Genome-wide association mapping revealed syntenic loci QFhb-4AL and QFhb-5DL for Fusarium head blight resistance in common wheat (Triticum aestivum L.)

doi:10.21203/rs.2.12667/v1

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Genome-wide association mapping revealed syntenic loci QFhb-4AL and QFhb-5DL for Fusarium head blight resistance in common wheat (Triticum aestivum L.)

https://doi.org/10.21203/rs.2.12667/v1

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Background:Fusarium head blight (FHB), primarily caused by Fusarium graminearum, is a major threat to wheat production and food security worldwide. Breeding stably and durably resistant cultivars is the most effective approach for managing and controlling the disease. The success of FHB resistance breeding relies on identification of an effective resistant germplasm. We performed a genome-wide association study (GWAS) using the high-density wheat 90K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of FHB resistance in natural population and identify associated molecular markers. Results:The resistance to FHB fungal spread along the rachis (Type II resistance) was evaluated on 171 wheat cultivars in the 2016-2017 and 2017-2018 growing seasons. Using Illumina Infinum iSelect 90K SNP genotyping data, a genome-wide association study (GWAS) identified 26 loci(88 marker-trait associations), which explained 6.65-14.18% of the phenotypic variances. The associated loci distributed across all chromosomes except 2D, 6A, 6D and 7D, with those on chromosomes 1B, 4A, 5D and 7A being detected in both years. New loci for Type II resistance were found on syntenic genomic regions of chromsome 4AL (QFhb-4AL, 621.85 - 622.24 Mb) and chromosome 5DL (QFhb-5DL, 546.09 - 547.27 Mb) which showed highly collinarity in gene content and order. SNP markers wsnp_JD_c4438_5568170 and wsnp_CAP11_c209_198467 of 5D, reported previously linked to a soil-borne wheat mosaic virus (SBWMV) resistance gene, were also associated with FHB resistance in this study. Conclusion:The syntenic FHB resistant loci and associated SNP markers identified in this study are valuable for FHB resistance breeding via marker-assisted selection.

Plant Physiology and Morphology

Plant Molecular Biology and Genetics

Triticum aestivum L.

Fusarium head blight (FHB)

Mixed linear model (MLM)

Genome-wide association study (GWAS)

Single nucleotide polymorphism (SNP)

Common wheat (Triticum aestivum L.) is one of the most important cereals in the world and is the raw material for breads, biscuits, noodles and cakes [1]. Fusarium head blight (FHB), caused by Fusarium graminearum, is one of the most destructive fungal diseases in wheat, which spreads considerably due to farming practices and climate changes [2]. FHB does not only reduce grain yield and quality but also leads to infected kernels with excessive deoxynivalenol (DON), resulting in severe harm to human and animal health [3]. China is the largest country for wheat production and consumption and has regular FHB epidemics, especially in the Middle and Lower Reaches of the Yangtze River with its warm, humid environment. In recent years, FHB has become more serious in the major wheat production area of the Yellow and Huai River Valleys [4].

The most effective way for wheat producers to manage and control FHB is by breeding resistant cultivars. Great efforts have been made to find FHB resistance genes and understand the genetic mechanism of the resistance [5-9]. The genetic mechanisms for FHB resistance are complex, and the genotype by environment interaction has very strong effects on trait expression [10, 11]. Resistance to F. graminearum in wheat has been classified into five categories: (1) type I for resistance to initial infection by the pathogen, (2) type II for resistance to fungal spread along the rachis, (3) type III for resistance to kernel infection, (4) type IV for resistance to toxin accumulation, and (5) type V for tolerance [12, 13]. Many quantitative trait loci (QTL) have been identified for multiple types of FHB resistance in wheat with different magnitudes of effects [14-17]. Major and stable QTL often have large effects in multiple environments and are more valuable for practical breeding than minor QTL. However, major and stable QTL are rare for FHB resistance. Fhb1, identified from Chinese wheat Wangshuibai and Sumai 3 and located on chromosome 3BS, is the best characterized FHB resistance locus with major effect and stable resistance. Fhb1 was reported as a pore-forming toxin-like gene (PFT) QTL [18]. However, recent studies revealed an histidine-rich calcium-binding protein (His) was responsible for the Fhb1 resistance [19, 20]. In addition, Fhb1 has shown linkage with poor agronomic traits and single resistance gene has been proven to be a major limitation for FHB resistance breeding as it may not provide sufficient protection under severe FHB epidemics [15, 21, 22]. A combination of Fhb1 with other QTL could be crucial for breeding new varieties with better resistance to FHB [4]. Therefore, discovering more FHB-resistant germplasms and new FHB-resistant loci is essential for breeding wheat varieties with better FHB resistance.

