The aim of this study was to identify quantitative trait loci (QTLs) influencing teat number traits in an F2 intercross between Landrace and Korean native pigs (KNP). Three teat number traits (left, right, and total) were measured in 1105 F2 progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We detect that seven chromosomes harbored QTLs for teat number traits: genome regions on SSC1, 3, 7, 8, 10, 11, and 13. Six of fourteen identified QTL reached genome-wide significance. In SSC7, we identified a major QTL affecting total teat number that accounted for 5.6% of the phenotypic variance, which was the highest test statistic (F-ratio = 61.1 under the additive model, nominal P = 1.3×10-14) observed in this study. In this region, QTL for left and right teat number were also detected with genome-wide significance. With exception of the QTL in SSC10, the allele from KNP in all 6 identified QTLs was associated with decreased phenotypic values. In conclusion, our study identified both previously reported and novel QTL affecting teat number traits. These results can play an important role in determining the genetic structure underlying the variation of teat number in pigs.
Rice production is largely affected by various environmental conditions such as cold, heat and flooding. Here, to identify cold tolerant QTLs at seedling stage in rice, we generated RIL population derived from a cross between Hanareum 2 and Unkwang which are a highly cold sensitive and cold tolerant, respectively. We observed cold phenotype of this population in the growth chamber conditions and natural field conditions. For observation of cold tolerant phenotype of RIL population in the growth chamber, we treated cold stress (5~13℃) for 14 days and recovery for 4 days. When we examined the phenotype of RIL in the field conditions, temperature range in the field conditions was about 6 to 25℃ in 2015~2016. We named QTLs as Seedling Cold Tolerant (SCT) in growth chamber and Cold induced Yellowing Tolerant (CYT) in the field, respectively. Three QTLs for SCT and 5 QTLs for CYT were detected on chromosome 1, 6, 7, 8, 10, 11 and 12. Among these QTLs, qSCT12 on chromosome 12 showed 26.3 LOD score with 25.5% of phenotypic variation. When qSCT11.1 and qSCT12 were combined, cold tolerant was most strongest in our experimental conditions. qCYT10 on chromosome 10 was identified in field experiment on both 2015 and 2016. These results may provide useful information for a marker-assisted breeding program to improve cold tolerance in rice.
Rice is the staple food of at least half of the world's population. Due to global warming, the weather is difficult to forecast nowadays. Therefore, it is necessary to breed various breeding to respond to such changes in the environment. This study was conducted to analyze the QTL about plant form, culm length, ear number and ear length by using 120 lines by anther culture, a cross between the Indica variety Cheongcheong and Japonica variety Nagdong. DNA marker was selected on the QTLs gene, and the following results were obtained. CNDH (Cheongcheong Nagdong Doubled Haploid) lines frequency distribution table curves about culm length, ear number and ear length exhibited showed a continuous variation close to a normal distribution. QTL analysis result, on culm length qPlL1-1 and qPlL1-2 were detected on the chromosome 1 and qPlL5 was detected on the chromosome 5. However, on ear length qPL2, qPL3 and qPL10, were detected on the chromosome 2, 3 and 10, while on ear number qPN1-1 and qPN1-2 were detected on the chromosome 1, qPN9 was detected on the chromosome 9. The QTLs related to culm length was found to chromosomes 5 and LOD scores were 3.81. The QTLs related to ear length was found to chromosomes 2 and 3 LOD scores were 7.13 and 3.20. The QTLs related to ear number was found to chromosome 9 and LOD scores were 4.27. Twenty two (22) Japonica cultivars and 12 Indica cultivars were analyzed polymorphisms, using selected 9 markers from the result about plant form analysis. RM5311, RM555 and RM8111 about the culm length, the ear length and number of ear were selected on the standard of Cheongcheong and Nagdong. Each rate of concordances about the culm length, the ear length and number of ear are 44.11%, 41.17% and 44.11%.
