Prediction of single-cross hybrid performance in maize using haplotype blocks associated with QTL for grain yield

Marker-based prediction of hybrid performance facilitates the identification of untested single-cross hybrids with superior yield performance. Our objectives were to (1) determine the haplotype block structure of experimental germplasm from a hybrid maize breeding program, (2) develop models for hybrid performance prediction based on haplotype blocks, and (3) compare hybrid performance prediction based on haplotype blocks with other approaches, based on single AFLP markers or general combining ability (GCA), under a validation scenario relevant for practical breeding. In total, 270 hybrids were evaluated for grain yield in four Dent × Flint factorial mating experiments. Their parental inbred lines were genotyped with 20 AFLP primer–enzyme combinations. Adjacent marker loci were combined into haplotype blocks. Hybrid performance was predicted on basis of single marker loci and haplotype blocks. Prediction based on variable haplotype block length resulted in an improved prediction of hybrid performance compared with the use of single AFLP markers. Estimates of prediction efficiency (R ² ) ranged from 0.305 to 0.889 for marker-based prediction and from 0.465 to 0.898 for GCA-based prediction. For inter-group hybrids with predominance of general over specific combining ability, the hybrid prediction from GCA effects was efficient in identifying promising hybrids. Considering the advantage of haplotype block approaches over single marker approaches for the prediction of inter-group hybrids, we see a high potential to substantially improve the efficiency of hybrid breeding programs. Tobias A. Schrag and Hans Peter Maurer contributed equally to this work.     

Prediction of hybrid performance in grain sorghum using RFLP markers

Heterosis is an important component of hybrid yield performance. Identifying high yielding hybrids is expensive and involves testing large numbers of hybrid combinations in multi-environment trials. Molecular marker diversity has been proposed as a more efficient method of selecting superior combinations. The aim of this study was to investigate the value of molecular marker-based distance information to identify high yielding grain sorghum hybrids in Australia. Data from 48 trials were used to produce hybrid performance-estimates for four traits (yield, height, maturity and stay green) for 162 hybrid combinations derived from 70 inbred parent lines. Each line was screened with 113 mapped RFLP markers. The Rogers distances between the parents of each hybrid were calculated from the marker information on a genome basis and individually for each of the ten linkage groups of sorghum. Some of the inbred parents were related so the hybrids were classified into 75 groups with each group containing individual hybrids that showed similar patterns of Rogers distances across linkage groups. Correlations between hybrid-group performance and hybrid-group Rogers distances were calculated. A significant correlation was observed between whole genome-based Rogers distance and yield ( r = 0.42). This association is too weak to be of value for identifying superior hybrid combinations. One reason for the generally poor association between parental genetic diversity and yield may be that important QTLs influencing heterosis are located in particular chromosome regions and not distributed evenly over the genome. Variation in the sign and magnitude of correlations between Rogers distance and hybrid-group performance for particular linkage groups observed in this study support this hypothesis. The concept of using diversity on individual linkage groups to predict performance was explored. Using data from just two linkage groups 38% of the variation in hybrid performance for grain yield could be explained. A model combining phenotypic trait data and parental diversity on particular linkage groups explained 71% of the variation in grain yield and has potential for use in the selection of heterotic hybrids.     

Genetic distance of inbred lines and prediction of maize single-cross performance using RAPD markers

 To evaluate the genetic diversity of 18 maize inbred lines, and to determine the correlation between genetic distance and single-cross hybrid performance, we have used random amplified polymorphic DNA (RAPD), a PCR-based technique. Eight of these lines came from a Thai synthetic population (BR-105), and the others derived from a Brazilian composite population (BR-106). Thirty two different primers were used giving a total of 325 reproducible amplification products, 262 of them being polymorphic. Genetic divergence was determinated using Jaccard’s similarity coefficient, and a final dendrogram was constructed using an unweighted pair-group method with arithmetical averages (UPGMA). Cluster analysis divided the samples into three distinct groups (GI, GII and GIII) that were confirmed by principal-coordinate analysis. The genetic distances (GD) were correlated with important agronomic traits for single-cross hybrids and heterosis. No correlation was found when group division was not considered, but significant correlations were detected between GI×GII and GI×GIII GDs with their respective single-cross hybrid grain-yield values. Three groups were identified; that is, the BR-106 population was divided in two different groups and the BR-105 population remained mostly as one group. The results indicated that RAPD can be used as a tool for determining the extent of genetic diversity among tropical maize inbred lines, for allocating genotypes into different groups, and also to aid in the choice of the superior crosses to be made among maize inbred lines, so reducing the number of crosses required under field evaluation. Received: 24 May 1996 / Accepted: 22 November 1996     

