QTLs conditioning early growth in a soybean population segregating for growth habit

 There are both economic and environmental reasons for reducing the use of herbicides for weed control in soybean [Glycine max (L.) Merr.] fields. Optimizing crop competitiveness can reduce reliance on chemical weed control. Fast and vigorous early growth and rapid canopy development can be effective in suppressing weed infestation of crop plants. The purposes of this study were to identify and molecularly map the quantitative trait loci (QTLs) conditioning soybean plant height and canopy width during the early vegetative stages of soybean growth. A restriction fragment length polymorphism (RFLP) linkage map was created using 142 markers and 116 F₂-derived lines from a cross of ‘S100’בTokyo’. The parents and the 116 F₂-derived lines were evaluated in the greenhouse and in the field at Athens, Ga., in 1996 and 1997. Combined over environments, Tokyo averaged 41 and 17% taller plants than S100 at the V7 and V10 stages of development. Transgressive segregation was observed among the progeny at both stages. Based on single-factor analysis of variance (ANOVA), three and four independent RFLP loci were associated with plant height at the V7 and V10 stages, respectively. All three loci detected [on linkage groups (LGs) C2 and F, and unlinked] at the V7 stage were also detected at the V10 stage along with one additional independent locus on LG E. The Tokyo allele contributed to increased plant height at all loci except at the unlinked locus. Three QTLs (on LGs C2, E, and F) were consistent across environments, three (on LGs C2 and F, and unlinked) were consistent across stages of plant development, and two (on LGs C2 and F) were consistent both across environments and stages of plant development. Within each stage of development, there was no interaction among the independent loci, and the respective loci together explained most of the variation in the traits. Three independent RFLP loci were associated with canopy width at the V10 stage, of which one was unique to the trait, while the remaining loci (on LGs C2 and F) were in common with the independent loci for plant height. Canopy width had a strong correlation (r=0.87) with plant height at the V10 stage. However, mature plant height, lodging, or seed weight had no phenotypic or QTL association with early plant height or canopy width. Received: 10 May 1998 / Accepted: 13 July 1998     

Genetic mapping of QTLs conditioning soybean sprout yield and quality

Soybean sprouts have been used as a food in the Orient since ancient times. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W1 and T) were used to identify quantitative trait loci (QTLs) associated with soybean sprout-related traits in 100 F₂-derived lines from the cross of ’Pureunkong’×’Jinpumkong 2’. The genetic map consisted of 76 loci which covered about 756 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected in 1996 and 1997 for hypocotyl length, percentage of abnormal seedlings, and sprout yield 6 days after germination at 20°C. Hypocotyl length was determined as the average length from the point of initiation of the first secondary root to the point of attachment of the cotyledons. The number of decayed seeds and seedlings, plus the number of stunted seedlings (less than 2-cm growth), was recorded a s abnormal seedlings. Seed weight was determined based on the 50-seed sample. Sprout yield was recorded as the total fresh weight of soybean sprouts produced from the 50-seed sample divided by the dry weight of the 50-seed sample. Four QTLs were associated with sprout yield in the combined analysis across 2 years. For the QTL linked to L154 on the Linkage Group (LG) G the positive allele was derived from Pureunkong (R ² = 0.19), whereas at the other three QTLs (A089 on LG B1, A668n on LG K and B046 on LG L) the positive alleles were from Jinpumkong 2. QTLs conditioning seed weight were linked to markers A802n (LG B1), A069 (LG E), Cr321 (LG F) and A235 (LG G). At these four markers, the Jinpumkong allele increased seed weight. Markers K011n on LG B1, W1 on LG F and A757 on LG L were linked to QTLs conditioning hypocotyl length; and Bng119, K455n and K418n to QTLs conditioning the abnormal seedlings. The QTLs conditioning sprout yield were in the same genomic locations as the QTLs for seed weight identified in this population or from previously published research, indicating that QTLs for sprout yield are genetically linked to seed-weight QTLs or else that seed-weight QTLs pleiotropically condition sprout yield. These data demonstrate that effective marker-assisted selection may be feasible for enhancing sprout yield in a soybean. The transgressive segregation of sprout yield, as well as the existence of two QTLs conditioning greater than 10% of the phenotypic variation in sprout yields provides an opportunity to select for progeny lines with a greater sprout yield than currently preferred cultivars such as Pureunkong. Received: 23 August 2000 / Accepted: 23 January 2001     

A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.)