The rice recombinant inbred lines derived from Milyang23 and Gihobyeo cross were used in genetic mapping and QTL analysis studies. In this study, we developed a new 101 CAPS markers based on the SNPs in the whole genome region between these varieties. As a result, the total genetic distance and average distances were 1,696.97 cM and 3.64 cM, respectively. In comparison to the distance of the previous genetic map constructed based on 365 DNA markers, the new genetic map was found to have a decreased distance. The map was applied for the detection of QTLs on all seven traits relevant to diameter of stem internode, length of culms, length of panicles and the number of panicles including the correlation analysis between each trait. The QTLs results were similar to the report in previous studies, whereas the distance between the markers was narrowed and accuracy increased with the addition of 101 CAPS markers. A total of 9 new QTLs were detected for stem internode traits. Among them, qI1D-6 had higher LOD of 5.1 and phenotype variation of 50.92%. In this experiment, a molecular map was constructed with CAPS markers using next generation sequencing showing high accuracy for markers and QTLs. In the future, developing more accurate QTL information on stem internode diameters with various agriculturally important traits will be possible for further rice breeding.
Recently, many breeders have preferred to use molecular markers for introgression backcross programs enabling foreground and background selection to cope with rapid cultivar changing of seed markets. In accumulation of target traits with marker-assisted selection, larger numbers of markers should give better resolution. For the analysis of quantitative traits, a high-density genetic map with a large number of markers is required for discovering more accurately linked markers with traits. Watermelon is a recalcitrant plant to generate a high-density genetic map with conventional molecular markers including simple sequence repeats (SSRs), since watermelon has narrow genetic diversity background and severe segregation distortions of those SSR markers. Thus, we have developed efficient and valid way to assemble genetic map and markers by next-generation sequencing coupled with genotyping by sequencing in F2 generation. After crosses between Citurullus lanatus ssp. citroides (PI254744 and PI189225) and C. lanatus ssp. lanatus (TS34, Korean cultigen), 163 of F2 progeny were sequenced through Illumina's Hi-Seq GAII platform. From sequence information of those variant call files, the SNPs were indexed and filtered by sequencing depth with genotype converter (SNP Genotyper), and optimized by heuristic physical bin mapping to construct more reliable genetic linkage map. Reliable SNP loci were determined and compared to sequences of physical reference map. Using the genetic map, we determined QTLs in F2:3 population and found major loci corresponding to seed size and powdery mildew race1 resistance in watermelon.
Understanding how crops interact with their environments is increasingly important in breeding program, especially in light of highly anticipated climate changes. A total of 150 recombinant inbred lines (RILs) of F12 generation derived from Dasanbyeo (Indica) x TR22183 (Japonica) were evaluated at Suwon 2010, Shanghai 2010, IRRI 2010 wet season, Suwon 2011, Shanghai 2011, IRRI 2011 dry season, and IRRI 2011 wet season as a total of seven diverse environments. Traits evaluation included eight important agronomical traits such as days to heading (DTH), culm length (CL), panicle length (PL), panicle number per plant (PN), spikelet number per panicle (SN), spikelet fertility (SF), 100-grain weight (GW), and grain yield (GY). As a result of genotyping using 384-plex GoldenGate oligo pool assay (OPA) set (RiceOPA3.1), the linkage map for 235 SNP markers covering a total of 926.53 cM with an average interval of 4.01 cM was constructed and a total of 44 main-effect quantitative trait loci (QTL)s and 35 QTLs by environment interaction (QEI) were detected for all eight traits using single environment and multi-environments analysis, respectively. Of these, fourteen putative QTLs for DTH, CL, PN, SN, GW and GY found in single environment analysis had the similar position to QEI for those traits, suggesting that these same QTLs from both single-and multi-environments are major and stable for certain traits. To the best of our knowledge, 12 QTLs consisted of four QTLs for CL (qCL2, qCL8.1, qCL8.2, and qCL8.3), six QTLs for GW (qGW3.1, qGW3.2, qGW7, qGW8, qGW10.1, and qGW10.2), one QTL for GY (qGY3) and one for SF (qSF4) out of 44 QTLs obtained from single environment analysis were considered to be novel since no overlapping QTL was reported from previous studies. In addition, 12 out of 35 QTLs obtained from multi-environments analysis were also novel.
