Genetic Mapping and QTL Analysis of Growth-Related Traits in the Pacific Oyster

The Pacific oyster (Crassostrea gigas) is one of the most important oysters cultured worldwide. To analyze the oyster genome and dissect growth-related traits, we constructed a sex-averaged linkage map by combining 64 genomic simple sequence repeats, 42 expressed sequence tag-derived SSRs, and 320 amplified fragment length polymorphism markers in an F₁ full-sib family. A total of 426 markers were assigned to 11 linkage groups, spanning 558.2 cM with an average interval of 1.3 cM and 94.7% of genome coverage. Segregation distortion was significant for 18.8% of the markers (P < 0.05), and distorted markers tended to occur on some genetic regions or linkage groups. Most growth-related quantitative traits were highly significantly (P < 0.01) correlated, and principal component analysis obtained four principal components. Quantitative trait locus (QTL) analysis identified three significant QTLs for two principal components, which explained 0.6–13.9% of the phenotypic variation. One QTL for sex was detected on linkage group 6, and the inheritabilities of sex for parental alleles and maternal alleles on that locus C15 are 39.8% and 0.01%, respectively. The constructed linkage map and determined QTLs can provide a tool for further genetic analysis of the traits and be potential for marker-assisted selection in C. gigas breeding.     

QTL Mapping for Frond Length and Width in Laminaria japonica Aresch (Laminarales, Phaeophyta) Using AFLP and SSR Markers

In Laminaria japonica Aresch breeding practice, two quantitative traits, frond length (FL) and frond width (FW), are the most important phenotypic selection index. In order to increase the breeding efficiency by integrating phenotypic selection and marker-assisted selection, the first set of QTL controlling the two traits were determined in F₂ family using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers. Two prominent L. japonicas inbred lines, one with “broad and thin blade” characteristics and another with “long and narrow blade” characteristics, were applied in the hybridization to yield the F₂ mapping population with 92 individuals. A total of 287 AFLP markers and 11 SSR markers were used to construct a L. japonica genetic map. The yielded map was consisted of 28 linkage groups (LG) named LG1 to LG28, spanning 1,811.1 cM with an average interval of 6.7 cM and covering the 82.8% of the estimated genome 2,186.7 cM. While three genome-wide significant QTL were detected on LG1 (two QTL) and LG4 for “FL,” explaining in total 42.36% of the phenotypic variance, two QTL were identified on LG3 and LG5 for the trait “FW,” accounting for the total of 36.39% of the phenotypic variance. The gene action of these QTL was additive and partially dominant. The yielded linkage map and the detected QTL can provide a tool for further genetic analysis of two traits and be potential for maker-assisted selection in L. japonica breeding.     

Dissection of complex traits in forest trees — opportunities for marker-assisted selection

Due to their long reproductive cycles and the time to expression of mature traits, marker-assisted selection is particularly attractive for tree breeding. In this review, we discuss different approaches used for developing markers and propose a method for application of markers in low linkage disequilibrium (LD) populations. Identification of useful markers for application in tree breeding is mainly based on two approaches, quantitative trait locus (QTL) mapping and association genetic studies. While several studies have identified significant markers, effect of the individual markers is low making it difficult to utilize them in breeding programs. Recently, genomic selection (GS) was proposed for overcoming some of these difficulties. In GS, high density markers are used for predicting phenotypes from genotypes. Currently small effective populations with high LD are being tested for GS in tree breeding. For wider application, GS needs to be applied in low LD populations which are found in many tree breeding programs. Here we propose an approach in which the significant markers from association studies may be used for developing prediction models in low LD populations using the same methods as in GS. Preliminary analyses indicate that a modest numbers of markers may be sufficient for developing prediction models in low LD populations. GS based on large numbers of random markers or small numbers of associated markers is poised to make marker-assisted selection a reality in forest tree breeding.     

