Review Paper for Mapping of Cottonseed Fiber Qtl in Brassica Napus L

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Research Article

A High-Density SNP Map for Accurate Mapping of Seed Fibre QTL in Brassica napus 50

• Liezhao Liu,
• Cunmin Qu,
• Benjamin Wittkop,
• Bin Yi,
• Yang Xiao,
• Yajun He,
• Rod J. Snowdon,
• Jiana Li

ten

• Published: Dec 26, 2013
• https://doi.org/10.1371/journal.pone.0083052

Figures

Abstract

A loftier density genetic linkage map for the complex allotetraploid crop species Brassica napus (oilseed rape) was constructed in a tardily-generation recombinant inbred line (RIL) population, using genome-broad unmarried nucleotide polymorphism (SNP) markers assayed by the Brassica 60 K Infinium BeadChip Array. The linkage map contains 9164 SNP markers covering 1832.ix cM. 1232 bins account for 7648 of the markers. A subset of 2795 SNP markers, with an boilerplate distance of 0.66 cM between side by side markers, was applied for QTL mapping of seed colour and the prison cell wall fiber components acid detergent lignin (ADL), cellulose and hemicellulose. Later phenotypic analyses across four dissimilar environments a total of eleven QTL were detected for seed color and cobweb traits. The high-density map considerably improved QTL resolution compared to the previous low-density maps. A previously identified major QTL with very high effects on seed color and ADL was pinpointed to a narrow genome interval on chromosome A09, while a minor QTL explaining eight.1% to 14.1% of variation for ADL was detected on chromosome C05. Five and three QTL accounting for four.vii% to 21.9% and 7.three% to 16.ix% of the phenotypic variation for cellulose and hemicellulose, respectively, were too detected. To our knowledge this is the first description of QTL for seed cellulose and hemicellulose in B. napus, representing interesting new targets for improving oil content. The high density SNP genetic map enables navigation from interesting B. napus QTL to Brassica genome sequences, giving useful new information for understanding the genetics of key seed quality traits in rapeseed.

Citation: Liu 50, Qu C, Wittkop B, Yi B, Xiao Y, He Y, et al. (2013) A High-Density SNP Map for Accurate Mapping of Seed Fibre QTL in Brassica napus L. PLoS 1 8(12): e83052. https://doi.org/10.1371/journal.pone.0083052

Editor: Tongming Yin, Nanjing Forestry University, China

Received: August 17, 2013; Accepted: November 7, 2013; Published: Dec 26, 2013

Copyright: © 2013 Liu et al. This is an open-access article distributed under the terms of the Artistic Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This research was supported by National Natural Science Foundation of China (number 31171584), Chongqing Natural Scientific discipline Foundation (number cstc2011jjA8000g), 948 projection (number 2011-G23) and the Earmarked Fund for Modern Agro-manufacture Engineering Inquiry Organization (number CARS-13). This piece of work as well funded from Germany with a grant to LL from the "Forschungsfonds Raps" and additional support from Norddeutsche Pflanzenzucht H.G. Lembke KG. The funders had no function in study design, data collection and analysis, decision to publish, or grooming of the manuscript.

Competing interests: The work presented in this paper was funded in part by the commercial breeding company Norddeutsche Pflanzenzucht H.Grand. Lembke KG, who also provided data for the study from ane location in Deutschland. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Introduction

Precise linkage map construction is the beginning step for mapping of quantitative trait loci (QTL) and comparative genome analysis of interesting QTL regions. In oilseed rape (Brassica napus Fifty.) a large number of low-density genetic maps, generated using electrophoretic marker systems like restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR), have been used to map qualitative and quantitative trait loci for a large number of traits [1]–[9].

A major disadvantage of many of these previous B. napus QTL mapping studies was an inability to derive and compare exact chromosomal locations for regions of involvement. This situation can exist improved using sequence data from tightly-linked markers, particularly as genome sequences get available for Brassica crops [10]. It will exist extremely useful for closer examination of QTL and potential positional gene cloning to be able to navigate directly form genetic map positions to the genome sequence. In genetic maps with low marker densities, or higher-density maps based on bearding markers like AFLP or SRAP, this is possible merely by labour-intensive development and addition of sequence-based markers to saturate regions of interest.

