| Literature DB >> 31959107 |
Wenjing Hu1,2,3,4, Derong Gao1,2,3, Hongya Wu1,2,3, Jian Liu1,2, Chunmei Zhang1,2,3, Junchan Wang1,2, Zhengning Jiang1,2, Yeyu Liu1,2, Dongsheng Li1,2, Yong Zhang5,6, Chengbin Lu7,8,9.
Abstract
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 conducted a genome-wide association study (GWAS) using the high-density wheat 90 K single nucleotide polymorphism (SNP) assays to better understand the genetic basis of FHB resistance in natural population and identify associated molecular markers.Entities:
Keywords: Fusarium head blight (FHB); mixed linear model (MLM); Genome-wide association study (GWAS); Single nucleotide polymorphism (SNP); Triticum aestivum L
Mesh:
Year: 2020 PMID: 31959107 PMCID: PMC6971946 DOI: 10.1186/s12870-019-2177-0
Source DB: PubMed Journal: BMC Plant Biol ISSN: 1471-2229 Impact factor: 4.215
Fig. 1The phenotypic response of the wheat spikelets classified into the four classes based on FHB severity. a resistant, b moderately resistant, c moderately susceptible and d susceptible plants
Fig. 2Boxplot of FHB severities. a FHB severities of natural population in 2017, 2018 and the mean of the two seasons, y-coordinate indicates the percentage of symptomatic spikelets. b FHB severities of wheat cultivars from nine major Chinese provinces, x-coordinate indicates the name of provinces, Guizhou(GZ), Sichuan(SC), Hunan(HN), Hubei(HB), Zhejiang(ZJ), Jiangsu(JS), Anhui(AH), Henan(HN), Shandong(SD), Shanxi(SX), Beijing(BJ), Hebei(HB) and Shaanxi(SAX) in turn from left to right; y-coordinate indicates the percentage of symptomatic spikelets
Fig. 3Population structure of 171 wheat cultivars based on 1676 polymorphic SNP markers with whole-genome coverage. a Number of subpopulations estimated by ∆K at a range of K-values, and (b) Genetic structure produced by Structure V2.3.2. c Estimated LD decay for 171 wheat accessions based on filtered markers from the Wheat 90 K array
Fig. 4Manhattan plots from genome-wide association scan for FHB severities among 171 wheat accessions in (a) 2017 and (b) 2018. Dashed horizontal line is the significant threshold level. c Numbers of significant FHB associated markers on different chromosomes
FHB resistance loci revealed by GWAS in 2 years
| Locus | Markera | Chrb | Postion (Mb) c | R2(%)d | Allele | Resistant allele | |
|---|---|---|---|---|---|---|---|
| 1B | 549.47 | 6.20E-04/7.50E-04 | 6.91–7.18 | C/T | C | ||
| 4A | 621.85 | 1.00E-04/2.40E-04 | 8.37–9.36 | C/T | C | ||
| 4A | 622.2 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | T | ||
| 4A | 622.2 | 2.00E-05/1.10E-04 | 9.33–11.63 | A/G | A | ||
| 4A | 622.24 | 2.00E-05/1.00E-04 | 9.65–11.53 | C/T | T | ||
| 4A | 622.24 | 2.00E-05/1.10E-04 | 9.33–11.63 | A/G | A | ||
| 4A | 622.24 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | T | ||
| 4A | 622.24 | 2.00E-05/1.10E-04 | 9.33–11.63 | A/G | G | ||
| 5D | 546.09 | 2.00E-05/1.30E-04 | 9.37–11.65 | A/G | G | ||
| 5D | 546.65 | 2.00E-05/1.10E-04 | 9.33–11.63 | A/G | A | ||
| 5D | 546.65 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | C | ||
| 5D | 546.65 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | C | ||
| 5D | 546.69 | 8.00E-05/1.60E-04 | 10.76–11.72 | A/G/R | A | ||
| 5D | 546.69 | 2.00E-05/1.10E-04 | 9.33–11.63 | A/G | A | ||
| 5D | 546.69 | 9.00E-05/4.10E-04 | 9.33–11.63 | C/T/Y | C | ||
| 5D | 546.69 | 7.00E-06/2.50E-04 | 8.89–14.18 | A/G | G | ||