Genome-wide association studies (GWAS), based on linkage disequilibrium (LD) between a marker and the causal polymorphism, provide a higher resolution than linkage mapping because it accounts for greater allelic diversity at a given locus and exploits the ancestral recombination events that have occurred in a group of unrelated individuals [15]. GWAS has been used to discover various quantitative traits associated nucleotide polymorphisms in plants. For example, using a panel of 192 bread wheat cultivars from southwest China, 57, 27, 30, and 34 single nucleotide polymorphism (SNP) were identified for associations with plant height (PH), grain protein content (GPC), thousand kernel weight (TKW) and sodium dodecyl sulfate (SDS) content, respectively [23]. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, and 78 were potentially new in a diverse panel of 166 varieties with the wheat 90 K and 660 K SNP arrays [24].The recently released reference genome sequence of Chinese Spring [25] provides an excellent platform for identifying genes linked to significant markers with known physical positions in the genome and accelerating the molecular breeding process [26].

In the present study, we report a GWAS analysis of FHB resistance using a panel of 171 common wheat cultivars with 90K SNP genotyping and two year’s phenotyping data. The aims of the present study were to identify stable loci for FHB resistance using GWAS and better understand the genetic basis of FHB resistance in natural population.

Plant materials

An association panel comprising 171 wheat cultivars was used for SNP genotyping and two years FHB resistance phenotyping. Among them, three cultivars were derived from Italy, Mexico and Japan, and the other 168 cultivars were collected from 8 provinces at winter wheat region in Northern China and 9 provinces from Southern China (Table S1). The population was planted at Wanfu Experimental Station, Institute of Agricultural Sciences of the Lixiahe, Yangzhou, Jiangsu Province, China (altitude 8 m, latitude 32.24°N, annual rainfall about 1000 mm, growing season from early November to the next May) in growing seasons 2016–2017 (17YZ) and 2017–2018 (18YZ). Field experiments were designed as randomized complete blocks with two replicates per environment. The cultivars in each replication were sown in two rows of 133×25 cm with 40 seeds per row. The field trials were managed following local practices.

Phenotyping

All cultivars were inoculated with four F. graminearum strains (F4, F15, F34, and F0609), kindly provided by Prof. Huaigu Chen from Jiangsu Academy of Agricultural Sciences, Nanjing, China. Ten spikes per row were inoculated at the late-heading stage by injecting 10 µL of macroconidial suspension (1.0 × 10⁵ conidia/ml) into a single floret in the middle of each spike. After inoculation, the disease nursery was mist-irrigated for five min every 30 min from 7:00 am to 6:00 pm each day to provide high humid conditions favorable for FHB infection [27]. FHB severities were recorded 25 days after inoculation as the number of symptomatic spikelets per infected spike, and the mean value was used for further analysis. The percentage of symptomatic spikelets (PSS) was calculated as the measure of FHB severity. All tested accessions were classified into four classes based on FHB severity, resistant (0 < PSS ≤25%), moderately resistant (25% < PSS ≤50%), moderately susceptible (50% < PSS ≤75%) and susceptible (75% < PSS ≤ 100%) [28].

Genotyping and SNP calling

Genomic DNA was extracted from fresh leaves of seedlings using the CTAB method [29]. The association mapping population was genotyped from the wheat Illumina 90K iSelect array with 81,587 SNPs (Wang et al. 2014) at the Biotechnology Center, Department of Plant Sciences, University of California, USA, using the Illumina SNP genotyping platform and BeadArray Microbead Chip [30]. To avoid spurious marker-trait associations (MTAs), SNP markers with minor allele frequencies (MAF) < 0.05 and missing data >10% were excluded from subsequent analyses. The physical positions of SNP markers were obtained from Chinese Spring reference genome sequences at the International Wheat Genome Sequencing Consortium website (IWGSC, http://www.wheatgenome.org/).