The near abundant and elementary Dna markers for mapping and other applications are single nucleotide polymorphisms (SNPs). Today SNPs have become the marker of selection in most species for genome-wide association studies (GWAS), phylogenetic analyses, mark-assisted selection, bulked segregant analysis and genomic pick. In 2012 an international Brassica SNP consortium produced a 60,000 (threescore k) SNP Infinium genotyping array for B. napus, in cooperation with Illumina Inc., San Diego, CA, Us [11]–[12]. This introduced a very low-cost and efficient method for high-density, sequence-based, genome-wide polymorphism screening in B. napus populations.

The use of high density genetic maps can greatly improve the precision of QTL localisation and the accuracy of event estimates for detected QTL, especially for small and medium sized QTL [13]. Peculiarly with the evolution of automatic sequencing and genotyping technologies, many high density linkage maps have been constructed in different crops including oilseed rape/canola (B. napus). For example, Sun et al. [14] synthetic an ultradense genetic map consisting of 13351 SRAP markers covering 1604.8 cM in B. napus. Raman et al. (2012a) [xv] used multifariousness array technology (DArT) markers to construct a linkage map for a doubled haploid (DH) mapping population of B. napus, and further synthetic a consensus linkage map for genetic autopsy of qualitative and quantitative traits (Raman et al. 2012b) [16]. The polymorphisms in the high throughput Dart mark organisation derive from restriction enzyme recognition sites and insertion/deletions (InDels). On the other hand, big stock-still panels of robust SNP markers on widely-used array platforms are highly reproducible in different genetic backgrounds. A major advantage of genetic maps based on (public) genome-broad SNP screening arrays is the high occurrence of consensus markers for integration and alignment of maps and QTL, both to each other and also to reference genome sequences. Delourme et al. [17] developed an integrated B. napus map comprising 5764 SNP and 1603 PCR markers covering a total genetic length of 2250 cM. Chen et al. [18] also constructed a high density B. napus bin map, using a modified double-digested restriction-associated DNA sequencing (ddRADseq) arroyo.

Rapeseed is grown worldwide for vegetable oil and biodiesel production, and after oil extraction it also provides a high quality meal used primarily for livestock feeding [xix]. Xanthous-seeded B. napus is considered advantageous for the meal quality due to a thinner seed coat and higher protein content [20] along with reduced quantities of non-energetic fibre (cellulose and hemicellulose) and anti-nutritional polyphenolics (acid detergent lignin: ADL) [21]. Undigestible fiber, a major antinutritional component in rapeseed repast, can exist reduced by breeding of light-seeded cultivars, whereas non-energetic cellulose and hemicellulose share photosynthesis products with seed oil and protein and are therefore important pleiotropic contributors to the agronomic value of the seed.

Numerous genetic mapping studies of seed colour loci have been reported in Brassica species using different biparental populations and marker technologies [22]–[35]. Many of these studies revealed QTL with different effects in different genetic backgrounds. A number of studies in B. napus suggested that i major locus on chromosome A09 explained most of the phenotype variation for both seed colour and meal quality traits in the most important Brassica oilseed crop [36]–[xl]. Even so, attempts to saturate this QTL with markers [38], [41] have revealed possible chromosome rearrangements that arrive difficult to detect markers and genes with close concrete linkage to the QTL. Alignment of QTL from all of these different studies has besides been rendered difficult by this complexity [41], and because of a lack of consensus markers spanning the QTL in the unlike studies. Whereas most PCR-based markers are polynary markers, peculiarly in the allopolyploid B.napus, the Illumina type Two beadtype SNPs utilized in the present study are robust binary markers which tin be compared directly among diverse genetic backgrounds.

In this study we constructed a new, loftier density genetic map of B. napus, using a homozygous, F_ix RIL population genotyped with the Brassica 60 k Infinium SNP array. To our knowledge this is the commencement high-density B. napus genetic map to be published with genotype data from the new Brassica 60 k SNP array. The map was used to precisely map QTL for seed colour, anti-nutritional seed ADL content, not-energetic seed cellulose and hemicellulose content using trait information from four field environments. The results provide tightly-linked and physically next markers for convenance of these important agronomic traits in rapeseed, and a ways to navigate directly from interesting map intervals to Brassica genome sequences every bit a key step in map-based QTL cloning.