The maize genome is complex with exceeding the levels of intra-specific variation, repetitive DNA content, and allelic content observed between many species. Because of tremendous diversity and variants, maize is considered as a forefront crop development and estimation of molecular markers for agricultural trait in genetics and breeding. Using quantitative trait loci (QTL) and marker assisted breeding (MAS), molecular breeders are able to development of drought tolerance and grain yield in maize genotype. To study QTL congruency, a meta QTL analysis including results from eight-teen QTL publications for grain yield and drought tolerance were considered. Among them, we assembled 420 QTLs for abscisic acid (ABA) concentration, anthesis silking interval (ASI), days to flower, days to silk, ear number, kernel number, grain number and grain yields, involved in drought tolerance and grain yield. The meta QTL analysis revealed significant evidence for linkage of these traits to 39 different segments as candidates regions on maize genome. A total of 571 marker was selected as QTL or integrated QTL markers for narrowing down the QTL region into specific functionally relevant candidates. The results of meta QTL analysis helped to refine the genomic regions of agricultural traits, interest described and provided the closest flanking markers.
To develop molecular markers for late flowering time in radish we performed QTL-seq analysis in which whole genomes are sequenced and SNPs between two groups showing opposite phenotypes in F2 population are analyzed to find regions or QTLs involved in a trait of interest. Two inbred lines (NH-JS1 and NH-JS2) showing opposite phenotypes of flowering time were selected to generate F2 population for the analysis. NH-JS1 showed late flowering time whereas NH-JS2 early flowering time. Genomic DNA from the two lines were extracted and sequenced. In addition F2 population from F1 between NH-JS1 and NH-JS2 was generated and flowering time phenotypes of 180 F2 plants were analyzed. We selected 11 plants with late flowering time and 12 plants showing early flowering time. We extracted DNA from each individuals from the two groups and bulked them to generate two bulked DNA samples that are subject to whole genome resequencing. Preliminary analysis of SNP data from the resequencing showed that there may be several QTLs involved in flowering time control in radish.
Phytophthora capsici an Oomycete pathogen is a major challenge to the pepper (Capsicum spp.) production around the world. Control measures are proved ineffective, so breeding resistant cultivars are the most promising strategy against the pathogen. Resistance against P. capsici is governed by quantitative trait loci (QTL). According to previous studies on QTL detection, the QTL on pepper chromosome 5 is a major contributor to resistance. In this study, to exploit the involvement of this QTL and identify its contributing genes, the F2 population derived from a cross between ECW30R and CM334 was inoculated with a medium virulence P. capsici strain JHAI1-7 zoospores at the 6-8 leaf stage. Composite interval mapping revealed two major QTLs; QTL5-1 from 7 days post inoculation (dpi) and QTL5-2 from 16 dpi on chromosome 5. To characterize and detect interactions of the two QTLs, near isogenic lines (NIL) were constructed by crossing Tean and recombinant inbred line (RIL) derived from a cross between YCM334 and Tean. RILs were screened with P. capsici strain MY-1 and resistant lines were selected. Among the resistance RILs most closely related to Tean were selected using AFLP and SSR genotyping data. These RILs were named as YT39-2 and YT143-2. To develop more advanced NILs, two rounds of marker-assisted backcrossing were done using a high-throughput SNP genotyping system (EPI Fluidigm, USA). Among the NILs derived from YT39-2, YT39-2-64 contains only QTL5-1 whereas YT39-2-61 and YT39-2-69 were identified to have both QTLs. On the other hand, YT143-2-55-7 with the highest Tean genetic background contains QTL5-1 only. In the next step, the 3 different NILs having QTL5-1, QTL5-2 individually and both QTLs will be identified. Furthermore, phenotyping and fine mapping will be done for the analysis of individual and interaction effects of QTLs.