A doubled haploid rye linkage map with a QTL affecting α-amylase activity

A rye doubled haploid (DH) mapping population (Amilo × Voima) segregating for pre-harvest sprouting (PHS) was generated through anther culture of F₁ plants. A linkage map was constructed using DHs, to our knowledge, for the first time in rye. The map was composed of 289 loci: amplified fragment length polymorphism (AFLP), microsatellite, random amplified polymorphic DNA (RAPD), retrotransposon-microsatellite amplified polymorphism (REMAP), inter-retrotransposon amplified polymorphism (IRAP), inter-simple sequence repeat (ISSR) and sequence-related amplified polymorphism (SRAP) markers, and extended altogether 732 cM (one locus in every 2.5 cM). All of the seven rye chromosomes and four unplaced groups were formed. Distorted segregation of markers (P ≤ 0.05) was detected on all chromosomes. One major quantitative trait locus (QTL) affecting α-amylase activity was found, which explained 16.1% of phenotypic variation. The QTL was localized on the long arm of chromosome 5R. Microsatellites SCM74, RMS1115, and SCM77, nearest to the QTL, can be used for marker-assisted selection as a part of a rye breeding program to decrease sprouting damage.     

Breeding without breeding: minimum fingerprinting effort with respect to the effective population size

We present a probabilistic model to minimize the fingerprinting effort associated with the implementation of the “breeding without breeding” scheme under partial pedigree reconstruction. Our approach is directed at achieving a declared target population’s minimum effective population size (N _e ), following the pedigree reconstruction and genotypic selection and is based on the graph theory algorithm. The primary advantage of the proposed method is to reduce the cost associated with fingerprinting before the implementation of the pedigree reconstruction for seed parent–offspring derived from breeding arboreta and production or natural populations. Stochastic simulation was conducted to test the method’s efficiency assuming a simple polygenic model and a single trait. Hypothetical population consisted of 30 parental trees that were paired at random (selfing excluded), resulting in 600 individuals (potential candidates for forwards selection). The male parentage was assumed initially unknown. The model was used to estimate the minimum genotyping sample size needed to reaching the prescribed N _e . Results were compared with the known pedigree data. The model was successful in revealing the true relationship pattern over the whole range of N _e . Two to three offspring entered genotyping to meet the N _e  = 2 while 41 to 43 were required to satisfy the N _e  = 14. Importantly, genetic gain was affected at the lower limits of the genotyping effort. Doubling the number of parents resulted in considerable reduction of the genotyping effort at higher N _e values.     

Genomic selection for growth and wood quality in Eucalyptus: capturing the missing heritability and accelerating breeding for complex traits in forest trees

? Genomic selection (GS) is expected to cause a paradigm shift in tree breeding by improving its speed and efficiency. By fitting all the genome-wide markers concurrently, GS can capture most of the 'missing heritability' of complex traits that quantitative trait locus (QTL) and association mapping classically fail to explain. Experimental support of GS is now required. ? The effectiveness of GS was assessed in two unrelated Eucalyptus breeding populations with contrasting effective population sizes (N(e) = 11 and 51) genotyped with > 3000 DArT markers. Prediction models were developed for tree circumference and height growth, wood specific gravity and pulp yield using random regression best linear unbiased predictor (BLUP). ? Accuracies of GS varied between 0.55 and 0.88, matching the accuracies achieved by conventional phenotypic selection. Substantial proportions (74-97%) of trait heritability were captured by fitting all genome-wide markers simultaneously. Genomic regions explaining trait variation largely coincided between populations, although GS models predicted poorly across populations, likely as a result of variable patterns of linkage disequilibrium, inconsistent allelic effects and genotype × environment interaction. ? GS brings a new perspective to the understanding of quantitative trait variation in forest trees and provides a revolutionary tool for applied tree improvement. Nevertheless population-specific predictive models will likely drive the initial applications of GS in forest tree breeding.     

Prospects for genomic selection in conifer breeding: a simulation study of Cryptomeria japonica

Genomic selection (GS) can be a powerful technology in conifer breeding because conifers have long generation intervals, protracted evaluation times, and high costs of breeding inputs. To elucidate the potential of GS for conifer breeding, we simulated 60-year breeding programs in Cryptomeria japonica with and without GS. In conifers, the rapid decay of linkage disequilibrium (LD) can constitute a severe barrier to application of GS. For overcoming that barrier, we proposed an idea to leverage a seed orchard system, which has been used commonly in conifers, because some degree of LD exists in progenies derived from the limited number of elite trees in a seed orchard. The base population used for simulations consisted of progenies from 25 elite trees. Results show that GS breeding (GSB) done without model updating outperformed phenotypic selection breeding (PSB) during the first 30 years, but the genetic gain achieved over the 60 years was smaller in GSB than in PSB. However, GSB with model updating outperformed PSB over the 60 years. The genetic gain achieved over the 60 years of GSB with model updating was nearly twice that of PSB. Advantages of GSB over PSB prevailed, even for a low heritability polygenic trait. The number of markers necessary for efficient GS was a realistic level (e.g., one in every 1 cM), although higher marker density engendered higher accuracy of selection. These results suggest that GS can be useful in C. japonica breeding. Updating of the prediction model was, however, indispensable for attaining the large genetic gain.     

