Identification and Validation of Quantitative Trait Loci for Agronomic Traits in Advanced Backcross Breeding Lines Derived from Oryza rufipogon × Oryza sativa Cultivar MR219

A backcross breeding strategy was used to identify quantitative trait loci (QTLs) associated with 14 traits in a BC₂F₂ population derived from a cross between MR219, an indica rice cultivar and an accession of Oryza rufipogon (IRGC 105491). A total of 261 lines were genotyped with 96 microsatellite markers and evaluated for plant morphology, yield components and growth period. The genetic linkage map generated for this population with an average interval size of 16.2?cM, spanning 1,553.4?cM (Kosambi) of the rice genome. Thirty-eight QTLs were identified with composite interval mapping (CIM), whereas simple interval mapping (SIM) resulted in 47 QTLs (LOD >3.0). The O. rufipogon allele was favourable for 59% of QTLs detected through CIM. Of 261 BC₂F₂ families, 26 advanced backcross breeding lines (BC₂F₅) were used for QTL validation. These lines were selected on the basis of the yield traits potentiality in BC₂F₃ and BC₂F₄ generations. The field trial was conducted at three different locations in Malaysia using randomized complete block design with three replications. Trait based marker analysis was done for QTL determination. Twenty-five QTLs were detected in BC₂F₅ generation whereas 29 QTLs were detected in BC₂F₂ generation of the same population. Two QTLs (qPL-1 and qSPL-7) were not considered for validation due to their low R ² values and two QTLs (qPSS-3-2 and qGW-3-2) were not detected in the BC₂F₅ population. Fifteen QTLs showed the beneficial effect to enhance the trait value of the breeding lines. QTL validation aided to select the promising lines for further utilization.     

Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F_2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F_2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.     

Analyzing quantitative trait loci for yield using a vegetatively replicated F2 population from a cross between the parents of an elite rice hybrid

Although F₂s are the most informative populations for genetic analysis, it has been difficult to use F₂ populations directly for QTL analysis because it is usually difficult to assess the reliability of the data, due to an inability to estimate the experimental errors. In this study, we performed a QTL analysis for yield and yield-component traits of an F₂ population based on data from replicated field trials over 2 years using vegetative shoots of ratooned plants, making use of the ratooning habit of rice. The objective of this study was to explore the possibility of conducting QTL analyses directly based on an F₂ population by means of ratooning plants. The experimental population was from a cross between ’Zhenshan 97’ and ’Minghui 63’, the parents of ’Shanyou 63’, an elite rice hybrid widely grown in China. A genetic linkage map containing 151 molecular markers was constructed for QTL mapping. A total of 20 distinct QTLs were detected; eight of these were detected in both years and remaining 12 in only 1 year. Compared with the results of our previous analysis of the F_2:3 families from the same cross, it was shown that most of the QTLs detected in the ratooned F₂ population were also detected in the F_2:3 population. However, the estimates of both additive and dominant types of genetic effects for many of the QTLs based on F₂ ratoons were substantially larger than those based on F_2:3 families. The results indicate that vegetatively ratooned F₂ populations may have considerable utility in the mapping of QTLs, especially if dominant types of gene actions are of concern, although there were certain technical limitations in making use of such populations in the experiments. Received: 11 November 1999 / Accepted: 24 November 1999     

Quantitative trait loci analysis of plant height and ear height in maize (Zea mays L.)

Genetic map containing 103 microsatellite loci obtained on 200 F₂ plants derived from the cross R15 × 478 was used for quantitative trait loci (QTL) mapping in maize. QTLs were characterized in a population of 200 F_2:4 lines, derived from selfing the F₂ plants, and were evaluated with two replications in two environments. QTL determinations were made from the mean of these two environments. Plant height (PH) and ear height (EH) were measured. Using composite interval mapping (CIM) method, a total of 14 distinct QTLs were identified: nine for PH and five for EH. Additive, partial dominance, dominance, and overdominance actions existed among all detected QTLs affecting plant height and ear height. The QTLs explained 78.27% of the phenotypic variance of PH and 41.50% of EH. The 14 QTLs displayed mostly dominance or partial dominance gene action and mapped to chromosomes 2, 3, 4, 8, and 9. The text was submitted by the authors in English.     