Drought stress is one of the major stresses affecting growth and productivity in rice. Drought tolerance is a complex trait governed by quantitative trait loci(QTLs) making it difficult to understand mechanisms underlying it. We generated a set of 55 introgression lines via backcrosses using Milyang23, the Korean Tongil-type rice variety as the recurrent parent and Oryza glaberrima (IRGC Acc. No. 103544) as a donor parent. 139 SSR markers were used to genotype 55 introgression lines. The 55 introgression lines with Milyang23 were evaluated for physiological traits such as fresh shoot weight (FSW), fresh root weight (FRW) and dry shoot weight (DSW) under the control and 30% PEG-treated condition. Three lines (IL9, IL12, and IL55) showing significant difference with Milyang23 were selected for further analysis. Genotyping revealed that three lines had four, four and two O. glaberrima homozygous segments, respectively. IL9 performed better than Milyang23 in all traits measured in the 30% PEG-treated condition. IL9 possessed four O. glaberrima introgressions on chromosomes 1, 2, 6 and 7. IL12 performed better than Milyang23 in FSW and FRW and contains four O. glaberrima introgressions on chromosomes 3 and 6. IL55 contains two O. glaberrima introgressions on chromosomes 2 and 6. Three lines shared the O. glaberrima segment delimited by markers RM133-RM225 at chromosomes 6. This region corresponds to the QTL region for drought tolerance reported by other previous studies. Although IL9 and IL12 showed improved drought tolerance at the seedling and vegetative stage, they performed poor under the drought stress at the reproductive stage implying that the level of drought tolerance differs according to the growth stage in rice. IL55 was not significantly different from Milyang 23 in SPP and FER and had significantly higher no. of the total grain than Milyang 23. This result seems to indicate that IL55 will be a good resource for drought tolerance breeding. The population would be useful not only in developing drought tolerant lines in the breeding program but also in fine-mapping the genes/QTLs for drought tolerance.
Clubroot is a devastating disease caused by Plasmodiophora brassicae and results in severe losses of yield and quality in Brassica crops including Brassica oleracea. Therefore, it is important to identify resistance gene for CR disease and apply it to breeding of Brassica crops. In this study, we applied genotyping-by-sequencing (GBS) technique to construct high resolution genetic map and mapping of clubroot resistance (CR) genes. A total of 18,187 GBS markers were identified between two parent lines resistant and susceptible to the disease, of which 4,103 markers were genotyped in all 78 F2 plants generated from crossing of both parent lines. The markers were clustered into nine linkage groups spanning 879.9 cM, generating high resolution genetic map enough to refine reported reference genome of cabbage. In addition, through QTL analysis using 78 F2:3 progenies and mapping based on the genetic map, two and single major QTLs were identified for resistance of race 2 and race 9 of P. brassicae, respectively. These QTLs did not show collinearity with CR loci found in Chinese cabbage (Brassica rapa) but roughly overlapped with CR loci identified in cabbage for resistance to race 4. Taken together, genetic map and QTLs obtained in this study will provide valuable information to improve reference genome and clubroot resistance in cabbage.