Population structure analysis

Population structure was estimated using Structure 2.3.4 with 1,676 polymorphic SNP markers distributing on all 21 wheat chromosomes with r² < 0.2, based on the Bayesian cluster analysis [31]. Six runs of Structure were performed with a K between 1 and 11, using the admixture model with 100,000 replicates each for burn-in and MCMC. The optimal K-value was determined using the ∆K method [32].

Linkage disequilibrium

Linkage disequilibrium among markers was calculated using the full matrix and sliding window options in Tassel v5.0 with the filtered SNP markers. Pairwise LD was confirmed through measuring squared allele frequency correlations r², and the significance of pairwise LD (P-values) was measured in Tassel v5.0 with 1000 permutations. The r² values were plotted against physical distance and a LOESS curve was fitted to the plot to show the association between LD decay and physical map distance. The critical value of r² beyond which the LD was possible due to genetic linkage was determined by taking the 95th percentile in the distribution of r² of the selected loci. The intersection of the right curve of r² values with this threshold was considered as an estimate of the LD range [33]. The distribution of the unlinked r² was used to define the critical value of r².

GWAS for FHB resistance

Associations between genotypic and phenotypic data were analyzed using the kinship matrix in a Mixed Linear Model (MLM) by Tassel v5.0 to control background variation and eliminate spurious MTAs. In the MLM analysis, the kinship matrix (K matrix) was considered a random effect factor, whereas the subpopulation data (Q matrix) was considered a fixed-effect factor [34]. The K matrix was calculated in the software Tassel v5.0, and the Q matrix was inferred in Structure v2.3.4. The P-value determining whether a SNP marker was associated with the trait and the R² indicating the variation explained by the marker were recorded [35]. Markers with an adjusted -log₁₀ (P-value) ≥3.0 were regarded as significant for FHB resistance. Significant SNP markers within one LD on the same chromosome were considered to represent one locus. Haplotype analyses of the significant SNPs were performed with Haploview v.4.2 [36].

Identification of candidate genes

To identify the candidate genes linked to significant SNPs, the physical positions of the markers preceded by the chromosome name were taken to Ensembl, and the genes in the same genetic positions were considered. The intervals were then explored for predicted genes and annotations. For genes that are unavailable from the IWGSC annotations, we evaluated orthologous genes (proteins) in related species with known predicted functions using the comparative genomics tool in Ensembl. The closest species, Triticum urartu (A-genome donor) and Aegilops tauschii (D-genome donor) were first considered, followed by more distant species including barley (Hordeum vulgare), Brachypodium (Brachypodium distachyon), rice (Oryza sativa), maize (Zea mays), foxtail millet (Setaria italica), thale cress (Arabidopsis thaliana) and banana (Musa acuminata). In some cases, when the genes had a less similar ortholog (< 70%) in the annotated genomes of related species in Ensembl, the sequence of the T. aestivum gene was taken to National Center for Biotechnology Information (NCBI) and basic local alignment search tool (BLAST) (http://blast.ncbi.nlm.nih.gov/Blast.cgi) search was performed to find highly similar sequences (megablast). This search also included gene predictions in different species available in GenBank, but not in Ensembl. We also looked at the T. aestivum gene transcripts and their domains that were available in Ensembl (using the transcript table link).

Phenotypic variation

Continuous variation for percentage of symptomatic spikelets (PSS) was observed at the GWAS panel in both 2016-2017 and 2017-2018 growing seasons, from highly resistant (PSS<25%) to highly susceptible (PSS>75%). The disease symptom was more severe in 2017-2018 growing season (Fig. 1a). Wheat cultivars from different provinces of China exhibited different levels of resistance to FHB（Fig. 1b). Cultivars from Hunan and Jiangsu provinces exhibited consistently highly resistant to FHB in two seasons, whereas cultivars from Shandong province showed the highest susceptibility.

Population structure analysis

To estimate the sub-populations of the 171 wheat cultivars, population structure analysis was performed using 1,676 polymorphic SNP markers distributing on 21 wheat chromosomes with r² values >0.2. The results indicated that the cultivars could be separated into two sub-populations (K=2) (Fig. 2a,2b). Subgroup 1 consists of 99 cultivars, mainly comprising varieties from Anhui, Jiangsu, Henan, Shaanxi and Hunan; subgroup 2 consists 72 cultivars (Table S1), most of which were from Henan, Jiangsu, Shandong, Shanxi. Wheat cultivars from Anhui and Hunan were all clustered into subgroup 1.

