A novel allele of <Emphasis Type="Italic">TaGW2</Emphasis>-<Emphasis Type="Italic">A1</Emphasis> is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Key message

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat.

Abstract

Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5′ flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

     

Mapping and validation of quantitative trait loci for spikelets per panicle and 1,000-grain weight in rice (Oryza sativa L.)

This study identified four and five quantitative trait loci (QTLs) for 1,000-grain weight (TGW) and spikelets per panicle (SPP), respectively, using rice recombinant inbred lines. QTLs for the two traits (SPP3a and TGW3a, TGW3b and SPP3b) were simultaneously identified in the two intervals between RM3400 and RM3646 and RM3436 and RM5995 on chromosome 3. To validate QTLs in the interval between RM3436 and RM5995, a BC₃F₂ population was obtained, in which TGW3b and SPP3b were simultaneously mapped to a 2.6-cM interval between RM15885 and W3D16. TGW3b explained 50.4% of the phenotypic variance with an additive effect of 1.81 g. SPP3b explained 29.1% of the phenotypic variance with an additive effect of 11.89 spikelets. The interval had no effect on grain yield because it increased SPP but decreased TGW and vice versa. Grain shape was strongly associated with TGW and was used for QTL analysis in the BC₃F₂ population. Grain length, grain width, and grain thickness were also largely controlled by TGW3b. At present, it is not clear whether one pleiotropic QTL or two linked QTLs were located in the interval. However, the conclusion could be made ultimately by isolation of TGW3b. The strategy for TGW3b isolation is discussed.     

Four rice QTL controlling number of spikelets per panicle expressed the characteristics of single Mendelian gene in near isogenic backgrounds

Development of quantitative trait loci (QTL) near isogenic lines is a crucial step to QTL isolation using the strategy of map-based cloning. In this study, a recombinant inbred line (RIL) population derived from two indica rice varieties, Zhenshan 97 and HR5, was employed to map QTL for spikelets per panicle (SPP). One major QTL (qSPP7) and three minor QTL (qSPP1, qSPP2 and qSPP3) were identified on chromosomes 7, 1, 2 and 3, respectively. Four sets of near isogenic lines (NILs) BC₄F₂ targeted for the four QTL were developed by following a standard procedure of consecutive backcross, respectively. These QTL were not only validated in corresponding NILs, but also explained amounts of phenotypic variation with much larger LOD scores compared with those identified in RILs. SPP in the four QTL-NILs expressed bimodal or discontinuous distributions and followed the expected segregation ratio of single Mendelian factor by progeny test. Finally, qSPP1, qSPP2, qSPP3 and qSPP7 were respectively mapped to a locus, 0.5 cM from MRG2746, 0.6 cM from MRG2762, 0.8 cM from RM49 and 0.7 cM from MRG4436, as co-dominant markers on the basis of progeny tests. These results indicate no matter how small effect minor QTL is, QTL may still express the characteristics of single Mendelian factor in NILs and isolation of minor QTL will be possible using high quality NILs. Pyramiding these QTL into a variety will largely enhance rice grain yield.     

Wild-type alleles of Rht-B1 and Rht-D1 as independent determinants of thousand-grain weight and kernel number per spike in wheat

The utilization of dwarfing genes Rht-B1b and Rht-D1b in wheat significantly increased grain yield and contributed to the “green revolution”. However, the benefit of Rht-B1b and Rht-D1b in drought environments has been debated. Although quantitative trait loci (QTL) for kernel number per spike (KN) and thousand-grain weight (TGW) have been found to be associated with Rht-B1 and Rht-D1, the confounding effect of environmental variation has made a direct association difficult to find. In this study, we used a doubled haploid population (225 lines) of Westonia × Kauz, in which both Rht-B1b (Kauz) and Rht-D1b (Westonia) segregated. The purpose of the study was to determine the interaction of Rht-B1 and Rht-D1 with grain yield components, namely KN and TGW, and to investigate genotype-by-environment interactions in glasshouse and field trials conducted in 2010 and 2011 in Western Australia. A genetic map of 1,156 loci was constructed using 195 microsatellite markers, two gene-based markers for Rht-B1 and Rht-D1, and 959 single nucleotide polymorphisms. The major QTL for TGW and KN were strongly linked to Rht-B1 and Rht-D1 loci and the positive effects were associated with the wild-type alleles, Rht-B1a and Rht-D1a. The major QTL of TGW were on chromosome 2D and 4B. The significant genetic effects (14.6–22.9 %) of TGW indicated that marker-assisted selection for TGW is possible, and markers gwm192a (206 bp) or gwm192b (236 bp) can be used as indicators of high TGW. For KN, one major QTL was detected on chromosome 4D in the analysis across three environments. The association of the wild-type alleles Rht-B1a and Rht-D1a in drought environments is discussed.     

QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted × high-yielding exotic soybean lines

Seed yield mega-environment-universal and specific QTL (QTL_U and QTL_SP, respectively) linked to Satt100, Satt130, Satt162, Satt194, Satt259 Satt277 and Sat_126, have been identified in a population derived from a cross between a Chinese and a Canadian soybean [Glycine max (L.) Merrill] elite line. The variation observed in yield could be the consequence of the variation of agronomic traits. Yield-component traits have been reported in the literature, but a better understanding of their impact at the molecular level is still lacking. Therefore, the objectives of this study were to identify traits correlated with yield and to determine if the yield QTL_U and QTL_SP were co-localized with QTL_U and QTL_SP associated with an agronomic trait. A recombinant inbred line (RIL) population was developed from a cross between a high-yielding adapted Canadian and a high-yielding exotic Chinese soybean elite line. The RIL were evaluated in multiple environments in China and Canada during the period from 2004 to 2006. Four yield QTL_U, tagged by markers Satt100, Satt277, Satt162 and Sat_126, were co-localized with a QTL associated with an agronomic trait, behaving as either QTL_U or QTL_SP for the agronomic trait. For example, the yield QTL_U, tagged by marker Satt100 was associated also with 100 seed weight, pods per plant, pods per node, plant height, R1, R5, R8, oil content and protein content in all Canadian environments, but only with pods per plant, pods per node, plant height, R1, R5, R8 and oil content in two or more Chinese environments. No agronomic traits QTL were co-localized with the yield QTL_U tagged by the marker Satt139 or the yield QTL_SP tagged by Satt259, suggesting a physiological basis of the yield in these QTL. The results suggest that a successful introgression of crop productivity alleles from plant introductions into an adapted germplasm could be facilitated by the use of both the QTL_U and QTL_SP because each type of QTL contributed either directly or indirectly through yield-component traits to seed yield of RILs.     

Mapping and validation of quantitative trait loci for resistance to Cercospora zeae-maydis infection in tropical maize (Zea mays L.)

Breeding for resistance to gray leaf spot, caused by Cercospora zeae-maydis (Cz) is paramount for many maize environments, in particular under warm and humid growing conditions. In this study, we mapped and characterized quantitative trait loci (QTL) involved in the resistance of maize against Cz. We confirmed the impact of the QTL on disease severity using near-isogenic lines (NILs), and estimated their effects on three major agronomic traits using their respective near isogenic hybrids (NIHs), which we obtained by crossing the NILs with an inbred from a complementary heterotic pool. We further validated three of the four QTL that were mapped using the Multiple Interval Mapping approach and showed LOD values >2.5. NILs genotype included all combinations between favorable alleles of the two QTL located in chromosome 1 (Q ₁ in bin 1.05 and Q ₂ in bin 1.07), and the allele in chromosome 3 (Q ₃ in bin 3.07). Each of the three QTL separately significantly reduced the severity of Cz. However, we found an unfavorable epistatic interaction between Q ₁ and Q ₂: presence of the favorable allele at one of the QTL allele effectively nullified the effect of the favorable allele at the other. In contrast, the interaction between Q ₂ and Q ₃ was additive, promoting the reduction of the severity to a greater extent than the sum of their individual effects. When evaluating the NIH we found significant individual effects for Q ₁ and Q ₃ on gray leaf spot severity, for Q ₂ on stalk lodging and grain yield, and for Q ₃ on grain moisture and stalk lodging. We detected significant epitasis between Q ₁ and Q ₂ for grain moisture and between Q ₁ and Q ₃ for stalk lodging. These results suggest that the combination of QTL impacts the effectiveness of marker-assisted selection procedures in commercial product development programs.     