Genomic mapping and testing for quantitative trait loci in tea (<Emphasis Type="Italic">Camellia sinensis</Emphasis> (L.) O. Kuntze)

The tea industry is significant in the economies of tea-growing countries. Prospects of improving yield of made tea genomic information were explored using clones from a cross between clones TRFCA SFS150 and AHP S15/10. The 42 clones were tested in two distinct tea-growing regions in Kenya. Bulk segregant analysis was performed followed by complete genotyping. Out of 260 informative markers, 100 markers that showed 1:1 segregation were used to construct a linkage map. The map contained 30 (19 maternal and 11 paternal) linkage groups that spanned 1,411.5 cM with mean interval of 14.1 cM between loci. Based on the map, quantitative trait loci (QTL) analysis was done on yield data over 2003–2007 across the two sites, Timbilil and Kangaita. Twenty-three putative QTLs were detected, 16 in five different linkage groups for Timbilil, two in two groups for Kangaita, and the rest were associated with unassigned markers. No QTL was detected at both sites, which showed strong genotype × site interaction (G × E) but highly effective within-site heritability ([^(h)]² {\hat{h}^2} generally > 0.7). Problems of overestimated and spurious QTL effects arising from the smallness of the population should be mitigated by generally high within-site heritability. At least two unassigned markers associated with yield at Kangaita over the whole study period, suggesting potential as candidate markers for site-specific marker-assisted selections. Implications of the results with respect to mapping population, G × E, and marker-assisted selection are discussed.     

Extent and consistency across generations of linkage disequilibrium in commercial layer chicken breeding populations

Recent studies report a surprisingly high degree of marker-to-marker linkage disequilibrium (LD) in ruminant livestock populations. This has important implications for QTL mapping and marker-assisted selection. This study evaluated LD between microsatellite markers in a number of breeding populations of layer chickens using the standardized chi-square (chi(2')) measure. The results show appreciable LD among markers separated by up to 5 cM, decreasing rapidly with increased separation between markers. The LD within 5 cM was strongly conserved across generations and differed among chromosomal regions. Using marker-to-marker LD as an indication for marker-QTL LD, a genome scan of markers spaced 2 cM apart at moderate power would have good chances of uncovering most QTL segregating in these populations. However, of markers showing significant trait associations, only 57% are expected to be within 5 cM of the responsible QTL, and the remainder will be up to 20 cM away. Thus, high-resolution LD mapping of QTL will require dense marker genotyping across the region of interest to allow for interval mapping of the QTL.     

Towards second-generation STS (sequence-tagged sites) linkage maps in conifers: a genetic map of Norway spruce ( Picea abies K.)

Genetic linkage maps have been produced for a wide range of organisms during the last decade, thanks to the increasing availability of molecular markers. The use of microsatellites (or Simple Sequence Repeats, SSRs) as genetic markers has led to the construction of “second-generation” genetic maps for humans, mouse and other organisms of major importance. We constructed a second-generation single-tree genetic linkage map of Norway spruce (Picea abies K.) using a panel of 72 haploid megagametophytes with a total of 447 segregating bands [366 Amplified Fragment Length Polymorphisms (AFLPs), 20 Selective Amplification of Microsatellite Polymorphic Loci (SAMPLs) and 61 SSRs, each single band being treated initially as a dominant marker]. Four hundred and thirteen markers were mapped in 29 linkage groups (including triplets and doublets) covering a genetic length of 2198.3 cM, which represents 77.4% of the estimated genome length of Picea abies (approximately 2839 cM). The map is still far from coalescing into the expected 12 chromosomal linkage groups of Norway spruce (2n = 2x = 24). A possible explanation for this comes from the observed non-random distribution of markers in the framework map. Thirty-eight SSR marker loci could be mapped onto 19 linkage groups. This set of highly informative Sequence Tagged Sites (STSs) can be used in many aspects of genetic analysis of forest trees, such as marker-assisted selection, QTL mapping, positional cloning, gene flow analysis, mating system analysis and genetic diversity studies. Received: 5 November 1997 / Accepted: 16 March 1998     