Linkage disequilibrium (LD) analysis

The filtered markers from the 90K SNP arrays were used to evaluate LD decay for the whole genome as well as the A, B, and D sub-genomes separately. Around 38.9% of all pairs of loci had significant LD (P < 0.001) with an average r² of 0.281 on a genome-wide level from 23,556 polymorphic SNPs. The B sub-genome contained the highest percentage of significant markers (50.0%), followed by A (39.7%) and D (24.0%) sub-genomes. The highest LD decay distance was observed in the D sub-genome and the lowest was found in the B sub-genome. The average LD decay distance was ~10.5 Mb for the whole genome and 10, 9.5, and 12 Mb for A, B, and D sub-genomes, respectively (Fig. 2c).

Marker-trait associations

Association analysis was conducted using PSS data across two years and 23,556 filtered markers. Altogether, 26 loci (88 MTAs, P < 10⁻³) with phenotypic variances explained (R²) ranging from 6.64–14.18% were identified across all of the chromosomes except for 2D, 6A, 6D and 7D (Fig. 3a, 3b). Among these, 41, 32 and 15 significant markers were located on the A, D and B sub-genomes, respectively (Fig. 3c; Table S2). More FHB MTAs were found on chromosomes 1A, 1D, 1B, 2A, 3B, 4A and 5D.

Twenty-eight MTAs located on chromosomes 1B, 4A (7), 5D (19) and 7A were consistently identified in both seasons and could be considered as stable QTL ( Table 1 ), SNP GENE-0293_154 located on 1B explained 6.91–7.18% of phenotypic variances (R²). Seven and 19 SNPs located on 4AL and 5DL chromosomes explained phenotypic variances (R²) ranging from 9.36–11.63% and 8.11–14.18%, respectively. The SNP BobWhite_c22875_239 located on 7A could explain 8.12–8.53% of phenotypic variances (R²).

Due to the high level of LD in wheat, the SNP clusters identified on chromosomes 4AL (QFhb-4AL) from 621.85 to 622.24 Mb and 5DL (QFhb-5DL) from 546.09 to 547.27 Mb most likely represented chromosome regions containing significant FHB associated loci, respectively. Haplotype analyses of the associated markers revealed three haplotype groups (Fig. 4a), Haplotype 1 consists of 149 cultivars with an average PSS of 48.92% over two years, whereas 24 were resistant, 55 were moderately resistant, and 70 were susceptible. Haplotype 2 consists of 19 cultivars with an average PSS of 19.94% over two years, and 12 were resistant and 7 were moderately resistant. Haplotype 3 comprises three resistant cultivars with an average PSS of 11.52%. The results indicated that other resistant genes also existed in the cultivars of Haplotype 1 (Table 2, S3). Interestingly, each haplotype contains wheat cultivars with same associated SNPs on both QFhb-4AL and QFhb-5DL simultaneously (Fig. 4b).

FHB resistance loci identified by GWAS

QTL for Fusarium head blight resistance have been extensively reported using different mapping populations and mapping planforms. From more than 250 documented QTL conferring FHB resistance, only Fhb1-Fhb7 haved been proven to be major effects. Fine genetic linkage maps of Fhb2, Fhb4 and Fhb5 have been reported [16] and Fhb1 has been cloned recently[18-20]. In current study, four loci ( 28 MTAs) were identified on chromosomes 1B, 4A, 5D and 7A in two seasons. In comparison to the SNP GENE-0293_154 on chromosome 1B identified for type II FHB resistance in this study, a minor QTL for type II resistance was found in a similar physical position from Chinese wheat landrace Huangfangzhu [37]. Two loci located on 4AL and 5DL chromosomes at physical intervals of 0.39 and 1.18 Mb , respectively, were related to type II resistance with phenotypic variations (R²) of 9.36–11.63% and 8.11–14.18%, respectively. The SNP BobWhite_c4438_162 itself on 5DL could explain 8.89-14.18% phenotypic variations.

