Quantitative Trait Loci In Linkage Groups Research Articles

Dose-Dependent Genetic Resistance to Azole Fungicides Found in the Apple Scab Pathogen.

The evolution of azole resistance in fungal pathogens presents a major challenge in both crop production and human health. Apple orchards across the world are faced with the emergence of azole fungicide resistance in the apple scab pathogen Venturia inaequalis. Target site point mutations observed in this fungus to date cannot fully explain the reduction in sensitivity to azole fungicides. Here, polygenic resistance to tebuconazole was studied across a population of V. inaequalis. Genotyping by sequencing allowed Quantitative Trait Loci (QTLs) mapping to identify the genetic components controlling this fungicide resistance. Dose-dependent genetic resistance was identified, with distinct genetic components contributing to fungicide resistance at different exposure levels. A QTL within linkage group seven explained 65% of the variation in the effective dose required to reduce growth by 50% (ED50). This locus was also involved in resistance at lower fungicide doses (ED10). A second QTL in linkage group one was associated with dose-dependent resistance, explaining 34% of variation at low fungicide doses (ED10), but did not contribute to resistance at higher doses (ED50 and ED90). Within QTL regions, non-synonymous mutations were observed in several ATP-Binding Cassette and Major Facilitator SuperFamily transporter genes. These findings provide insight into the mechanisms of fungicide resistance that have evolved in horticultural pathogens. Identification of resistance gene candidates supports the development of molecular diagnostics to inform management practices.

Genetic architecture of tipburn resistance in lettuce.

Two major QTLs for tipburn were identified in LGs 1 and 5 contributing to resistance in cv. Salinas. The findings suggest pleiotropic effects between leaf crinkliness/savoy and tipburn. Tipburn is a physiological disorder in lettuce that is thought to be caused by a localized deficiency of calcium in leaf tissues. To elucidate the genetic architecture of resistance to tipburn in lettuce, seven recombinant inbred line populations were analyzed in multiple environments and years to identify quantitative trait loci (QTLs) for tipburn. Core height, head firmness, head closure, leaf crinkliness, plant fresh weight, and leaf savoy were also analyzed to investigate whether QTLs for these morphological traits collocated with QTLs for tipburn, which would be indicative of pleiotropic effects. Twenty-three major, intermediate, and minor unique QTLs for tipburn were identified in one or more populations scattered throughout the genome. Two major QTLs for tipburn incidence were identified in linkage groups (LGs) 1 and 5, which determined up to 45 and 66% of the phenotypic variance. The major QTL in LG 1 collocated with the head firmness QTL. The major QTL in LG 5 collocated with the QTL for core height, leaf crinkliness, and head firmness. Further research is needed to determine whether these associations are due to pleiotropic effects of the same gene or if the genes determining these traits are tightly linked. The beneficial alleles at the QTLs in LGs 1 and 5 are present in Lactuca sativa cv. Salinas, the genotype sequenced for the reference genome assembly. Therefore, these QTLs are good targets to identify genes causing tipburn as well as regions for marker-assisted selection to improve resistance to tipburn in lettuce.

Mapping quantitative trait loci conferring resistance to Marssonina leaf spot disease in Populus deltoides

Two large-effect QTLs and 14 candidate genes conferring resistance to Marssonina leaf spot disease were identified in an F1Populus deltoides pedigree, which provided valuable information for cloning the particular underlying genes in future. Marssonina leaf spot disease (MLSD), which is caused by Marssonina brunnea, is a devastating threat to poplar plantations. To map quantitative trait loci (QTLs) underlying resistance to MLSD, an F1P. deltoides pedigree has been established and genetic maps were constructed for the mapping parents according to the two-way pseudo-testcross mapping strategy. The female map contained 913 markers spanning a total genetic distance of 3132 cM, with linkage groups (LGs) corresponding to the 19 haploid chromosomes in poplar, whereas the paternal map contained 252 markers distributed on 22 LGs and covered a genetic length of 1809 cM. The established maps were further aligned to the poplar consensus genetic map based on the integrated SSR markers. The resistance to MLSD was recorded as a complex binary trait based on the black spot symptom on leaves. Analyses of QTLs revealed two large-effect QTLs in LGs VI and XVI, namely qMLSD-VI-1 and qMLSD-XVI-2, which explained 50.3% and 34.5% of the total phenotypic variance, respectively. A significant interaction between these two QTLs was detected based on a two-way ANOVA. In this mapping pedigree, the female parent contributed all of the QTL alleles conferring resistance to M. brunnea. Genome sequences in the target regions were obtained by aligning the QTL intervals to the poplar genome sequence with the mapped SSR markers. The importance and utility of the 14 candidate genes associated with disease resistance identified in the QTL intervals should be more thoroughly characterized in future studies.

