Oligosaccharides are carbohydrates composed of three to ten monosaccharides joined via glycosidic linkages. They can be classified as digestible or functional, according to their digestion and absorption by animals. Digestible oligosaccharides like sucrose, lactose, cyclodextrin, and maltose, are readily digested by enzymes in the human gut and provide energy. Functional oligosaccharides, such as stachyose and raffinose, are neither digested nor absorbed in the human stomach and intestine (Kaneko et al., 1995). These functional oligosaccharides are considered to be prebiotics that promote the growth of colonic bifid bacteria and Lactobacillus acidophilus, thereby improving human gut health. 

Oligosaccharides are naturally present in various grains. Wheat (Triticum aestivum L., 2n=42, AABBDD genomes), which is one of the major food crops worldwide, contains a number of oligosaccharides in its grains, including sucrose, maltose, and raffinose. In wheat grains, oligosaccharides are significantly less abundant than starch and protein, and they are complicated quantitative traits. Quantitative trait locus (QTL) analysis has provided an effective approach to dissect complicated traits into component loci to study their relative effects on a specific trait (Doerge, 2002). 

Many QTLs for oligosaccharide content and polysaccharide content have been detected in some crops by using recombinant inbred lines (RILs), double haploid (DH) lines, or other populations, combined with genetic linkage maps. QTL analyses have been used to examine several polysaccharides, for example, barley fructan (Hayes et al., 1993) and β-glucan (Han et al., 1997; Igartua et al., 2000; Han et al., 2004), oat β-glucan (de Koeyer et al., 2004), and soybean oligosaccharides (sucrose, raffinose and stachyose) (Hyeun et al., 2006; Cicek et al., 2006) . 

Although quality traits in wheat have been studied using QTL analyses, such analyses have not been used to examine water-soluble oligosaccharide contents in wheat grains. The objectives of the present study were to identify the QTLs controlling water-soluble oligosaccharides and clarify the relationships among the QTLs using a population of recombinant inbred lines (RIL) derived from two Chinese winter wheat varieties. The results may be used by breeders in marker-assisted selection for crop improvement.

1 Results and Analysis
1.1 Phenotypic variations and correlations between traits
Five types of water-soluble saccharides (glucose, fructose, sucrose, maltose, and raffinose) were detected by high-performance liquid chromatography (HPLC) (Figure 1; Table 1). The two parents, Chuan 35050 and Shannong483, differed significantly in their water-soluble saccharide contents (Table 1). Chuan 35050 had higher sucrose and raffinose contents than Shannong 483, while Shannong483 had higher fructose, glucose, and maltose contents than Chuan 35050. The RIL population showed wide variations in the contents of all water-soluble saccharides. The coefficient of variation (CV) for raffinose, sucrose, glucose, fructose, and maltose content was 48.48%, 42.50%, 36.97%, 35.31%, and 33.09%, respectively.
 

Figure 1 Chromatogram of water-soluble saccharides separated by high performance liquid chromatography (HPLC)

Table 1 Water-soluble saccharide contents of RILs and their parents

Simple correlation coefficients (r) between pairs of water-soluble saccharides are listed inTable 2. The highest simple correlation coefficient was between glucose content and fructose content (0.848). Raffinose content was significantly negatively correlated with glucose content and fructose content. The relationships between the other pairs of water-soluble saccharides were all non- significant at 0.05 and 0.01 levels.
 

1.2 QTL analysis
A total of ten putative QTLs for three water-soluble oligosaccharide contents (sucrose, maltose, and raffinose content) were located on nine chromosomes that assign to chromosome of 1B, 1D, 2B, 2D, 3B, 4A, 5A, 5D, and 6B. The ability of a single QTL to explain phenotypic variance ranged from 6.98% to 38.30% (Table 3; Figure 2). The additive effects for five QTLs were positive, with increasing effects coming from Chuan 35050. The additive effects of the other five QTLs were negative, with increasing effects coming from Shannong 483. The maltose content QTL, qMac-2D-1, showed the highest contribution to phenotypic variation (38.30%). This QTL was a major QTL, and the increasing effect was from Shannong 483.
 