QTL mapping and confirmation for tolerance of anaerobic conditions during germination derived from the rice landrace Ma-Zhan Red

Wide adoption of direct-seeded rice practices has been hindered by poorly leveled fields, heavy rainfall and poor drainage, which cause accumulation of water in the fields shortly after sowing, leading to poor crop establishment. This is due to the inability of most rice varieties to germinate and reach the water surface under complete submergence. Hence, tolerance of anaerobic conditions during germination is an essential trait for direct-seeded rice cultivation in both rainfed and irrigated ecosystems. A QTL study was conducted to unravel the genetic basis of tolerance of anaerobic conditions during germination using a population derived from a cross between IR42, a susceptible variety, and Ma-Zhan Red, a tolerant landrace from China. Phenotypic data was collected based on the survival rates of the seedlings at 21 days after sowing of dry seeds under 10 cm of water. QTL analysis of the mapping population consisting of 175 F_2:3 families genotyped with 118 SSR markers identified six significant QTLs on chromosomes 2, 5, 6, and 7, and in all cases the tolerant alleles were contributed by Ma-Zhan Red. The largest QTL on chromosome 7, having a LOD score of 14.5 and an R ² of 31.7 %, was confirmed using a BC₂F₃ population. The QTLs detected in this study provide promising targets for further genetic characterization and for use in marker-assisted selection to rapidly develop varieties with improved tolerance to anaerobic condition during germination. Ultimately, this trait can be combined with other abiotic stress tolerance QTLs to provide resilient varieties for direct-seeded systems.     

QTLs for resistance to Setosphaeria turcica in an early maturing Dent×Flint maize population

Quantitative trait loci (QTLs) for resistance to the fungal pathogen Setosphaeria turcica, the cause of northern corn leaf blight (NCLB), were mapped in a population of 220 F₃ families derived from a cross between two moderately resistant European inbred lines, D32 (dent) and D145 (flint). The population was genotyped with 87 RFLP and 7 SSR markers. Trials were conducted in the field in Switzerland, and in the greenhouse with selected F₃ families in Germany. The F₃ population segregated widely for resistance with transgression of the parents. By composite interval mapping, a total of 13 QTLs were detected with two disease ratings (0 and 3 weeks after flowering). Together these QTLs explained 48% and 62% of the phenotypic variation. Gene action at most QTLs was partially dominant. Eight out of the 13 QTL alleles for resistance were contributed by the more-resistant parent, D145. On chromosomes 3, 5 and 8, QTLs were located in the same chromosomal regions as QTLs in tropical and U.S. Corn Belt germplasm. Some QTLs affected NCLB, head smut and common rust at the same time, with alleles at these loci acting isodirectionally. Received: 25 January 1999 / Accepted: 20 Februar 1999     

Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects

Mixed linear model approach was proposed for mapping QTLs with the digenic epistasis and QTL by environment (QE) interaction as well as additive and dominant effects. Monte Carlo simulations indicated that the proposed method could provide unbiased estimations for both positions and genetic main effects of QTLs, as well as unbiased predictions for QE interaction effects. A method was suggested for predicting heterosis based on individual QTL effects. The immortalized F₂ (IF₂) population constructed by random mating among RI or DH lines is appropriate for mapping QTLs with epistasis and their QE interaction. Based on the models and methodology proposed, we developed a QTL mapping software, QTLMapper 2.0 on the basis of QTLmapper 1.0, which is suitable for analyzing populations of DH, RIL, F₂ and IF₂. Data of thousand grain weight of IF₂ population with 240 lines derived from elite hybrid rice Shanyou 63 were analyzed as a worked example.     

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

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

Identification of QTLs for grain yield and grain-related traits of maize (Zeamays L.) using an AFLP map, different testers, and cofactor analysis