Age-dependent QTL affecting body weight in gilthead seabream (Sparus aurata L.)

We examined 24 maternal half-sib families of gilthead seabream to identify quantitative trait loci (QTL) associated with body weight at four time points during a production cycle. 57 brooders and 637 offspring were genotyped for 14 informative microsatellite markers, spanning linkage groups 1 and 21. The QTL detection method was based on half-sib interval mapping analysis through a linear regression approach. One QTL was found significant at all time points in linkage group 1, with its effect having different profile across time, and one QTL in linkage group 21 that seems to impact body weight at a later growth stage of the species. Current results verified previously published QTL for growth in the above linkage groups, using a different genetic background of seabream. These QTL can be considered as valuable candidates for use in marker-assisted selective breeding programs, aiming at high rates of genetic improvement for growth in S. aurata.

Identification of QTLs Conferring Resistance to Deltamethrin in Culex pipiens pallens.

Culex pipiens pallens is the most abundant Culex mosquito species in northern China and is an important vector of bancroftian filariasis and West Nile virus. Deltamethrin is an insecticide that is widely used for mosquito control, however resistance to this and other insecticides has become a major challenge in the control of vector-borne diseases that appear to be inherited quantitatively. Furthermore, the genetic basis of insecticide resistance remains poorly understood. In this study, quantitative trait loci (QTL) mapping of resistance to deltamethrin was conducted in F2 intercross segregation populations using bulked segregation analysis (BSA) and amplified fragment length polymorphism markers (AFLP) in Culex pipiens pallens. A genetic linkage map covering 381 cM was constructed and a total of seven QTL responsible for resistance to deltamethrin were detected by composite interval mapping (CIM), which explained 95% of the phenotypic variance. The major QTL in linkage group 2 accounted for 62% of the variance and is worthy of further study. 12 AFLP markers in the map were cloned and the genomic locations of these marker sequences were determined by applying the Basic Local Alignment Search Tool (BLAST) tool to the genome sequence of the closely related Culex quinquefasciatus. Our results suggest that resistance to deltamethrin is a quantitative trait under the control of a major QTL in Culex pipiens pallens. Cloning of related AFLP markers confirm the potential utility for anchoring the genetic map to the physical map. The results provide insight into the genetic architecture of the trait.

The detection of QTLs controlling bacterial wilt resistance in tobacco (N. tabacum L.)

The bacterial tobacco wilt caused by Ralstonia solanacearum is one of the most destructive soil-borne diseases worldwide. One strategy to improve the resistance to bacterial wilt is to make use of plant varieties expressing wilt resistance genes. To characterize the genetics of wilt resistance and to identify relevant molecular markers for use in plant breeding, quantitative trait loci (QTLs) affecting tobacco bacterial wilt resistance were mapped in the F2:3 and F2:4 progeny produced from two crosses between the wilt-resistant breeding lines Enshu and Yanyan97 and the susceptible cultivar TI448A. A linkage map containing 118 loci in 24 linkage groups was constructed for 236 lines from the Enshu×TI448A cross, and a linkage map containing 96 loci in 24 linkage groups was constructed for 264 lines from the Yanyan97×TI448A cross. The wilt resistance of the progeny was examined in field trials conducted in Xuancheng, China, in 2010, 2011, and 2012. The disease severity was assessed on stems using separate rating scales. Mapmaker/EXP 3.0 and Mapmaker/QTL 1.1 were used to identify the qBWR-3a, qBWR-3b, qBWR-5a and qBWR-5b QTLs in linkage group 3 and 5; these four loci were strongly associated with resistance and explain 9.00, 19.70, 17.30, and 17.40 % of the variance in resistance, respectively. The close linkage of the markers PT20275 and PT30229 was detected in both the TI448A×Enshu and TI448A×Yanyan97 crosses, and this linkage group could be used to select individual resistant plants. These findings suggest that one strategy to combat bacterial wilt could be to exploit the resistance genes of the Enshu and Yanyan97 strains.