Field evaluation of cotton near-isogenic lines introgressed with QTLs for productivity and drought related traits

Quantitative trait loci (QTLs) for yield and drought related physiological traits, osmotic potential (OP), carbon isotope ratio (δ¹³C, an indicator of water use efficiency), and leaf chlorophyll content (Chl), were exchanged via marker-assisted selection (MAS) between elite cultivars of the two cotton species Gossypium barbadense cv. F-177 and G. hirsutum cv. Siv’on. The resulting near isogenic lines (NILs) were examined in two field trials, each with two irrigation regimes, in order to (1) evaluate the potential to improve cotton drought resistance by MAS and (2) test the role of physiological traits in plant productivity. NILs introgressed with QTLs for high yield rarely exhibited an advantage in yield relative to the recipient parent, whereas a considerable number of NILs exhibited the expected phenotype in terms of lower OP (5 out of 9), higher δ¹³C (4 out of 6) or high Chl (2 out of 3). Several NILs exhibited considerable modifications in non-targeted traits including leaf morphology, stomatal conductance and specific leaf weight (SLW). In G. barbadense genotypes, yield was correlated negatively with δ¹³C and OP and positively with stomatal conductance, SLW and Chl, whereas in G. hirsutum yield was negatively correlated with δ¹³C, SLW and Chl. This dissimilarity suggests that each of the respective species has evolved different mechanisms underlying plant productivity. We conclude that the improvement of drought related traits in cotton NILs may lead to improved drought resistance via MAS, but that conventional breeding may be necessary to combine the introduced QTL(s) with high yield potential.     

Rapid Identification of Major QTLs Associated with Rice Grain Weight and Their Utilization

To uncover the genetics of rice grain weight, we constructed an RIL population derived from a cross between a large grain accession M201 and a small size variety JY293. Specific Locus Amplified Fragment Sequencing (SLAF-Seq) technology was used to genotype two bulked DNA pools made from individual DNA of the heaviest 30 lines and the lightest 30 lines according to the 1000 grain weight (TGW). Bulked segregant analysis (BSA) was used to identify SLAFs strongly associated with TGW. Two marker-intensive regions at 24,600,000–24,850,000 bp and 25,000,000–25,350,000 bp on chromosome 3 were identified tightly related to the TGW. Then a linkage map of chromosome 3 was constructed with SSR markers and some SLAF derived single nucleotide polymorphisms (SNPs). Quantitative trait locus (QTL) mapping for TGW, grain length, grain width, and grain thickness revealed one major QTL in the second hot-region and two other minor QTLs for grain weight. These three QTLs displayed hierarchical effects on grain length and grain weight in order of qTGW3.2 (qGL3) qTGW3.1 (GS3) qTGW3.3. Multiple comparisons of means among the eight combinations of 3 QTLs revealed that the lines with two of three QTLs deriving from M201 displayed a large grain weight phenotype (TGW 40.2g, average data of three years) and lines with both qTGW3.1 and qTGW3.3 alleles from M201 (42.5g) had similar grain weight to the qTGW3.2 (40.8g) alone. Two strategies with similar effectiveness were proposed to improve grain weight by marker-assisted selection (MAS). One is to introduce the novel qTGW3.2 allele alone, and the other is to pyramid qTGW3.1 and qTGW3.3 alleles together. One new allele of GS3 (39 bp deletion in intron 1) and two SNPs in coding sequence of qGL3 identified in this study from M201 are useful in pyramiding elite alleles for molecular breeding for improvement of rice yield.     