Inheritance of Flowering Time in Apricot (<Emphasis Type="Italic">Prunus armeniaca</Emphasis> L.) and Analysis of Linked Quantitative Trait Loci (QTLs) using Simple Sequence Repeat (SSR) Markers

Time of flowering was studied during 3 years in a BC1 apricot progeny of 73 seedlings derived from a cross between the F1 selection “Z506-07” (“Orange Red” × “Currot”) and the Spanish cultivar “Currot”. Results indicated a quantitative inheritance of flowering time in apricot with an influence of juvenility and environmental conditions (chill accumulation) on the evaluation and expression of this trait. Genetic maps consisting of 11 linkage groups for both parents representing the eight chromosomes of apricot were developed using 46 apricot and peach simple sequence repeat (SSR-microsatellites) markers and were used for the identification of quantitative trait loci (QTL). QTL analysis for flowering time allowed the identification of one significant QTL on the linkage group 5 (G5) of “Z506-07”, and explaining most of the phenotypic variation. Two microsatellite loci (UDAp-423r and AMPA-105) were found to be tightly linked to this important agronomic trait. Finally, we discuss the stability of the QTL described during the 3 years of the study and the development of efficient marker-assisted selection strategies applied to apricot and other Prunus breeding programs.     

Linkage mapping and QTL analysis in coconut (Cocos nucifera L.)

Different DNA marker types were used to construct linkage maps in coconut (Cocos nucifera L.; 2n = 32) for the two parents of the cross Malayan Yellow Dwarf (MYD) × Laguna Tall (LAGT). A total of 382 markers was sufficient to generate 16 linkage groups for each parent. The total genome length corresponded to 2226 cM for the LAGT map and 1266 cM for the MYD map with 4–32 markers per linkage group. Common markers allowed the association of 9 linkage groups for the two parents MYD and LAGT. QTL analysis for the trait early germination identified six loci. These QTLs correlate with early flowering and yield, representing characters which are important in coconut breeding. The co-segregation of markers with these QTLs provides the first opportunity for marker-assisted selection in coconut breeding programmes. Received: 22 September 1999 / Accepted: 29 November 1999     

Effect of genomic prediction on response to selection in forest tree breeding

Through stochastic simulations, estimates of breeding values accuracies and response to selection were assessed under traditional pedigree-based and genomic-based evaluation methods. More specifically, several key parameters such as the trait’s heritability (0.2 and 0.6), the number of QTLs underlying the trait (100 to 200), and the marker density (1 to 10 SNPs/cM) were evaluated. Additionally, impact of two contrasting mating designs (partial diallel vs. single-pair mating) was investigated. Response to selection was then assessed in a seed production population (seed orchard consisting of unrelated selections) for different effective population sizes (N_e?=?5 to 25). The simulated candidate population comprised a fixed size of 2050 individuals with fast linkage disequilibrium decay, generally found in forest tree populations. Following the genetic/genomic evaluation, top-ranked individuals were selected to meeting the predetermined effective population size in target production population. The combination of low h², high N_e, and dense marker coverage resulted at maximum relative genomic prediction efficiency and the most efficient exploitation of the Mendelian sampling term (within-family additive genetic variance). Since genomic prediction of breeding values constitutes the methodological foundation of genomic selection, our results can be used to address important questions when similar scenarios are considered.     

Mapping quantitative trait loci associated with chlorophyll a fluorescence parameters in soybean (Glycine max (L.) Merr.)