Late leaf spot (LLS) and rust are two major foliar diseases of groundnut (Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTL_rust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing.     

Molecular markers associated with seed weight in two soybean populations

Seed weight (SW) is a component of soybean, Glycine max (L.) Merr., seed yield, as well as an important trait for food-type soybeans. Two soybean populations, 120 F₄-derived lines of YoungxPI416937 (Pop1) and 111 F₂-derived lines of PI97100xCoker 237 (Pop2), were mapped with RFLP makers to identify quantitative trait loci (QTLs) conditioning SW across environments and populations. The genetic map of Pop1 consisted of 155 loci covering 973 cM, whereas Pop2 involved 153 loci and covered 1600 cM of map distance. For Pop1, the phenotypic data were collected from Plains, GA., Windblow, N.C., and Plymouth, N.C., in 1994. For Pop2, data were collected from Athens, GA., in 1994 and 1995, and Blackville, S.C., in 1995. Based on single-factor analysis of variance (ANOVA), seven and nine independent loci were associated with SW in Pop1 and Pop2, respectively. Together the loci explained 73% of the variability in SW in Pop1 and 74% in Pop2. Transgressive segregation occurred among the progeny in both populations. The marker loci associated with SW were highly consistent across environments and years. Two QTLs on linkage group (LG) F and K were located at similar genomic regions in both populations. The high consistency of QTLs across environments indicates that effective marker-assisted selection is feasible for soybean SW.     

Identification and mode of action of quantitative trait loci affecting seedling height and leaf area in Eucalyptus nitens

 Regions of the genome influencing height and leaf area in seedlings of a three-generation outbred pedigree of Eucalyptus nitens have been identified. Three QTLs affecting height and two QTLs affecting leaf area were located using single-factor analysis of variance. The three QTLs affecting height each explained between 10.3 and 14.7% of the phenotypic variance, while the two QTLs for leaf area each explained between 9.8 and 11.6% of the phenotypic variation. Analysis of fully informative marker loci linked to the QTLs enabled the mode of action of the QTLs to be investigated. For three loci the QTL effect segregated from only one parent, while for two loci the QTL showed multiple alleles and the effect segregated from both parents in the pedigree. The two QTLs affecting leaf area were located in the same regions as two of the QTLs affecting height. Analysis of these regions with fully informative markers showed that both QTLs were linked to the same markers, but one had a similar size of effects and a similar mode of action for both height and leaf area, whilst the other showed a different mode of action for the two traits. These regions may contain two closely linked genes or may involve a single gene with a pleiotrophic effect on both height and leaf area. The QTL with the greatest effect showed multiple alleles and an intra-locus interaction that reduced the size of the effect. Assessment for two of the QTLs in a second related family did not show an effect associated with the marker loci; however, this was consistent with the mode of action of these QTLs and the pattern of inheritance in the second family. Received: 1 August 1996 / Accepted: 25 October 1996     

RFLP markers associated with soybean cyst nematode resistance and seed composition in a ‘Peking’בEssex’ population

 Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, causes severe damage to soybean [Glycine max (L.) Merr] throughout North America and worldwide. Molecular markers associated with loci conferring SCN resistance would be useful in breeding programs using marker-assisted selection (MAS). In this study, 200 F_2:3 families derived from two contrasting parents, SCN-resistant ‘Peking’ with relatively low protein and oil concentrations, and SCN-susceptible ‘Essex’ with high protein and oil concentrations, were used to determine loci underlying the SCN resistance and seed composition. Three different SCN Race isolates (1, 3, and 5) were used to screen both parents and F_2:3 families. The parents were surveyed with 216 restriction fragment length polymorphism (RFLP) probes with five different restriction enzymes. Fifty-six were polymorphic and contrasted with trait data from bioassays to identify molecular markers associated with loci controlling resistance to SCN and seed composition. Five RFLP markers, A593 and T005 on linkage group (LG) B, A018 on LG E, and K014 and B072 on LG H, were significantly linked to resistance loci for Race 1 isolate, which jointly explained 57.7% of the total phenotypic variation. Three markers (B072 and K014, both on LG H; T005 on LG B) were associated with resistance to the Race 3 isolate and jointly explained 21.4% of the total phenotypic variation. Two markers (K011 on LG I, A963 on LG E) associated with resistance to the Race 5 isolate together explained 14.0% of the total phenotypic variation. In the same population we also identified two RFLP markers (B072 on LG H, B148 on LG F) associated with loci conferring protein concentration, which jointly explained 32.3% of the total phenotypic variation. Marker B072 was also linked to loci controlling the concentration of seed oil, which explained 21% of the total phenotypic variation. Clustering among quantitative trait loci (QTLs) conditioning resistance to different SCN Race isolates and seed protein and oil concentrations may exist in this population. We believe that markers located near these QTLs could be used to select for new SCN resistance and higher levels of seed protein and oil concentrations in breeding improved soybean cultivars. Received: 3 March 1998 / Accepted: 18 August 1998     

Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The stay-green character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 × Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI.1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL × Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r=0.22, P ≤ 0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the stay-green QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P ≤ 0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs. Received: 10 October 1998 / Accepted: 12 July 1999     

QTL analysis to study the association between leaf size and abscisic acid accumulation in droughted rice leaves and comparisons across cereals

Plants accumulate abscisic acid (ABA) under droughted conditions. Genetic variation in the accumulation of ABA in detached and partially dehydrated leaves of rice has previously been reported, and this was found to be associated with variation in leaf size (smaller leaves made more ABA). Correlation analysis failed to distinguish clearly between a causal relationship between the two traits and close genetic linkage between loci controlling the traits. Here we present a detailed genetic analysis of ABA accumulation in detached and partially dehydrated rice leaves, using a population of F₂ plants generated from the lowland × upland cross IR20 (high-ABA) × 63-83 (low-ABA) which was mapped with RFLP and AFLP markers. Several highly significant quantitative trait loci (QTLs) for ABA accumulation and leaf weight were identified. Only one of the minor QTLs for ABA accumulation (accounting for only 4% of the phenotypic variance) was coincident with any QTLs for leaf size such that the high-ABA allele was associated with smaller leaves. This analysis, therefore, showed that the association previously found between ABA accumulation and leaf size was probably largely due to genetic linkage and not to a direct effect of leaf size on ABA accumulation or vice versa. Because of the importance of ABA accumulation in regulating responses of plants to drought stress and the effects of plant size on the rate of development of stress, QTLs for drought-induced ABA accumulation, leaf size and tiller number were compared between rice and wheat. In particular, a possible location in rice was sought for a homoeologue of the major wheat vernalization responsive gene, Vrn1, as this gene is also associated with major effects on leaf size, tiller number and ABA accumulation in wheat. The likelihood of homoeologous loci regulating ABA accumulation, leaf size and tiller number in the two crops is discussed.     

Quantitative trait locus analysis for rice panicle and grain characteristics

 The development of molecular genetic maps has accelerated the identification and mapping of genomic regions controlling quantitative characters, referred to as quantitative trait loci or QTLs. A molecular map derived from an F₂ population of a tropical japonica×indica cross (Labelle/Black Gora) consisted of 116 restriction fragment length polymorphism (RFLP) markers. Composite interval mapping was used to identify the QTLs controlling six panicle and grain characteristics. Two QTLs were identified for panicle size at LOD>3.0, with one on chromosome 3 accounting for 16% of the phenotypic variation. Four loci controlling spikelet fertility accounted for 23% of the phenotypic variation. Seven, four, three and two QTLs were detected for grain length, breadth, shape and weight, respectively, with the most prominent QTLs being on chromosomes 3, 4, and 7. Grain shape, measured as the ratio of length to breadth, was mostly controlled by loci on chromosomes 3 and 7 that coincided with the most important QTLs identified for length and breadth, respectively. A model including three loci accounted for 45% of the phenotypic variation for this trait. The identification of economically important QTLs will be useful in breeding for improved grain characteristics. Received: 18 July 1997 / Accepted: 9 December 1997     

Comparative QTL mapping of resistance to Ustilago maydis across four populations of European flint-maize