QTL for FHB resistance on chromosome 4AL have been reported from European wheat cultivars. Holzapfel et al. [38] identified two FHB resistance QTL on chromosome 4AL from a French cultivar (Apache) linked with XP7452-646 and a German cultivar (Pirat) linked with XP7553-254.AR. Another QTL, QFhs.fal-4AL, has been mapped on 4AL at a physical position 357.2 Mb from a Swiss winter wheat cultivar (Arina) [39]. FHB QTL identified on 4AL at a physical position from 621.85 to 622.24 Mb in the current study is different from the reported ones and should be new FHB resistance loci. A type II resistance QTL from FHB-resistant wheat cultivar Chokwang (Korea) was mapped on 5DL and linked to the SSR marker Xbarc239 [40, 41] with a physical position of 420.96 Mb. Jia et al. [42] reported a QTL on chromosome 5D linked with Xgwm358 with a physical position of 120.61 Mb. Since no QTL for Type II resistance has ever been reported on chromosome 5DL at the physical interval of 546.09 to 547.27 Mb, QFhb-5DL is likely to be a new FHB resistance locus. SNPs wsnp_JD_c4438_5568170 and wsnp_CAP11_c209_198467 in this QTL region of 5DL were reported to be closely linked to a soil-borne wheat mosaic virus (SBWMV) resistance gene Sbwm1 [43]. The SNPs have been converted into breeder-friendly Kompetitive Allele-Specific Polymerase chain reaction (KASP) markers for effectively distinguish resistant and susceptible alleles of Sbwm1 in a diverse wheat panel in breeding programs. It would be interesting to verify whether these KASP markers can be used in marker-assisted selection of FHB resistance in wheat breeding. Furthermore, BobWhite_c22875_239 was found associated with type II resistance on chromosome 7AL at 661.3 Mb that is about the same proximal region of a reported QTL QFhb.nau-7A from Wangshuibai [44, 45] (Table 3).

QFhb-4AL and QFhb-5DL are located on syntenic genomic regions

We detected two loci significant associated with FHB resistance on 4AL and 5DL at a physical intervals of 0.39 and 1.18 Mb, respectively. Through LD of markers and FHB severity analysis, each haplotype contains wheat cultivars with associated SNP on both QFhb-4AL and QFhb-5DL simultaneously. Gene annotations of the genomic intervals revealed homologous gene pairs between 4AL and 5DL. Highly collinearity in gene order and content were observed for the two FHB resistant QTL regions, even through large fragment insertions/deletions were also presented (Table S4; Fig. 5).

Wheat has experienced structural evolution involved chromosome translocation of 4A, 5A, and 7B. The 4AL/5AL translocation was occurred at the diploid level and is present both in T. monococcum and T. aestivum, followed by a 4AL/7BS translocation, a pericentric inversion (4AS;4AL) and a paracentric inversion (4AL;4AL) that taken place in the tetraploid progenitor of hexaploid wheat[46]. Recently, Dvorak et al. [47] reassessed the evolution of wheat chromosomes 4A, 5A and 7B after sequence comparison of wild emmer wheat and Aegilops tauschii. They found that the 596.2-631.84 Mb genomic region of 4A pseudomolecule was derived from ancestral 5AL with nested inversion and is corresponding to the end of the Ae. tauschii arm 5DL. The two FHB associated loci on 4AL (621.81– 622.49 Mb) and 5DL (546.45–546.92 Mb) are located on the syntenic block with sequence inversion (Fig. 5), providing further information of this structure rearrangement containing important genes for agronomic trait.

The hypothetical proteins were predicted for the 4AL and 5DL syntenic blocks. Two kinase proteins, homologous to PTI1-like tyrosine-protein kinase 1 and Putative receptor protein kinase ZmPK1, proved to be associated with plant disease resistance were annotated in the corresponding genomic regions (Tables 3, S4). Protein kinases (PKs) are important for transmembrane signaling that regulates plant development and adaptation to diverse environmental conditions[48]. Several kinase proteins have been reported related to plant innate immunity. For example, the combination of a kinase and a putative START lipid-binding domain is necessary to confer wheat rust resistance of Yr36 [49]. Wheat stripe rust resistance gene Yr15 (WTK1)[50] and barley (Hordeum vulgare L.) stem rust (P. graminis f. sp. tritici) resistance gene Rpg1 [51]contain a structure with tandem kinase domains. A maize wall-associated kinase protein (ZmWAK) was reported to confer quantitative resistance to maize head smut [52] and the PTI1-like kinase (ZmPti1a) was known to play an important role in the signaling pathway that facilitates pollen performance and male fitness [53].

