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PubMed2005

[Study on location of QTLs controlling cocoon traits in silkworm].

On the basis of the molecular linkage map, mapmaker software QTLMapper 2.0 was used to analyze the QTLs effect of the whole cocoon weight,cocoon shell weight, ratio of cocoon shell and pupa weight of domestic silkworm. For these four cocoon quantitative traits, 7, 6, 2 and 8 effective QTLs were detected and mapped to 7, 5, 2 and 7 linkage groups, respectively. Complicated epistatic effects were found involved in the genetic variation of the whole cocoon weight and cocoon shell weight. For the whole cocoon weight, there were three pairs of QTLs with significant additive by additive interactions, in which, one pair had significant additive by dominance and dominance by dominance interactions. Whereas significant dominance were detected for three QTLs and significant additive effects one QTL had. For the cocoon shell weight, significant genetic effects, including epistatic effects were found for one pair of QTLs, significant dominance by dominance interaction for another pair of QTLs; one QTL had significant dominance and another QTL had additive by additive interaction. The ratio of cocoon shell and the pupa weight were controlled mainly by additive or dominance effects. No interaction between QTL was found for the ratio of cocoon. Most QTLs, associated with the pupa weight, had negative dominance effects. Only significant additive by additive interaction was found between one pair of QTLs. The 2nd, 3rd, 4th, 11th, 13th, 24th, 34th, 37th, and 40th linkage groups are the common chromosomal regions harboring QTLs of two or more cocoon quantitative traits. There are identical QTL or chromosomal region for the whole cocoon weight and cocoon shell weight, indicating they can be simultaneously improved by utilizing epistatic effects in breeding.

Animals↗

PubMed2002

Molecular dissection of complex traits in autopolyploids: mapping QTLs affecting sugar yield and related traits in sugarcane.

Mapping quantitative trait loci (QTLs) for sugar yield and related traits will provide essential information for sugarcane improvement through marker-assisted selection. Two sugarcane segregating populations derived from interspecific crosses between Saccharum offinarum and Saccharum spontaneum with 264 and 239 individuals, respectively, were evaluated in three replications each for field performance from 1994 to 1996 at Weslaco, Texas. These two populations were analyzed for a total of 735 DNA marker loci to seek QTLs for sugar yield, pol, stalk weight, stalk number, fiber content and ash content. Among the 102 significant associations found between these six traits and DNA markers, 61 could be located on sugarcane linkage maps, while the other 41 were associated with unlinked DNA markers. Fifty of the 61 mapped QTLs were clustered in 12 genomic regions of seven sugarcane homologous groups. Many cases in which QTLs from different genotypes mapped to corresponding locations suggested that at least some of the QTLs on the same cluster might be different allelic forms of the same genes. With a few exceptions that explained part of the transgressive segregation observed for particular traits, the allele effects of most QTLs were consistent with the parental phenotype from which the allele was derived. Plants with a high sugar yield possessed a large number of positive QTLs for sugar yield components and a minimal number of negative QTLs. This indicates the potential effectiveness of marker-assisted selection for sugar yield in sugarcane.

Journal Article↗

PubMed2002

Analysis on additive effects and additive-by-additive epistatic effects of QTLs for yield traits in a recombinant inbred line population of rice.

A linkage map consisting of 158 DNA markers were constructed by using a recombinant inbred line (RIL) population derived from the indica-indica rice cross Zhenshan 97B x Milyang 46. Quantitative trait loci (QTLs) conditioning grain yield and five yield component traits were determined at the one-locus and two-locus levels, and genotype-by-environment (GE) interactions were analyzed. Thirty-one QTLs were detected to have significant additive effects for yield traits, of which 12 also exhibited significant epistatic effects. Sixteen significant additive-by-additive (AA) interactions were detected, of which nine occurred between QTLs with own additive effects (M(ep)QTLs), four occurred between QTLs showing epistatic effects only (epQTLs), and three occurred between M(ep)QTLs and epQTLs. Significant GE interactions were found for six QTLs with additive effects and one AA interaction. Generally, the contributions to the phenotypic variation were higher due to QTL main effects than to epistatic effects. The detection of additive effects and AA effects of a QTL interfered with each other, indicating that the detection of QTLs with main effects, as well as the magnitude and directions of the additive effects, might vary depending on their interactions with other loci.

