Mapping quantitative trait loci for tolerance to phosphorus-deficiency at the seedling stage in barley

Phosphorus (P) deficiency in soil is a major factor that limits barley yield production. Increasing the tolerance to P-deficiency of barley is one of the most cost-effective solutions. Quantitative trait loci (QTLs) controlling P acquisition, P utilization efficiency and biomass at the seedling stage were identified using a population of recombinant inbred lines (RILs) subjected to two P concentrations (low P (LP), 25 µM and normal P (NP), 250 µM). The population was derived from a cross between Baudin and CN4027, which is a Hordeum spontaneum accession. In two hydroponic trials conducted in 2014 and 2016, seventeen QTLs were detected on chromosomes 2H, 3H, 4H and 5H at the two P concentrations. Eight of these QTLs influenced P acquisition efficiency (PAE). Phenotypic variation explained by a particular PAE-related QTL ranged from 13.3 to 39.9%. One QTL designated as Qspue.sau-3H.01 was related to P utilization efficiency (PUE); the phenotypic variation explained by this QTL was 12.5% (NP concentration) and 13.1% (LP concentration), respectively. Strong associations were observed between biomass and P efficiency-related traits in our study. Two QTL clusters controlling biomass, PAE- and PUE-related traits simultaneously were stably identified in the intervals bPb3263664–bPb3931069 and bPb3264570–bPb4786261 on chromosome 3H at both P concentrations in both trials. The QTLs related to PAE, PUE and biomass are important for the P-tolerant phenotype and may offer valuable clues for fine mapping and map-based cloning of barley.     

QTLs for barley yield adaptation to Mediterranean environments in the ‘Nure’ × ‘Tremois’ biparental population

Multi-environment trials represent a highly valuable tool for the identification of the genetic bases of crop yield potential and stress adaptation. A Diversity Array Technology^®-based barley map has been developed in the ‘Nure’ × ‘Tremois’ biparental Doubled Haploid population, harbouring the genomic position of a gene set with a putative role in the regulation of flowering time and abiotic stress response in barley. The population has been evaluated in eighteen location-by-year combinations across the Mediterranean basin. QTL mapping identified several genomic regions responsible for barley adaptation to Mediterranean conditions in terms of phenology, grain yield and yield component traits. The most frequently detected yield QTL had the early flowering HvCEN_EPS2 locus (chromosome 2H) as peak marker, showing a positive effect from the early winter parent ‘Nure’ in eight field trials, and explaining up to 45.8 % of the observed variance for grain yield. The HvBM5A_VRN-H1 locus on chromosome 5H and the genomic region possibly corresponding to PPD-H2 on chromosome 1H were significantly associated to grain yield in five and three locations, respectively. Environment-specific QTLs for grain yield, and clusters of yield component QTLs not related to phenology and or developmental genes (e.g. on chromosome 4H, BIN_09) were observed as well. The results of this work provide a valuable source of knowledge and tools for both explaining the genetic bases of barley yield adaptation across the Mediterranean basin, and using QTL-associated markers for MAS pre-breeding and breeding programmes.     

Detection of exotic QTLs controlling nitrogen stress tolerance among wild barley introgression lines