Kinase proteins were also found to be important in F. graminearum. A MAP kinase gene (MGV1) in F. graminearum was involved in multiple developmental processes related to sexual reproduction, plant infection, and cell wall integrity [54]. The glycogen synthase kinase gene orthologous to mammalian GSK3 was an important virulence factor and Fgk3 glycogen synthase kinase was also important for growth, pathogenesis, conidiogenesis, DON production and stress responses in F. graminearum [55]. Taken the potential importance of kinase proteins in FHB resistance synthetic loci identified on 4AL and 5DL, the wheat homologs of PTI1-like tyrosine-protein kinase 1 and putative receptor protein kinase ZmPK1 might be considered as candidates of FHB resistance and need further characterization.

In the present study, four FHB resistance loci were identified using wheat 90 K SNP assay and GWAS analysis. Two new FHB resistance loci on 4AL and 5DL were found to be located on syntenic genomic regions. The SNP markers significantly associated with FHB resistance and cultivars could be used in wheat breeding.

DON Deoxynivalenol

FHB Fusarium head blight

GPC Grain protein content

GWAS Genome-wide association study

His Histidine-rich calcium-binding protein

LD Linkage disequilibrium

MAF Minor allele frequencies

MAS Marker-assisted selection

MLM Mixed linear model

MTA Marker-trait association

PH Plant height

PFT Pore-forming toxin-like gene

PSS The percentage of symptomatic spikelets

QTL Quantitative trait loci

R² Phenotypic variance explained

SDS Sodium dodecyl sulfate

SNP Single nucleotide polymorphism

TKW Thousand kernel weight

Conclusions

Acknowledgments

The authors are grateful Dr. Jindong Liu, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences for critical review of this manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2017YFD0100801; 2016YFD0101802), the Natural Science Foundation of Jiangsu Province (BK20171279), the China Agricultural Research System (CARS-03-03B).

Availability of data and materials

The phenotypic data of the current study is available in the Additional file 1: Table S1. Any other datasets used and/or analyzed are available upon request.

Consent for publication

Not applicable.

Conflicts of interest

The authors declare that they have no competing interests.

Ethical Standards

We declare that these experiments complied with the ethical standards in China.

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Table 1 FHB resistance loci revealed by GWAS in two years

Locus	Markera	Chrb	Postionc(Mb)	P value	R2d(%)	Allele	Resistant allele
QFhb-1B.2	GENE-0293_154	1B	549.47	6.20E-04/7.50E-04	7.18/6.91	C/T	C
QFhb-4A	BS00011469_51	4A	621.85	1.00E-04/2.40E-04	9.36/8.37	C/T	C
	Excalibur_c22724_85	4A	622.2	2.00E-05/1.10E-04	11.63/9.33	C/T	T
	Kukri_c24695_273	4A	622.2	2.00E-05/1.10E-04	11.63/9.33	A/G	A
	Kukri_c1073_91	4A	622.24	2.00E-05/1.00E-04	11.53/9.65	C/T	T
	Excalibur_c687_961	4A	622.24	2.00E-05/1.10E-04	11.63/9.33	A/G	A
	Excalibur_c687_907	4A	622.24	2.00E-05/1.10E-04	11.63/9.33	C/T	T
	Excalibur_c687_886	4A	622.24	2.00E-05/1.10E-04	11.63/9.33	A/G	G
QFhb-5D	BobWhite_c13030_406	5D	546.09	2.00E-05/1.30E-04	11.65/9.37	A/G	G
	BS00079676_51	5D	546.65	2.00E-05/1.10E-04	11.63/9.33	A/G	A
	RAC875_c13169_459	5D	546.65	2.00E-05/1.10E-04	11.63/9.33	C/T	C
	D_GA8KES401AL4GG_122	5D	546.65	2.00E-05/1.10E-04	11.63/9.33	C/T	C
	wsnp_JD_c4438_5568170	5D	546.69	8.00E-05/1.60E-04	11.72/10.76	A/G/R	A
	wsnp_JD_c4438_5567972	5D	546.69	2.00E-05/1.10E-04	11.63/9.33	A/G	A
	wsnp_JD_c4438_5567834	5D	546.69	9.00E-05/4.10E-04	11.63/9.33	C/T/Y	C
	BobWhite_c4438_162	5D	546.69	7.00E-06/2.50E-04	14.18/8.89	A/G	G
	IACX10520	5D	546.69	2.00E-05/1.10E-04	11.63/9.33	C/T	T
	BS00088587_51	5D	546.69	2.00E-05/1.10E-04	11.63/9.33	G/T	G
	D_GDS7LZN01CBWNE_99	5D	546.7	2.00E-05/1.10E-04	11.63/9.33	C/T	T
	Kukri_c5528_603	5D	546.7	2.00E-05/1.10E-04	11.63/9.33	C/T	C
	Excalibur_c42190_383	5D	546.91	4.10E-04/4.40-E04	9.57/9.55	A/G/R	A
	Excalibur_c28592_377	5D	546.91	9.00E-05/3.00E-04	9.47/8.11	C/T	T
	Excalibur_c28592_173	5D	546.91	4.10E-04/4.40-E04	9.57/9.55	C/T/Y	T
	Excalibur_c14043_548	5D	546.91	9.00E-05/3.00E-04	9.47/8.11	C/T	C
	CAP8_c145_89	5D	547.27	2.00E-05/1.10E-04	11.63/9.33	C/T	T
	wsnp_CAP11_c209_198467	5D	547.27	2.00E-05/1.30E-04	11.65/9.37	A/G	A
	BS00011794_51	5D	547.27	2.00E-05/1.30E-04	11.65/9.37	C/T	T
QFhb-7A	BobWhite_c22875_239	7A	661.3	2.20E-04/3.00E-04	8.53/8.12	C/T	C

