CHANG Li-fang, Ll Hui-hui, WU Xiao-yang, LU Yu-qing, ZHANG Jin-peng, YANG Xin-ming, Ll Xiuquan, LlU Wei-hua, Ll Li-hui

National Key Facility for Gene Resources and Genetic Improvement/Key Laboratory of Crop Germplasm Utilization, Ministry of Agriculture/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China

1. lntroduction

Wheat (Triticum aestivumL.) is one of the most important crops affecting the global economy and food security, and most of the world’s wheat is produced by China, which produces >120 million tons per year (National Bureau of Statistics of the Republic of China, http://www.stats.gov.cn/; and Food and Agriculture Organization of the United Nations, FAO, http://www.fao.org/statistics/en/). Since the 1950s, thousands of wheat cultivars have been bred in pedigree selection programs, which have significantly increased the yield and total production of wheat in China.Pedigree analysis indicates that most released cultivars are derived from 16 founder parents (Zhuang 2003). Among these founder parents, Bima 4, Beijing 8 (Liet al. 2012),Nanda 2419 (Jiaet al. 2013), Abbondanza, Funo, Xiaoyan 6,and Youzimai are also widely planted (>667 000 ha) in China(Zhuang 2003). Founder parents have played a crucial role in modern crop breeding for have bred many wheat cultivars, especially widely planted cultivars, and have introduced favorable gene resources, such as the “reduced height genes” (Rhtgenes) from Akakomughi and Norin 10(Gale and Youssefian 1985; Borojevic and Borojcvic 2005a).Pedigree analysis has also been used to identify the founder parents of other crops, including rice (Oryza sativaL.; Tianet al. 2006; Zhouet al. 2012; Zhanget al. 2013), maize(Zea maysL.; Luet al. 2009), soybean (Glycine maxL.Merr.; Lorenzenet al. 1996; Leeet al. 2004), and barley(Hordeum vulgareL.; Russellet al. 2000; Sjaksteet al.2003). Many studies have reported the genetic contribution of founder parents to derivative lines, and important founder parents quantitative trait loci (QTLs) have been identified by molecular markers and pedigree analysis (Pestsova and R?der 2002; Borojevic and Borojcvic 2005b; Maet al. 2007;Hanet al. 2009; Liet al. 2009, 2012; Zhouet al. 2012; Jiaet al. 2013; Xiaoet al. 2014; Wuet al. 2015). However,the basic genetic characteristics of founder parents are still poorly understood.

Mazhamai (M), a local landrace of the Guanzhong District in Shaanxi Province of China, was a major founder parent for wheat breeding in the 1950s. M has ecological adaptability,high tolerance to abiotic stress, and a high number of grain numbers per spike (GNS), but it is susceptible to stripe rust. Biyumai (B), which is highly resistant to stripe rust,was introduced from the United States (Zhuang 2003). In China, six wheat cultivars named BM1–6 are derived from the cross M×B. BM1 has been planted over 6 000 000 ha,but few cultivars have been bred from it. BM4 has been planted over 867 000 ha, and 80 released cultivars have been bred from it, including six widely planted cultivars(> 667 000 ha) and the founder parents Beijing 8 (Zhuang 2003; Liet al. 2012) and Jing 411 (Xiaoet al. 2014).However, the other four sibling lines (BM2, 3, 5, and 6) have not been used extensively for breeding or planting. Because the six BM sibling lines are derived from the same cross but exhibit different performances, they provide an ideal system to analyze the genetic characteristics of founder parents and widely planted cultivars.

The development of the wheat 9K and 90K single nucleotide polymorphism (SNP) wheat assays has allowed the determination of detailed haplotype structure and the genetic basis of trait variation (Cavanaghet al. 2013; Wanget al. 2014). These assays have been widely used to identify genomic regions targeted by breeding and improvement selection, to characterize genetic variation in allohexaploid and allotetraploid populations, and to dissect complex traits by QTL (Wuet al. 2015) and association mapping(Selaet al. 2014; Zankeet al. 2014a, b; Maccaferriet al.2015). In the present study, the wheat 90K SNP assay was used to genotypes BM1–6 and their parents to identify the genomic characteristics of founder parents and widely planted cultivars.