A metabolome‐based core hybridisation strategy for the prediction of rice grain weight across environments

Marker‐based prediction holds great promise for improving current plant and animal breeding efficiencies. However, the predictabilities of complex traits are always severely affected by negative factors, including distant relatedness, environmental discrepancies, unknown population structures, and indeterminate numbers of predictive variables. In this study, we utilised two independent F₁ hybrid populations in the years 2012 and 2015 to predict rice thousand grain weight (TGW) using parental untargeted metabolite profiles with a partial least squares regression method. A stable predictive model for TGW was built based on hybrids from the population in 2012 (r = 0.75) but failed to properly predict TGW for hybrids from the population in 2015 (r = 0.27). After integrating hybrids from both populations into the training set, the TGW of hybrids could be predicted but was largely dependent on population structures. Then, core hybrids from each population were determined by principal component analysis and the TGW of hybrids in both environments were successfully predicted (r > 0.60). Moreover, adjusting the population structures and numbers of predictive analytes increased TGW predictability for hybrids in 2015 (r = 0.72). Our study demonstrates that the TGW of F₁ hybrids across environments can be accurately predicted based on parental untargeted metabolite profiles with a core hybridisation strategy in rice. Metabolic biomarkers identified from early developmental stage tissues, which are grown under experimental conditions, may represent a workable approach towards the robust prediction of major agronomic traits for climate‐adaptive varieties.     

Detection of two quantitative trait loci for resistance to ascochyta blight in an intra-specific cross of chickpea (Cicer arietinum L.): development of SCAR markers associated with resistance

Two quantitative trait loci (QTLs), (QTL_AR1 and QTL_AR2) associated with resistance to ascochyta blight, caused by Ascochyta rabiei, have been identified in a recombinant inbred line population derived from a cross of kabuli×desi chickpea. The population was evaluated in two cropping seasons under field conditions and the QTLs were found to be located in two different linkage groups (LG4a and LG4b). LG4b was saturated with RAPD markers and four of them associated with resistance were sequenced to give sequence characterized amplified regions (SCARs) that segregated with QTL_AR2. This QTL explained 21% of the total phenotypic variation. However, QTL_AR1, located in LG4a, explained around 34% of the total phenotypic variation in reaction to ascochyta blight when scored in the second cropping season. This LG4a region only includes a few markers, the flower colour locus (B/b), STMS GAA47, a RAPD marker and an inter-simple-sequence-repeat and corresponds with a previously reported QTL. From the four SCARs tagging QTL_AR2, SCAR (SCY17₅₉₀) was co-dominant, and the other three were dominant. All SCARs segregated in a 1:1 (presence:absence) ratio and the scoring co-segregated with their respective RAPD markers. QTL_AR2 on LG4b was mapped in a highly saturated genomic region covering a genetic distance of 0.8 cM with a cluster of nine markers (three SCARs, two sequence-tagged microsatellite sites (STMS) and four RAPDs). Two of the four SCARs showed significant alignment with genes or proteins related to disease resistance in other species and one of them (SCK13₆₀₃) was sited in the highly saturated region linked to QTL_AR2. STMS TA72 and TA146 located in LG4b were described in previous maps where QTL for blight resistance were also localized in both inter and intraspecific crosses. These findings may improve the precision of molecular breeding for QTL_AR2 as they will allow the choice of as much polymorphism as possible in any population and could be the starting point for finding a candidate resistant gene for ascochyta blight resistance in chickpea.     

Effects of introgression of two QTL for fusarium head blight resistance from Asian spring wheat by marker-assisted backcrossing into European winter wheat on fusarium head blight resistance,yield and quality traits

Breeding for fusarium head blight (FHB) resistance of wheat is a continuous challenge for plant breeders. Resistance to FHB is a quantitative trait, governed by several to many genes and modulated by environmental conditions. The presented study was undertaken to assess the effect on improving FHB resistance and on possible unwanted side effects (‘linkage drag’) of two resistance QTL, namely Fhb1 and Qfhs.ifa-5A, from the spring wheat line CM-82036 when transferred by marker-assisted backcrossing into several European winter wheat lines. To achieve these goals, we developed and evaluated fifteen backcross-two–derived families based on nine European winter wheat varieties as recipients and the FHB resistant variety CM-82036 as resistance donor. The QTL Qfhs.ifa-5A had a relatively small impact on increasing FHB resistance. On average lines with Fhb1 plus Qfhs.ifa-5A combined were only slightly more resistant compared to lines with Fhb1 alone. The obtained results suggest that the effect of the spring wheat–derived QTL on improving FHB resistance increases in the order Qfhs.ifa-5A < Fhb1 ≤ Qfhs.ifa-5A plus Fhb1 combined. The genetic background of the recipient line had a large impact on the resistance level of the obtained lines. No systematic negative effect of the spring wheat–derived QTL on grain yield, thousand grain weight, hectoliter weight and protein content was found. The use of spring wheat–derived FHB resistance QTL for breeding high yielding cultivars with improved FHB resistance appears therefore highly promising.     