Journal Article↗

PubMed2003

Identification of QTLs associated with Fusarium head blight resistance in Zhedar 2 barley.

Fusarium head blight (FHB) in barley and wheat, caused by Fusarium graminearum, is a continual problem worldwide. Primarily, FHB reduces yield and quality, and results in the production of the toxin deoxynivalenol (DON), which can affect food safety. Identification of QTLs for FHB severity, DON level and related traits heading-date (HD) and plant-height (HT) with consistent effects across a set of environments, would provide the basis for marker-assisted selection (MAS) and potentially increase the efficiency of selection for resistance. A segregating population of 75 double-haploid lines, developed from the three-way cross Zhedar 2/ND9712//Foster, was used for genome mapping and FHB severity evaluation. A linkage map of 214 RFLP, SSR and AFLP markers was constructed. Phenotypic data were collected in replicated field trials from five environments in two growing seasons. The data were analyzed using MQTL software to detect quantitative trait locus (QTL) x environment (E) interactions. Because of the presence of QTL x E, the MQM procedure in MAPQTL was applied to identify QTLs in single environments. We identified nine QTLs for FHB severity and five for low DON. Many of the disease-related QTLs identified were coincident with FHB QTLs identified in previous studies. Only two of the QTLs identified in this study were consistent across all five environments, and both were Zhedar 2 specific. Five of the FHB QTLs were associated with HD, and two were associated with HT. Regions that appear to be promising candidates for MAS and further genetic analysis include the two FHB QTLs on chromosome 2H and one on 6H, which were also associated with low DON and later heading-date in multiple environments. This study provides a starting point for manipulating Zhedar 2-derived resistance by MAS in barley to develop cultivars that will show effective resistance under disease pressure.

Chromosome Mapping↗

PubMed2006

Stability over genetic backgrounds, generations and years of quantitative trait locus (QTLs) for organoleptic quality in tomato.

The efficiency of marker-assisted backcross for the introgression of a quantitative trait locus (QTL) from a donor line into a recipient line depends on the stability of QTL expression. QTLs for six quality traits in tomato (fruit weight, firmness, locule number, soluble solid content, sugar content and titratable acidity) were studied in order to investigate their individual effect and their stability over years, generations and genetic backgrounds. Five chromosome regions carrying fruit quality QTLs were transferred following a marker-assisted backcross scheme from a cherry tomato line into three modern lines with larger fruits. Three sets of genotypes corresponding to three generations were compared: (1) an RIL population, which contained 50% of each parental genome, (2) three BC3S1 populations which segregated simultaneously for the five regions of interest but were almost fully homozygous for the recipient genome on the eight chromosomes carrying no QTL and (3) three sets of QTL-NILs (BC3S3 lines) which differed from the recipient line only in one of the five regions. QTL detection was performed in each generation, in each genetic background and during 2 successive years for QTL-NILs. About half of the QTLs detected in QTL-NILs were detected in both years. Eight of the ten QTLs detected in RILs were recovered in the QTL-NILs with the genetic background used for the initial QTL mapping experiment, with the exception of two QTLs for fruit firmness. Several new QTLs were detected. In the two other genetic backgrounds, the number of QTLs in common with the RILs was lower, but several new QTLs were also detected in advanced generations.

Fruit↗

PubMed2005

The main effects, epistatic effects and environmental interactions of QTLs on the cooking and eating quality of rice in a doubled-haploid line population.