The objectives of the present study were to (1) analyze the phenotypic characteristics of the founder parent BM4 and the widely planted cultivar BM1; (2) analyze the genetic characteristics of BM4 and BM1 by evaluating the genomic similarities and differences of BM1–6. The present study provides theoretical guidance for the selection of parents for wheat and self-pollinating crop breeding.

2. Materials and methods

2.1. Plant materials and field trials

B, M, and BM1–6 were evaluated over three consecutive years from 2007 to 2009 in five major wheat ecological regions in China, including Shijiazhuang in Hebei Province(114.36′E, 37.38′N), Tai’an in Shandong Province(116.02′E, 35.38′N), Yangling in Shaanxi Province(108.82′E, 34.36′N), Chengdu in Sichuan Province(104.06′E, 34.66′N), and Yangzhou in Jiangsu Province(119.4′E, 32.15′N). A randomized complete block design was used at all locations with three replications per site.Each plot consisted of five rows (2 m long and 30 cm wide), and 40 seeds were planted in each row. Ten plants from the center of each plot were harvested for each line to measure eight yield-related traits including plant height(PH), grain number per spike (GNS), thousand-grain weight(TGW), effective tiller number (ETN), spike length (SL),spikelet number per spike (SNS), sterile spikelet number per spike (SS), and heading date (HD). Details about the measurements and timing of measurements are described in Liet al. (2006).

2.2. Statistical analysis

Basic statistics for each trait were calculated for B, M, and BM1–6. Analysis of variance (ANOVA) was used to test the statistical significance of various sources of variation using SAS software (Release 9.1.3; SAS Institute, Cary,NC, USA). Duncan’s new multiple range test (MRT) was used to conduct multiple comparison analysis tests for B,M, and BM1–6 (Duncan 1955).

2.3. SNP genotyping

DNA was extracted from fresh leaf tissue of each individual using a modified cetyltrimethyl ammonium bromide (CTAB)method (Allenet al. 2006). SNP genotyping was performed on purified DNA by Capital Bio Technology of Beijing, using the Illumina iSelect 90K SNP assay (Wanget al. 2014)according to the manufacturer’s protocols (Illumina, USA).SNP allele clustering and genotype calling was performed using GenomeStudio polyploid clustering v1.0 software(Wanget al. 2014).

2.4. SNP data analysis

The Illumina iSelect 90K SNP assay contains 81 587 SNPs in total, and 40 267 of these SNPs were genetically mapped onto the consensus map of 21 wheat chromosomes (Wanget al. 2014). SNPs were filtered by removing monomorphic SNPs and those with a large number of missing values(>10%). Based on the 40 267 mapped SNPs, 8 331 SNPs polymorphic between B and M were used to evaluate the genomic differences of BM1–6.

The proportion of the genome inherited from each parent and the alleles specific to each line were identified by comparing the BM1–6, B and M alleles in Excel. The genetic similarity between B, M, and BM1–6 was evaluated by principal coordinates analysis (PCoA) based on a similarity matrix calculated on the Flapjack platform (downloaded from https://ics.hutton.ac.uk/flapjack/) (Milneet al. 2010).Based on the 90K consensus map (Wanget al. 2014),we constructed a heatmap of BM1–6 where 8 331 SNPs with alleles derived from B and M are shown as different colored blocks (black and white). We were able to visualize the important genomic variation by comparing the colored blocks. For example, in the heatmap, a switch from B to M(i.e., a change in color) indicates a recombination breakpoint in the chromosomal region. We compared the genotypic data of BM1–6, and alleles that differentiated one line from the other five lines were viewed as being specific to that line. Similarly, a chromosomal region (＜20 cM in length)harboring alleles specific to one line was viewed as a region specific to that line. We compared the SNP markers in these genomic regions to the locations of previously identified QTLs. When any SNP in the specific region was within the confidence interval of a QTL, this region was viewed as being specifically associated with the trait of interest.

3. Results

3.1. Comparison of phenotypic characteristics

Combined ANOVA indicated that there was a significant(P＜0.01) difference among B, M, and BM1–6 for five traits(PH, GNS, TGW, SL, and SNS), but not for ETN, SS and HD(Table 1). The variation explained by year was significant for most traits, except for SL and SS, whereas the variation explained by location was significant for all traits except ETN. All interactions between the eight cultivars and three years, and between the eight cultivars and five locations were not significant, indicating that genotypic variation was the primary contributor to the observed phenotypic variation in the eight traits.