Nitrogen (N) is one of the most important plant nutrients, controlling growth and, ultimately, yield of a cultivar. Hordeum vulgare ssp. spontaneum, the wild barley progenitor of cultivated barley, is known to possess genes that can improve tolerance against biotic and abiotic stresses. A quantitative trait locus (QTL) study with two levels of N fertilization was conducted under glasshouse in order to locate wild barley alleles that improve N stress tolerance in the genetic background of an elite barley cultivar. For this, a set of 28 barley introgression lines (S42ILs), which originate from the cross ??Scarlett???×???ISR42-8??, was studied. The S42ILs, containing single or multiple wild barley introgressions, and ??Scarlett?? were evaluated in regard to a total of 15 traits, related to morphological parameters, grain parameters as well as to carbon (C) and N content parameters. A mixed model analysis and a subsequent Dunnett test was conducted to identify S42ILs that significantly deviate from the recurrent parent ??Scarlett??, either tested separately for each N level, or simultaneously across both N levels. In total, 65 QTLs were detected for the S42IL set. Most QTLs were found for chlorophyll content during heading (10 QTLs) and the fewest for C/N ratio of straw (1 QTL). The individual S42ILs possessed different numbers of QTLs. For S42IL-108, a maximum of eight QTLs were found whereas S42IL-145 did not show any significant difference from ??Scarlett??. Wild barley alleles revealed decreasing effects at 32 QTLs and increasing effects at 33 QTLs. Although 25 QTLs exhibited similar effects across both N levels, 18 and 22 QTLs exhibited effects that were only detected under N0 or N1, respectively. We, thus, conclude that it may be worth to select improved barley cultivars for N stress tolerance separately under low N fertilization, rather than extrapolating trait performances from experiments carried out under standard N fertilization conditions. A number of wild barley QTL alleles improved N stress tolerance. For example, a wild barley QTL allele on chromosome 4H, present in the Hsp introgression of S42IL-119, was associated with a 13.0?% increase of thousand grain weight across both N levels and a 20?% increase under low N supply. QTLs detected in the present study were compared with those of previous field studies of the same cross and with other QTL studies in barley and other small grains. Accordance between QTL studies (QTLs showing similar effects at the same map location) is documented and discussed. Based on our study, promising wild barley QTL alleles are available in S42ILs, which can be readily utilized to select for improved N use efficiency in barley breeding.     

Mapping genes for deep-seeding tolerance in barley

Deep-seeding tolerance, the emergence of seedlings from deep seeded conditions, is involved in stand establishment in semi-arid regions, where the soil surface is too dry for seed germination. Genes determining deep-seeding tolerance in barley were mapped using two doubled haploid populations derived from the following crosses: Harrington × TR306 (H/T)and Step toe × Morex (S/M). Significant quantitative trait loci (QTLs) for deep-seeding tolerance were found in each population. Two QTL sex plained 40% of the phenotypic variation in the H/T population and one QTL (S/M) 8% of the total phenotypic variance. Multiple QTLs accounting for coleoptile length and first internode length were detected in both populations. In the H/T population, there were coincident QTLs for deep-seeding tolerance, coleoptile length and first internode length on the long arm of chromosome 5H. These QTLs correspond with previously reported QTLs for abscisic acid and gibberellic acid response. QTL coincidence may be due to the pleiotropic effects of alleles at a single locus. This information may be useful for breeding programs manipulating morphological and physiological traits in order to develop varieties for semi-arid regions. This revised version was published online in August 2006 with corrections to the Cover Date.     

Advanced-backcross QTL analysis in spring barley: IV. Localization of QTL × nitrogen interaction effects for yield-related traits

The advanced backcross quantitative trait locus (AB-QTL) analysis has proven its usefulness to identify and localize favourable alleles from exotic germplasm and to transfer those alleles into elite varieties. In a balanced design with up to six environments and two nitrogen fertilization (N treatment) levels, a 4-factorial mixed model analysis of variance (ANOVA) was used to identify QTL main effects, QTL × environment interaction effects and QTL × N treatment interaction effects in the spring barley BC₂DH population S42. The yield-related traits studied were number of ears per m², days until heading, plant height, thousand grain weight (TGW) and grain yield. In total, 82 QTLs were detected for all traits. This finding was compared to a previous QTL study of the same population S42, where the current field data was reduced to one half through restriction of the analysis to the standard N treatment level (von Korff et al., Theor Appl Genet 112: 1221–1231, 2006). These authors located 54 QTLs for the same traits by applying a 3-factorial mixed model similar to the current model but excluding the factor N treatment. We found that QTL × environment interaction, alone or in combination, accounted for 24 of the newly uncovered QTLs, whereas QTL × N treatment interaction was of lesser importance with six new cases in total. A valuable QTL interacting with N treatment has been identified on chromosome 7H where lines carrying the wild barley allele were superior in number of ears per m² in either N treatment. We conclude that in population S42 the extension of the phenotype data set and the inclusion of N treatment into the mixed model increased the power of QTL detection by providing an additional replication rather than by revealing specific N treatment QTLs.     