Amylose content (AC), gel consistency (GC) and gelatinazation temperature (GT) are three important traits that influence the cooking and eating quality of rice. The objective of this study was to characterize the genetic components, including main-effect quantitative trait loci (QTLs), epistatic QTLs and QTL-by-environment interactions (QEs), that are involved in the control of these three traits. A population of doubled haploid (DH) lines derived from a cross between two indica varieties Zhenshan 97 and H94 was used, and data were collected from a field experiment conducted in two different environments. A genetic linkage map consisting of 218 simple sequence repeat (SSR) loci was constructed, and QTL analysis performed using QTLMAPPER 1.6: resolved the genetic components into main-effect QTLs, epistatic QTLs and QEs. The analysis detected a total of 12 main-effect QTLs for the three traits, with a QTL corresponding to the Wx locus showing a major effect on AC and GC, and a QTL corresponding to the Alk locus having a major effect on GT. Ten digenic interactions involving 19 loci were detected for the three traits, and six main-effect QTLs and two pairs of epistatic QTLs were involved in QEs. While the main-effect QTLs, especially the ones corresponding to known major loci, apparently played predominant roles in the genetic basis of the traits, under certain conditions epistatic effects and QEs also played important roles in controlling the traits. The implications of the findings for rice quality improvement are discussed.

Amylose↗

PubMed2005

QTLs mapping for fruit size and shape in chromosomes 2 and 4 in pepper and a comparison of the pepper QTL map with that of tomato.

Quantitative trait locus (QTL) mapping for fruit weight and shape in pepper (Capsicum spp.) was performed using C. chinense and C. frutescens introgression lines of chromosomes 2 and 4. In chromosome 2, a single major fruit-weight QTL, fw2.1, was detected in both populations that explained 62% of the trait variation. This QTL, as well as a fruit-shape QTL, fs2.1, which had a more minor effect, were localized to the tomato fruit-shape gene ovate. The cloned tomato fruit-weight QTL, fw2.2, did not play a major role in controlling fruit size variations in pepper. In chromosome 4, two fruit-weight QTLs, fw4.1 and fw4.2, were detected in the same genomic regions in both mapping populations. In addition, a single fruit-shape QTL was detected in each of the mapping populations that co-localized with one of the fruit-weight QTLs, suggesting pleiotropy or close linkage of the genes controlling size and shape. fw2.1 and fw4.2 represent major fruit-weight QTLs that are conserved in the three Capsicum species analyzed to date for fruit-size variations. Co-localization of the pepper QTLs with QTLs identified for similar traits in tomato suggests that the pepper and tomato QTLs are orthologous. Compared to fruit-shape QTLs, fruit-weight QTLs were more often conserved between pepper and tomato. This implies that different modes of selection were employed for these traits during domestication of the two Solanaceae species.

Capsicum↗

PubMed2003

Inferences regarding the numbers and locations of QTLs under multiple-QTL models using interval mapping and composite interval mapping.

This paper examines the properties of likelihood maps generated by interval mapping (IM) and composite interval mapping (CIM), two widely used methods for detecting quantitative trait loci (QTLs). We evaluate the usefulness of interpretations of entire maps, rather than only evaluating summary statistics that consider isolated features of maps. A simulation study was performed in which traits with varying genetic architectures, including 20-40 QTLs per chromosome, were examined with both IM and CIM under different marker densities and sample sizes. IM was found to be an unreliable tool for precise estimation of the number and locations of individual QTLs, although it has greater power for simply detecting the presence of QTLs than CIM. The ability of CIM to resolve the correct number of QTLs and to estimate their locations correctly is good if there are three or fewer QTLs per 100 centiMorgans, but can lead to erroneous inferences for more complex architectures. When the underlying genetic architecture of a trait consists of several QTLs with randomly distributed effects and locations likelihood profiles were often indicative of a few underlying genes of large effect. Studies that have detected more than a few QTLs per chromosome should be interpreted with caution.

Animals↗

PubMed2004

[Identification of QTLs on substituted segments in single segment substitution lines of rice].