Materials and Methods

Mapping population and trait analysis

A population of 172 F₉ RILs was derived by unmarried seed descent from F_ii offspring of a cantankerous between the Chinese semi-winter oilseed rape parental lines GH06 (yellow seeds, low seed fibre content) and P174 (black seeds, high seed fibre content). Seed quality traits were measured on self-pollinated seed samples collected from field evaluations of the RIL population in four different environments over two years equally follows: 2008 at the agricultural field station of Justus Liebig University Giessen at Weilburger Grenze (central Deutschland), in the convenance nursery of the German plant breeding visitor NPZ Lembke KG in Hohenlieth (northern Germany) and in the breeding plant nursery of Southwest University in Beibei, Chongqing (southwest China), and 2009 over again at the field station Weilburger Grenze in Giessen. No specific permissions are required to grow conventional oilseed rape on these agricultural locations. Inflorescences of up to iii randomly-chosen plants in each plot were covered in pollen-proof numberless at the onset of flowering to prevent cantankerous-pollination. Self-pollinated seeds were collected in the bags at maturity for quality assay.

All trials were performed with a plot size of iv.5 m² (1.5 m×3 yard) with 5 or 6 rows per plot depending on the location. Measurements for seed colour and fibre components on the self-pollinated seeds were obtained by about-infrared reflectance spectroscopy (NIRS) using an NIR System 6500 with WinISI II software (FOSS GmbH, Rellingen, Germany). Phenotype values for seed color (visual lite absorbance), acid detergent lignin (ADL; % seed dry out weight), acid detergent fibre (ADF; % seed dry out weight) and neutral detergent fibre (NDF; % seed dry weight) were extrapolated from NIRS spectra using the NIRS calibrations for these traits as described by Wittkop et al. [20]. NIRS-derived estimates for each trait and genotype were averaged over two technical repetitions. In the RIL population, mean trait values were averaged from upwards to three cocky-pollinated plants from each genotype over the four environments. The predicted ways (eblups) were used for QTL identification of the seed colour and fiber traits. Cellulose concentrations were calculated equally the divergence between NDF and ADF, hemicellulose as the difference between ADF and ADL. Basic statistical assay of the phenotype data was performed using Microsoft Excel 2010.

SNP marker assay

The Brassica 60 Thou SNP BeadChip Array was used to genotype 172 RIL lines and parental lines. This array, which successfully assays 52,157 Infinium Type Ii SNP loci in B. napus, was developed past an international consortium using preferentially single-locus SNPs contributed from genomic and transcriptomic sequencing in genetically diverse Brassica germplasm (Isobel Parkin, Agriculture and AgriFood Canada, unpublished information).

Total genomic Deoxyribonucleic acid was extracted from 150 mg of leafage tissue from 5 young seedings per RIL and from the two parental lines, using DP321-03 Deoxyribonucleic acid extraction kits (Tiangen, Beijing, Mainland china). The Deoxyribonucleic acid samples were diluted to 50 ng/μL. The SNP analysis was washed in National Primal Laboratory of Ingather Genetic Improvement, National Subcenter of Rapeseed Improvement in Wuhan, Huazhong Agronomical University, 430070 Wuhan, Communist china. DNA sample preparation, hybridisation to the BeadChip, washing, primer extension and staining were performed according to the work flow described in the Infinium HD Assay Ultra manual. Imaging of the arrays was performed using an Illumina HiSCAN scanner after BeadChip washing and blanket. Allele calling for each locus was performed using the GenomeStudio genotyping software v2011 (Illumina, Inc.). Cluster definition was based on genotype information from 216 B. napus lines (nine Beadchips) including the 172 RILs and parental lines from this population and 42 additional B. napus genotypes. SNP markers were named using SNP plus index numbers assigned past GenomeStudio, followed by the chromosome number. Positions of A-genome SNPs were provided past the assortment manufacturer, while C genome SNP source sequences were subjected to a BLAST search confronting the B.oleracea genome database (BRAD, http://brassicadb.org/) to locate chromosome positions (Due east value < = 1e-l).

Linkage analysis and QTL mapping

Genetic linkage analysis was performed using the software packages MSTmap [42] and JoinMap 4.0 [43]. The algorithm implemented in MSTMap can efficiently handle ultra-dense datasets from 10,000 to 100,000 markers, and independent comparisons of MSTMap with JoinMap have found it to produce the most accurate maps for most experiments with vey fast adding times [44]. Co-ordinate to Wu et al. [42] the software generates extremely accurate map outputs when the data quality is high.