a Markers were detected at the threshold -log10 (P) = 3.0.

b Chr, Chromosome.

c Physical positions of SNP markers based on wheat genome sequences from the International Wheat Genome Sequencing Consortium (IWGSC, http://www.wheatgenome.org/).

d Percentage of phenotypic variance explained by the MTA.

Table 2 Statistical analysis of three haplotypes for FHB severities

Haplotype^a	No.^b	Minimum (%)	Maximum (%)	Mean ^c (%)	Standard deviation	Variance
Haplotype1	149	7.71	94.73	48.92A	22.29	496.69
Haplotype2	19	4.29	41.25	19.94B	11.36	129.06
Haplotype3	3	7.3	16.58	11.52B	4.7	22.09

a Three haplotype groups revealed through haplotype analyses of the associated markers.

b No., Number of cultivars

c indicates extremely significant differences at 0.01 significance level among parents and controls（P<0.01）.

Table 3 Physical positions of reported FHB resistance QTL related to those in the current study

Chr.	Source	QTL/Gene	Linked marker	Position^a (Mb)	Reference
1B	Huangfangzhu	Not named	Xbarc207	506.33	Li et al. 2012
1B	Wangshuibai	Not named	Xwms759	unknown	Zhou et al. 2004
1B	Wangshuibai	Not named	Xbarc302	455.99	Liu et al. 2009
			Xglu-1B	unknown
1B	Seri 82	Not named	Xgwm273	212.51	Liu et al. 2009
			Xbarc302	455.99
1B	CM 82036	Not named	Xbarc302	455.99	Liu et al. 2009
			Xgwm153	628.83
1B	Fundulea201R	Not named	Xgwm264	15.03	Liu et al. 2009
			Xgwm131	459.16
1B	Romanus	Not named	Xgwm018	222.58	Liu et al. 2009
			Xgwm153	628.83
1B	Arina	Not named	Xgwm264	15.03	Liu et al. 2009
			Xgwm273	212.51
1B	Ralito	Not named	Xgwm018	222.58	Liu et al. 2009
			Xgwm131	459.16
1B	Yumechikara	Not named	Glu-B3	unknown	Nishio et al. 2016
			Xbarc32	unknown
4AL	Arina	QFhs.fal-4AL	Xgwm160	357.2	Paillard et al. 2004
			Xcdo545	unknown
4AL	Pirat		XP7553-254.AR	unknown	Holzapfel et al. 2008
4AL	Apache		XP7452-646	unknown	Holzapfel et al. 2008
5D	Chokwang	Qfhb.ksu-5DL1	Xbarc239	420.96	Yang et al. 2005
5D	Alondra‘s’		Xgwm190	unknown	Jia et al. 2005
			Xgwm358	120.61
7A	Huangfangzhu	Qfhb.uhgl-7AL	Xgwm276	642.88	Li et al. 2012
			Xbarc121	611.84
7A	Wangshuibai	Not named	Xgwm276	642.88	Jia et al. 2005
			Xgwm282	681.39
7A	Romanus	Not named	Xbarc121	611.84	Liu et al. 2009
			Xbarc29	616.22
7A	NK93604	Not named	Xbarc29	616.22	Liu et al. 2009
			Xgwm276	642.88
7A	Spark	Not named	Xbarc121	611.84	Liu et al. 2009
			Xgwm276	642.88
7A	Fontana	Not named	Xfbb121	611.84	Liu et al. 2009
			Xgwm233	11.36
7A	Wangshuibai	Not named	Xwms1083	unknown	Zhou et al. 2004