This study was conducted to identify quantitative trait loci (QTL) related to grain qualities under high temperature during ripening stage using 187 Korean rice varieties. To analyze grain qualities under high temperature during ripening stage, grain appearance such as head rice and chalky grains percentage and physicochemical characteristics were investigated and SNP genotyping of 187 Korean varieties was conducted for association analysis related with grain qualities under high temperature. Five traits exhibited continuous distributions in the non-glutinous Korean varieties, indicating that these traits are controlled by multiple genes. Association mapping among non-glutinous Korean varieties was conducted using 223 markers showed polymorphism among 384 SNP markers. Six QTLs for chalk grains percentage were mapped to chromosomes 1, 4, 10 and 11. These six QTLs were linked to the SNP marker id1014176 on chromosome 1, id4010924 on chromosome 4, id10000644 on chromosome 10 and id11011505 on chromosome 11, and explained approximately 21, 61, 50, 23, 23 and 21% of the total phenotypic variance. Four QTLs for head rice percentage in chromosomes 4, 10 explained the total phenotypic variance by over 47% and around 20%. Fifteen QTLs for RVA characteristics including hot paste viscosity, peak viscosity and setback viscosity were mapped to chromosome 1, 6, 7, 12 and QTLs were explained around 20% of the total phenotypic variance.
The whitebacked planthopper(WBPH), Sogatella furcifera is a serious pest of rice. The nymphs and adults suck phloem sap which causes reduced plant vigor, stunting, yellowing of leaves, delayed tillering in rice. This study was conducted to identify the optimum screening time for improved WBPH-associated QTL analysis and to develop the markers for use in breeding WBPH resistance. Resistance after 7 days infestation was observed in 100 lines(83.3%), after infestation for 14 days, resistance was observed in 14 lines(11.7%), and after infestation for 21 days, resistance was observed in 10 lines(8.3%). However, no after 14 days infestation was as similar as normal distribution in WBPH resistance. QTLs associated of the resistance detected in four regions on qWBPH1 and qWBPH8 in the intervals marker. After 7 days of infestation, the qWBPH1 was located in the interval RM3482-RM11966 and RM3709-RM11694 with LOD 4.0 and RM3709-RM11694 with LOD 3.5. After 14 days of infestation, The qWBPH1 was located in the interval RM3709-RM11694 with LOD 3.3. and RM3709-RM11694 with LOD 3.3. After 21 days of infestation, The qWBPH8 was located in the interval RM17699 with LOD 3.3. The QTLs on chromosome 1 was the most effective RM11694-RM11669 (LOD 3.3, variance 30%). The resistance lines were collected 10 plants of phenotye variation with genotype. The ratios of coincidence were used to determine resistance in 10 plants with phenotypic variation and a genotype of 8 markers. 3 markers were used: RM3482 on chr.1 represented 100%, RM8235 and RM11694 represented 80%, 90%, respectively, RM17699 on chr.8 represented 80% of the coincident ratio. These selected markers will be useful to rice breeding programs interested in new sources of WBPH resistance
The White backed planthopper (WBPH), Sogatella furcifera (Horvath) is one of the serious insect pests in rice growing region in Asia. When rice is attacked by the insect it releases secondary metabolites for self-defense. In this study, we identified WBPH-mediated compounds from a cross ‘Cheongcheongbyeo/Nagdongbyeo’ doubled haploid (CNDH). The compounds were located in chromosome. Leaves and stem of CNDH lines were infected by 2∼3 insta of 3 weeks WBPH and samples were extracted by 90% methanol. Extracted compounds were analyzed through HPLC. TLC was used in separating the target compounds. QTL analysis of compound was done using winQTLcart 2.5 program. Chrysoeriol was highly contained in Cheongcheongbyeo. QTL location is found on chromosome by winQTLcart 2.5. QTL analcited with compound7 was detected on chromosome 4, 7 and 12. qFla4 was detected on chromosome 4 in RM280-RM6909 at LOD 3.5 with 30% of variation. qFla7 was detected on chromosome 7 in RM248-RM1134 with LOD 3.0 with 30% of variation. qFla12 was detected on chromosome 12 in RM1226-RM12 with LOD 2.7 with 40% of variation. Cochlioquinone was detected on chromosome8, qFla8 in RM23230-RM3689 with LOD 2.5 with 30% of variation. Chrysoeriol and Cochlioquinone separated to condition of (Chloroform: Methanol:1-Butanol:Water=4:5:6:4). Separated compounds were analyzed by LC/MS and NMR. These results, investigation is being done to ditermine how the secondary metabolites come lead to pathways of genes and its effect on WBPH relation.