Polymorphic SNP markers were first grouped at LOD 5.0 using MSTmap, and so marker orders were determined by finding the minimum spanning tree of a graph for each linkage group based on pairwise recombination frequencies. The marker order and distance in each linkage group were recalculated and confirmed by Joinmap 4.0, applying the mapping role of Kosambi [45] and a minimum LOD score of 3.0. Marker pairs with zero recombination were assigned to the same genetic bin. A reference genetic map was synthetic with SNP bins being designated according to the index number of the start SNP marker in each bin.

Detection of QTL for seed colour, cellulose, hemicellulose and ADL content were performed in the RIL population by composite interval mapping using the QTL Cartographer software version WinQTLCart2.5 [46]. The LOD threshold for detection of significant QTL was ready by permutation analysis with 300 permutations. The linkage map and QTL positions were drawn using the software Mapchart [47].

Results

SNP map structure

A total of 16613 SNP markers from the Brassica 60 K array showed polymorphisms between the mapping parents GH06 and P174. Of these, 9804 homologous SNP markers showing the expected segregation 1:i ratio in the RIL population were used for genetic linkage assay AND linkage map construction using MSTmap and Joinmap 4.0. SNP markers expected to be specific to the B. napus A and C genome were cleanly separated into different linkage groups according to their chromosomal origin past using MSTmap at LOD five, and some groups remained intact even at LOD 10. Finally, a set of 9164 SNP markers were successfully assigned to linkage groups representing the 19 B. napus chromosomes of the A genome (A01–A10) and C genome (C01–C09), respectively. As expected from the variable size of the B. napus chromosomes [48] and from previous genetic mapping studies, the marker number and density varied considerably across the unlike chromosomes (Figure 1). In the A genome three chromosomes displayed gaps of more than twenty cM, while 1 chromosome in the C genome as well showed a gap over over 20 cM. The highest marker density was institute on chromosome C02, with 1507 markers distributed over a genetic map distance of 52.iv cM.

Figure 1. Overview of genome-wide SNP density in the B. napus SNP map.

The abscissa indicates the number of SNP markers in each map interval, while the ordinate shows the genetic distance along each of the xix linkage groups corresponding to the 19 B. napus chromosomes. The superlative of the QTL was pinpointed to a narrow region at the terminal end of the chromosome flanked by two adjacent SNP markers.

https://doi.org/10.1371/periodical.pone.0083052.g001

A SNP bin map comprising 1232 bins was constructed (File S1). The number of SNP markers per bin varied from 2 to 950. The largest bin on C02 containing 950 markers, and only 504 markers from this bin gave successful Nail hits in the B.oleracea database to chromosome C02.

The final loftier density B. napus linkage map for the GH06 ten P174 RIL population contains a total of 2795 singled-out loci, including 976 loci on C genome chromosomes and 1819 loci in the A genome. The map covers 1832.nine cM, with total chromosome lengths of 970.2 cM and 862.7 cM for the A and C genomes, respectively (File S1). The marker density in A genome was thus considerably college than in the C genome, with an average distance between markers of 0.53 cM in the A genome and 0.93 cM in the C genome, respectively (Table 1).

Table 1. Summary of locus numbers, marker numbers, multiple-marker bins and linkage group genetic distances of the 19 A-genome (A01–A10) and C-genome (C1–C9) chromosomes in the Brassica napus SNP bin map.