Genetic analysis of iron chlorosis tolerance in Prunus rootstocks

The high economic losses caused by the occurrence of iron chlorosis in Prunus orchards in the Mediterranean area justifies the implementation of breeding programs to generate high-performance rootstocks for different edaphoclimatic area conditions. For that reason, the genetic control of iron chlorosis tolerance was studied in an F1 population derived from a three-way interspecific cross between a Myrobalan plum (P 2175) and an almond × peach hybrid (Felinem). Several phenotypic measurements were assessed to guarantee an accurate data set for genetic analysis. SPAD (Soil and Plant Analyzer Development) values, chlorophyll concentration, and visual diagnostic symptoms were highly correlated with leaf chlorosis in trees. SPAD value was the most reliable measure, since it was an objective, unbiased, and non-destructive method. Two significant quantitative trait loci (QTLs) involved in SPAD and chlorophyll concentration were identified for Felinem in linkage groups 4 and 6. Both QTLs were detected in four of the six consecutive years of the experiment. For P 2175, two of the three putative QTLs identified, pspad4.1 and chl4.1, were placed in linkage group 4. These QTLs were related to the SPAD values and chlorophyll concentration, respectively, and co-localized with QTLs detected in the Felinem map affecting the same traits. Candidate gene PFIT, related to iron metabolism, was localized within the confidence interval of the QTL in linkage group 4. This research suggests an association of this chromosome region with tolerance to iron chlorosis in Prunus, and it provides a first approach to localize candidate genes involved in tolerance to this abiotic stress.

Inheritance of chilling and heat requirements for flowering in almond and QTL analysis

The chilling and heat requirements and flowering time were studied, for 2 years, in an almond progeny from the cross between the late-flowering French selection “R1000” and the early-flowering Spanish “Desmayo Largueta”. These three temperature-dependent traits showed quantitative inheritance, although for chilling requirements and flowering time a major gene could be involved, modified by other minor genes. The results indicate that flowering time is mainly a consequence of the chilling requirements; heat requirements having a smaller effect. In agreement with the genetic findings, a significant Quantitative Trait Loci (QTL) for chilling requirements was found in G4 together with other minor QTLs in G1, G3, and G7. For heat requirements, two QTLs in G2 and G7 were identified. The results also show the high influence of temperature in the expression of the three traits and their QTL analyses. In addition, QTL analysis for flowering time allowed the identification of one significant QTL in linkage group 4 (G4) that explained most of the phenotypic variation together with other minor QTLs located in G1, G6, and G7.

QTLs for resistance to soybean cyst nematode, races 3, 9, and 14 in cultivar Hartwig

The objective of this work was to identify major and minor-effect quantitative trait loci (QTL) for resistance to races 3, 9, and 14 of soybean cyst nematode (SCN) in Hartwig cultivar; to map new resistance QTLs for these races; and to check for the existence of epistatic interactions between QTLs. Cultivar Hartwig is an important resistance source to SCN. Recombinant inbred lines (RIL) obtained from a cross between 'Hartwig' (resistant) and Y23 (susceptible) were evaluated regarding resistance to the three races. New genomic regions for resistance to SCN were identified by microsatellites. Four QTLs, which explained between 12 and 34% of phenotypic variance, were detected for resistance to race 3 in linkage groups (LG) A2, G, J, and M. The QTL in LG G is also important for resistance to race 9. Epistatic interactions were detected between loci, which indicate resistance to races 9 and 14. There are high and low-effect resistance QTLs to SCN.