Identification of QTL for maize grain yield and kernel-related traits

Grain yield (GY) is one of the most important and complex quantitative traits in maize (Zea mays L.) breeding practice. Quantitative trait loci (QTLs) for GY and three kernel-related traits were detected in a set of recombinant inbred lines (RILs). One hundred and seven simple sequence repeats (SSRs) and 168 insertion/deletion polymorphism markers (Indels) were used to genotype RILs. Eight QTLs were found to be associated with four yield-related traits: GY, 100-kernel weight (HKW), 10-kernel length (KL), and 10-kernel length width (KW). Each QTL explained between 5.96 (qKL2-1) and 13.05 (qKL1-1) per cent of the phenotypic variance. Notably, one common QTL, located at the marker interval between bnlg1893 and chr2-236477 (chromosomal bin 2.09) simultaneously controlled GY and HKW; another common QTL, at bin 2.03 was simultaneously responsible for HKW and KW. Of the QTLs identified, only one pair of significant epistatic interaction involved in chromosomal region at bin 2.03 was detected for HKW; no significant QTL × environment interactions were observed. These results provide the common QTLs and for marker-assisted breeding.     

Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction

Accurate prediction of the phenotypic performance of a hybrid plant based on the molecular fingerprints of its parents should lead to a more cost-effective breeding programme as it allows to reduce the number of expensive field evaluations. The construction of a reliable prediction model requires a representative sample of hybrids for which both molecular and phenotypic information are accessible. This phenotypic information is usually readily available as typical breeding programmes test numerous new hybrids in multi-location field trials on a yearly basis. Earlier studies indicated that a linear mixed model analysis of this typically unbalanced phenotypic data allows to construct ɛ-insensitive support vector machine regression and best linear prediction models for predicting the performance of single-cross maize hybrids. We compare these prediction methods using different subsets of the phenotypic and marker data of a commercial maize breeding programme and evaluate the resulting prediction accuracies by means of a specifically designed field experiment. This balanced field trial allows to assess the reliability of the cross-validation prediction accuracies reported here and in earlier studies. The limits of the predictive capabilities of both prediction methods are further examined by reducing the number of training hybrids and the size of the molecular fingerprints. The results indicate a considerable discrepancy between prediction accuracies obtained by cross-validation procedures and those obtained by correlating the predictions with the results of a validation field trial. The prediction accuracy of best linear prediction was less sensitive to a reduction of the number of training examples compared with that of support vector machine regression. The latter was, however, better at predicting hybrid performance when the size of the molecular fingerprints was reduced, especially if the initial set of markers had a low information content.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.     

Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds

The identification of superior hybrids is important for the success of a hybrid breeding program. However, field evaluation of all possible crosses among inbred lines requires extremely large resources. Therefore, efforts have been made to predict hybrid performance (HP) by using field data of related genotypes and molecular markers. In the present study, the main objective was to assess the usefulness of pedigree information in combination with the covariance between general combining ability (GCA) and per se performance of parental lines for HP prediction. In addition, we compared the prediction efficiency of AFLP and SSR marker data, estimated marker effects separately for reciprocal allelic configurations (among heterotic groups) of heterozygous marker loci in hybrids, and imputed missing AFLP marker data for marker-based HP prediction. Unbalanced field data of 400 maize dent × flint hybrids from 9 factorials and of 79 inbred parents were subjected to joint analyses with mixed linear models. The inbreds were genotyped with 910 AFLP and 256 SSR markers. Efficiency of prediction (R ²) was estimated by cross-validation for hybrids having no or one parent evaluated in testcrosses. Best linear unbiased prediction of GCA and specific combining ability resulted in the highest efficiencies for HP prediction for both traits (R ² = 0.6–0.9), if pedigree and line per se data were used. However, without such data, HP for grain yield was more efficiently predicted using molecular markers. The additional modifications of the marker-based approaches had no clear effect. Our study showed the high potential of joint analyses of hybrids and parental inbred lines for the prediction of performance of untested hybrids.     