Phenotypic variation was observed among the six sibling lines (BM1–6) and their two parents (B and M) (Tables 1 and 2). GNS, TGW, SL, SNS, and HD of the B and M were significantly different (Table 2). M had higher GNS and SNS, and B had higher TGW and SL. Compared with phenotypes observed in the parental lines, transgressive phenotypes were observed in BM1–6, in both directions for PH and in one direction for GNS, TGW, ETN, SNS, SS, and HD. Furthermore, the means of GNS and SNS of BM1–6 were closer to those of M, whereas the means of TGW and SL were closer to those of B, which indicated that all the six cultivars inherited good phenotypic characters from their parents and were superior to the parents.

Among the six sibling lines, BM1 had the highest TGW and SL, whereas BM4 had the most ETN, shortest SL,and minimum SS (Table 2). Compared with the other four cultivars (BM2, 3, 5, and 6), BM4 and BM1 had higher TGW and shorter HD. Although there were no significant differences in the yield components (TGW, GNS, and ETN)between BM1 and BM4, BM4 had fewer SS, shorter PH,

Table 1 Analysis of variance (ANOVA) for eight yield-related traits in the six sibling lines (BM1–6) and their parents (Mazhamai (M)and Biyumai (B)) across five locations (Shijiazhuang, Tai’an, Yangling, Chengdu, and Yangzhou) and three years (2007–2009)1)

Table 2 Descriptive statistics for eight traits measured for BM1–6 and their parents (Mazhamai (M) and Biyumai (B)) across five locations (Shijiazhuang, Tai’an, Yangling, Chengdu, and Yangzhou) and three years (2007–2009)

(Continued on next page)and lower CV than BM1 for most traits across years and locations, which indicated that BM4 is more adaptable to various ecological zones (Table 2). BM2 had the lowest TGW (26.16 g) and the most SS (2.52); BM3 had the minimum GNS and the longest HD; and BM5 and 6 showed higher PH than the other four lines (Table 2). These negative characteristics partially explain why these lines have not been widely planted or used as founder parents in wheat breeding.

Table 2 (Continued from preceding page)

3.2. Comparison of genotypic characteristics

To determine the genetic variation of BM1–6, the proportion of the genome inherited from the parents B and M and similarity of the lines were evaluated by genotyping 8 331 polymorphic SNPs that effectively represent the genetic variation across the consensus map (Wanget al. 2014)(Appendix A). Except for BM3, five sibling lines inherited more than 55% of alleles from M (Fig. 1). BM3 inherited 45% of alleles from M and 55% from B, a proportion that is significantly different (P＜0.05) from the other lines. PCoA analysis was performed to evaluate the genetic similarity of eight cultivars. B and M were clearly separated from BM1–6 and each other. BM1–6 could be separated into four groups:BM2, 3, 1, and BM4, 5, and 6 (Fig. 2). Overall, the genetic compositions of BM4 and 1 are similar to each other but dissimilar to those of BM2, 3, 5, and 6.

Using a heatmap constructed from the 8 331 SNPs, we detected the recombination events on each chromosome and found that the numbers and locations of recombination breakpoints in the six lines were diverse, with 32, 45, 40, 40,39, and 37 recombination breakpoints identified for BM1–6,respectively (Table 3 and Fig. 3). Compared with BM1, there were more recombination breakpoints in BM4, especially on the A genome (Table 3). For BM1, no recombination events were identified on chromosomes 3A, 7A, 1B, and 6B,whereas for BM4, no recombination events were identified on chromosomes 4A and 4B. The maximum number of crossovers in BM1 (n=3) was observed on chromosomes 2A, 3B, 4B, and 5D, whereas in BM4, five crossovers were observed on chromosome 3B, and no fewer than three were observed on chromosomes 1A, 3A, 3B, 5B, and 6D (Table 3).

Fig. 1 Proportion of the BM1–6 genomes inherited from the Biyumai (B) and Mazhamai (M) parents based on 8 331 single nucleotide polymorphisms (SNPs). ＊, the proportion of BM3 inherited from B and M is significantly different from other lines at P＜0.05.

Fig. 2 Principal coordinate analysis (PCoA) based on a similarity matrix showing the genetic similarities between BM1–6(six sibling lines). B, Biyumai; M, Mazhamai.