Table 3 Additive QTLs for water-soluble saccharide contents of RILs

Figure 2 Locations of additive QTLs for water-soluble oligosaccharide contents in wheat grains

1.2.1 Sucrose content
Four QTLs for sucrose content were detected on chromosomes 1B, 2B, 3B, and 4A. Their total contribution was 49.30% (Table 3). The effects of qSuc-2B-1 and qSuc-4A-1 on sucrose content were positive, with increasing effects coming from Chuan 35050. The effects of qSuc-1B-1 and qSuc-3B-1 on sucrose content were negative with increasing effects coming from Shannong 483. The contribution of qSuc-1B-1 was 18.09% which was highest among the four QTLs.

1.2.2 Maltose content
Four QTLs for maltose content (total contribution, 79.39%) were also found on chromosomes 1B, 1D, 2D and 5D. The positive effects of qMac-1D-1 and qMac-5D-1 mainly came from Chuan 35050 while the negative effects of qMac-1B-1 and qMac-2D-1 came from Shannong 483. Of these four QTLs, qMac-2D-1 made the greatest contribution (38.30%) to phenotypic variation in maltose content, and qMac-1B-1 and qMac-1D-1 also made significant contributions (19.71% and 14.41%, respectively).

1.2.3 Raffinose content
Two QTLs for raffinose content, qRac-5A-1 and qRac-6B-1, were located on chromosomes 5A and 6B, with a total contribution of 25.65% (Table 3; Figure 2). The effect of qRac-6B-1 was positive with the increasing effect contributed by Chuan 35050. The effect of qRac-5A-1 was negative with the increasing effect contributed by Shannong 483. The contributions of qRac-5A-1 and qRac-6B-1 to phenotypic variations in raffinose contents were 14.32% and 11.33%, respectively.

2 Discussions
QTL analyses have been used to study fructan content in wheat grains (Huynh et al., 2008). However, to our knowledge, there have been no QTL analyses of water-soluble oligosaccharide contents. Using a ChSh population, we detected 10 additive QTLs for sucrose, maltose, and raffinose contents of wheat grains. Single QTLs for sucrose and maltose contents were located on 1B, while the other QTLs were located on different chromosomes. This result indicates that the traits tend to be distributed among all the chromosomes.

We did not detect any QTLs for glucose and fructose contents in this study. This may be because the genetic map used for QTL analyses did not fully cover all of the wheat genomes; that is, there were few markers on some chromosomes, and some individual chromosomes were very short in length (Li et al., 2007). The genetic complexity of these traits may be another reason why it was difficult to detect QTLs for glucose and fructose.

We detected four additive QTLs for sucrose content (total contribution, 49.30%), and four for maltose content (total contribution, 79.39%). Thus, sucrose and maltose content were mainly controlled by additive QTLs. The maltose content QTL qMac-2D-1 showed the highest contribution to phenotypic variation (38.30%). This major QTL showed an increasing effect coming from Shannong 483. Although there were some significant  correlation coefficients (r), e.g., between glucose content and fructose content, between glucose content and raffinose content, and between raffinose content and fructose content, we did not detect co-located QTLs on the corresponding chromosomes. 

Water-soluble oligosaccharides contents in grains are connected with wheat quality traits. As microbial energy sources, sucrose and maltose affect the fermentability of wheat by yeasts. In wheat foods, this can affect quality traits such as the volume, appearance and taste of Chinese steamed bread, and the stickiness of noodles (Liu et al., 2001). In previous studies, QTLs for protein and starch quality traits (Sun et al., 2008), kernel shape and weight traits (Sun et al., 2009), and quality traits of Chinese dry noodles (Zhao et al., 2009) were detected using this population. Moreover, some were co-located in similar chromosome regions to those of the QTLs for water-soluble oligosaccharide contents identified in this study. For example, three QTLs for Zeleny sedimentation volume, mixing tolerance index, and final viscosity were mapped to the Xwmc432a-Xwmc336c region on Chromosome 1D (Sun et al., 2008). This indicated that maltose content in wheat is connected to protein and starch traits. Viscosity of the hot pulp and the final viscosity of rice starch decreased with increasing maltose content; moreover, different maltose concentrations resulted in significantly different effects (Xie et al., 2009).