 We mapped and characterized quantitative trait loci (QTLs) for resistance to Ustilago maydis and investigated their consistency across different flint-maize populations. Four independent populations, comprising 280 F₃ lines (A×B^I), 120 F₅ lines (A×B^II), 131 F₄ lines (A×C) and 133 F₄ lines (C×D), were produced from four European elite flint inbreds (A, B, C, D) and genotyped at 89, 151, 104, and 122 RFLP marker loci, respectively. All F_n lines were evaluated in field trials with two replications in five German environments. Genotypic variances were highly significant for the percentage of U. maydis infected plants (UST) in all populations, and heritabilities exceeded 0.69. Between five and ten QTLs were detected in individual populations by composite interval mapping, explaining between 39% and 58% of the phenotypic variance. These 19 different QTLs were distributed over all ten chromosomes without any clustering on certain chromosomes. In most cases, gene action was dominant or overdominant. Fourteen pairs of the detected QTLs for UST displayed significant digenic epistatic interactions, but only two of them did so after arcsin √UST/100 transformation. Significant QTL× environment interactions occurred frequently. Between two to four QTLs were common between pairs of populations. Population C×D was also grown in Chartres, a location with a high U. maydis incidence. Two out of six QTLs identified for Chartres were in common with QTLs detected across five German environments for C×D. Consequently, marker-assisted or phenotypic selection based on results from natural infection seem to be suitable breeding strategies for improving the resistance of maize to U. maydis. Received: 3 July 1998 / Accepted: 24 July 1998     

QTL analysis and mapping of pi21, a recessive gene for field resistance to rice blast in Japanese upland rice

Field resistance is defined as the resistance that allows effective control of a parasite under natural field conditions and is durable when exposed to new races of that parasite. To identify the genes for field resistance to rice blast, quantitative trait loci (QTLs) conferring field resistance to rice blast in Japanese upland rice were detected and mapped using RFLP and SSR markers. QTL analysis was carried out in F₄ progeny lines from the cross between Nipponbare (moderately susceptible, lowland) and Owarihatamochi (resistant, upland). Two QTLs were detected on chromosome 4 and one QTL was detected on each of chromosomes 9 and 12. The phenotypic variation explained by each QTL ranged from 7.9 to 45.7% and the four QTLs explained 66.3% of the total phenotypic variation. Backcrossed progeny lines were developed to transfer the QTL with largest effect using the susceptible cultivar Aichiasahi as a recurrent parent. Among 82 F₃ lines derived from the backcross, resistance segregated in the expected ratio of resistant 1 : heterozygous 2 : susceptible 1. The average score for blast resistance measured in the field was 4.2 ± 0.67, 7.5 ± 0.51and 8.2 ± 0.66, for resistant, heterozygous and susceptible groups, respectively. The resistance gene, designated pi21, was mapped on chromosome 4 as a single recessive gene between RFLP marker loci G271 and G317 at a distance of 5.0 cM and 8.5 cM, respectively. The relationship to previously reported major genes and QTLs conferring resistance to blasts, and the significance of marker-assisted selection to improve field resistance, are discussed. Received: 8 June 2000 / Accepted: 24 November 2000     

Association of specific leaf weight, an estimate of chlorophyll, and chlorophyll concentration with apparent photosynthesis in soybean

Increasing specific leaf weight (SLW) may improve leaf apparent photosynthesis (AP) in soybean [Glycine max (L.) Merr.] but screening for SLW and AP is laborious. The Objectives of this study were (i) to determine the time course of SLW and chlorophyll concentration in experimental lines selected for differences in SLW and (ii) to evaluate the potential use of the Minolta 502 SPAD meter as a rapid estimator of SLW, AP and chlorophyll concentration in leaves of soybean. In 1991 and 1992, sixteen experimental lines representing extremes in SLW were grown at Urbana, IL, and West Lafayette, IN, with three replications at each location. SPAD values, SLW and AP were measured at the R2 (full flower), R4 (full pod) and R5 (beginning seed) growth stages. In 1992 SLW, SPAD values and chlorophyll concentration were measured weekly. Seasonal patterns of SPAD values, SLW, and chlorophyll concentration were very similar through R5. After R5, SLW continued to increase but SPAD values and chlorophyll concentration declined. SPAD values and SLW were highly correlated at the R2, R4 and R5 stages at both locations and in both years. Environmental conditions during this research were not suitable for maximum AP expression, which is likely why AP and SPAD values were correlated only at the R4 growth stage at Urbana in 1992. SPAD measurements were consistent across diverse environments and effectively separated the high SLW lines from the low SLW lines. Measuring with the Minolta 502 SPAD meter is rapid, simple and non-destructive and could be an alternative method for direct selection for SLW.Abbreviations AP- leaf apparent photosynthesis - CV- coefficient of variation - Rug- leaf rugosity - SLW- specific leaf weight - SPAD-L- SPAD value of the most recently expanded terminal leaflet - SPAD-P- SPAD value of leaflet used to measure AP - SPAD-S- SPAD value of leaflets used to measure SLW - SPAD-U- SPAD value of the terminal leaflet one node above the most recently expanded terminal leaflet The US Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged     