By comparing the genotypes datasets of BM1–6, we identified alleles specific to each line that differentiate each line from the other five lines, and the number and distribution of these specific alleles differed between the six lines(Table 4 and Fig. 4). BM4 has 724 specific alleles that are mainly distributed on the homoeologous groups 5, 6, and 7, whereas BM1 has 409 specific alleles that are mainly distributed on the homoeologous groups 6 and 7 (Table 4 and Fig. 4). Of the 291 specific alleles shared by BM1 and BM4 but not found in the other four sibling lines, 244 and 47 were inherited from M and B, respectively (Table 4).Although the number of BM3-specific alleles was similar to the number of BM4-specific alleles, most of these alleles were inherited from B and are distributed on homoeologous groups 3 and 4 (Table 4 and Fig. 4).

Most of the specific alleles were concentrated on special chromosomal regions that were inherited as haplotypes from parents. For example, the region near 60 cM on chromosome 1A for BM4 was inherited from B (Fig. 3, black and white), whereas the same region was inherited from M in all the other lines (Fig. 3, black block). In total, the 676 BM4-specific alleles make up 13 specific regions on 11 chromosomes (1A, 1D, 3A, 3B, 4B, 5A, 5B, 6A, 6B, 6D, and 7B; Tables 4 and 5), and the 360 BM1-specific alleles make up 11 specific regions on 7 chromosomes (1B, 2A, 3D, 4B,5B, 6A, and 7A; Tables 4 and 5). In addition, 236 of the 291 alleles specific to BM1 and BM4 form 10 genomic regions.Overall, the number and distribution of the specific alleles and regions in the six sibling lines were different from each other, and BM4 had more specific alleles and chromosomal regions than BM1, 2, 5, and 6.

Table 3 Distribution of breakpoints for the BM1–6 (six sibling lines) across 21 chromosomes and genomes

4. Discussion

Increasing yield potential is a major goal of most crop breeding programs (Zhuang 2003; Reynoldset al. 2009). Thus, lines with favorable yield components have been preferentially selected as parents or elite cultivars. Furthermore, according to the rules for parents select in breeding, it is widely agreed that the parents of a cross should mostly have superior and complementary phenotypes and not have obvious flaws(Zhuang 2003). In present study, the founder parent BM4 and the widely planted cultivar BM1 were selected from tens of thousands of progeny derived from the cross M×B due to their enhanced phenotypic performance, especially higher TGW and shorter PH (Table 2). Compared with BM1, BM4 had shorter PH, fewer SS, and lower CV for most yieldrelated traits across years and locations (Table 2). This indicates that better comprehensive performance could be an important characteristic of founder parents, as reported for the founder parent Beijing 8 (Liet al. 2012) and Nanda 2419 (Jiaet al. 2013).

In the present study, the genomic characteristics of the six sibling lines were investigated using the wheat 90K SNP assay. BM1 and BM4 inherited similar proportions of genetic components from their parents but are dissimilar to BM2, 3,5, and 6 (Figs. 1 and 2). Compared with BM1, BM4 has more specific alleles, chromosomal regions and recombination breakpoints (Table 3), which indicates that BM4 has more genetic diversity than BM1. Similarly, based on 481 SSR loci, Geet al. (2009) found that the founder parents BM4 and St2422-464 contain more favorable alleles and more diversity than their sister lines, the widely planted cultivars BM1 and St1472-506, respectively.

