Immortalized F2 Population Research Articles

Fine-Tuning Quantitative Trait Loci Identified in Immortalized F2 Population Are Essential for Genomic Prediction of Hybrid Performance in Maize

Maize breeding is greatly affected by hybrid vigor, a phenomenon that hybrids exhibit superior performance than parental lines. The immortalized F2 population (IMF2) is ideal for the genetic dissection and prediction of hybrid performance. Here, in this study, we conducted the QTL mapping and genomic prediction of six traits related to plant architecture using an IMF2 population. Broad-sense heritability of these traits ranged from 0.85 to 0.94. Analysis of genetic effects showed that additive variance was the main contributor to phenotypic variations. The mapping of quantitative trait loci (QTLs) revealed 10 to 16 QTLs (including pleiotropic loci and epistatic QTLs) for the six traits. Additionally, we identified 15 fine-tuning QTLs for plant height (PH). For genomic prediction (GP), the model of additive and dominance (AD) exhibited higher prediction accuracy than those fitting general combining ability (GCA) and its combination with special combining ability (SCA) effects for all tested traits. And adding the epistasis (E) effect into the AD model did not significantly increase its prediction accuracy. Moreover, the identified 15 fine-tuning QTLs of PH, which exerted large genomic prediction effects, were verified by the marker effect of GP. Our results not only provide an approach for the fine-mapping of fine-tuning QTLs but also serve as references for GP breeding in crops.

Genetic dissection of ear-related traits using immortalized F2 population in maize

Ear-related traits are often selection targets for maize improvement. This study used an immortalized F2 (IF2) population to elucidate the genetic basis of ear-related traits. Twelve ear-related traits (namely, row number (RN), kernel number per row (KNPR), ear length (EL), ear diameter (ED), ten-kernel thickness (TKT), ear weight (EW), cob diameter (CD), kernel length (KL), kernel width (KW), grain weight per ear (GW), 100-kernel weight (HKW), and grain yield per plot (GY)), were collected from the IF2 population. The ear-related traits were comprised of 265 crosses derived from 516 individuals of the recombinant inbred lines (RILs) under two separated environments in 2017 and 2018, respectively. Quantitative trait loci (QTLs) analyses identified 165 ear traits related QTLs, which explained phenotypic variation ranging from 0.1 to 12.66%. Among the 165 QTLs, 19 underlying nine ear-related traits (CD, ED, GY, RN, TKT, HKW, KL, GW, and KNPR) were identified across multiple environments and recognized as reliable QTLs. Furthermore, 44.85% of the total QTLs showed an overdominance effect, and 12.72% showed a dominance effect. Additionally, we found 35 genomic regions exhibiting pleiotropic effects across the whole maize genome, and 17 heterotic loci (HLs) for RN, EL, ED and EW were identified. The results provide insights into genetic components of ear-related traits and enhance the understanding of the genetic basis of heterosis in maize.

Modification of Experimental Design and Statistical Method for Mapping Imprinted QTLs Based on Immortalized F2 Population.

Genomic imprinting is an epigenetic phenomenon, which plays important roles in the growth and development of animals and plants. Immortalized F2 (imF2) populations generated by random cross between recombinant inbred (RI) or doubled haploid (DH) lines have been proved to have significant advantages for mapping imprinted quantitative trait loci (iQTLs), and statistical methods for this purpose have been proposed. In this paper, we propose a special type of imF2 population (R-imF2) for iQTL mapping, which is developed by random reciprocal cross between RI/DH lines. We also propose two modified iQTL mapping methods: two-step point mapping (PM-2) and two-step composite point mapping (CPM-2). Simulation studies indicated that: (i) R-imF2 cannot improve the results of iQTL mapping, but the experimental design can probably reduce the workload of population construction; (ii) PM-2 can increase the precision of estimating the position and effects of a single iQTL; and (iii) CPM-2 can precisely map not only iQTLs, but also non-imprinted QTLs. The modified experimental design and statistical methods will facilitate and promote the study of iQTL mapping.