https://doi.org/10.1371/journal.pone.0083052.t001

QTL analysis using the high-density SNP map

A single major QTL explaining 36.9% to 47.two% of the phenotypic variation for seed colour across the three different environments was detected at the cease of linkage group A09 (Table 2, Figure 2, Figure iii). Two QTL for seed ADL content were localised on chromosomes A09 and C05, accounting for 31.vi–42.8% and 8.1–14.1% of the phenotypic variation in the 4 different environments, respectively (Table 2, Figure 2 and Figure 3). The negative condiment effects of these three QTL indicated that the yellowish-seeded parent GH06 contributed to a strong subtract in seed color and seed ADL content. The QTL for seed colour and ADL on chromosome A09 showed perfect colocalisation- This is presumably indicative of a stiff pleiotropic upshot caused by reduced seed coat thickness [36], which also explains their high correlation of R = 0.67 in the RIL population (File S2). The conviction interval of these ii QTL spans a physical region from 32.22 Mbp to 32.84 Mbp in the B. rapa A genome reference sequence (Effigy two). We scanned the 620 kbp concrete interval betwixt the SNP markers flanking the QTL conviction interval for potential candidate genes involved in seed phenylpropanoid (lignin biosynthesis) or proanthocyanin pigmentation (flavanoid biosynthesis). The flavonoid biosynthesis cistron Bra007813, homologous to FLAVONOL 3-HYDROXYLASE (F3H, as well known as TRANSPARENT TESTA 6, TT6) was located 32.52 Mbp on A09. In the flavonoid biosynthetic pathway F3H catalyzes naringenin to dihydrokaempferol, a key forerunner of proanthocyanins that accumulate every bit dark seed pigments (condensed tannins) in the testa of Brassica seeds. Other lignin biosynthesis and flavonoid genes which previous studies take suggested every bit potential candidates for the major QTL for seed colour and fibre content on chromosome A09 [36], [38], [41], were shown to be outside the narrow QTL conviction interval calculated using the high-density SNP map.

Figure 2. Graph showing a major QTL with big additive effects acid detergent lignin (ADL, four environments) and seed colour (Col, iii environments) plotted according to logarithmic odds (LOD) score across the length of linkage group A09.

Locations: Cq, Chongqing Red china; Ho, Hohenlieth Deutschland; Gi, Giessen Germany. Years: 08, 2008; 09, 2009.

https://doi.org/10.1371/periodical.pone.0083052.g002

Figure 3. Locations of significant QTL for acid detergent lignin (ADL), cellulose (Cel), hemicellulose (Hem) and seed colour (Col) in 4 dissimilar environments on the high-density SNP map.

For simplicity only the markers in the QTL confidence intervals, along with the terminal two markers at each end of the QTL-containing chromosomes, are shown. Full map data is provided in File S1.

https://doi.org/10.1371/journal.pone.0083052.g003

Based on the high density linkage map, 5 QTL with phenotypic furnishings on seed cellulose content ranging from 4.7% to 21.nine% were detected across the four different environments. For four of these QTL the alleles from GH06 contributed to a decrease in seed cellulose content, whereas the decrease in cellulose caused by QTL qCelA09 on chromosome A09 was contributed past P174. The QTL with the greatest effect on cellulose content, qCelA08, was detected beyond all four environments on chromosome A08 with an effect of 12.ane% to 15.one% on the phenotypic variation. A unmarried QTL for hemicellulose content was localised on chromosome A03, with a phenotypic effect of around viii% on this trait in the three German language environments.

Discussion

The identification of genome-wide SNP markers for B. napus based on growing quantities of next-generation sequencing information has opened the possibility for evolution of cost-effective, high-density SNP screening arrays for high-throughput genotyping of big oilseed rape mapping and convenance populations [12]. Whereas most QTL studies in B. napus in the past were based on lower-density genetic maps, often without sequence note of the marker loci, loftier-density SNP maps open up the possibility for accurate alignment of B. napus genetic maps to physical chromosome segments in assembled Brassica genomes. This greatly increases the utility of genetic linkage maps for characterisation and comparison of QTL controlling important agronomic traits.

The marker density of a genetic map cannot exist increased solely by increasing the number of markers used for genotyping, since physically linked markers volition co-segregate on chromosome segments that testify no recombination in a given population. Past utilize of a F9 RILs mapping population we were able to capture a large amount of recombination in our mapping study, greatly increasing the number of individual loci that were able to exist mapped to discrete genetic map positions. On this regard, one great advantage of robust SNP array screening platforms like the Brassica 60 k SNP BeadArray is the low proportion of missing information. Other high-density marker types, similar Diverseness Array Technology (Dart) or sequencing-based restriction site-associated DNA (RAD) markers, can be problematic for accurate genetic mapping because of the large corporeality of missing information normally associated with such methods: Missing data can exist very difficult to distinguish from real polymorphisms and can therefore introduce significant errors into a high-density genetic map. To reduce mapping errors and avert artificial exaggeration of map distances, missing data form must be dealt with using complex imputation analyses [49]. Furthermore, the use of high-throughput screening arrays enables automated assaying of very large numbers of markers in a very brusk fourth dimension (in our instance 52157 SNP loci in 174 genotypes in around 3 days).