Markers associated with a QTL for grain yield in wheat under drought

Drought is a major abiotic stress that adversely affects wheat production in many regions of the world. The objective of this study was to identify quantitative trait loci (QTL) controlling grain yield and yield components under reduced moisture. A cross between common wheat cultivars ‘Dharwar Dry’ (drought tolerant) and ‘Sitta’ was the source of one hundred twenty-seven recombinant inbred lines evaluated for two-seasons in a field under differing soil moisture regimes in Ciudad Obregon, Sonora, Mexico. An SSR/EST-STS marker map was constructed and a grain yield QTL on the proximal region of chromosome 4AL was found to have a significant impact on performance under reduced moisture. This region was associated with QTL for grain yield, grain fill rate, spike density, grains m⁻², biomass production, biomass production rate, and drought susceptibility index (DSI). Molecular markers associated with these traits explained 20, 33, 15, 23, 30, 26, and 41% of phenotypic variation, respectively on chromosome 4A. Microsatellite locus Xwmc89 was associated with all significant QTL covering a 7.7 centiMorgans (cM) region and generally explained the greatest proportion of phenotypic variation. The alleles associated with enhanced performance under drought stress were contributed by Dharwar Dry. Microsatellite marker wmc89 may be useful for marker assisted selection to enhance drought tolerance.     

QTL analysis for grain protein content using SSR markers and validation studies using NILs in bread wheat

QTL interval mapping for grain protein content (GPC) in bread wheat was conducted for the first time, using a framework map based on a mapping population, which was available in the form of 100 recombinant inbred lines (RILs). The data on GPC for QTL mapping was recorded by growing the RILs in five different environments representing three wheat growing locations from Northern India; one of these locations was repeated for 3 years. Distribution of GPC values followed normal distributions in all the environments, which could be explained by significant g x e interactions observed through analyses of variances, which also gave significant effects due to genotypes and environments. Thirteen (13) QTLs were identified in individual environments following three methods (single-marker analysis or SMA, simple interval mapping or SIM and composite interval mapping or CIM) and using LOD scores that ranged from 2.5 to 6.5. Threshold LOD scores (ranging from 3.05 to 3.57), worked out and used in each case, however, detected only seven of the above 13 QTLs. Only four (QGpc.ccsu-2B.1; QGpc.ccsu-2D.1; QGpc.ccsu-3D.1 and QGpc.ccsu-7A.1) of these QTLs were identified either in more than one location or following one more method other than CIM; another QTL (QGpc.ccsu-3D.2), which was identified using means for all the environments, was also considered to be important. These five QTLs have been recommended for marker-assisted selection (MAS). The QTLs identified as above were also validated using ten NILs derived from three crosses. Five of the ten NILs possessed 38 introgressed segments from 16 chromosomes and carried 42 of the 173 markers that were mapped. All the seven QTLs were associated with one or more of the markers carried by the above introgressed segments, thus validating the corresponding markers. More markers associated with many more QTLs to be identified should become available in the future by effective MAS for GPC improvement.     

Allozyme marker loci associated with favorable alleles for grain yield in maize

Summary The evaluation of germplasm to identify its potential as a source of new favorable alleles is a time-consuming phase of maize hybrid breeding programs. The objective of this paper was to study the relationship between allozyme diversity and quantitative estimators of the relative number of new favorable alleles for grain yield, present in donor lines but not present in the elite hybrid. Twenty-two maize inbred lines representing heterotic groups from the United States (US) and Yugoslavia (YU) were used as donors to estimate the presence of new favorable alleles for grain yield improvement for the hybrid B73 x Mo17. In a second experiment, a 15-line diallel was grown, and 13 single crosses differing in allozyme relatedness measure (ARM) and heterotic grouping were considered as targets to be improved by the remaining 13 lines. Minimally biased estimates of new favorable alleles for grain yield (G) and ARM values were made for all donor lines within each target hybrid. Donor lines were grouped in four allozyme-pedigree classes for each target hybrid to compare the effect of allozyme diversity with pedigree diversity. Pedigree dissimilarities had significant effects on G estimates. Dissimilar pedigree classes had higher G estimates than similar pedigree classes. Allozyme differences between donor inbred lines and target hybrids had inconsistent effects on G estimates. Significant differences in G estimates among allozyme classes were found for 31% of the target hybrids. Classes with similar allozymes had higher G estimates more frequently than classes with disimilar allozymes. Correlation coefficients between G estimates and ARM values were low and not significant for 12 of the 14 target hybrids.This project was partially supported by the USDA and Republic Funds for Scientific work of Serbia through funds available to the United States-Yugoslav Joint Board of Scientific and Technological Cooperation, Project JFP 662     