Identification of quantitative trait loci for kernel-related traits and the heterosis for these traits in maize (Zea mays L.).

Heterosis has been extensively applied for many traits during maize breeding, but there has been relatively little attention paid to the heterosis for kernel size. In this study, we evaluated a population of 301 recombinant inbred lines derived from a cross between 08-641 and YE478, as well as 298 hybrids from an immortalized F2 (IF2) population to detect quantitative trait loci (QTLs) for six kernel-related traits and the mid-parent heterosis (MPH) for these traits. A total of 100 QTLs, six pairs of loci with epistatic interactions, and five significant QTL × environment interactions were identified in both mapping populations. Seven QTLs accounted for over 10% of the phenotypic variation. Only four QTLs affected both the trait means and the MPH, suggesting the genetic mechanisms for kernel-related traits and the heterosis for kernel size are not completely independent. Moreover, more than half of the QTLs for each trait in the IF2 population exhibited dominance, implying that dominance is more important than other genetic effects for the heterosis for kernel-related traits. Additionally, 20 QTL clusters comprising 46 QTLs were detected across ten chromosomes. Specific chromosomal regions (bins 2.03, 6.04-6.05, and 9.01-9.02) exhibited pleiotropy and congruency across diverse heterotic patterns in previous studies. These results may provide additional insights into the genetic basis for the MPH for kernel-related traits.

Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.)

BackgroundUtilization of heterosis in maize could be critical in maize breeding for boosting grain yield. However, the genetic architecture of heterosis is not fully understood. To dissect the genetic basis of yield-related traits and heterosis in maize, 301 recombinant inbred lines derived from 08 to 641 × YE478 and 298 hybrids from the immortalized F2 (IF2) population were used to map quantitative trait loci (QTLs) for nine yield-related traits and mid-parent heterosis.ResultsWe observed 156 QTLs, 28 pairs of loci with epistatic interaction, and 10 significant QTL × environment interactions in the inbred and hybrid mapping populations. The high heterosis in F1 and IF2 populations for kernel weight per ear (KWPE), ear weight per ear (EWPE), and kernel number per row (KNPR) matched the high percentages of QTLs (over 50%) for those traits exhibiting overdominance, whereas a notable predominance of loci with dominance effects (more than 70%) was observed for traits that show low heterosis such as cob weight per ear (CWPE), rate of kernel production (RKP), ear length (EL), ear diameter (ED), cob diameter, and row number (RN). The environmentally stable QTL qRKP3–2 was identified across two mapping populations, while qKWPE9, affecting the trait mean and the mid-parent heterosis (MPH) level, explained over 18% of phenotypic variations. Nine QTLs, qEWPE9–1, qEWPE10–1, qCWPE6, qEL8, qED2–2, qRN10–1, qKWPE9, qKWPE10–1, and qRKP4–3, accounted for over 10% of phenotypic variation. In addition, QTL mapping identified 95 QTLs that were gathered together and integrated into 33 QTL clusters on 10 chromosomes.ConclusionsThe results revealed that (1) the inheritance of yield-related traits and MPH in the heterotic pattern improved Reid (PA) × Tem-tropic I (PB) is trait-dependent; (2) a large proportion of loci showed dominance effects, whereas overdominance also contributed to MPH for KNPR, EWPE, and KWPE; (3) marker-assisted selection for markers at genomic regions 1.09–1.11, 2.04, 3.08–3.09, and 10.04–10.05 contributed to hybrid performance per se and heterosis and were repeatedly reported in previous studies using different heterotic patterns is recommended.