Bakanae disease is one of the most serious and oldest problems of rice production, which was first described in 1828 in Japan (Ito and Kimura 1931). This disease may infect rice plants from the pre-emergence stage to the mature stage, with severe infection of rice seeds resulting poor germination or withering (Iqbal et al. 2011). Under favorable environmental conditions, infected plants have the capacity to produce numerous conidia that subsequently infect proximate healthy plants, resulting in major yield loss (Ou 1985). One hundred sixty nine NILs, YR28297 (BC6F4) generated by five backcrosses of Shingwang with the genetic background of susceptible japonica variety, Ilpum were used for QTL analysis. Rice bakanae disease pathogen, CF283, was mainly used in this study and inoculation and evaluation of bakanae disease was performed with the method of the large-scale screening method developed by Kim et al. (2014). A major QTL for resistance against bakanae disease on chromosome 1 was identified using SSR marker, RM9, which explaining 65 % of the total phenotype variation. The major QTL designated as qBK1 and mapped to a 4.4 Mbp region between RM24 (19.30 Mb) and RM11295 (23.72 Mb). The results of this study are expected to provide useful information toward developing resistant rice lines to this detrimental fungal disease.
최근 급속하게 발달한 차세대 유전체분석기술을 기반으로 밀양23호와 기호벼의 유전체 서열을 분석하고, 새로운 CAPS 마커를 개발하였다. NGS를 통해 Nipponbare 유전체 길이의 60 배수만큼 염기서열을 결정하였고, CDS 안에서 두 품종간 특이적으로 나타나는 SNP를 CAPS 마커로 이용하였다. 새롭게 개발된 146개 CAPS 마커와 기존의 보고된 219개 마커를 통합하여 총 365개의 마커로 밀양23호/기호벼의 재조합자식 유전집단에 대해 분자 유전지도를 작성하였다. 벼의 줄기굵기와 간장 그리고 수장에 관한 QTL을 탐색한 결과, 총 19개의 유의성이 있는 QTL을 찾을 수 있었다. 이 중에 4개 줄기굵기 형질 관련 QTL과 2개 간장 형질 관련 QTL이 기존에 보고되지 않은 새로운 QTL이었다. 그 줄기굵기 QTL 중 가장 큰 LOD값을 갖는 qI1D5는 5번 염색체에서 탐색되었으며, 1절굵기 표현형 변이는 8.99%였다. 또한, 간장관련 QTL 중 가장 큰 LOD 값을 갖는 qCL5은 5번 염색체에서 탐색되었고, 이 QTL의 간장 표현형 변이는 4.24%였다. 재염기서열을 통해 밝혀진 SNP 중 소수만이 본 연구에 사용되었다. 향후 본 연구에서 밝혀진 SNP 정보를 이용한다면 더 많은 마커를 개발하여, 고밀도 유전지도 작성이 가능할 것이다. 더 나아가 MGRIL을 이용하여 농업적으로 유용한 형질에 대해 더 정확한 QTL 분석과 유용유전자의 개발이 가능하게 될 것이다.
Heterosis describes the increased performance of F1 hybrid plants in terms of increased biomass, yield, vegetative growth rate, and tolerance against biotic and abiotic stresses as compared with their inbred parents. Two sets of rice materials, 166 RILs derived from a cross between Milyang 23 (Korean indica-type rice) and Tong 88-7 (japonica Rice), and BC1F1 hybrids derived from crosses between the RILs and the female parent, Milyang 23, were produced to identify QTLs for heterosis of yield and yield-related traits. The QTLs were detected from three different phenotype data sets including the RILs, BC1F1 hybrids, and mid-parental heterosis data set. A total of 57 QTLs were identified for nine traits. Of eight QTLs detected for yield heterosis, five overlapped with other heterosis QTLs for yield-related traits such as spikelet number per panicle, days to heading, and spikelet fertility. Four QTLs for yield heterosis, gy1.1, py6, gy10, and py11, were newly identified in this study. We identified a total of 17 EpQTLs for yield heterosis that explain 21.4 ~ 59.0 % of total phenotypic variation, indicating that epistatic interactions may play an important role in heterosis.