Seed quality QTLs identified in a molecular map of early maturing soybean

This study identified QTLs influencing seed quality characters in a cross of two early maturing soybean (Glycine max [L.] Merr.) cultivars (Ma.Belle and Proto) adapted to the short growing seasons of Central Europe. A molecular linkage map was constructed by using 113 SSR, 6 RAPD and 1 RFLP markers segregating in 82 individuals of an F₂ population. The map consists of 23 linkage groups and corresponds wellto previously published soybean maps. Using phenotypic data of the F₂-derived lines grown in five environments, four markers for protein content, three for oil content and eight for seed weight were identified. Four from fifteen seed quality QTL-regions identified in the present study were also found by other authors. Markers associated with seed weight QTLs were consistent across all environments and proved to have effects large enough to be useful in a marker-assisted breeding program, whereas protein and oil QTLs showed environmental interactions. Received: 9 October 2000 / Accepted: 26 February 2001     

Identification of quantitative trait loci for plant height, lodging, and maturity in a soybean population segregating for growth habit

The use of molecular markers to identify quantitative trait loci (QTLs) has the potential to enhance the efficiency of trait selection in plant breeding. The purpose of the present study was to identify additional QTLs for plant height, lodging, and maturity in a soybean, Glycine max (L.) Merr., population segregating for growth habit. In this study, 153 restriction fragment length polymorphisms (RFLP) and one morphological marker (Dt1) were used to identify QTLs associated with plant height, lodging, and maturity in 111 F₂-derived lines from a cross of PI 97100 and Coker 237. The F₂-derived lines and two parents were grown at Athens, Ga., and Blackville, S.C., in 1994 and evaluated for phenotypic traits. The genetic linkage map of these 143 loci covered about 1600 cM and converged into 23 linkage groups. Eleven markers remained unlinked. Using interval-mapping analysis for linked markers and single-factor analysis of variance (ANOVA), loci were tested for association with phenotypic data taken at each location as well as mean values over the two locations. In the combined analysis over locations, the major locus associated with plant height was identified as Dt1 on linkage group (LG) L. The Dt1 locus was also associated with lodging. This locus explained 67.7% of the total variation for plant height, and 56.4% for lodging. In addition, two QTLs for plant height (K007 on LG H and A516b on LG N) and one QTL for lodging (cr517 on LG J) were identified. For maturity, two independent QTLs were identified in intervals between R051 and N100, and between B032 and CpTI, on LG K. These QTLs explained 31.2% and 26.2% of the total variation for maturity, respectively. The same QTLs were identified for all traits at each location. This consistency of QTLs may be related to a few QTLs with large effects conditioning plant height, lodging, and maturity in this population.     

Molecular breeding for grain yield in barley: an evaluation of QTL effects in a spring barley cross

 We report results from a breeding strategy designed to accumulate favorable QTL alleles for grain yield identified in the SteptoeבMorex’ (SM) barley germplasm. Two map lines (SM73 and SM145) from the original mapping population were selected based on their marker genotype and QTL structure. When crossed, these lines would be expected to produce progeny with most favorable QTL alleles. One hundred doubled haploid (DH) lines from the F₁ hybrid of this cross were genotyped with ten RFLP markers and one morphological marker defining grain yield to monitor QTL segregation. A subset of 24 lines representing various combinations of putatively favorable and unfavorable QTL alleles, together with Steptoe, ‘Morex’, SM73, and SM145, were phenotyped for grain yield in five environments. Multiple regression procedures were used to explore phenotype and genotype relationships. Most target QTLs showed significant effects. However, significance and magnitude of QTL effects and favorable QTL allele phase varied across environments. All target QTLs showed significant QTL-by-environment interaction (QTL×E), and the QTL on chromosome 2 expressed alternative favorable QTL alleles in different environments. Digenic epistatic effects were also detected between some QTL loci. For traits such as grain yield, marker-assisted selection efforts may be better targeted at determining optimum combinations of QTL alleles rather than pyramiding alleles detected in a reference mapping population. Received: 2 June 1998 / Accepted: 17 September 1998     