We exploited the AFLP®¹(AFLP® is a registered trademark of Keygene, N.V.) technique to map and characterise quantitative trait loci (QTLs) for grain yield and two grain-related traits of a maize segregating population. Two maize elite inbred lines were crossed to produce 229 F₂ individuals which were genotyped with 66 RFLP and 246 AFLP marker loci. By selfing the F₂ plants 229 F₃ lines were produced and subsequently crossed to two inbred testers (T1 and T2). Each series of testcrosses was evaluated in field trials for grain yield, dry matter concentration, and test weight. The efficiency of generating AFLP markers was substantially higher relative to RFLP markers in the same population, and the speed at which they were generated showed a great potential for application in marker-assisted selection. AFLP markers covered linkage group regions left uncovered by RFLPs; in particular at telomeric regions, previously almost devoided of markers. This increase of genome coverage afforded by the inclusion of the AFLPs revealed new QTL locations for all the traits investigated and allowed us to map telomeric QTLs with higher precision. The present study has also provided an opportunity to compare simple (SIM) and composite interval mapping (CIM) for QTL analysis. Our results indicated that the method of CIM employed in this study has greater power in the detection of QTLs, and provided more precise and accurate estimates of QTL positions and effects than SIM. For all traits and both testers we detected a total of 36 QTLs, of which only two were in common between testers. This suggested that the choice of a tester for identifying QTL alleles for use in improving an inbred is critical and that the expression of QTL alleles identified may be tester-specific.     

A combined RFLP and AFLP linkage map of upland rice (Oryza sativa L.) used to identify QTLs for root-penetration ability

Acombined RFLP and AFLP linkage map of an F₆ recombinant inbred population, which was derived from a previously mapped F₂ of a cross between the two drought resistant upland rice varieties Bala and Azucena, is presented. The map contains 101 RFLP and 34 AFLP markers on 17 linkage groups covering 1680 cM. Also presented is the approximate mapping position of a further four RFLP and 75 AFLP markers, which either could not be given a unique place on the map or for which the available data is not sufficient to allow confident positioning, and the result of quantitative trait locus (QTL) mapping of traits related to root-penetration ability. Root penetration was assessed by counting the number of root axes that penetrated a 3 mm-thick layer consisting of 80% wax and 20% white soft paraffin. Good root penetration would be expected to increase drought resistance where soil strength is high. Single-marker analysis revealed seven QTLs for the number of roots which penetrate the wax layer. In identical locations were seven QTLs for the ratio of penetrated to the total number of roots. Transgressive inheritance of positive alleles from Bala explained four of these QTLs. Comparison of the QTLs identified here with previous reports of QTLs for root morphology suggest that alleles which improve root penetration ability may also either make the roots longer or thicker. Received: 3 February 1999 / Accepted: 30 April 1999     

Combination of Eight Alleles at Four Quantitative Trait Loci Determines Grain Length in Rice

Grain length is an important quantitative trait in rice (Oryza sativa L.) that influences both grain yield and exterior quality. Although many quantitative trait loci (QTLs) for grain length have been identified, it is still unclear how different alleles from different QTLs regulate grain length coordinately. To explore the mechanisms of QTL combination in the determination of grain length, five mapping populations, including two F₂ populations, an F₃ population, an F₇ recombinant inbred line (RIL) population, and an F₈ RIL population, were developed from the cross between the U.S. tropical japonica variety ‘Lemont’ and the Chinese indica variety ‘Yangdao 4’ and grown under different environmental conditions. Four QTLs (qGL-3-1, qGL-3-2, qGL-4, and qGL-7) for grain length were detected using both composite interval mapping and multiple interval mapping methods in the mapping populations. In each locus, there was an allele from one parent that increased grain length and another allele from another parent that decreased it. The eight alleles in the four QTLs were analyzed to determine whether these alleles act additively across loci, and lead to a linear relationship between the predicted breeding value of QTLs and phenotype. Linear regression analysis suggested that the combination of eight alleles determined grain length. Plants carrying more grain length-increasing alleles had longer grain length than those carrying more grain length-decreasing alleles. This trend was consistent in all five mapping populations and demonstrated the regulation of grain length by the four QTLs. Thus, these QTLs are ideal resources for modifying grain length in rice.     

Three QTLs from Lycopersicon peruvianum confer a high level of resistance to Clavibactermichiganensis ssp. michiganensis

Lycopersicon peruvianum LA2157 originates from 1650 m above sea level and harbours several beneficial traits for cultivated tomatoes such as cold tolerance, nematode resistance and resistance to bacterial canker (Clavibacter michiganensis ssp. michiganensis). In order to identify quantitative trait loci (QTLs) for bacterial canker resistance, a QTL mapping approach was carried out in an F₂ population derived from the interspecific F₁ between Lycopersicon esculentum cv Solentos and L. peruvianum LA2157. Three QTLs for resistance mapped to chromosomes 5, 7 and 9 respectively. The resistance loci were additive and co-dominant with the QTL on chromosome 7 explaining the largest part of the variation for resistance in the F₂ population. The combination of this QTL with either of the other two QTLs conferred a resistance similar to the level in the resistant parent L. peruvianum. Some RFLP markers flanking this QTL on chromosome 7 were converted into SCAR markers allowing efficient marker-assisted selection of plants with high resistance to bacterial canker. Received: 26 February 1999 / Accepted: 12 March 1999     