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

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

Improvement of hybrid yield by advanced backcross QTL analysis in elite maize

We applied an advanced backcross breeding strategy to identify quantitative trait loci (QTLs) of agronomic importance in a cross between two elite inbreds of maize, RD6502 (Mo17-type recurrent parent) and RD3013 (Iodent donor parent). Two hundred and four BC(2) families were scored at 106 SSR, 15 AFLP, and 38 Heartbreaker (MITE) loci. BC(2) testcrosses (TC) with B73 were phenotyped at six locations in the Midwest and N.Y. We detected four grain yield, six grain moisture, and three plant height QTLs at which the RD3013 allele had a favorable effect ( p < 0.05). All four yield QTLs were selected as target introgressions in the development of BC(3)TC families. As predicted by BC(2)TC analysis, BC(3)TC entries containing introgressions at yld3.1 and yld10.1 significantly outperformed non-carrier entries by 11.1% (15.6 bu/A at one location) and 6.7% (7.1 bu/A averaged across two locations), respectively, in replicated Midwestern trials ( p < 0.05). Detection of yld10.1 effects in the BC(2)TC by spatial analysis (i.e., incomplete block, response surface, autoregressive, moving average or autoregressive moving average), but not by conventional single point analysis or interval mapping, indicated the utility of local environmental control for QTL mapping in unreplicated maize progeny. This work demonstrated that the advanced backcross QTL method can be applied to identify and manipulate useful QTLs in heterotic inbreds of elite maize. Genetic gains by this approach can be coupled with the maintenance and selection of favorable epistatic gene complexes by traditional hybrid breeding for maize improvement.     

Prediction of maize hybrid performance using similarity in state and similarity by descent information

We evaluated the efficiency of the best linear unbiased predictor (BLUP) and the influence of the use of similarity in state (SIS) and similarity by descent (SBD) in the prediction of untested maize hybrids. Nine inbred lines of maize were crossed using a randomized complete diallel method. These materials were genotyped with 48 microsatellite markers (SSR) associated with the QTL regions for grain yield. Estimates of four coefficients of SIS and four coefficients of SBD were used to construct the additive genetic and dominance matrices, which were later used in combination with the BLUP for predicting genotypic values and specific combining ability (SCA) in unanalyzed hybrids under simulated unbalance. The values of correlations between the genotypic values predicted and the means observed, depending on the degree of unbalance, ranged from 0.48 to 0.99 for SIS and 0.40 to 0.99 using information from SBD. The results obtained for the SCA ranged from 0.26 to 0.98 using the SIS and 0.001 to 0.990 using the SBD information. It was also observed that the predictions using SBD showed less biased than SIS predictions demonstrating that the predictions obtained by these coefficients (SBD) were closer to the observed value, but were less efficient in the ranking of genotypes. Although the SIS showed a bias due to overestimation of relatedness, this type of coefficient may be used where low values are detected in the SBD in the group of parents because of its greater efficiency in ranking the candidates hybrids.     

A simplified QTL mapping approach for screening and mapping of novel AFLP markers associated with beef marbling

Genome screening of quantitative trait loci (QTL) for a complex trait is usually costly and highly laborious, as it requires a large number of markers spanning the whole genome. Here we present a simplified approach for screening and mapping of QTL-linked markers for beef marbling using a WagyuxLimousin F(2) reference population. This simplified approach involves integration of the amplified fragment length polymorphism (AFLP) with DNA pooling and selective genotyping and comparative bioinformatics tools. AFLP analysis on two high and two low marbling DNA pools yielded ten visually different markers. Among them, four were confirmed based on individual AFLP validation. Sequencing and in silico characterization assigned two of these AFLP markers to bovine chromosomes 1 (BTA1) and 13 (BTA13), which are orthologous to human chromosomes HSA21q22.2 and HSA10p11.23 with both regions harboring QTL for obesity-related phenotypes. Both AFLP markers showed significantly large additive genetic effects (0.28+/-0.11 on BTA1 and 0.54+/-0.21 on BTA13) on beef-marbling score (BMS) (P<0.05). Overall, this approach is less time consuming, inexpensive and in particular, suitable for screening and mapping QTL-linked markers when targeting one or a few complex traits.     

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.     