QTL Mapping for Photoperiod Insensitivity of a Japanese Soybean Landrace Sakamotowase

The insensitivity of flowering to long daylength is an important characteristic which soybeans have used to adapt to environments at higher latitude. The objective of this study was to map the novel gene(s) for photoperiod insensitivity in the Japanese soybean landrace Sakamotowase. A previous study suggested that Sakamotowase possessed the genotype e1e1e3e3E4E4. The progeny of testcrosses with the Harosoy isoline for e3 (L62-667) produced the roughly expected segregation pattern for the monogenic inheritance, suggesting the major involvement of a single gene in photoperiod insensitivity of Sakamotowase. By mapping analysis for 6 linkage groups (LGs) harboring the known major genes and quantitative trait loci (QTLs) for flowering, we detected a major QTL for the insensitivity near an simple sequence repeat marker (Satt577) in LG C2 and a minor QTL in LG L. Our results therefore suggest that a novel gene for photoperiod insensitivity of Sakamotowase was located in LG C2. It was estimated from the position of the tagging marker that the novel gene may be an allele at the E1 or E7 loci or a novel gene tightly linked to the E1 locus.

Aroma profile of a collection of near-isogenic lines of melon (Cucumis melo L.)

This paper characterizes the aroma volatile profile found in a collection of near-isogenic lines (NILs) of melon (Cucumis melo L.) obtained by solid-phase microextraction and analyzed by gas chromatography–mass spectrometry. The collection was built with introgressions of an exotic accession (PI 161375) into the parental line ‘Piel de sapo’ (PS) and was useful for mapping quantitative trait loci (QTLs) associated with melon flesh aroma. The aroma profile was composed of 24 compounds detected in PS or the NILs: three esters, six aldehydes, three alkanes, three aromatic hydrocarbons, two terpenes, two ketones, one alcohol, one sulphur-derived compound, one cyclic branched alkene, one naphthalene and one ether. Hexanal showed the highest relative concentration in the collection, followed by camphor and methanethiolate with no difference between PS and the NILs. These results allowed us to map four QTLs in linkage groups IV, VIII and XI associated with the formation of 3-hydroxy-2,4,4-trimethylpentyl 2-methylpropanoate, octanal and (Z,Z)-3,6-nonadienal.

Mapping EST-derived SSRs and ESTs involved in resistance to bacterial blight inManihot esculenta

Cassava (Manihot esculenta Crantz) is a major root crop widely grown in the tropics. Cassava bacterial blight, caused by Xanthomonas axonopodis pv. manihotis (Xam), is an important disease in Latin America and Africa resulting in significant losses. The preferred control method is the use of resistant genotypes. Mapping expressed sequence tags (ESTs) and determining their co-localization with quantitative trait loci (QTLs) may give additional evidence of the role of the corresponding genes in resistance or defense. Twenty-one EST-derived simple sequence repeats (SSRs) were mapped in 16 linkage groups. ESTs showing similarities with candidate resistance genes or defense genes were also mapped using strategies such as restriction fragment length polymorphisms, cleaved amplified polymorphic sequences, and allele-specific primers. In total, 10 defense-related genes and 2 bacterial artificial chromosomes (BACs) containing resistance gene candidates (RGCs) were mapped in 11 linkage groups. Two new QTLs associated with resistance to Xam strains CIO121 and CIO151 were detected in linkage groups A and U, respectively. The QTL in linkage group U explained 61.6% of the phenotypic variance and was associated with an RGC-containing BAC. No correlation was found between the new EST-derived SSRs or other mapped ESTs and the new or previously reported QTLs.

Identification of quantitative trait loci (QTL) for plant structure, growth habit and yield in lentil

Lentil quantitative trait loci (QTL) related to plant structure (branches at first node, height of first node, total number of branches, plant height), growth habit (flowering time, pod dehiscence) and yield (number of seeds, seed weight, seed diameter) were located using a F2 population of 113 individuals derived from the intersubspecific cross of Lens culinaris ssp. culinaris and L. c. ssp. orientalis. Several traits were found to be significantly correlated. Using interval and composite interval mapping a total of 23 QTL for nine quantitative traits were located. No QTL was identified for the number of F3 seed produced. Six QTL were positioned respectively in linkage groups III and VI, and five QTL in linkage group I. Each remaining group included one or two QTL, except groups VII and IX where no QTL was found. The multiple QTL model explained more than 80% of the observed phenotypic variance with logarithm of the odds (LOD) scores above 10 for three of the quantitative traits analyzed (branches at first node, flowering time, and dehiscence). For the remaining traits the phenotypic variance explained was relatively low, between the 50% and 20%, and the LOD scores ranged between 4 and 8. The possible homology between some QTL and other previously described is discussed in relation to their chromosomal location.