Genetic basis of heterosis for yield and yield components explored by QTL mapping across four genetic populations in upland cotton

BackgroundQuantitative trait loci (QTL) mapping provides a powerful tool to unravel the genetic bases of cotton yield and its components, as well as their heterosis. In the present study, the genetic basis underlying inbreeding depression and heterosis for yield and yield components of upland cotton was investigated in recombinant inbred line (RIL), immortalized F2 (IF2), and two backcross (BCF1) populations based on a high-density SNP linkage map across four environments.ResultsSignificant inbreeding depression of fruit branches per plant (FB), boll numbers per plant (BN), seed cotton yield (SY), and lint yield (LY) in RIL population and high levels of heterosis for SY, LY, and boll weight (BW) in IF2 and two BCF1 populations were observed. A total of 285 QTLs were identified in the four related populations using a composite interval mapping approach. In the IF2 population, 26.60% partially dominant (PD) QTLs and 71.28% over-dominant (OD) QTLs were identified. In two BCF1 populations, 42.41% additive QTLs, 4.19% PD QTLs, and 53.40% OD QTLs were detected. For multi-environment analysis, phenotypic variances (PV) explained by e-QTLs were higher than those by m-QTLs in each of the populations, and the average PV of m-QTLs and e-QTLs explained by QTL × environment interactions occupied a considerable proportion of total PV in all seven datasets.ConclusionsAt the single-locus level, the genetic bases of heterosis varied in different populations. Partial dominance and over-dominance were the main cause of heterosis in the IF2 population, while additive effects and over-dominance were the main genetic bases of heterosis in two BCF1 populations. In addition, the various genetic components to heterosis presented trait specificity. In the multi-environment model analysis, epistasis was a common feature of most loci associated with inbreeding depression and heterosis. Furthermore, the environment was a critical factor in the expression of these m-QTLs and e-QTLs. Altogether, additive effects, over-dominance, epistasis and environmental interactions all contributed to the heterosis of yield and its components in upland cotton, with over-dominance and epistasis more important than the others.

Genetic mapping of QTL for maize leaf width combining RIL and IF2 populations.

Leaf width is an important component of plant architecture that affects light capture during photosynthesis and wind circulation under dense planting conditions. To improve understanding of the genetic mechanisms involved in leaf width at different positions, a comprehensive evaluation using the RIL (Recombinant Inbred Line) and IF2 (Immortalized F2) populations and a subsequent meta-analysis were performed. Forty-seven QTL associated with leaf width at different positions below the tassel were detected. The individual effects of QTL explained 3.5% to 17.0% of the observed phenotypic variation, and ten QTL explained over 10%. The initial QTL were integrated into eight mQTL (meta-QTL) through a meta-analysis. Our results suggested that leaf widths at different positions may be affected by several of the same mQTL and may also be regulated by many different mQTL. These results provide useful information for breeding high density tolerant inbred lines and hybrid cultivars, as well as for using marker-assisted selection for important mQTL.

Hybrid Performance of an Immortalized F2 Rapeseed Population Is Driven by Additive, Dominance, and Epistatic Effects.

Genomics-based prediction of hybrid performance promises to boost selection gain. The main goal of our study was to investigate the relevance of additive, dominance, and epistatic effects for determining hybrid seed yield in a biparental rapeseed population. We re-analyzed 60,000 SNP array and seed yield data points from an immortalized F2 population comprised of 318 hybrids and 180 parental lines by performing genome-wide QTL mapping and predictions in combination with five-fold cross-validation. Moreover, an additional set of 37 hybrids were genotyped and phenotyped in an independent environment. The decomposition of the phenotypic variance components and the cross-validated results of the QTL mapping and genome-wide predictions revealed that the hybrid performance in rapeseed was driven by a mix of additive, dominance, and epistatic effects. Interestingly, the genome-wide prediction accuracy in the additional 37 hybrids remained high when modeling exclusively additive effects but was severely reduced when dominance or epistatic effects were also included. This loss in accuracy was most likely caused by more pronounced interactions of environments with dominance and epistatic effects than with additive effects. Consequently, the development of robust hybrid prediction models, including dominance and epistatic effects, required much deeper phenotyping in multi-environmental trials.