Transferring a major QTL for oil content using marker-assisted backcrossing into an elite hybrid to increase the oil content in maize

Maize oil is highly valued as a human vegetable oil and in animal feed. The normal hybrid, Zhengdan958, is one of the most widely distributed varieties in China. To increase its oil content, a favorable allele of a major quantitative trait locus for oil content, qHO6 on chromosome 6 from the high-oil inbred line, By804, was transferred into the two parents of Zhengdan958, Zheng58, and Chang7-2, using marker-assisted backcrossing. Two improved inbred lines, Zheng58-qHO6 and Chang7-2-qHO6, were developed through six generations of backcrosses guided by molecular markers. An approximately 260-kb fragment from the donor parent was transferred into recurrent lines, and over 99 % of recurrent genomes were recovered. Both of the improved inbred lines showed increased oil content of roughly 1 % without a change in grain weight. Consequently, the oil content in improved Zhengdan958-qHO6, crossed from Zheng58-qHO6 to Chang7-2-qHO6, reached 4.5 %, with increases in absolute and relative content of 0.71 and 18 %, respectively, compared with the original Zhengdan958. The grain yield of the improved Zhengdan958-qHO6 ranged from 5,928 to 11,826 kg/ha in ten environments, similar to the original Zhengdan958. This study provides a practical example of the feasibility of improving quantitative traits by transferring desirable alleles using marker-assisted backcrossing.     

QTL mapping ofFusarium moniliforme ear rot resistance in maize. 1. Map construction with microsatellite and AFLP markers

To map the QTLsof Fusarium moniliforme ear rot resistance inZea mays L., a total of 230 F₂ individuals, derived from a single cross between inbred maize lines R15 (resistant) and Ye478 (susceptible), were genotyped for genetic map construction using simple sequence repeat (SSR) markers and amplified fragment length polymorphism (AFLP) markers. We used 778 pairs of SSR primers and 63 combinations of AFLP primers to detect the polymorphisms between parents, R15 and Ye478. From the polymorphic 30 AFLP primer combinations and 159 SSR primers, we scored 260 loci in the F₂ population, among which 8 SSR and 13 AFLP loci could not be assigned to any of the linkage groups. An integrated molecular genetic linkage map was constructed by the remaining 151 SSR and 88 AFLP markers, which distributed throughout the 10 linkage groups of maize and spanned the genome of about 3463.5 cM with an average of 14.5 cM between two markers. On 4 chromosomes, we detected 5 putative segregation distortion regions (SDR_s), including 2 new ones (SDR₂ and SDR₇). The other 3 SDR_s were located near the regions where gametophyte genes were mapped, indicating that segregation distortion could be partially caused by gametophytic factors.     

Application of AFLP markers for QTL mapping in the rabbit.

Two rabbit (Oryctolagus cuniculus) inbred strains (AX/JU and IIIVO/JU) have been used for genetic analysis of quantitative traits related to dietary cholesterol susceptibility. Application of the AFLP (amplified fragment length polymorphism) technique with 15 primer combinations revealed 226 polymorphisms between the 2 inbred strains. A total of 57 animals from a backcross progeny (IIIVO/JU x [IIIVO/JU x AX/JU]F1) were available for the genetic analysis. These backcross animals were fed a commercial pelleted diet fortified with 0.3% w/w cholesterol during a test period that lasted five weeks. A male genetic map could be constructed, consisting of 12 linkage groups and 103 AFLP markers. Linkage analysis between the cholesterol-related traits and marker loci revealed a significant LOD score for the relative weight of adrenal glands in males (LOD score = 3.83), whereas suggestive linkages were found for basal serum total cholesterol levels in females (LOD score = 2.69), for serum total cholesterol response (area under the curve) in males (LOD score = 2.21), and for hematocrit in males (LOD score = 3.24).     

A genetic linkage map based on AFLP and SSR markers and mapping of QTL for dry-matter content in sweetpotato

We developed a genetic linkage map of sweetpotato using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers and a mapping population consisting of 202 individuals derived from a broad cross between Xushu 18 and Xu 781, and mapped quantitative trait loci (QTL) for the storage root dry-matter content. The linkage map for Xushu 18 included 90 linkage groups with 2077 markers (1936 AFLP and 141 SSR) and covered 8,184.5 cM with an average marker distance of 3.9 cM, and the map for Xu 781 contained 90 linkage groups with 1954 markers (1824 AFLP and 130 SSR) and covered 8,151.7 cM with an average marker distance of 4.2 cM. The maps described herein have the best coverage of the sweetpotato genome and the highest marker density reported to date. These are the first maps developed that have 90 complete linkage groups, which is in agreement with the actual number of chromosomes. Duplex and triplex markers were used to detect the homologous groups, and 13 and 14 homologous groups were identified in Xushu 18 and Xu 781 maps, respectively. Interval mapping was performed first and, subsequently, a multiple QTL model was used to refine the position and magnitude of the QTL. A total of 27 QTL for dry-matter content were mapped, explaining 9.0–45.1 % of the variation; 77.8 % of the QTL had a positive effect on the variation. This work represents an important step forward in genomics and marker-assisted breeding of sweetpotato.