Genetic control of yield and yield components in winter oilseed rape (Brassica napus L.) grown under nitrogen limitation

Despite its high nitrogen absorption capacity, oilseed rape (OSR) has a low apparent nitrogen use efficiency (NUE), which makes its production highly dependent on nitrogen fertilization. Improving NUE in OSR is therefore a main target in breeding. The objectives of the present work were to determine the genomic regions (QTLs) associated with yield and to assess their stability under contrasted nitrogen nutrition regimes. One mapping population, AM, was tested in a French location for three growing seasons (2011, 2012 and 2013), under two nitrogen conditions (optimal and low). Eight yield-related traits were scored and nitrogen-responsive traits were calculated. A total of 104 QTLs were detected of which 28 controlled flowering time and 76 were related to yield and yield components. Very few genotype × nitrogen interactions were detected and the QTLs were highly stable between the nitrogen conditions. In contrast, only a few QTLs were stable across the years of the trial, suggesting a strong QTL × year interaction. Finally, eleven critical genomic regions that were stable across nitrogen conditions and/or trial years were identified. One particular region located on the A5 linkage group appears to be a promising candidate for marker assisted selection programs. The different strategies for OSR breeding using the QTLs found in the present study are discussed.     

Identification of QTLs associated with salinity tolerance at late growth stage in barley

Salinity is a major abiotic stress to barley (Hordum vulgare L.) growth and yield. In the current study, quantitative trait loci (QTL) for yield and physiological components at the late growth stage under salt stress and non-stress environments were determined in barley using a double haploid population derived from a cross between CM72 (salt-tolerant) and Gairdner (salt-sensitive). A total of 30 QTLs for 10 traits, including tiller numbers (TN), plant height, spikes per line (SPL), spikes per plant (SPP), dry weight per plant, grains per plant, grain yield, shoot Na⁺ (NA) and K⁺ concentraitions (K) in shoot, and Na⁺/K⁺ ratio (NAK), were detected, with 17 and 13 QTLs under non-stress and salt stress, respectively. The phenotypic variation explained by individual QTL ranged from 3.25 to 29.81%. QTL flanked by markers bPb-1278 and bPb-8437 on chromosomes 4H was associated with TN, SPL, and SPP under salt stress. This locus may be useful in the breeding program of marker-assisted selection for improving salt tolerance of barley. However, QTLs associated with NA, K, and NAK differed greatly between non-stress and salt stress environments. It may be suggested that only the QTLs detected under salt stress are really associated with salt tolerance in barley. D. Xue and Y. Huang contributed equally to the article.     

Quantitative trait locus analysis for days-to-heading and morphological traits in an RIL population derived from an extremely late flowering F<Subscript>1</Subscript> hybrid of sorghum

The hybrid vigor typical of F₁ cultivars is used to boost biomass production of sorghum (Sorghum bicolor (L.) Moench). The high dry-matter yielding F₁ cultivar Kazetachi uniquely shows extremely late flowering and a long culm, and is greatly different from its parents. We investigated the genetic mechanisms underlying these phenotypes by quantitative trait locus (QTL) analysis of recombinant inbred lines derived from a male-fertile line and a restorer line and grown in 3 years. QTL analysis for six traits (days-to-heading, culm length, culm width, culm number, panicle length, panicle number) revealed that the unique phenotypes of the F₁ plants were controlled by the genetic combination of 12 or more QTLs detected in at least 2 years. Two putative QTLs for days-to-heading (qDH1 on SBI-01 and qDH6 on SBI-06) would strongly affect the other phenotypes because of their co-localization with QTLs for other traits, as supported by significant phenotypic correlations. These QTLs would be useful for understanding the association of plant type with biomass production in sorghum.     

Detection of quantitative trait loci (QTLs) for seedling traits and drought tolerance in wheat using three related recombinant inbred line (RIL) populations

In order to detect quantitative trait loci (QTLs) for drought tolerance in wheat during seed germination conditional and unconditional QTL analyses of eight seedling traits were conducted under two water regimes using three related F₉ recombinant inbred line populations with a common female parent. A total of 87 QTLs for the eight seedlings traits and 34 specific QTLs related to drought tolerance were detected. Seventy-one of these QTLs were major QTLs with contributions to phenotypic variance of >10 %. Of the 34 QTLs related to drought tolerance only eight were also detected by unconditional analysis of seedling traits under osmotic stress conditions indicating that most of the QTLs related to drought tolerance could not be detected by unconditional QTL analysis. Therefore, conditional QTL analysis of stress-tolerance traits such as drought tolerance was feasible and effective. Of 11 important QTL clusters located on chromosomes 1BL, 1D, 2A, 2B, 2D, 4A, 6B, and 7B, nine were detected in multiple populations and eight were detected by both unconditional and conditional analyses.     