RFLP loci associated with soybean seed protein and oil content across populations and locations

Molecular markers provide the opportunity to identify marker-quantitative trait locus (QTL) associations in different environments and populations. Two soybean [Glycine max (L.) Merr.] populations, Young x PI 416 937 and PI 97100 x Coker 237, were evaluated with restriction fragment length polymorphism (RFLP) markers to identify additional QTLs related to seed protein and oil. For the Young x PI 416937 population, 120 F₄-derived lines were secored for segregation at 155 RFLP loci. The F₄-derived lines and two parents were grown at Plains, G.a., and Windblow and Plymouth, N.C. in 1994, and evaluated for seed protein and oil. For the PI 97100 x Coker 237 population, 111 F₂-derived lines were evaluated for segregation at 153 RFLP loci. Phenotypic data for seed protein and oil were obtained in two different locations (Athens, G.a., and Blackville, S.C.) in 1994. Based on single-factor analysis of variance (ANOVA) for the Young x PI 416937 population, five of seven independent markers associated with seed protein, and all four independent markers associated with seed oil in the combined analysis over locations were detected at all three locations. For the PI 97 100 x Coker 237 population, both single-factor ANOVA and interval mapping were used to detect QTLs. Using single-factor ANOVA, three of four independent markers for seed protein and two of three independent markers for seed oil were detected at both locations. In both populations, singlefactor ANOVA, revealed the consistency of QTLs across locations, which might be due to the high heritability and the relatively few QTLs with large effects conditioning these traits. However, interval mapping of the PI 97100 x Coker 237 population indicated that QTLs identified at Athens for seed protein and oil were different from those at Blackville. This might result from the power of QTL mapping being dependent on the level of saturation of the genetic map. Increased seed protein was associated with decreased seed oil in the PI 97100 x Coker 237 population (r = –0.61). There were various common markers (P0.05) on linkage groups (LG) E, G,H,K, and UNK2 identified for both seed protein and oil. One QTL on LG E was associated with seed protein in both populations. The other QTLs for protein and oil were population specific.     

Mapping of QTLs for lycopene and other fruit traits in a Lycopersicon esculentum × L. pimpinellifolium cross and comparison of QTLs across tomato species

Quantitative trait loci (QTLs) for several fruit traits in tomato were mapped and characterized in a backcross population of an interspecific cross between Lycopersicon esculentum fresh-marker breeding line NC84173 and L. pimpinellifolium accession LA722. A molecular linkage map of this cross that was previously constructed based on 119 BC1 individuals and 151 RFLP markers was used for the QTL mapping. The parental lines and 119 BC1S1 families (self-pollinated progeny of BC1 individuals) were grown under field conditions at two locations, Rock Spring, PA, and Davis, CA, and fruits were scored for weight (FW), polar (PD) and equatorial diameters (ED), shape (FS), total soluble solids content (SSC), pH and lycopene content (LYC). For each trait, between 4 and 10 QTLs were identified with individual effects ranging between 4.4% and 32.9% and multilocus QTL effects ranging between 39% and 75% of the total phenotypic variation. Most QTL effects were predictable from the parental phenotypes, and several QTLs were identified that affected more than one trait. A few pairwise epistatic interactions were detected between QTL-linked and QTL-unlinked markers. Despite great differences between PA and CA growing conditions, the majority of FW QTLs (78%) and SSC QTLs (75%) in the two locations shared similar genomic positions. Almost all of the QTLs that were identified in the present study for FW and SSC were previously identified in six other studies that used different interspecific crosses of tomato; this indicates conservation of QTLs for fruit traits across tomato species. Altogether, the seven studies identified at least 28 QTLs for FW and 32 QTLs for SSC on the 12 tomato chromosomes. However, for each trait a few major QTLs were commonly identified in 4 or more studies; such ‘popular’ QTLs should be of considerable interest for breeding purposes as well as basic research towards cloning of QTLs. Notably, a majority of QTLs for increased SSC also contributed to decreased fruit size. Therefore, to significantly increase SSC of the cultivated tomato, some compromise in fruit size may be unavoidable. This revised version was published online in June 2006 with corrections to the Cover Date.     