The quantitative trait loci (QTLs) for 21 traits of agronomy importance on ten substituted chromosomal segments were identified using single segment substitution lines (SSSLs) in rice, which were developed by the use of Taichung 65 as a recipient and zhai-ye-qing and dee-geo-woo-gen as donors respectively. Total length of the substituted segments in the SSSLs was 230.00 cM, which was 12.62% of rice genome. T-test was used to detect QTLs in the condition that the difference in phenotypes between a SSSL and the recipient parent (Taichung 65) was significant at the 0.1% level (P< or = 0.001). A total of 57 QTLs for 17 traits had been detected on the ten substituted segments, which were on chromosomes 1, 3, 5, 7, 8, 10 and 12 respectively. The additive effect percentages of the QTLs ranged from 1.10% to 89.73%. Among of 57 QTLs, fifteen QTLs had the additive effect percentage over 10%, thirty QTLs varied from 3% to 10% and other twelve QTLs were below 3%.

Oryza↗

PubMed2003

Mapping QTLs influencing rice floral morphology using recombinant inbred lines derived from a cross between Oryza sativa L. and Oryza rufipogon Griff.

To understand the genetic basis of floral traits associated with the mating system in rice, we analyzed pistil, stamen and glume traits using a recombinant inbred line population, derived from a cross between an Asian cultivated rice ( Oryza sativa L.), Pei-kuh, and a wild rice ( Oryza rufipogon Griff.), W1944. Quantitative trait loci (QTLs) affecting floral morphology were detected by composite interval mapping using a linkage map constructed using 147 markers, mostly RFLPs. A total of 7, 4, 14 and 6 QTLs were detected for traits related to pistil, stamen, and size and shape of the glume, respectively. Comparison of 31 QTLs affecting these organs revealed ten QTLs affecting the different organs in four adjacent regions on chromosomes 2, 4, 5 and 10, but most QTLs (68%) were located separately on the whole chromosomes. Although four QTLs for stigma breadth, anther length and thickness of lemma and palea explained more than 25% of the total phenotypic variance, most QTLs (87%) had smaller effects. These results suggest that quantitative variation observed for pistil, stamen and glume traits is controlled by several distinct genes with small effects.

Chromosome Mapping↗

PubMed2005

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.

Chromosome Mapping↗

PubMed2006

Mapping QTLs that control the performance of rice tissue culture and evaluation of derived near-isogenic lines.

Quantitative trait loci (QTLs) that control the performance of tissue culture in rice were detected by using 116 RFLP markers and 183 BC1F3 lines derived from two varieties, Koshihikari and Kasalath. With time, the seed callus of Koshihikari tends to turn brown and stop growing, while that of Kasalath remains yellowish-white and proliferates continuously. The performance of tissue culture in the induction of calli from seed, the subculture of induced calli, and shoot regeneration were evaluated by five indices: induced-callus weight, induced-callus color, subcultured-callus volume, subcultured-callus color, and regeneration rate. Through callus induction and subculture, eight putative QTLs (P < 0.001) were located on chromosomes 1, 4, and 9. Among these QTLs, five Kasalath alleles and three Koshihikari alleles improved tissue culture performance. No QTL for regeneration was found. Among all the QTLs, qSv1 explained the largest phenotypic variance, 33%, in subcultured-callus volume. In induced-callus color, two detected QTLs accounted for 36.4% of the total phenotypic variance; this was the highest score among the five indices used to evaluate the performance of tissue culture. Three near-isogenic lines for QTLs, located in two regions on chromosome 1, were developed to evaluate their tissue culture performance. The Kasalath alleles in qSv1 and qSc1-1 improved callus color through callus induction and subculture, and increased the subcultured-callus volume and the fresh weight of regenerated calli, including shoots, roots, and differentiated structures. In qSc1-2, the Kasalath allele improved callus color through induction and subculture. These results verified the presence of QTLs for the volume and color of subcultured callus on chromosome 1, qSv1, qSc1-1, and qSc1-2.

Chromosome Mapping↗

PubMed2025

Identifying canopy wilting QTLs and evaluating remote sensing approaches for selecting drought-tolerant soybean.