Identification and validation of a yield-enhancing QTL cluster in rice (Oryza sativa L.)

Improvement of rice grain yield (YD) is an important goal in rice breeding. YD is determined by its related traits such as spikelet fertility (SF), 1,000-grain weight (TGW), and the number of spikelets per panicle (SPP). We previously mapped quantitative trait loci (QTLs) for SPP and TGW using the recombinant inbred lines (RILs) derived from the crosses between Minghui 63 and Teqing. In this study, four QTLs for SF and four QTLs for YD were detected in the RILs. Comparison of the locations of QTLs for these three yield-related traits identified one QTL cluster in the interval between RM3400 and RM3646 on chromosome 3. The QTL cluster contained three QTLs, SPP3a, SF3 and TGW3a, but no YD QTL was located there. To validate the QTL cluster, a BC₄F₂ population was obtained, in which SPP3a, SF3 and TGW3a were simultaneously mapped to the same region. SPP3a, SF3 and TGW3a explained 36.3, 29.5 and 59.0 % of phenotype variance with additive effect of 16.4 spikelets, 6 % SF and 1.8 g grain weight, respectively. In the BC₄F₂ population, though the region has opposite effects on TGW and SPP/SF, a YD QTL YD3 identified in this cluster region can increase 4.6 g grains per plant, which suggests this QTL cluster is a yield-enhancing QTL cluster and can be targeted to improve rice yield by marker aided selection.     

Identification of quantitative trait loci across interspecific F2, F2:3 and testcross populations for agronomic and fiber traits in tetraploid cotton

The most widely grown tetraploid Gossypium hirsutum and G. barbadense differ greatly in yield potential and fiber quality and numerous quantitative trait loci (QTLs) have been reported. However, correspondence of QTLs between experiments and populations is poor due to limited number of markers, small population size and inaccurate phenotyping. The purpose of the present study was to map QTLs for yield, yield components and fiber quality traits using testcross progenies between a large interspecific F₂ population and a commercial cotton cultivar as the tester. The results were compared to these from its F₂ and F_2:3 progenies. Of the 177 QTLs identified from the three populations, 65 fiber QTLs and 51 yield QTLs were unique with an average of 8–12 QTLs per traits. All the 26 chromosomes carried QTLs, but differed in the number of QTLs and the number of QTLs between fiber and yield QTLs. The congruence of QTLs identified across populations was higher (20–60 %) for traits with higher heritabilities including fiber quality, seed index and lint percentage, but lower (10–25 %) for lower heritability traits-seedcotton and lint yields. Major QTLs, QTL clusters for the same traits and QTL ‘hotspots’ for different traits were also identified. This research represents the first report using a testcross population in QTL mapping in interspecific cotton crosses and provides useful information for further comparative analysis and marker-assisted selection.     

Mapping QTLs with epistatic effects and QTL × treatment interactions for salt tolerance at seedling stage of wheat

Quantitative trait loci (QTLs) with additive (a), additive × additive (aa) epistatic effects, and their treatmental interactions (at and aat) were studied under salt stress and normal conditions at seedling stage of wheat (Triticum aestivum L.). A set of 182 recombinant inbred lines (RILs) derived from cross Xiaoyan 54 × Jing 411 were used. A total of 29 additive QTLs and 17 epistasis were detected for 12 traits examined, among which eight and seven, respectively, were identified to have QTL × treatment effects. Physiological traits rather than biomass traits were more likely to be involved in QTL × treatment interactions. Ten intervals on chromosomes 1A, 1D, 2A (two), 2D, 3B, 4B, 5A, 5B and 7D showed overlapping QTLs for different traits; some of them represent a single locus affecting different traits and/or the same trait under both treatments. Eleven pairs of QTLs were detected on seemingly homoeologous positions of six chromosome groups of wheat, showing synteny among the A, B and D genomes. Ten pairs were detected in which each pair was contributed by the same parent, indicating a strong genetic plasticity of the QTLs. The results are helpful for understanding the genetic basis of salt tolerance in wheat and provide useful information for genetic improvement of salt tolerance in wheat by marker-assisted selection.     