Mixed model regression mapping for QTL detection in experimental crosses

This paper presents mixed model regression mapping (MMRM) as a method for mapping quantitative trait loci (QTL) in backcross and F2 data arising from crosses of inbred lines. It is related to interval mapping, composite interval mapping and other regression approaches but differs in that it tests for QTL presence in each linkage group before conditionally modeling QTL location. The three key ideas presented are to promote use of a Likelihood Ratio type of test for the presence of QTL in linkage groups before searching for QTL as a method of controlling false discovery rate, to present an alternative QTL profile to the LOD score for identifying the possible location of a QTL, and to promote the use of a local smoother to identify turning points in a profile based on evaluation at marker points rather than directly predicting all intermediate points. MMRM requires fitting a short series of models to locate and then evaluate putative QTL. Assuming marker covariates are allocated to linkage groups, MMRM first fits all the markers as independent random effects with common variance within the linkage groups. If there is no significant variance component associated with a linkage group, there is no evidence for a QTL associated with that group. Otherwise a QTL profile is predicted as a weighted sum of the marker BLUPs from which to postulate the most likely position of the QTL. A putative QTL covariate for that position is then calculated from flanking markers and added to the model. If this does not explain all the marker variance, the model is refined. Since MMRM is based on a linear mixed model, the model is easily extended to include extraneous sources of variation such as spatial variation in field experiments, to handle multiple QTL and to test for genotype by environment interactions. It is expounded using two simple examples analysed in the ASReml linear models software. Two simulation studies show that MMRM identifies QTL as reliably as but more directly than other common methods.

Use of the QTL approach to the study of soybean trait relationships in two populations of recombinant inbred lines at the F7 and F8 generations

This work aimed to identify the quantitative trait loci (QTL) associated with photosynthesis and growth and productivity traits of soybean and to study possible associations between these traits by the analysis of coincidence of QTL in linkage groups (LGs). Thus, populations of recombinant inbred lines (RILs) of the F7 and F8 generations derived from the cross between the varieties BARC-8 and Garimpo were used. The traits evaluated were net assimilation rate of CO2 under saturating light (Asat), potential photosynthesis rate (Pmax), leaf area (A), specific leaf area (SLA), specific leaf nitrogen (N); root (W R), nodule (W N), stem (W ST), leaf (W L), pod (W P) and plant dry mass (W T); nodule (nN), seed (n s), and pod number (nP); seed fresh mass per plant (W S), one-hundred seed fresh mass (W HS) and seed protein percentage (P%). It was possible to identify the following QTL associated with the following soybean traits: SLA, Asat, N, W R, W ST, W L, W T, W P, W HS, n s and nP, indicating that the RIL population has a great potential for mapping loci associated with quantitative traits of the soybean crop. The correlations between the soybean traits were partially confirmed by coincidence of QTL.

Genetic analysis of floral anthocyanin pigmentation traits in Asiatic hybrid lily using molecular linkage maps.

To understand the genetic background of two floral anthocyanin pigmentation traits, anthocyanin pigmentation in the flower tepals and spot formation, in the Asiatic hybrid lily (2n = 24), segregation of the two traits among 96 F(1) plants derived from a cross between commercial cultivars 'Montreux' and 'Connecticut King' were investigated. 'Montreux' has anthocyanin pigmentation in the tepals with many spots, and 'Connecticut King' has flowers with carotenoid pigmentation without spots. The F(1) plants with or without anthocyanin pigment in the tepals segregated with a 1:1 segregation ratio, indicating that a single gene controls anthocyanin pigmentation in the tepals. The number of spots per square centimeter of all tepals showed continuous distribution in the F(1) plants. To map the loci for the two anthocyanin pigmentation traits, molecular linkage maps in the Asiatic hybrid lily were constructed using a double pseudo-testcross strategy, with the same F(1) plants used for phenotypic evaluation, and 212 PCR-based DNA markers. The trait for anthocyanin pigmentation in tepals was used as a trait marker. The map of 'Montreux' comprised 95 markers in 26 linkage groups, and the map of 'Connecticut King' used 119 markers in 24 linkage groups. The total map lengths were 867.5 and 1,114.8 cM, respectively. The trait locus for anthocyanin pigmentation in the tepals was between markers ASR35-180 and P506-40 in linkage group 1 of the 'Montreux' map with a map distance of 1.2 cM and 2.6 cM, respectively. A single-point analysis of quantitative trait loci (QTLs) for tepal spot number identified two putative QTLs in linkage groups 1 and 19 of the 'Connecticut King' map. One putative QTL in linkage group 19 explained 64% of the total phenotypic variation. Because both putative QTLs were mapped on the linkage map of 'Connecticut King' that has no spots, dominant alleles of them might suppress spot formation.

