of Saltol QTL responsible for salinity tolerance and Sub1 gene responsible for submergence tolerance into the high yielding rice variety Aiswarya independently through MABB. Final objective of the study is to develop dual stress tolerant (tolerance to salinity and submergence) Aiswarya rice variety by pyramiding the both target QTLs introgressed BC₂F₂ progenies having maximum background homozygosity. The donors of Saltol QTL and Sub1 gene used in the present study were FL478 and Swarna Sub1, respectively. Based on the background genome analysis of the introgressed plants, the plants with > 85–90% background similarity were selected for pyramiding of Saltol QTL and Sub1 gene into the elite background of rice variety Aiswarya. Those selected introgressed lines with Saltol QTL and Sub1 gene will be again crossed to pyramid both Saltol QTL and Sub1 gene into the rice variety Aiswarya. Such a mega rice variety pyramided with dual stress tolerant QTLs is the expected outcome of this study and can be recommended for cultivation in the flood prone saline coastal agroecosystem.     

Comparative QTL analysis of salinity tolerance in terms of fruit yield using two solanum populations of F<Subscript>7</Subscript> lines

Salt tolerance has been analysed in two populations of F₇ lines developed from a salt sensitive genotype of Solanum lycopersicum var. cerasiforme, as female parent, and two salt tolerant lines, as male parents, from S. pimpinellifolium, the P population (142 lines), and S. cheesmaniae, the C population (116 lines). Salinity effects on 19 quantitative traits including fruit yield were investigated by correlation, principal component analysis, ANOVA and QTL analysis. A total of 153 and 124 markers were genotyped in the P and C populations, respectively. Some flowering time and salt tolerance candidate genes were included. Since most traits deviated from a normal distribution, results based on the Kruskal–Wallis non-parametric test were preferred. Interval mapping methodology and ANOVA were also used for QTL detection. Eight out of 15 QTLs at each population were detected for the target traits under both control and high salinity conditions, and among them, only average fruit weight (FW) and fruit number (FN) QTLs (fw1.1, fw2.1 and fn1.2) were detected in both populations. The individual contribution of QTLs were, in general, low. After leaf chloride concentration, flowering time is the trait most affected by salinity because different QTLs are detected and some of their QTL×E interactions have been found significant. Also reinforcing the interest on information provided by QTL analysis, it has been found that non-correlated traits may present QTL(s) that are associated with the same marker. A few salinity specific QTLs for fruit yield, not associated with detrimental effects, might be used to increase tomato salt tolerance. The beneficial allele at two of them, fw8.1 (in C) and tw8.1 (for total fruit weight in P) corresponds to the salt sensitive parent, suggesting that the effect of the genetic background is crucial to breed for wide adaptation using wild germplasm.     

Introgression of Drought Tolerance into Elite Basmati Rice Variety through Marker-Assisted Backcrossing

Drought is one of the major abiotic threat to rice production in the context of climate change. Super Basmati is an elite, fine grain basmati rice variety grown in Punjab, Pakistan. Due to drought sensitive in nature, its yield has been facing an alarming situation in production because of gradual decrease in irrigated water for a couple of years. Three reported novel QTLs for drought tolerance were selected for incorporation into Super Basmati by employing marker assisted selection strategy. IR55419-04 with novel QTLs was used as a donor parent. Foreground selection was performed by applying PCR based QTL linked SSR markers followed by recombinant selection by using 2–4 flanking markers. Background selection was exercised by using polymorphic SSR markers for maximum genome recovery of the Super Basmati. The individuals homozygous at the target QTLs and with maximum background of Super Basmati at the rest of the non-target genome was selected for evaluation of drought tolerance. Under drought stress conditions, the yields of all introgressed lines (ILs) were 44.2%–125.7% higher than recurrent parent. Six superior ILs that are drought tolerant and very similar to Super Basmati in terms of agronomic and grain quality traits are marked for release as drought-tolerant varieties in arid regions or for use in breeding programs of high grain quality and drought-tolerant parents.