Genetic dissection of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) tiller,plant height,and grain yield based on QTL mapping and metaanalysis

Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length <0.3 Mb; 13 of the 21 MQTLs, and 34 candidate genes related to grain yield and plant development, were screened. Five major QTLs, viz. qGY6-2, qPH7-2, qPH6-3, qTN6-1, and qTN7-1, were not detected in the MQTL intervals and could be used as newly discovered QTLs. Candidate genes within these QTL intervals will play a meaningful role in molecular marker-assisted selection and map-based cloning of rice TN, PH, and GY.     

Quantitative trait loci for grain-quality traits across a rice F2 population and backcross inbred lines

Improving grain-quality is an important goal in rice breeding programs. One vital step is to find major quantitative trait loci (QTLs) for quality related traits and then investigate the relationships among them. We crossed ‘N22’, an indica variety with good appearance but low grain weight, to a japonica variety, ‘Nanjing35’, with superior grain yield but poor appearance. This enabled us to construct an F₂ population and a set of backcross inbred lines (BILs) for QTL-mapping for the traits related grain appearance. In all, 37 QTLs were identified for grain length (GL), grain width (GW), grain thickness (GT), thousand-grain weight (TGW), and the percentage of grains with chalkiness (PGWC). Of these, 17 QTLs detected from 184 plants in the F₂ population explained 4.97–27.26 % of the phenotypic variance, another 20 QTLs were identified using BILs from 2009 to 2010. Quantitative trait loci for major effects were detected in different populations and across years. A new QTL hot spot (marker interval RM504–RM520) was found on Chromosome 3, which harbored QTLs for GL, GW, GT, and TGW. Among our five examined traits, grain shape was significantly correlated with TGW and PGWC. The PGWC values of two heavier grains BILs, L93, and L145 are much lower than Nanjiing35, the analysis of genotype showed that this greater weight may due to the locus for GL occurring within RM504–RM520 on Chromosome 3. Therefore, those two lines will allow us to develop a long-grain high-yield rice variety with less chalkiness.     

QTL analysis of quality traits in the spring wheat cross RL4452 × 'AC Domain'

Wheat grain quality is a complex group of traits of tremendous importance to wheat producers, end‐users and breeders. Quantitative trait locus (QTL) analysis studied the genetics of milling, mixograph, farinograph, baking, starch and noodle colour traits in the spring wheat population RL4452/‘AC Domain’. Forty‐seven traits were measured on the population and 99 QTLs were detected over 18 chromosomes for 41 quality traits. Forty‐four of these QTLs mapped to three major QTL clusters on chromosomes 1B, 4D, and 7D. Fourteen QTLs mapped near Glu‐B1, 20 QTLs mapped near a major plant height QTL on chromosome 4D, and 10 QTLs mapped near a major time to maturity QTL on chromosome 7D. Large QTLs were detected for grain and flour protein content, farinograph absorption, mixograph parameters, and dietary fibre on chromosome 2BS. QTLs for yellow alkaline noodle colour parameter L* mapped to chromosomes 5B and 5D, while the largest QTL for the b* parameter mapped to 7AL.     

Detection of QTLs for salt tolerance in Asian barley (Hordeum vulgare L.) by association analysis with SNP markers

Two hundred ninety-six Asian barley (Hordeum vulgare L.) accessions were assessed to detect QTLs underlying salt tolerance by association analysis using a 384 single nucleotide polymorphism (SNP) marker system. The experiment was laid out at the seedling stage in a hydroponic solution under control and 250 mM NaCl solution with three replications of four plants each. Salt tolerance was assessed by leaf injury score (LIS) and salt tolerance indices (STIs) of the number of leaves (NL), shoot length (SL), root length (RL), shoot dry weight (SDW) and root dry weight (RDW). LIS was scored from 1 to 5 according to the severity of necrosis and chlorosis observed on leaves. There was a wide variation in salt tolerance among Asian barley accessions. LIS and STI (SDW) were the most suitable traits for screening salt tolerance. Association was estimated between markers and traits to detect QTLs for LIS and STI (SDW). Seven significant QTLs were located on chromosomes 1H (2 QTLs), 2H (2 QTLs), 3H (1 QTL), 4H (1 QTL) and 5H (1 QTL). Five QTLs were associated with LIS and 2 QTLs with STI (SDW). Two QTLs associated with LIS were newly identified on chromosomes 3H and 4H.     