A QTL for sucrose content (qSuc-3B-1) was located around the locus of Xubc834a on Chromosome 3B, near a previously reported test weight QTL (Sun et al., 2009). Sucrose and starch can be transformed into each other enzymatically, and starch content has a significant impact on test weight (Zhang et al., 2007). Therefore, test weight may be indirectly affected by sucrose content in wheat grains. Furthermore, two QTLs for stickiness and total score of Chinese dry noodles were located in the same region as the QTL for sucrose content on Chromosome 4A (Zhao et al., 2009). These findings indicate that sucrose content may influence stickiness and total score of Chinese dry noodles. In summary, the QTLs for water-soluble oligosaccharide content and quality traits in wheat were compared using the same population. These results can increase our understanding of the effects of water-soluble oligosaccharides on the quality of wheat grains and foods made from them.

3 Materials and Methods
3.1 Materials
The RILs population containing 131 lines used for QTL analysis was derived from ‘Chuan 35050’ × ‘Shannong 483’ (ChSh population, F17 in 2009). Chuan 35050 is a variety with higher sucrose and raffinose contents that has been planted in the west-southern winter wheat region of China. Shannong 483 is a variety with higher maltose content that has been grown in the Huang-huai winter wheat region. Shannong 483 was derived from “Ai-Meng-Niu”, a famous germplasm and backbone parent used extensively in wheat breeding in China. Shannong 483 was released by Shandong Agricultural University in 1980 and led to the development of more than 16 notable varieties that have been planted over 30 million ha.

The 131 RILs and their parents were planted at Heze, China, in 2008. The RILs were planted in a randomized block designed with two replicates. Each six-row plot was 2 m in length, the rows were spaced 26.7 cm apart, and 70 seeds were grown in each row. The RILs were harvested and ground into flour in 2009. 

3.2 Extraction and detection of water-soluble oligosaccharides
Whole wheat flour (0.100 0 g) was accurately weighed before extraction of water-soluble oligosaccharides in 5 mL double-distilled water for 10 h at 4℃. The samples were then subjected to ultrasonic extraction for 30 min and centrifuged at 4 500 r/min for 30 min. Supernatants were filtered with C18-SPE and 0.45-µm filter paper.

Water-soluble saccharide content was determined by high-pressure liquid chromatography (HPLC) with a Waters 515 pump and refractive index detector (Waters 2410, USA) (Zhu and Yang, 2005). Compounds were separated on a 4.6×250 mm Inertsil NH₂ column (Dikma, Japan) with the mobile phase consisting of 25% water and 75% acetonitrile (flow rate, 1 mL/min). The column temperature was 40℃.

3.3 QTL analysis
The water-soluble saccharide content data and the linkage map of the Sh Ch population, which were reported previously (Li et al., 2007), were used for QTL analysis. This map included 381 loci on all the wheat chromosomes, comprising 167 SSR, 94 EST-SSR, 76 ISSR, 26 SRAP, 15 TRAP, and 3 Glu loci, and covering 3636.7 cM with an average distance of 14.8 cM between markers. QTL mapping was conducted using QTLMapper 1.6 based on a mixed-model (Wang et al., 1999). The walking speed chosen for all QTLs was 1.0 cM. Additive effects of detected QTLs were estimated by Bayesian test. A QTL was considered significant at a LOD peak value 2.5 (Zhao et al., 2009).

Authors’ contributions
XYF conceived the overall study, performed the experiment designs, carried out the trait phenotyping, and drafted the manuscript. ZLQ took part to the data analysis and the writing. SSL obtained and analyzed the QTL data and was involved in the writing. All authors read and approved the final manuscript.

Acknowledgements
We thank Shubo Gu (State Key Laboratory of Crop Biology, Agronomy College of Shandong Agriculture University, Tai’an, China) for help and advice on the experiment.

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