All 1 424 BM1- and BM4-specific alleles (409 specific to BM1, 724 specific to BM4, and 291 specific to BM1 and BM4) are distributed across 18 chromosomes and comprise 34 genomic regions. These regions might be critical for breeding a founder parent or widely planted cultivar. To better understand the functions of these specific regions,we searched for QTLs from a recombinant inbred line (RIL)population derived from M and B (unpublished results;Table 5) and from the literature that are associated with these regions (Zankeet al. 2014a, b; Zegeyeet al. 2014;Kerthoet al. 2015; Lopeset al. 2015; Naruokaet al. 2015;Sukumaranet al. 2015; Wuet al. 2015). Seven of the 11 BM1-specific regions are associated with QTLs for TGW,PH, ETN, SL, SNS, GNS, HD, and stripe rust (Yr) or leaf rust (Lr) (Table 5). Four pleiotropic regions, BM1.R1, BM1.R5, BM1.R7, and BM1.R11, harbor QTL2, QTL23, QTL29,and QTL33, respectively (Table 5). The favorable alleles of QTL2 and QTL33 that increase TGW and PH are derived from M and B, respectively. BM1.R1 and BM1.R11 harbor both of these alleles, which is consistent with the relatively high TGW and PH of BM1 (Tables 2 and 5). Nine of the 13 BM4-specific regions are associated with QTLs for yield-related traits (GNS, ETN, SNS, PH, and SL) and for yellow rust and leaf rust (Table 5). BM4 harbors alleles that increase GNS on BM4.R8, BM4.R9, and BM4.R10, and alleles that decrease PH on BM4.R11 and BM4.R1, which is consistent with the relatively short PH of BM4 (Table 2).Three BM4-specific regions (BM4.R8, BM4.R10, and BM4.R13) are associated with HD, which may explain the broad adaptability of BM4 (Tables 2 and 5). In addition, 8 of 10 specific regions that are common to BM1 and BM4 but not found in the other four sibling lines are associated with yield components and harbor favorable alleles that could increase TGW and ETN, which might explain the higher TGW of BM1 and BM4 compared with the other lines. The association of pleiotropic regions with favorable QTLs could explain why BM1 is a widely planted cultivar and BM4 is a founder parent.

As reported in several studies, alleles or genomic regions specific to founder parents can harbor QTLs or genes for important traits, and those alleles or regions are transmitted to the progeny (Leeet al. 2004; Borojevic and Borojcvic 2005b; Liet al. 2012; Zhouet al. 2012; Jiaet al. 2013; Xiaoet al. 2014). In the present study, 9 of 13 BM4-specific regions were found to be associated with QTLs for multiple traits of interest. In future work, we will detect variation in these regions in BM4 derivative lines to assess the genetic contributions of the founder parent to the performance of progeny and the potential value of these regions for further improvement in breeding.

Fig. 3 Genotypic map of BM1–6 based on 8 331 single nucleotide polymorphisms (SNPs). White block indicate alleles inherited from Biyumai (B), black block indicates allele inherited from Mazhamai (M).

Table 4 Number and origin of alleles and genomic regions specific to BM1–6

Fig. 4 Distribution of genomic alleles specific to six sibling lines (BM1–6) on the seven wheat homoeologous groups.

(Continued on next page)

Table 5 (Continued from preceding page)

5. Conclusion

Phenotypic and genomic comparisons indicated that both the widely planted cultivar BM1 and the founder parent BM4 were superior to other sibling lines based on performance and have specific alleles and regions that differ from these other lines and are found to associate with favorable QTLs. Furthermore, BM4 has more genetic diversity than BM1 based on the number of specific alleles, regions and recombination breakpoints. Our work illustrates that the combination of phenotypic and SNP genotyping analyses is useful for revealing the genomic characteristics speicifc to and shared by elite common wheat lines derived from the parents, though the resolution needs to be improved through using a higher number of polymorphic SNPs or by performing additional complementary experiments.

Acknowledgements

This work was supported by grants from the National Basic Research Program of China (973 Program, 2011CB100104)and the National Natural Science Foundation of China(31471174).

Appendixassociated with this paper can be available on http://www.ChinaAgriSci.com/V2/En/appendix.htm

Allen G, Flores-Vergara M, Krasynanski S, Kumar S, Thompson W. 2006. A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide.Nature Protocols, 1, 2320–2325.

Borojevic K, Borojcvic K. 2005a. Historic role of wheat variety Akakomughi in Southern and Central European wheat breeding programs.Breed Science, 55, 253–256.

Borojevic K, Borojcvic K. 2005b. The transfer and history of “reduced height genes” (Rht) in wheat from Japan to Europe.Journal of Heredity, 96, 455–459.

Cavanagh C R, Chao S, Wang S, Huang B E, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira G L, Akhunova A, See D, Bai G, Pumphrey M, Tomar L, Wong D, Kong S,Reynolds M, da Silva M L, Bockelman H, Talbert L,et al.2013. Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars.Proceedings of the National Academy of Sciences of the United States of America, 110,8057–8062.

Duncan D B. 1955. Multiple range and multipleFtest.Biometrics, 11, 1–42.