Genetic Components of Heterosis for Seedling Traits in an Elite Rice Hybrid Analyzed Using an Immortalized F2 Population

Utilization of heterosis has greatly contributed to rice productivity in China and many Asian countries. Superior hybrids usually show heterosis at two stages: canopy development at vegetative stage and panicle development at reproductive stage resulting in heterosis in yield. Although the genetic basis of heterosis in rice has been extensively investigated, all the previous studies focused on yield traits at maturity stage. In this study, we analyzed the genetic basis of heterosis at seedling stage making use of an “immortalized F2” population composed of 105 hybrids produced by intercrossing recombinant inbred lines (RILs) from a cross between Zhenshan 97 and Minghui 63, the parents of Shanyou 63, which is an elite hybrid widely grown in China. Eight seedling traits, seedling height, tiller number, leaf number, root number, maximum root length, root dry weight, shoot dry weight and total dry weight, were investigated using hydroponic culture. We analyzed single-locus and digenic genetic effects at the whole genome level using an ultrahigh-density SNP bin map obtained by population re-sequencing. The analysis revealed large numbers of heterotic effects for seedling traits including dominance, overdominance and digenic dominance (epistasis) in both positive and negative directions. Overdominance effects were prevalent for all the traits, and digenic dominance effects also accounted for a large portion of the genetic effects. The results suggested that cumulative small advantages of the single-locus effects and two-locus interactions, most of which could not be detected statistically, could explain the genetic basis of seedling heterosis of the F1 hybrid.

Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

Comparative QTL analysis of maize seed artificial aging between an immortalized F2 population and its corresponding RILs

Seed aging decreases the quality and vigor of crop seeds, thereby causing substantial agricultural and economic losses in crops. To identify genetic differences in seed aging between homozygotes and heterozygotes in maize, the seeds of a set of recombinant inbred lines (RILs) and an immortalized F2 (IF2) population were subjected to artificial aging treatments for 0, 2, 3, and 4days under 45ºC and 85% relative humidity and seed vigor was then evaluated in a field experiment. Seed vigor of all entries tested decreased sharply with longer aging treatment and seed vigor decreased more slowly in heterozygotes than in homozygotes. Forty-nine QTL were detected for four measured seed vigor traits in the RIL (28 QTL) and IF2 (21 QTL) populations. Only one QTL, qGP5, was detected in both populations, indicating that the genes involved in anti-aging mechanisms differed between inbred lines and hybrids. Several QTL were identified to be responsible for multiple seed vigor traits simultaneously in the RIL and IF2 populations under artificial aging conditions. These QTL may include major genes for seed vigor or seed aging. QTL qVI4b and qGE3a detected in the RIL population coincided with genes ZmLOX1 and ZmPLD1 in the same respective chromosomal regions. These QTL would be useful for screening for anti-aging genes in maize breeding.

Mapping of Imprinted Quantitative Trait Loci Using Immortalized F2 Populations

Mapping of imprinted quantitative trait loci (iQTLs) is helpful for understanding the effects of genomic imprinting on complex traits in animals and plants. At present, the experimental designs and corresponding statistical methods having been proposed for iQTL mapping are all based on temporary populations including F2 and BC1, which can be used only once and suffer some other shortcomings respectively. In this paper, we propose a framework for iQTL mapping, including methods of interval mapping (IM) and composite interval mapping (CIM) based on conventional low-density genetic maps and point mapping (PM) and composite point mapping (CPM) based on ultrahigh-density genetic maps, using an immortalized F2 (imF2) population generated by random crosses between recombinant inbred lines or doubled haploid lines. We demonstrate by simulations that imF2 populations are very desirable and the proposed statistical methods (especially CIM and CPM) are very powerful for iQTL mapping, with which the imprinting effects as well as the additive and dominance effects of iQTLs can be unbiasedly estimated.

Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits

The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F2 (IF2) to the two parents, from random-cross of IF2 or from selfing of IF2 population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF2 population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.

Whole-genome quantitative trait locus mapping reveals major role of epistasis on yield of rice.

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F2 population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.

Genetic analysis of plant height using two immortalized populations of “CRI12 × J8891” in Gossypium hirsutum L.

Plant height is an important plant architecture trait that determines the canopy structure, photosynthetic capacity and lodging resistance of upland cotton populations. To understand the genetic basis of plant height for marker-assisted breeding, quantitative trait loci (QTL) analysis was conducted based on the genetic map of recombinant inbred lines (RILs) derived from the cross “CRI12 × J8891” (Gossypium hirsutum L.). Three methods, including composite interval mapping, multiple interval mapping and multi-marker joint analysis, were used to detect QTL across multiple environments in the RILs and in the immortalized F2 population developed through intermating between RILs. A total of 19 QTL with genetic main effects and/or genetic × environment interaction effects were identified on 15 chromosomes or linkage groups, each explaining 5.8–14.3 % of the phenotypic variation. Five digenic epistatic QTL pairs, mainly involving additive × additive and/or dominance × dominance, were detected in different environments. Seven out of eight interacting loci were main-effect QTL, suggesting that these loci act as major genes as well as modifying genes in the expression of plant height. The results demonstrate that additive effects, dominance and epistasis are all important for the genetic constitution of plant height, with additive effects playing a more important role in reducing plant height. QTL showing stability across environments that were repeatedly detected by different methods can be used in marker-assisted breeding.

QTL-based analysis of heterosis for number of grains per spike in wheat using DH and immortalized F 2 populations

To map quantitative trait loci (QTL) and heterotic loci (HL) related to grain number per spike (GNS), 168 double haploid (DH) populations derived from Huapei 3 × Yumai 57 and an immortalized F2 population (IF2) generated by randomly permutated intermating of these DH populations were investigated. Using inclusive composite interval mapping (ICIM), a total of nine and eight significant QTLs for GNS were detected in three different environments in DH and IF2 populations, respectively. QTLs on chromosomes 1A, 2B, 3B, and 6A were observed between two populations. Five QTLs were detected on chromosome 1A. Of these QTLs, QGns1A-1 was a major QTL explaining 31.25 % of phenotypic variation. QGns2B-2 detected on chromosome 2B had the most significant additive effects, explaining 46.75 % of phenotypic variation with the favorable allele contributed by Yumai 57 corresponding to an increase of 5.69 kernels. Mid-parent heterosis of each cross in the IF2 population was used to map heterotic quantitative trait loci. A total of 17 HLs were detected. QTLs and HLs on chromosomes 2B and 6A were observed in the IF2 population. Three HLs, QHgns1B-2, QHgns2B, and QHgns6A-1, were detected in two environments and expressed stably. These results showed that some intervals on chromosomes 1B, 2B, and 6A play an important role in GNS heterosis in wheat, improving understanding of this phenomenon.

QTL mapping and epistasis analysis of brace root traits in maize

Root architecture is a major factor influencing root lodging, which limits greater yield stability at high planting density. Total brace root tier number (TBRTN) and effective brace root tier number (EBRTN) are the two most important root architecture traits influencing root lodging. However, the genetic mechanisms that underlie these traits remain poorly understood. In this study, quantitative trait loci (QTL) for TBRTN and EBRTN were mapped using a set of 201 recombinant inbred lines (RILs) and 278 immortalized F2 (IF2) populations derived from these RILs, which were evaluated in three environments. Ten QTL in the RILs and 15 QTL in the IF2 population were detected. In the two populations, we identified two coincident major QTL for TBRTN and a single identical major QTL for EBRTN. The QTL for TBRTN showed the largest additive effect, accounting for 16.36 and 17.88% of the phenotypic variance in the RILs and IF2 population, respectively. Additional epistatic effects were identified for all the maize chromosomes, except for chromosome 4. Most epistatic effects involved pairs of loci that were on different chromosomes. At the same time, we found loci that interacted simultaneously with several other loci to affect expression of the traits, which was particularly evident in the IF2 population. For example, qTAR1-2 interacted simultaneously with qTAR2-1, qTAR3-1, qTAR5-1, and qITAR8-2 to affect the expression of TBRTN. Therefore, a complex network controlling the traits was found in maize. These results provide useful information for understanding the molecular mechanisms controlling root architecture.