| 5D | 546.69 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | T | ||
| 5D | 546.69 | 2.00E-05/1.10E-04 | 9.33–11.63 | G/T | G | ||
| 5D | 546.7 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | T | ||
| 5D | 546.7 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | C | ||
| 5D | 546.91 | 4.10E-04/4.40-E04 | 9.55–9.57 | A/G/R | A | ||
| 5D | 546.91 | 9.00E-05/3.00E-04 | 8.11–9.47 | C/T | T | ||
| 5D | 546.91 | 4.10E-04/4.40-E04 | 9.55–9.57 | C/T/Y | T | ||
| 5D | 546.91 | 9.00E-05/3.00E-04 | 8.11–9.47 | C/T | C | ||
| 5D | 547.27 | 2.00E-05/1.10E-04 | 9.33–11.63 | C/T | T | ||
| 5D | 547.27 | 2.00E-05/1.30E-04 | 9.37–11.65 | A/G | A | ||
| 5D | 547.27 | 2.00E-05/1.30E-04 | 9.37–11.65 | C/T | T | ||
| 7A | 661.3 | 2.20E-04/3.00E-04 | 8.12–8.53 | 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
Fig. 5Haplotype analysis results. a Frequency distributions of the mean FHB severities for 171 cultivars with different haplotypes on chromosomes 4A and 5D. Gray, orange and red represent haplotype 1, haplotype 2 and haplotype 3, respectively. The x-axis exhibits 1–4 scores based on FHB severity (resistant, 0 < PSS ≤25%; moderately resistant, 25% < PSS ≤50%; moderately susceptible, 50% < PSS ≤75% and susceptible, 75% < PSS ≤ 100%). The y-axis represents the number of cultivars (also numbered on the bar) showing the FHB severity in different haplotypes. b Haplotype analysis of significant SNPs on chromosomes 4A and 5D. Solid bar plot displays average FHB severity of each haplotype. Gray, orange and red represent haplotype 1, haplotype 2 and haplotype 3, respectively. Left: Haplotypes of the significant SNPs based on 4A among wheat lines; right: Haplotypes of the significant SNPs based on 5D among wheat lines
Descriptive statistics of the three haplotypes for FHB severities
| Haplotypea | 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)
Fig. 6Gene annotation of SNPs identified on chromosome 4AL (a) and 5DL (b) for FHB resistance. The far left and right image is a visualization of linkage disequilibrium (red is a D’ value of 100%) (I). Names of the markers (II) and physical position (III) were observed in the region of interest. Most significant marker is highlighted in red. The middle image is a physical map of candidate genes on 4AL and 5DL chromosome segments spanning from 621.793 to 622.509 Mb and 546.085 to 547.418 Mb, respectively (IV). The physical position is based on IWGSC 2018. Dotted lines indicate a linear relationship between the significantly associated regions on 4AL and 5DL, respectively
Candidate genes for SNPs significantly associated with FHB resistance
| Markera | Chrb | Positionc (cM) | Adjacent | Predicted functione | Identity | Orthologous gene |
|---|---|---|---|---|---|---|
| 1B | 549.47 | – | – | – | ||
| 4A | 621.85 | PTI1-like tyrosine-protein kinase | 100 | |||
| 4A | 622.20 | protein FAR1-RELATED SEQUENCE 6-like | 96.62 | |||
| 4A | 622.24 | putative receptor protein kinase ZmPK1 | 99.25 | |||
| 5D | 546.09 | uncharacterized protein | 100 | |||
| 5D | 546.65 | putative RNA-binding protein Luc7-like 2 | 100 | |||
| 5D | 546.69 | putative receptor protein kinase ZmPK1 | 100 | |||
| 5D | 546.70 | probable ion channel CASTOR | 100 | |||
| 5D | 546.91 | PTI1-like tyrosine-protein kinase | 100 | |||
| 5D | 547.30 | uncharacterized protein | 99 | |||
| 7A | 661.30 | probable polyamine transporter At3g13620 | 98.73 |
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