Drought is the most damaging abiotic stress for soybean yield; cultivars with improved drought tolerance are needed to sustain and increase crop production. PI 603535 previously was identified as an ultra-slow canopy wilting (CW) line in a genome-wide association study but the quantitative trait loci (QTLs) underlying this phenotype have not been determined. In this study, a recombinant inbred line (RIL) population derived from Benning × PI 603535 was evaluated for three years under rain-fed conditions. CW was rated following extended periods of drought when CW variation was present. Aerial multispectral and thermal imagery was also captured in conjunction with visual ratings to explore the feasibility of implementing remote sensing to improve the efficiency and objectivity of drought evaluations. The normalized difference vegetation index (NDVI) and green-based NDVI (GNDVI) exhibited strong, significant correlations (|r|= 0.42-0.44) with CW across years. CW scores and the remote sensing traits were used as phenotypes for QTL mapping. Seven CW QTLs were identified across six chromosomes in the combined analysis, with NDVI and GNDVI QTLs generally colocalizing with the CW QTLs with the highest percentage of variation explained (PVE). The QTLs were not consistently identified among individual years, highlighting the complex genetics and gene expression of drought tolerance. The instability and low additive effect estimates of individual QTLs imply challenges of improving drought tolerance through the selection of a few QTLs. However, the slow CW RILs developed in this study can serve as valuable breeding stocks for future drought improvement breeding efforts and genetic studies.

Quantitative Trait Loci↗

PubMed2006

Identification of related QTLs at late developmental stage in rice (Oryza sativa L.) under two nitrogen levels.

QTL underlying related traits at the late developmental stage under two different nitrogen levels were investigated in rice using a population of chromosome segment substitution lines (CSSL) derived from a cross between Teqing and Lemont. A total of 31 QTLs referring 5 traits, that is, plant height (PH), panicle number per plant (PN), chlorophyll content (CC), shoot dry weight (SDW) and grain yield per plant (YD), were detected. Under normal N level, 3 QTLs were detected for each trait, while under low N level, 5, 4, 5 and 2 QTLs were detected for PH, PN, CC and SDW respectively. Most of the QTLs were located on chromosome 2, 3, 7, 11 and 12. QTLs controlling different traits or the same trait under different N levels were mapped on the same or adjacent intervals, forming several clusters in rice chromosomes. More than two traits were controlled by QTLs on one of four intervals (RM30-RM439, RM18-RM478, RM309-RM270, and RM235-RM17), suggesting that there were some pleiotropic effects. It was supposed that some QTLs only detected at low N level might be associated with the ability to tolerate the low N stress in rice.

Chlorophyll↗

PubMed2006

QTL analysis of popping fold and the consistency of QTLs under two environments in popcorn.

Popping fold (PF) is the most important quality trait in popcorn. In this study, a total of 259 F2:3 families, derived from the cross between a dent corn inbred Dan232 and a popcorn inbred N04, were evaluated for their popping folds in replicated experiments under two environments. Of 613 simple sequence repeat (SSR) primer pairs screened, 183 pairs were selected to construct a genetic linkage map with the genetic distance of 1,762.2 cM (centimorgan) and on average 9.63 cM every marker. Quantative trait loci (QTL) were identified, and their genetic effects were estimated using CIM (composite interval mapping) method. The interactions among QTLs detected were calculated using MIM (multiple interval mapping) method. In all, 22 QTLs were detected, and only 5 of them were common under two environments. Contribution to phenotypic variation of a single QTL varied from 3.07% to 12.84%, and total contributions of all QTLs under two environments were 66.46% and 51.90%, respectively. Three QTLs (qPF-6-1, qPF-8-1 and qPF-1-3) with more than 10% contributions were observed. The additive effects were larger than dominant effects for most QTLs. The amount of QTLs showing additive, partially dominant, dominant and over-dominant effects were 4, 5, 0, 2 in spring sowing and 2, 5, 2, 2 in summer sowing, respectively. There were only 2.60% pairs of QTLs or maker intervals expressing AA, DA or DD interactions.