At 1832.4 cM the length of the SNP linkage map was somewhat longer than a previous 1589 cM map from a younger generation of the same population which was constructed using SSR, SRAP and AFLP markers [50]. This minor increase in map length is expected due to the huge increase in the number of mapped loci. The length is similar to that of the map reported by Chen et al. [sixteen] for 8827 sequence-derived SNP loci mapped over 1860 cM. Nearly 80 cM of our map was deemed for by 4 gaps of around 20 cM. These may result form of distorted segregation caused by rearrangements among homoeologous chromosomes in one or both of the mapping parents [51]. Interestingly, the marking density and recombination frequency was considerably college in in A genome than the C genome in this population. This may reverberate a frequent implementation of diverse B. rapa (A genome) germplasm in breeding of Chinese rapeseed, which may accept reduced the extent of linkage disequilibrium and higher polymorphism in the A genome of the mapping parents used in this written report. The largest bin, containing 950 SNP markers on chromosome C02, provides an example for a particularly recombination-poor region of the C genome in this cross. Interestingly, a relatively large number of SNP markers from the C genome of B. napus gave no BLAST hit in the B. oleracea database. Such results suggest signficant genome-scale differences between B. napus and its C-genome progenitor B. oleracea.

Almost two decades subsequently the first genetic mapping of seed colour loci in B. napus [22] the responsible genes are even so unclear. The considerably college accuracy for QTL detection enabled by a college map density [13] at present gives us the opportunity to more accurately localise candidate genes and compare different mapping studies via the genome sequence. In a previous written report we fine-mapped the major locus for seed colour and ADL to 1 side of SSR marker KBrH092O19.5_400, still no polymorphic reference markers could exist identified in the nearby chromosome sequence on the other side of the QTL. In the nowadays study the SNP marker SNP21195A09 was identified to the other side of the QTL peak, enabling the QTL to be conspicuously located on the B. rapa genome sequence. Xiao et al. [39] mapped a recessive gene for seed colour on chromosome A09 in B. rapa, however the physical region containing this gene (between nineteen.three and 22.one Mbp) does not correspond to the locus identified in our study. Furthermore, Kebede et al [40] mapped a major seed color QTL in B. rapa on the middle of A09. These contrasting results suggest that different genes on chromosome A09 are involved in seed colour variation in unlike genetic backgrounds in B. rapa and B. napus. A major locus influencing seed colour and ADL content in a genetically diverse wintertime oilseed rape groundwork was as well mapped by Stein et al. [41] on A09. The most closely and consistently linked marker in that report, Ni4D09, is located at 32.89 Mbp in the B. rapa sequence, only 4 kpb from the plasma membrane proton-ATPase Bra039228. This gene is an orthologue of another Arabidopsis TRANSPARENT TESTA gene, AHA10, which is a seed-expressed H+-ATPase pathway, Bra007813, was found inside the QTL confidence interval, Bra007813 is a homolog of FLAVANONE 3-HYDROXYLASE (F3H, also known equally TRANSPARENT TESTA 6) and thus another highly interesting candidate for seed variation. These results indicate that independent mutations in unlike phenylpropanoid genes may cause similar seed coat phenotypes in different genetic backgrounds.

To our knowledge this study is the commencement to report QTL for seed cellulose and hemicellulose content in B. napus. The environmentally consistent QTL on A08, which can reduce the seed cellulose content more than 10%, may be an interesting target for convenance to meliorate oil content. Both cellulose and hemicellulose showed negative correlations with seed oil content in the GH06 × P174 RIL population, demonstrating that reduction of cellulose and hemicellulose tin can improve the seed oil content due to a redirection of photosynthetic assimilates from sugar biosynthesis into seed oil biosynthesis. The two QTL qCelA09 and qHemA09 were found overlapped on A09 with opposite condiment furnishings for cellulose and hemicellulose content, respectively. These ii QTL may represent the same QTL with negative pleiotropic effects. Accurate mapping of this QTL represents a first footstep towards marking development and gene identification for potential improvement of oil content.

Supporting Information

Acknowledgments

The authors thank Martin Frauen and Felix Dreyer, NPZ Lembke KG, for providing seed samples for quality assay from one location in Federal republic of germany.

Author Contributions

Conceived and designed the experiments: RJS JL LL. Performed the experiments: LL CQ Past BW. Analyzed the data: YX YH. Contributed reagents/materials/analysis tools: BW. Wrote the paper: LL RJS.

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Source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0083052

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