Mapping of the quantitative trait locus (QTL) conferring partial resistance to rice leaf blast disease

Malaysian rice, Pongsu Seribu 2, has wide-spectrum resistance against blast disease. Chromosomal locations conferring quantitative resistance were detected by linkage mapping with SSRs and quantitative trait locus (QTL) analysis. For the mapping population, 188 F₃ families were derived from a cross between the susceptible cultivar, Mahsuri, and a resistant variety, Pongsu Seribu 2. Partial resistance to leaf blast in the mapping population was assessed. A linkage map covering ten chromosomes and consisting of 63 SSR markers was constructed. 13 QTLs, including 6 putative and 7 putative QTLs, were detected on chromosomes 1, 2, 3, 5, 6, 10, 11 and 12. The resulting phenotypic variation due to a single QTL ranged from 2 to 13 %. These QTLs accounted for approx. 80 % of the total phenotypic variation within the F₃ population. Therefore, partial resistance to blast in Pongsu Seribu 2 is due to combined effects of multiple loci with major and minor effects.     

Genes on mouse Chromosomes 2 and 9 determine variation in ethanol consumption

Quantitative trait locus (QTL) mapping efforts in alcohol (ethanol) research are beginning to generate promising data that may ultimately lead to the identification of genes influencing alcohol addiction. Rodents have been extensively utilized to study ethanol's rewarding and aversive effects, and to demonstrate the existence of genetic influences on traits such as free-choice ethanol-consumption, ethanol-conditioned place preference and ethanol-conditioned taste aversion. The purpose of the current investigation was to verify or eliminate from further consideration putative QTLs for free-choice ethanol consumption originally identified in BXD Recombinant Inbred (RI) strains and other informative genetic crosses. B6D2F₂ mice were utilized in a verification testing strategy to evaluate the viability of putative ethanol consumption QTLs. When data were combined from BXD RI, B6D2F₂ and short-term selected line (STSL) mapping studies, verification was obtained for two QTLs, one on Chromosome (Chr) 9 (proximal-mid) and another on Chr 2 (distal), and suggestive verification was obtained for QTLs on Chrs 2 (proximal), 3, 4, 7, and 15. In addition, the possible genetic association of ethanol consumption with conditioned place preference was evaluated. Genetic correlations were estimated from BXD RI strain means, and QTL maps for these traits were compared to evaluate the possibility of a genetic association. The correlational analysis yielded a trend (r = 0.34, p = 0.09), but no statistically significant results. However, comparisons of QTL mapping results between phenotypes suggested some possible genetic overlap for these traits, both putative measures of ethanol reward. These data suggest that the determinants of these two measures are genetically diverse, but may share some common genetic elements. Received: 15 September 1998 / Accepted: 8 October 1998     

水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

控制水稻叶片叶绿素含量及其离体叶片叶绿素降解速度相关的QTL定位(简报)

许多研究认为,在一定范围内,叶绿素含量与光合速率成正相关关系、叶绿素含量高的水稻叶片能延缓衰老。理论上推算,水稻叶片如果推迟1天衰老,可使水稻增产2％左右,而实际实验结果表明可增产1％左右。叶片早衰往往也是造成有些水稻品种结实率偏低、空秕率较高及产量降低的主要原因。叶片衰老是水稻发育过程中的生命现象,它是水稻在长期进化过程中形成的适应性。叶片衰老的显著特征之一是叶绿素含量下降,叶色褪绿变黄。[第一段]     

QTL associated with resistance to cassava brown streak and cassava mosaic diseases in a bi-parental cross of two Tanzanian farmer varieties,Namikonga and Albert

Key message

QTL consistent across seasons were detected for resistance to cassava brown streak disease induced root necrosis and foliar symptoms. The CMD2 locus was detected in an East African landrace, and comprised two QTL.