Characterization and detection of epistatic interactions of 3 QTLs, Hd1, Hd2, and Hd3, controlling heading date in rice using nearly isogenic lines

To characterize quantitative trait loci (QTLs), we used marker-assisted selection (MAS) to develop three nearly isogenic lines (NILs) differing only for the presence of a single, specific QTL (QTL-NILs) –Hd1, Hd2, and Hd3 – for heading date in rice. The three lines contained the chromosomal region of the target QTL from donor variety Kasalath(indica) in the genetic background of var. Nipponbare (japonica). To analyze epistatic interactions in pairs of these QTLs, we also used MAS to develop four combined QTL-NILs with 2 of the 3 QTLs or with all 3. Different daylength treatment testing of the QTL-NILs revealed that the three QTLs control photoperiod sensitivity. Genetic analysis of F₂ populations derived from crosses between the three QTL-NILs with a single QTL using molecular markers revealed the existence of epistatic interactions between Hd1 and Hd2, and Hd2 and Hd3. These interactions were also confirmed by the analysis of combined QTL-NILs under different daylength conditions. The existence of an epistatic interaction between Hd1 and Hd3 was also clarified. Based on these results, we suggest that the Kasalath allele of Hd3 does not affect photoperiod sensitivity by itself but that it is involved in enhancement of the expression of the Nipponbare alleles of Hd1 and Hd2. Received: 22 October 1999 / Accepted: 21 March 2000     

Cloning of <Emphasis Type="Italic">TaTPP-6AL1</Emphasis> associated with grain weight in bread wheat and development of functional marker

Trehalose 6-phosphate phosphatase (TPP) dephosphorylates trehalose 6-phosphate to trehalose, an important growth regulator, and is involved in starch accumulation and grain yield. In this study, wheat TPP homologs were isolated from chromosomes 6AL, 6BL, and 6DL, designated as TaTPP-6AL1, TaTPP-6BL1, and TaTPP-6DL1, respectively. Sequence alignment showed a single-nucleotide polymorphism (SNP) at TaTPP-6AL1 locus between cultivars with contrasting thousand grain weight (TGW), forming alleles TaTPP-6AL1a and TaTPP-6AL1b, respectively. A cleaved amplified polymorphic sequence (CAPS) marker, TaTPP-6AL1-CAPS, was developed to differentiate the two alleles. TaTPP-6AL1 was mapped within the interval of IWB65749 and IWB60449 in a recombinant inbred line (RIL) population derived from Zhou8425B/Chinese Spring using the wheat 90K SNP assay. A QTL for TGW identified in the interval explained 12.1–19.1% of the phenotypic variance across five environments. Association analysis on 141 Chinese wheat cultivars also indicated a significant correlation of TaTPP-6AL1 with TGW. In conclusion, TaTPP-6AL1 and its functional marker are valuable to improve grain yield in wheat breeding.     

Genetic dissection of seed weight by QTL analysis and detection of allelic variation in Indian and east European gene pool lines of <Emphasis Type="Italic">Brassica juncea</Emphasis>

Key message

Seed weight QTL identified in different populations were synthesized into consensus QTL which were shown to harbor candidate genes by in silico mapping. Allelic variation inferred would be useful in breeding B. juncea lines with high seed weight.