Gale M D, Youssefian S. 1985. Dwarfing genes in wheat.In: Russell G E, ed.,Progress in Plant Breeding. 1st ed.Butterworths, London. pp. 1–35.

Ge H, Wang L, You G, Hao C, Dong Y, Zhang X. 2009.Fundamental roles of cornerstone breeding lines in wheat reflected by SSR random scanning.Scientia Agricultura Sinica, 42, 1503–1511. (in Chinese)

Han J, Zhang L, Li J, Shi L, Xie C, You M, Yang Z, Liu G, Sun Q, Liu Z. 2009. Molecular dissection of core parental cross‘Triumph/Yanda 1817’ and its derivatives in wheat breeding program.Acta Agronomica Sinica, 35, 1395–1404. (in Chinese)

Jia H, Wan H, Yang S, Zhang Z, Kong Z, Xue S, Zhang L,Ma Z. 2013. Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding.Theoretical and Applied Genetics, 126, 2123–2139.

Kertho A, Mamidi S, Bonman J M, McClean P E, Acevedo M.2015. Genome-wide association mapping for resistance to leaf and stripe rust in winter-habit hexaploid wheat landraces.PLoS ONE, 10, e0129580.

Lee G, Boerma H, Villagarcia M, Zhou X, Carter T, Li Z, Gibbs M. 2004. A major QTL conditioning salt tolerance in S-100 soybean and descendent cultivars.Theoretical and Applied Genetics, 109, 1610–1619.

Li L, Li X. 2006.The Descriptors and Data Standard for Wheat.China Agricultural Press, Beijing. (in Chinese)

Li X, Xu X, Liu W, Li X, Li L. 2009. Genetic diversity of the founder parent orofen and its progenies revealed by SSR markers.Scientia Agricultura Sinica, 42, 3397–3404. (in Chinese)

Li X, Xu X, Yang X, Li X, Liu W, Gao A, Li L. 2012. Genetic diversity among a founder parent and widely grown wheat cultivars derived from the same origin based on morphological traits and microsatellite markers.Crop and Pasture Science, 63, 303–310.

Lopes M, Dreisigacker S, Pena R, Sukumaran S, Reynolds M.2015. Genetic characterization of the wheat association mapping initiative (WAMI) panel for dissection of complex traits in spring wheat.Theoretical and Applied Genetics,128, 453–464.

Lorenzen L, Lin S, Shoemaker R. 1996. Soybean pedigree analysis using map-based molecular markers:Recombination during cultivar development.Theoretical and Applied Genetics, 93, 1251–1260.

Lu Y L, Yan J B, Guimar?es C T, Taba S, Hao Z F, Gao S B,Chen S J, Li J S, Zhang S H, Vivek B S, Magorokosho C,Mugo S, Makumbi D, Parentoni S N, Shah T, Rong T Z,Crouch J H, Xu Y B. 2009. Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms.Theoretical and Applied Genetics, 120, 93–115.

Ma Z, Zhao D, Zhang C, Zhang Z, Xue S, Lin F, Kong Z, Tian D,Luo Q. 2007. Molecular genetic analysis of five spike-related traits in wheat using RIL and immortalized F2populations.Molecular Genetics and Genomics, 277, 31–42.

Maccaferri M, Zhang J, Bulli P, Abate Z, Chao S, Cantu D,Bossolini E, Chen X, Pumphrey M, Dubcovsky J. 2015. A genome-wide association study of resistance to stripe rust(Puccinia striiformisf. sp.tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivumL.).G3(Bethesda), 5, 449–465.

Milne I, Shaw P, Stephen G, Bayer M, Cardle L, Thomas W T B,Flavell A J, Marshall D. 2010. Flapjack-graphical genotype visualization.Bioinformatics, 26, 3133–3134.

Naruoka Y, Garland-Campbell K A, Carter A H. 2015. Genomewide association mapping for stripe rust (Puccinia striiformisF. sp.tritici) in US Pacific Northwest winter wheat (Triticum aestivumL.).Theoretical and Applied Genetics, 128,1083–1101.

Pestsova E, R?der M. 2002. Microsatellite analysis of wheat chromosome 2D allows the reconstruction of chromosomal inheritance in pedigrees of breeding programmes.Theoretical and Applied Genetics, 106, 84–91.