Abstract

Cassava production in Africa is compromised by cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). To reduce costs and increase the precision of resistance breeding, a QTL study was conducted to identify molecular markers linked to resistance against these diseases. A bi-parental F₁ mapping population was developed from a cross between the Tanzanian farmer varieties, Namikonga and Albert. A one-step genetic linkage map comprising 943 SNP markers and 18 linkage groups spanning 1776.2 cM was generated. Phenotypic data from 240 F₁ progeny were obtained from two disease hotspots in Tanzania, over two successive seasons, 2013 and 2014. Two consistent QTLs linked to resistance to CBSD-induced root necrosis were identified in Namikonga on chromosomes II (qCBSDRNFc2Nm) and XI (qCBSDRNc11Nm) and a putative QTL on chromosome XVIII (qCBSDRNc18Nm). qCBSDRNFc2Nm was identified at Naliendele in both seasons. The same QTL was also associated with CBSD foliar resistance. qCBSDRNc11Nm was identified at Chambezi in both seasons, and was characterized by three peaks, spanning a distance of 253 kb. Twenty-seven genes were identified within this region including two LRR proteins and a signal recognition particle. In addition, two highly significant CMD resistance QTL (qCMDc12.1A and qCMDc12.2A) were detected in Albert, on chromosome 12. Both qCMDc12.1A and qCMDc12.2A lay within the range of markers reported earlier, defining the CMD2 locus. This is the first time that two loci have been identified within the CMD2 QTL, and in germplasm of apparent East African origin. Additional QTLs with minor effects on CBSD and CMD resistance were also identified.

     

Mapping quantitative trait loci (QTLs) for resistance to Cercospora leaf spot disease (Cercospora beticola Sacc.) in sugar beet (Beta vulgaris L.)

The breeding of sugar beet varieties that combine resistance to Cercospora and high yield under non-diseased conditions is a major challenge to the breeder. The understanding of the quantitative trait loci (QTLs) contributing to Cercospora resistance offers one route to solving this problem. A QTL analysis of Cercospora resistance in sugar beet was carried out using a linkage map based on AFLP and RFLP markers. Two different screening methods for Cercospora resistance (a field test at Copparo, Italy, under natural infection, and a newly-developed leaf disc test) were used to estimate the level of Cercospora resistance; the correlation between scores from the field (at 162 days after sowing) and the leaf disc test was significant. QTL analysis was based on F₂ and F₃ (half-sib family) generations derived from crosses between diploid single plants of 93164P (resistant to Cercospora leaf spot disease) and 95098P (susceptible). Four QTLs associated with Cercospora resistance (based on Lsmean data of the leaf disc test) on chromosomes III, IV, VII and IX were revealed using Composite interval mapping. To produce populations segregating for leaf spot resistance as a single Mendelian factor, we selected for plants heterozygous for only one of the QTLs (on chromosome IV or IX) but homozygous for the others. Received: 1 September 1999 / Accepted 7 October 1999     

Genetic mapping in maize with hybrid progeny across testers and generations: plant height and flowering

DNA markers were used to identify quantitative trait loci (QTLs) for plant height, ear height, and three flowering traits in hybrid progeny of two generations (F_2:3, F_6:8) of lines from a Mo17×H99 maize population. For both generations, testcross (TC) progeny were developed by crossing the lines to three inbred testers (B91, A632, B73). The hybrid progeny from the two generations were evaluated at the same locations but in different years as per an early generation testing program. QTLs were identified within each TC population and for mean testcross (MTC) performance. Overall, more QTLs were detected in the F_6:8 than the F_2:3 generation. Totalled over all five traits, 41 (B91) to 69% (B73) of the QTLs for tester effects and 67% of the QTLs for MTC detected in the F_2:3 generation were verified in the F_6:8 generation. Although differences in relative rank of the QTL effects across generations were observed, especially for the flowering traits, parental contributions were nearly always consistent. Several (8–11) QTLs were identified with effects for all three tester populations and for all traits except the anthesis-silk interval, which had only two such regions. Over all five traits, previous evaluations in this population identified 26 QTLs with consistent effects for two (F_2:3, F_6:8) inbred-progeny evaluations, and 20 (77%) were also associated with MTC in at least one of the generations evaluated herein. In all instances of common inbred and TC QTLs, parental contributions were the same. Received: 26 November 1999 / Accepted: 18 April 2000