Abstract

Seed weight is an important yield influencing trait in oilseed Brassicas and is a multigenic trait. Among the oilseed Brassicas, Brassica juncea harbors the maximum phenotypic variation wherein thousand seed weight varies from around 2.0 g to more than 7.0 g. In this study, we have undertaken quantitative trait locus/quantitative trait loci (QTL) analysis of seed weight in B. juncea using four bi-parental doubled-haploid populations. These four populations were derived from six lines (three Indian and three east European lines) with parental phenotypic values for thousand seed weight ranging from 2.0 to 7.6 g in different environments. Multi-environment QTL analysis of the four populations identified a total of 65 QTL ranging from 10 to 25 in each population. Meta-analysis of these component QTL of the four populations identified six ‘consensus’ QTL (C-QTL) in A3, A7, A10 and B3 by merging 33 of the 65 component Tsw QTL from different bi-parental populations. Allelic diversity analysis of these six C-QTL showed that Indian lines, Pusajaikisan and Varuna, hold the most positive allele in all the six C-QTL. In silico mapping of candidate genes with the consensus QTL localized 11 genes known to influence seed weight in Arabidopsis thaliana and also showed conserved crucifer blocks harboring seed weight QTL between the A subgenomes of B. juncea and B. rapa. These findings pave the way for a better understanding of the genetics of seed weight in the oilseed crop B. juncea and reveal the scope available for improvement of seed weight through marker-assisted breeding.

     

QTL analysis of agronomic traits in recombinant inbred lines of sunflower under partial irrigation

The objective of the present research was to map QTLs associated with agronomic traits such as days from sowing to flowering, plant height, yield and leaf-related traits in a population of recombinant inbred lines (RILs) of sunflower (Helianthus annuus). Two field experiments were conducted with well-irrigated and partially irrigated conditions in randomized complete block design with three replications. A map with 304 AFLP and 191 SSR markers with a mean density of 1 marker per 3.7 cM was used to identify QTLs related to the studied traits. The difference among RILs was significant for all studied traits in both conditions. Three to seven QTLs were found for each studied trait in both conditions. The percentage of phenotypic variance (R ²) explained by QTLs ranged from 4 to 49%. Three to six QTLs were found for each yield-related trait in both conditions. The most important QTL for grain yield per plant on linkage group 13 (GYP-P-13-1) under partial-irrigated condition controls 49% of phenotypic variance (R ²). The most important QTL for 1,000-grain weight (TGW-P-11-1) was identified on linkage group 11. Favorable alleles for this QTL come from RHA266. The major QTL for days from sowing to flowering (DSF-P-14-1) were observed on linkage group 14 and explained 38% of the phenotypic variance. The positive alleles for this QTL come from RHA266. The major QTL for HD (HD-P-13-1) was also identified on linkage group 13 and explained 37% of the phenotypic variance. Both parents (PAC2 and RHA266) contributed to QTLs controlling leaf-related traits in both conditions. Common QTL for leaf area at flowering (LAF-P-12-1, LAF-W-12-1) was detected in linkage group 12. The results emphasise the importance of the role of linkage groups 2, 10 and 13 for studied traits. Genomic regions on the linkage groups 9 and 12 are specific for QTLs of leaf-related traits in sunflower.     

Multi-Environmental Genetic Analysis of Grain Size Traits Based on Chromosome Segment Substitution Line in Rice (<i>Oryza sativa</i> L.)

Grain size traits are critical agronomic traits which directly determine grain yield, but the genetic bases of these traits are still not well understood. In this study, a total of 154 chromosome segment substitution lines (CSSLs) population derived from a cross between a japonica variety Koshihikari and an indica variety Nona Bokra was used to investigate grain length (GL), grain width (GW), length-width ratio (LWR), grain perimeter (GP), grain area (GA), and thousand grain weight (TGW) under four environments. QTL mapping analysis of six grain size traits was performed by QTL IciMapping 4.2 with an inclusive composite interval mapping (ICIM) model. A total of 64 QTLs were identified for these traits, which mapped to chromosomes 1, 2, 3, 4, 6, 7, 8, 10, 11, and 12 and accounted for 1.6%–27.1% of the total phenotypic variations. Among these QTLs, thirty-six loci were novel and seven QTLs were identified under four environments. One locus containing the known grain size gene, qGL3/GL3.1/OsPPKL1, also have been found. Moreover, five pairs of digenic epistatic interactions were identified except for GL and GP. These findings will facilitate fine mapping of the candidate gene and QTL pyramiding to genetically improve grain yield in rice.     