The HWC-line of rice showed wide compatibility with both indica and japonica cultivars, tall culm length, long and slender grain shape. For QTL analysis, two F2 populations were derived from the crosses between the HWC-line and each of two Korean variety, Dasanbyeo (Korean Tongil-type cultivar) and Hwacheongbyeo (temperate japonica cultivar), respectively. A total of 190 F2 plants were evaluated in each of two F2 populations. Eight agronomic characters were measured for QTL analysis in F2 populations and parents.
Two molecular linkage maps were constructed. In the F2 population from cross between HWC-line / Dasanbyeo (HD) cross, 93 STS markers and 13 SSR markers were mapped on 12 chromosomes, covering a total length of 1942.6 cM, with an average distance of 18.33cM between adjacent markers. In the F2 population from HWC-line / Hwacheongbyeo (HH) cross, 28 STS markers, 29 SSR markers and 1 FNP marker were mapped on 11 chromosomes, spanning a total length of 925.53cM, with an average distance of 15.96cM between adjacent markers. In the F2 population from HD cross, 16 M-QTLs and 1 E-QTL were detected for culm length, spikelets per panicle, spikelet fertility, grain length, grain width, grain shape and 100 grains weight. 7 QTLs of spikelet fertility, grain length, grain width and grain shape were newly identified in this study. In the F2 population from HH cross, 15 M-QTLs were detected for culm length, panicle length, spikelet fertility, grain length, grain width, grain shape and 100 grains weight. 6 QTLs of culm length, grain length, grain width and grain shape were newly identified in this study. The QTLs identified in this study would provide basic information on putative functional genes related agronomic characters and facilitate breed new rice cultivar.
In order to clarify the chromosomal location of quantitative trait loci (QTL) associated with the yield and agronomic traits in waxy corn and sweet corn (Zea maysL.), we were conducted identifying of QTLs associated with yield and agronomic traits by employing genetic linkage map of F2:3 population. A total of 14 QTLs each for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-Ear) and kernel setting length (L-Sear) were detected in the 158 F2 families. The number of QTL per each trait was ranged from 1 to 6, and also phenotypic variance was ranged from 3.55 to 16.86%. For DTS, one QTLs was found to be controlled by genomic regions at locations chromosomes 1 contributing 9.21% of phenotypic variance. While three QTLs for PH, were found to be controlled by 3 genomic regions at locations chromosomes 1 and 2 contributing 6.68, 6.85 and 8.17% of phenotypic variance, respectively. For EH, six QTLs were found to be controlled by 6 genomic regions at locations chromosomes 1, 7, 8 and 10 range from 3.55 to 11.44% of phenotypic variance. The one QTLs for ER was found at locations chromosomes 1 contributing 7.25% of phenotypic variance. For L-Ear, two QTLs were found to be controlled by 2 genomic regions at location chromosome 7 and 10 contributing 7.40 and 11.63% of phenotypic variance, respetively. The one QTLs for L-Sear was found at locations chromosomes 3 contributing 16.86% of phenotypic variance. Among them, three QTLs, such as qEH8 (11.44%), qLEar10 (11.63%), and qLSear3 (16.86%) may be considered as a major QTLs, while the remaining 11 QTLs might be regarded as minor QTLs. This study may provide valuable information for the further identification and characterization of genes responsible for agronomic traits in waxy corn and sweet corn.