Environment↗

PubMedDate not supplied

Mapping QTLs associated with drought avoidance in upland rice grown in the Philippines and West Africa.

Localizing genes that contribute to drought avoidance in a quantitative way should enable the exploitation of these genes in breeding through marker-assisted selection, and may lead to the discovery of gene identity and function. Between 110 and 176 F6 recombinant inbred lines from a mapping population derived from a cross of upland rice varieties Bala and Azucena have been evaluated for indicators of drought avoidance in sites in the Philippines and West Africa over two dry seasons. A molecular map with 102 RFLP, 34 AFLP and six microsatellite markers has been used to map (by composite interval mapping) quantitative trait loci (QTLs) for the visual scores of leaf rolling and leaf drying and leaf relative water content. QTLs were mapped for each site and across sites. A total of 17 regions were identified which contained QTLs with a LOD score greater than 3.2. For leaf rolling, Bala was the parent contributing the majority of positive alleles whilst for the other traits, Bala and Azucena contributed more evenly. Six of the 17 regions influenced more than one trait, explaining the phenotypic correlations between traits that were observed. Three QTLs appeared to be specific to the Philippines experiments. One QTL had opposing effects in the Philippines and West Africa. QTLs for relative water content were detected on chromosome 8, congruent with an osmotic adjustment QTL identified in another population. Only three of the QTLs identified here have not been reliably identified in the two other populations that have been screened for drought avoidance. By using several populations assessed for drought avoidance in different sites, the distribution and utility of QTLs for drought avoidance in rice is being elucidated.

Adaptation, Physiological↗

PubMed2004

Identification of QTLs for weight and cross-sectional area on cervical enlargement of spinal cord in mice.

Two inbred strains of mice, A/J, C57BL/6J and F2 intercross progenies,were used for QTL mapping for weight and cross-sectional area on cervical enlargement of spinal cord in mice. 13 QTLs located on Chromosome 2, 4, 8, 14, 15, 17, 18, 19 and X, respectively, for these two traits were found. Six QTLs were responsible for the cord weight, four for the cross-sectional area and three for both. Among 13 QTLs, three QTLs (P < 0.01) termed SC1 (located near D15Mit158) ,SC2 (DXMit140) and SC3 (DXMit64) accounted for 24%, 19% and 15% of the total variance in weight phenotype, and -3.78, 3.41 and 2.06 mg additive effect, respectively. The P value of other QTLs is between 0.01 and 0.05. SC1 is only one QTL that responsible for both weight and cross-sectional area in three QTLs above. This study revealed the location of major QTLs related size of spinal cord in mice, and may be helpful in fine mapping and ultimate identification of candidate genes.

Animals↗

PubMed2002

Mapping QTLs for field resistance to the rice blast pathogen and evaluating their individual and combined utility in improved varieties.

Lines from a Lemont x Teqing recombinant inbred population were evaluated for dilatory resistance to rice blast disease using: (1) the Standard Evaluation System (SES) for rating leaf blast, (2) the percentage diseased leaf area (%DLA), and (3) the area under a disease progress curve (AUDPC). RFLP mapping using 175 well-distributed loci revealed nine QTLs, one each on chromosomes 1, 2, 3, 4, 6, 7 and 9, with two loci on chromosome 12. All nine putative QTLs were associated with AUDPC, six with both a %DLA and a SES rating. Teqing contributed the resistance allele for all these loci except for the one located on chromosome 4. Individual QTLs accounted for 5-32% of the observed phenotypic variation, and combined QTL models accounted for 43-53%. Three QTLs were located near three of the four major resistance genes previously identified in this population. The resistances of both Lemont and Teqing were attributable to a combination of both major genes capable of inducing hypersensitive reactions and minor genes causing less-distinctive phenotypic differences. Interactions were noted between QTLs and major genes. Our findings are in support of the strategy of pyramiding major genes and QTLs in carefully selected combinations to develop improved varieties with resistance to the blast fungus that is both broad in spectrum and durable.

Journal Article↗