a Physical positions of SNP markers based on wheat genome sequences from the International Wheat Genome Sequencing Consortium (IWGSC, http://www.wheatgenome.org/).

Table 4 Collinearity analysis of the significantly associated regions on chromosomes 4A and 5D

Marker^a	Chr^b	Position^c(cM)	*Adjacent T. aestivum* gene^d**	Predicted function^e	Identity (%)	Orthologous gene
GENE-0293_154	1B	549.47	–	–	–
BS00011469_51	4A	621.85	TraesCS4A02G341700	PTI1-like tyrosine-protein kinase	100	LOC109767070
Excalibur_c22724_85 Kukri_c24695_273 Kukri_c1073_91	4A	622.20	TraesCS4A02G507700LC	protein FAR1-RELATED SEQUENCE 6-like	96.62	LOC109763821
Excalibur_c687_961 Excalibur_c687_907 Excalibur_c687_886	4A	622.24	TraesCS4A02G342500	putative receptor protein kinase ZmPK1	99.25	TRIUR3_00921
BobWhite_c13030_406	5D	546.09	TraesCS5D02G529700	uncharacterized protein	100	LOC109743624
BS00079676_51 RAC875_c13169_459 D_GA8KES401AL4GG_122	5D	546.65	TraesCS5D01G530300	putative RNA-binding protein Luc7-like 2	100	LOC109763817
wsnp_JD_c4438_5568170 wsnp_JD_c4438_5567972 wsnp_JD_c4438_5567834 BobWhite_c4438_162 IACX10520 BS00088587_51	5D	546.69	TraesCS5D02G530600	putative receptor protein kinase ZmPK1	100	LOC109763820
D_GDS7LZN01CBWNE_99 Kukri_c5528_603	5D	546.70	TraesCS5D02G530700	probable ion channel CASTOR	100	LOC109763818
Excalibur_c42190_383 Excalibur_c28592_377 Excalibur_c28592_173 Excalibur_c14043_548	5D	546.91	TraesCS5D02G531200	PTI1-like tyrosine-protein kinase	100	LOC109767070
CAP8_c145_89 wsnp_CAP11_c209_198467 BS00011794_51	5D	547.30	TraesCS5D02G532100	uncharacterized protein	99	LOC109767042
BobWhite_c22875_239	7A	661.30	TraesCS7A02G464900	probable polyamine transporter At3g13620	98.73	LOC109739139

a Markers were detected at the threshold -log10 (P) = 3.0.

b Chr, Chromosome.

c Physical positions of SNP markers based on wheat genome sequences from the International Wheat Genome Sequencing Consortium (IWGSC, http://www.wheatgenome.org/).

d T. aestivum gene transcripts and their domains were explored in Ensembl (using the transcript table link).

e The sequences of T.aestivum gene were blasted in the NCBI (http://www.ncbi.nlm.nih.gov/), databases to identify putative gene functions.

Table S1 171 wheat accessions used in the genome-wide association study (GWAS) for FHB severities and their origins

Table S2 Marker-trait associations (MTAs) for FHB resistance in 171 wheat accessions identified by the Tassel v5.0

Table S3 Cultivars belonging to different haplotype and their FHB severities

Table S4 The associated regions with FHB resistance with the same function exists in the corresponding sections of 4A and 5D

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Genome-wide association mapping revealed syntenic loci QFhb-4AL and QFhb-5DL for Fusarium head blight resistance in common wheat (Triticum aestivum L.)

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