Chlorophyll a fluorescence parameters can provide qualitative and quantitative information about photosynthetic processes in chloroplasts. JIP-test and modulated fluorescence (MF) parameters are commonly used chlorophyll a fluorescence parameters. This study was conducted to identify quantitative trait loci (QTLs) associated with JIP-test parameters, MF parameters, and photosynthetic rate (P_N), and to examine the relationships among them in soybean (Glycine max (L.) Merr.). Pot and field experiments were performed to evaluate 184 recombinant inbred lines (RILs) for five JIP-test parameters (ABS/RC, TR_o/ABS, ET_o/TR_o, RE_o/ET_o, and PI_ABS), four MF parameters (Fv/Fm, Fv′/Fm′, ΦPSII, and qP), and P_N. Significant correlations were commonly observed among JIP-test parameters, MF parameters, and P_N. QTL mapping analysis identified 13, 9, and 4 QTLs for JIP-test parameters, MF parameters, and P_N, respectively, of which 13 were stable. Four major genomic regions were detected: LG A2 (19.81 cM) for JIP-test parameters, LG C1 (94.31 and 97.61 cM) for P_N and MF parameters, LG M (100.51 cM) for JIP-test and MF parameters, and LG O (30.61–49.91 cM) for P_N, JIP-test, and MF parameters. These results indicate that chlorophyll fluorescence parameters, especially ΦPSII and qP, could play an important role in regulating P_N, and that JIP-test and MF parameters could be controlled by the same or different genes. The QTLs identified in this study will help in the understanding of the genetic basis of photosynthetic processes in plants. They will also contribute to the development of marker-assisted selection breeding programs for photosynthetic capacity in soybean.     

A Genetic linkage map of Pinyon pine (Pinus edulis) based on amplified fragment length polymorphisms

 Amplified fragment length polymorphisms (AFLP) were used to rapidly generate a dense linkage map for pinyon pine (Pinus edulis). The map population consisted of 40 megagametophytes derived from one tree at Sunset Crater, Arizona. A total of 78 primer combinations, each with three to five selective nucleotides, amplified 542 polymorphic markers. Of these, 33 markers showed significant deviation from the expected Mendelian genotypic segregation ratio of 1 : 1, and 164 showed complete linkage with another marker. This resulted in 338 unique markers mapping to 25 linkage groups, each of which ranged from 2 to 22 markers, averaging 80 centiMorgans (cM) in size and covering 2,012 cM (2,200 cM with the inclusion of 25 cM for each of 7 unlinked markers). Pairwise linkage values gave a genome size estimate of 2,390 cM, suggesting comprehensive coverage of the genome. A search for subsets of primer combinations giving the best map coverage found 10 primer combinations which together marked 72% of the linkage map to within 10 cM; an additional 10 primer combinations increased this percentage to 85%. Our map represents an initial step towards the identification of quantitative trait loci associated with pest resistance and water stress in pinyons and will further allow us to examine introgression rates between P. edulis and P. californiarum. Received: 14 October 1997 / Accepted: 29 April 1998     

Using SNP markers to dissect linkage disequilibrium at a major quantitative trait locus for resistance to the potato cyst nematode Globodera pallida on potato chromosome V

The damage caused by the parasitic root cyst nematode Globodera pallida is a major yield-limiting factor in potato cultivation . Breeding for resistance is facilitated by the PCR-based marker ‘HC’, which is diagnostic for an allele conferring high resistance against G. pallida pathotype Pa2/3 that has been introgressed from the wild potato species Solanum vernei into the Solanum tuberosum tetraploid breeding pool. The major quantitative trait locus (QTL) controlling this nematode resistance maps on potato chromosome V in a hot spot for resistance to various pathogens including nematodes and the oomycete Phytophthora infestans. An unstructured sample of 79 tetraploid, highly heterozygous varieties and breeding clones was selected based on presence (41 genotypes) or absence (38 genotypes) of the HC marker. Testing the clones for resistance to G. pallida confirmed the diagnostic power of the HC marker. The 79 individuals were genotyped for 100 single nucleotide polymorphisms (SNPs) at 10 loci distributed over 38 cM on chromosome V. Forty-five SNPs at six loci spanning 2 cM in the interval between markers GP21-GP179 were associated with resistance to G. pallida. Based on linkage disequilibrium (LD) between SNP markers, six LD groups comprising between 2 and 18 SNPs were identified. The LD groups indicated the existence of multiple alleles at a single resistance locus or at several, physically linked resistance loci. LD group C comprising 18 SNPs corresponded to the ‘HC’ marker. LD group E included 16 SNPs and showed an association peak, which positioned one nematode resistance locus physically close to the R1 gene family. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture,Training Population Composition,Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite,Tropical Rice Breeding Lines

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute''s (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.     