QTL identification of flowering time at three different latitudes reveals homeologous genomic regions that control flowering in soybean

Since the genetic control of flowering time is very important in photoperiod-sensitive soybean (Glycine max (L.) Merr.), genes affecting flowering under different environment conditions have been identified and described. The objectives were to identify quantitative trait loci (QTLs) for flowering time in different latitudinal and climatic regions, and to understand how chromosomal rearrangement and genome organization contribute to flowering time in soybean. Recombinant inbred lines from a cross between late-flowering ‘Jinpumkong 2’ and early-flowering ‘SS2-2’ were used to evaluate the phenotypic data for days to flowering (DF) collected from Kamphaeng Saen, Thailand (14°01′N), Suwon, Korea (37°15′N), and Longjing, China (42°46′N). A weakly positive phenotypic correlation (r = 0.36) was found between DF in Korea and Thailand; however, a strong correlation (r = 0.74) was shown between Korea and China. After 178 simple sequence repeat (SSR) markers were placed on a genetic map spanning 2,551.7 cM, four independent DF QTLs were identified on different chromosomes (Chrs). Among them, three QTLs on Chrs 9, 13 and 16 were either Thailand- or Korea-specific. The DF QTL on Chr 6 was identified in both Korea and China, suggesting it is less environment-sensitive. Comparative analysis of four DF QTL regions revealed a syntenic relationship between two QTLs on Chrs 6 and 13. All five duplicated gene pairs clustered in the homeologous genomic regions were found to be involved in the flowering. Identification and comparative analysis of multiple DF QTLs from different environments will facilitate the significant improvement in soybean breeding programs with respect to control of flowering time.     

QTL analysis of leaf morphology in tetraploid Gossypium (cotton)

Molecular markers were used to map and characterize quantitative trait loci (QTLs) determining cotton leaf morphology and other traits, in 180 F₂ plants from an interspecific cross between a Gossypium hirsutum genotype carrying four morphological mutants, and a wild-type Gossypium barbadense. The prominent effects of a single region of chromosome 15, presumably the classical ”Okra-leaf” locus, were modified by QTLs on several other chromosomes affecting leaf size and shape. For most traits, each parent contained some alleles with positive effects and others with negative effects, suggesting a large potential for adapting leaf size and shape to the needs of particular production regimes. Twenty one QTLs/loci were found for the morphological traits at LOD≥3.0 and P≤0.001, among which 14 (63.6%) mapped to D-subgenome chromosomes. Forty one more possible QTLs/loci were suggested with 2.0≤LOD<3.0 and 0.001<P≤0.01. Among all of the 62 possible QTLs (found at LOD≥2.0 and P≤0.01) for the 14 morphological traits in this study, 38 (61.3%) mapped to D-subgenome chromosomes. This reinforces the findings of several other studies in suggesting that the D-subgenome of tetraploid cotton has been subject to a relatively greater rate of evolution than the A-subgenome, subsequent to polyploid formation. Received: 26 April 1999 / Accepted: 30 July 1999     

Abnormal leaf formation in soybean: genetic and environmental effects

Soybean is trifoliolate, but 4-, 5-, or 6-foliolate leaves have been reported and expression of such multi-foliolate (MF) leaf forms has been shown to be heritable. Here we analyze the genetic complexity of the MF phenotype and the dependence of its expression on the environment. Recombinant inbred (RI) segregants of soybean were grown in different environments. The frequency of plants expressing the MF phenotype as well as the frequency of nodes exhibiting MF leaves varied with both the environment and the RI segregant genotype. Growth chamber experiments supported field observations suggesting that environment (day length, temperature, etc.) at emergence influenced expression of MF during subsequent growth. Marker facilitated analyses of three RI segregant populations identified quantitative trait loci (QTLs) in 17 regions of the soybean genome. These either directly regulated MF phenotype expression, or were involved in interactions with such loci. Loci, identified in one RI population also were identifiable in another, different, RI population. Most of the loci affected both the frequency of plants expressing MF, and the number of nodes on MF plants that expressed the phenotype. However, a few loci differentiated between these two effects. Many loci affected plants in both field experiments, however, a few differentiated between the two environments. Similar patterns were observed for interactions between loci. QTLs regulating the MF phenotype were located in genome regions that also contained QTLs regulating major agronomic traits—e.g. yield, lodging, etc. This suggests that the loci involved regulate plant growth at some over-arching level, controlling multiple phenotypes or traits.