Quantitative trait loci mapping for two seed yield component traits in an oilseed rape (Brassica napus) cross

With 1 figure and 6 tablesAbstractSeed yield per plant is one of the most important traits of rapeseed, and it is determined by three yield component traits viz. siliques per plant, seeds per silique (SS) and seed weight (SW). In this study, quantitative trait loci (QTL) mapping for SS and SW was conducted in doubled haploid and immortalized F2 populations of the cross ‘Quantum’ × ‘No.2127 17’. The correlation analysis showed that SS had a significant negative correlation with SW. Using data from three natural field trials, 4 and 11 QTL for SS and SW were detected, respectively. Three QTL for SS were colocalized to QTL involved in SW. For both traits, the favourable alleles existed in both parents. The results could contribute to rapeseed yield improvement and provide useful information for marker‐assisted selection.

Mapping of QTL for tiller number at different stages of growth in wheat using double haploid and immortalized F2 populations

Effective tiller number is one of the most important traits for wheat (Triticum aestivum L.) yield, but the inheritance of tillering is poorly understood. A set of 168 doubled haploid (DH) lines derivatives of a cross between two winter wheat cultivars (Huapei 3 and Yumai 57), and an immortalized F(2) (IF(2)) population generated by randomly permutated intermating of these DHs were investigated, and QTLs of tillering related to the maximum tillering of pre-winter (MTW), maximum tillering in spring (MTS), and effective tillering in harvest (ETH) were mapped. Phenotypic data were collected for the two populations from two different environments. Using inclusive composite interval mapping (ICIM), a total of 9 and 18 significant QTL were detected across environments for tillering in the DH and IF(2) populations, respectively. Four QTLs were common between two populations. A major QTL located on the 5D chromosome with the allele originating from Yumai 57 was detected and increased 1.92 and 3.55 tillers in MTW and MTS, respectively. QTLs (QMts6D, QEth6D) having a neighbouring marker interval at Xswes679.1 and Xcfa2129 on chromosome 6D was detected in MTS and ETH. These results provide a better understanding of the genetic factors for selectively expressing the control of tiller number in different growth stages and facilitate marker-assisted selection strategy in breeding.

Dissection of the genetic basis of heterosis in an elite maize hybrid by QTL mapping in an immortalized F2 population

The genetic basis of heterosis for grain yield and its components was investigated at the single- and two-locus levels using molecular markers with an immortalized F(2) (IF(2)) population, which was developed by pair crosses among recombinant inbred lines (RILs) derived from the elite maize hybrid Yuyu22. Mid-parent heterosis of each cross in the IF(2) population was used to map heterotic quantitative trait loci. A total of 13 heterotic loci (HL) were detected. These included three HL for grain yield, seven for ear length, one for ear row number and two for 100-kernel weight. A total of 143 digenic interactions contributing to mid-parent heterosis were detected at the two-locus level involving all three types of interactions (additive x additive = AA, additive x dominance = AD or DA, dominance x dominance = DD). There were 25 digenic interactions for grain yield, 36 for ear length, 31 for ear row number and 51 for 100-kernel weight. Altogether, dominance effects of HL at the single-locus level as well as AA interactions played an important role in the genetic basis of heterosis for grain yield and its components in Yuyu22.