Genetics of resistance to ascochyta blight (Ascochyta lentis) of lentil and the identification of closely linked RAPD markers

 Foliar resistance to Ascochyta lentis is controlled at a single major locus by a dominant gene (AbR ₁ ) in the lentil accession ILL5588 (cv ‘Northfield’). Flanking RAPD markers that are closely linked to the resistance locus in coupling phase were identified by bulked segregant analysis. Out of 261 decanucleotide primers screened 7 produced a polymorphic marker that segregated with the resistance locus, and all markers were found to exist within a single linkage group. Five of the seven RAPD markers were within 30 cM of the resistance locus. Log likelihood analysis for detecting QTL associated with the foliar resistance revealed that a single narrow peak accounted for almost 90% of the variance of resistance between the bulks. Preliminary mapping in an F₃ population revealed that the closest flanking markers were approximately 6 and 14 centiMorgans (cM) away from the resistance locus. These markers should be useful for the discrimination of resistant germplasm through marker-assisted selection in future breeding programmes and represent the first essential step towards the map-based cloning of this resistance gene. Received: 18 December 1997 / Accepted: 9 June 1998     

Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus

Eucalyptus globulus Labill. ssp. globulus is an important tree species for the pulp and paper industry, and several breeding programmes throughout the world are striving to improve key traits such as growth and wood density. This study aimed to detect quantitative trait loci (QTL) for growth, wood density, relative bark thickness and early flowering in a single full-sib E. globulus family grown across seven sites. Growth was measured a number of times over a 6-year period, enabling temporal stability of growth QTL to be studied. Ten putative QTL (LOD > 2.0) were detected in the single family, which was of moderate size. Based on permutations of the trait data, six of these QTL were significant at the experimentwise significance level of 0.1 for at least one of the four models implemented in analysis to remove site effects. For wood density, two putative QTL explained 20% of the variance for the trait, indicating that a small number of QTL might explain a reasonable proportion of the trait variance. One of these QTL was found to be independent of QTL for growth whereas the second QTL co-segregated with a QTL for relative incremental growth. The marker nearest to this QTL was associated with fast growth but low wood density. A putative growth QTL at year 6 was found to be relatively stable across ages. In addition, it was found that residuals from models based on measurements from across all families across all sites in the trial detected QTL with greater experimentwise significance.     

High‐density genetic map of Miscanthus sinensis reveals inheritance of zebra stripe

Miscanthus is a perennial C₄ grass that has recently become an important bioenergy crop. The efficiency of breeding improved Miscanthus biomass cultivars could be greatly increased by marker‐assisted selection. Thus, a high‐density genetic map is critical to Miscanthus improvement. In this study, a mapping population of 261 F₁ progeny was developed from a cross between two diploid M. sinensis cultivars, ‘Strictus’ and ‘Kaskade’. High‐density genetic maps for the two parents were produced with 3044 newly developed single nucleotide polymorphisms (SNPs) obtained from restriction site‐associated DNA sequencing, and 138 previously mapped GoldenGate SNPs. The female parent (‘Strictus’) map spanned 1599 cM, with 1989 SNPs on 19 linkage groups, and an average intermarker spacing of 0.8 cM. The length of the male parent (‘Kaskade’) map was 1612 cM, with 1821 SNPs, and an average intermarker spacing of 0.9 cM. The utility of the map was confirmed by locating quantitative trait loci (QTL) for the zebra‐striped trait, which was segregating in this population. Three QTL for zebra‐striped presence/absence (zb1, zb2 on LG 7, and zb3 on LG 10) and three for zebra‐striped intensity (zbi1, zbi2, zbi3 on LGs 7, 10, 3) were identified. Each allele that caused striping was recessive. Incomplete penetrance was observed for each zb QTL, but penetrance was greatest when two or more zb QTL were homozygous for the causative alleles. Similarly, the intensity of striping was greatest when two or more zbi QTL were homozygous for alleles that conferred the trait. Comparative mapping indicated putative correspondence between zb3 and/or zbi2 on LG 10 to previously sequenced genes conferring zebra stripe in maize and rice. These results demonstrate that the new map is useful for identifying marker–trait associations. The mapped markers will become a valuable community resource, facilitating comparisons among studies and the breeding of Miscanthus.