High congruency of QTL positions for heterosis of grain yield in three crosses of maize

The genetic basis of heterosis in maize has been investigated in a number of studies but results have not been conclusive. Here, we compare quantitative trait loci (QTL) mapping results for grain yield, grain moisture, and plant height from three populations derived from crosses of the heterotic pattern Iowa Stiff Stalk Synthetic × Lancaster Sure Crop, investigated with the Design III, and analyzed with advanced statistical methods specifically developed to examine the genetic basis of mid-parent heterosis (MPH). In two populations, QTL analyses were conducted with a joint fit of linear transformations Z ₁ (trait mean across pairs of backcross progenies) and Z ₂ (half the trait difference between pairs of backcross progenies) to estimate augmented additive and augmented dominance effects of each QTL, as well as their ratio. QTL results for the third population were obtained from the literature. For Z ₂ of grain yield, congruency of QTL positions was high across populations, and a large proportion of the genetic variance (~70%) was accounted for by QTL. This was not the case for Z ₁ or the other two traits. Further, almost all congruent grain yield QTL were located in the same or an adjacent bin encompassing the centromere. We conclude that different alleles have been fixed in each heterotic pool, which in combination with allele(s) from the opposite heterotic pool lead to high MPH for grain yield. Their positive interactions very likely form the base line for the superior performance of the heterotic pattern under study.     

Mapping two major effect grain dormancy QTL in rice

The intrachromosomal positions of the two grain dormancy quantitative trait loci (QTL) qSdn-1 (chromosome 1) and qSdn-5 (chromosome 5) were obtained from the segregation analysis of the advanced backcross populations derived from the cross between rice (Oryza sativa L.) cultivars N22 (indica) and Nanjing35 (japonica). Marker-assisted selection (MAS) was applied to select derivatives carrying one or both of qSdn-1 and qSdn-5 in a genetic background which was nearly isogenic to Nanjing35. An analysis of dormancy in the BC4F2 population allowed qSdn-1 to be located between the simple sequence repeat (SSR) markers RM11669 and RM1216; the QTL explained 24.58% of the overall phenotypic variation and the most closely linked marker was RM11694. qSdn-5 was mapped between RM480 and RM3664, and explained 17.58% of the overall phenotypic variation. The SSR locus RM19080 mapped within 0.4 cM of qSdn-5. No epistasis was observed between qSdn-1 and qSdn-5. The mean germination rates of lines containing qSdn-1, qSdn-5 and both qSdn-1 and qSdn-5 were 7.9, 11.1 and 6.1%, respectively, whereas that of the check line lacking both QTL was 86.3%. The SSR loci linked most tightly to qSdn-1 and qSdn-5 are suitable for MAS for reduced pre-harvest sprouting in rice. The dormancy of both qSdn-1 and qSdn-5 could be readily broken by a 7-day post-harvest treatment at 50°C.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Recombinant near-isogenic lines: a resource for the mendelization of heterotic QTL in maize

Although heterosis is widely exploited in agriculture, a clear understanding of its genetic bases is still elusive. This work describes the development of maize recombinant near-isogenic lines (NILs) for the mendelization of six heterotic QTL previously identified based on a maize (Zea mays L.) RIL population. The efficient and inexpensive strategy adopted to generate sets of NILs starting from QTL-specific residual heterozygous lines (RHLs) is described and validated. In particular, we produced nine pairs of recombinant NILs for all six QTL starting from RHLs F_4:5 originally obtained during the production of the RIL population mentioned above. Whenever possible, two different NIL pairs were generated for each QTL. The efficiency of this procedure was tested by analyzing two segregating populations for two of the selected heterotic QTL for plant height, yield per plant and ears per plant. Both additive and dominant effects were observed, consistently with the presence of the QTL within the introgressed regions. Refinement of QTL detection was consistent with previous observations in terms of effects and position of the considered QTL. The genetic material developed in this work represents the starting point for QTL fine mapping aimed at understanding the genetic bases of hybrid vigor in maize. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.