Molecular mapping of QTLs for non-parasitic leaf spot resistance and comparison of half-sib DH populations in spring barley

Quantitative trait loci (QTLs) for resistance against non-parasitic leaf spots (NPLS) were first characterized in a spring barley double haploid population derived from the cross IPZ 24727/Barke (Behn et al., 2004). The aim of the present study was to identify QTLs for NPLS resistance in the half-sibling DH population IPZ 24727/Krona and to compare them with the QTLs of the population IPZ 24727/Barke. An anther culture-derived doubled haploid population of 536 DH lines was developed from the cross IPZ 24727 (resistant)/Krona (susceptible). Field trials were performed over two years in two replications, scoring NPLS and agronomic traits that might interact with NPLS. A molecular linkage map of 1035 cM was constructed based on AFLPs, SSRs and the mlo marker. QTL analyses for NPLS identified three QTLs that accounted for 30% of the phenotypic variation. For comparison of the QTLs from each DH population, a consensus map was generated comprising 277 markers with a length of 1199 cM. In both populations, the QTLs for NPLS mapped to chromosomes 1H, 4H and 7H. A common QTL with a great effect in both populations and over all environments was localized at the mlo locus on chromosome 4H, indicating that the mlo powdery mildew resistance locus has a considerable effect on NPLS susceptibility. The steps necessary to validate the QTLs and to improve the NPLS resistance by breeding were discussed.     

QTL for spikelet number from a high-yielding rice variety, Hoshiaoba, detected in an introgression line with the genetic background of an indica rice variety, IR64

Total spikelet number per panicle (TSN) is thought to be one of the most important agronomic traits associated with grain production in rice (Oryza sativa L.). We previously reported the development of 334 introgression lines (ILs) with variations in agronomic traits in the genetic background of indica rice variety IR64. Among these, an IL derived from high-yielding rice variety Hoshiaoba showed significantly higher TSN than IR64. We therefore have conducted a quantitative trait locus (QTL) analysis for TSN in an F₂ population of IL × IR64 to ascertain the genetic basis for the high TSN of the IL. The analysis revealed the presence of a QTL for TSN on chromosome 7, where several QTLs for grain number have been previously reported. We developed a near-isogenic line (NIL) for this QTL by using DNA marker-assisted selection and characterized its effect. The NIL showed significantly higher TSN than IR64. These results suggest that the QTL and the NIL will be useful materials in breeding programs aimed at increasing TSN.     

Identification of QTL for stalk sugar-related traits in a population of recombinant inbred lines of maize

Increasing sugar content in silage maize stalk improves its forage quality and palatability. The genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement, yet little information on QTL for stalk sugar content in maize has been reported. To this end, we investigated QTLs associated with stalk sugar traits including Brix, plant height (PHT), three ear leaves area (TELA), and days to silking (DTS) in two environments using a population of 202 recombinant inbred lines from a cross between YXD053, which has a high stalk sugar content, and Y6-1, which has a low stalk sugar content. A genetic map with 180 SSR and 10 AFLP markers was constructed, which spanned 1,648.6 cM of the maize genome with an average marker distance of 8.68 cM, and QTLs were detected using composite interval mapping. Seven QTLs controlling Brix were mapped on chromosomes 1, 2, 6 and 9 in the combined environments. These QTLs could explain 2.69–13.08 % of the phenotypic variance. One major QTL for Brix on chromosome 2 located between the markers bnlg1909 and umc1635 explained 13.08 % of the phenotypic variance. Y6-1 also contributed QTL allele for increased Brix on chromosome 6. One major QTLs controlling PHT on chromosome 1 and TELA on chromosome 4 were also identified and accounted for 13.68 and 12.49 % of the phenotypic variance, respectively. QTL alleles for increased DTS were located on chromosomes 1 and 5 of YXD053. Significant epistatic effects were identified in four traits, but no significant QTL × environment interactions were observed. The information presented here may be valuable for stalk sugar content improvement via marker-assisted selection in silage maize breeding programs.