Quantitative trait loci for growing degree days to flowering and photoperiod response in Sunflower (Helianthus annuus L.)

The number of days from seedling emergence to flowering (DTF) is a major consideration in sunflower breeding programs. This is a complex trait determined by the genotype, environmental conditions and interactions. Photoperiod and temperature have major effects on DTF and could be important sources of genotype× environment interaction. The objectives of this study were to locate quantitative trait loci (QTLs) associated with growing degree days (GDD) to flowering and photoperiod (PP) response in an elite sunflower population. Two hundred and thirty five F2-generation plants and their F2:3 and F2:4 progenies of a single-cross population of two divergent inbred lines were evaluated in six environments (locations, years and sowing dates) with photoperiods known to elicit a PP response between the inbred lines. Detection of QTLs was facilitated with a genetic linkage map of 205 RFLP loci and composite interval mapping. The 205 restriction fragment length polymorphism (RFLP) loci covered 1380 cM and were arranged in 17 linkage groups, which is the haploid number of chromosomes in this species. The average interval size was 5.9 cM. Six QTLs in linkage groups A, B, F, I, J and L were associated with GDD to flowering and accounted for 76% of the genotypic variation in the mean environment. QTLs in linkage groups A and B accounted for 72% of the genetic variation. QTL×environment (QTL×E) interactions were highly significant for linkage groups A, B, F and J (P<0.01). QTLs in linkage groups A and B were highly dependent on PP. Also, QTL mapping of the ratio of the GDD required by a progeny to flower at a PP of 12.1 and 15.0 h, defined as the photoperiod response (PPR), suggested that alleles at QTLs in linkage groups A and B were responsive to PP. QTLs in linkage groups F and J showed QTL×E interaction but the LOD values were not associated with PP. QTL×E interactions for additive effects were highly significant (P<0.01) for linkage groups A, B and F. QTL×E interactions for QTLs with dominant effects were significant (P<0.01) for linkage groups A, B and J. The dominant effect of QTLs in linkage group B increased in environments with a longer PP. The knowledge of how these QTLs influence the GDD for flowering and how they interact with the environment will facilitate marker- assisted selection and backcross conversion of photoperiod-sensitive germplasm.

Soybean Response to Water: A QTL Analysis of Drought Tolerance

Soybean [Glycine max (L.) Merr.] yield, when regressed on water needed to replenish 0 to 100% seasonal evapotranspiration (ET), generates an estimate of season‐specific water‐use efficiency (WUE). The impact of unpredictable water deficits might be lessened if high‐yielding genotypes had a smaller beta. Our objective was to determine the genetic basis of beta and carbon isotope discrimination (CID), a theorized indicator of transpiration efficiency (TE). A ‘Minsoy’ × ‘Noir 1’ population of 236 recombinant inbred lines (RILs), genotyped at 665 loci, was evaluated in six water treatments (100, 80, 60, 40, 20, and 0% ET) for 2 yr. Water stress was mild in 1994, but high temperatures and no rainfall in 1995 led to a drought so severe that the 100% ET treatment required 41 cm of irrigation. The 1995 yield‐to‐water regression was highly linear (28 kg ha−1 cm−1). Genotype × water (G × W) interaction was due to genotypic heterogeneity in beta The CID vs. beta correlation was low (r = 0.26), so selection for better leaf TE may not improve crop WUE. Selection of low beta (less sensitivity to drought) will be difficult, given the yield beta vs. yield correlation (r = 0.71). The major quantitative trait loci (QTL) for yield beta, yield, and CID were coincident with maturity and/or determinancy QTLs, except for a CID QTL in linkage group U09‐C2, but it had no effect on beta Genetic improvement of soybean yield performance under drought would be better achieved by coupling a high‐yield grand mean with a high‐ (not low‐) yield beta