Reynolds M, Foulkes M, Slafer G, Berry P, Parry M, Snape J,Angus W. 2009. Raising yield potential in wheat.Journal of Experimental Botany, 60, 1899–1918.

Russell J, Ellis R, Thomas W, Waugh R, Provan J, Booth A, Fuller J, Lawrence P, Young G, Powell W. 2000.A retrospective analysis of spring barley germplasm development from ‘foundation genotypes’ to currently successful cultivars.Molecular Breeding, 6, 553–568.

SAS Institute, SAS 9.1.3. 2000–2004.Help and Documentation,SAS Institute, Cary, NC.

Sela H, Ezrati S, Ben-Yehuda P, Manisterski J, Akhunov E,Dvorak J, Breiman A, Korol A. 2014. Linkage disequilibrium and association analysis of stripe rust resistance in wild emmer wheat (Triticum turgidumssp.Dicoccoides)population in Israel.Theoretical and Applied Genetics,127, 2453–2463.

Sjakste TG, Rashal I, R?der M S. 2003. Inheritance of microsatellite alleles in pedigrees of Latvian barley varieties and related European ancestors.Theoretical and Applied Genetics, 106, 539–549.

Sukumaran S, Dreisigacker S, Lopes M, Chavez P, Reynolds M. 2015. Genome-wide association study for grain yield and related traits in an elite spring wheat population grown in temperate irrigated environments.Theoretical and Applied Genetics, 128, 353–363.

Tian F, Zhu Z, Zhang B, Tan L, Fu Y, Wang X, Sun C. 2006. Fine mapping of a quantitative trait locus for grain number per panicle from wild rice (Oryza rufipogonGriff.).Theoretical and Applied Genetics, 113, 619–629.

Wang S, Wong D, Forrest K, Allen A, Chao S, Huang B E,Maccaferri M, Salvi S, Milner S G, Cattivelli L, Mastrangelo A M, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, International Wheat Genome Sequencing C, Lillemo M, Mather D, Appels R,et al. 2014. Characterization of polyploidy wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array.Plant Biotechnology Journal, 12, 787–796.

Wu Q, Chen Y, Zhou S, Fu L, Chen J, Xiao Y, Zhang D, Ouyang S, Zhao X, Cui Y, Zhang D, Liang Y, Wang Z, Xie J, Qin J,Wang G, Li D, Huang Y L, Yu M, Lu P,et al. 2015. High-density genetic linkage map construction and QTL mapping of grain shape and size in the wheat population Yanda 1817×Beinong 6.PLoS ONE, 10, e0118144.

Xiao Y, Lu Y, Wen W, Chen X, Xia X, Wang D, Li S, Tong Y,He Z. 2014. Genetic contribution of seedling root traits among elite wheat parent Jing 411 to its derivatives.Scientia Agricultura Sinica, 47, 2916–2926. (in Chinese)

Zanke C, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V,Argillier O, Stiewe G, Hinze M, Beier S, Ganal M W, R?der M S. 2014a. Genetic architecture of main effect QTL for heading date in European winter wheat.Frontiers in Plant Science, 5, 1–12.

Zanke C, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V,Argillier O, Stiewe G, Hinze M, Neumann K, Ganal M W,R?der M S. 2014b. Whole genome association mapping of Plant height in winter wheat (Triticum aestivumL.).PLoSONE, 9, e113287.

Zegeye H, Rasheed A, Makdis F, Badebo A, Ogbonnaya F C.2014. Genome-wide association mapping for seeding and adult plant resistance to stripe rust in synthetic hexaploid wheat.PLoS ONE, 8, e105593.

Zhang H, Wang H, Qian Y, Xia J, Li Z, Shi Y, Zhu L, Ali J, Gao Y, Li Z. 2013. Simultaneous improvement and genetic dissection of grain yield and its related traits in a backbone parent of hybrid rice (Oryza sativaL.) using selective introgression.Molecular Breeding, 31, 181–194.

Zhou J, Zhang Y, Lü H, You A, Zhu L, He G. 2012. Transmission of important chromosomal regions under selection revealed in rice pedigree breeding programs.Molecular Breeding,30, 717–729.

Zhuang Q. 2003.Chinese Wheat Improvement and Pedigree Analysis. China Agricultural Press, Beijing. (in Chinese)