Genome-wide association analysis of Fusarium crown rot resistance in Chinese wheat landraces

Abstract

Key message
A novel locus for Fusarium crown rot (FCR) resistance was identified on chromosome 1B at 641.36–645.13 Mb using GWAS and could averagely increase 39.66% of FCR resistance in a biparental population.

Abstract
Fusarium crown rot can cause considerable yield losses. Developing and growing resistance cultivars is one of the most effective approaches for controlling this disease. In this study, 361 Chinese wheat landraces were evaluated for FCR resistance, and 27 with the disease index lower than 30.00 showed potential in wheat breeding programs. Using a genome-wide association study approach, putative quantitative trait loci (QTL) for FCR resistance was identified. A total of 21 putative loci on chromosomes 1A, 1B, 2B, 2D, 3B, 3D, 4B, 5A, 5B, 7A, and 7B were significantly associated with FCR resistance. Among these, a major locus Qfcr.sicau.1B-4 was consistently identified among all the trials on chromosome 1B with the physical regions from 641.36 to 645.13 Mb. A polymorphism kompetitive allele-specific polymerase (KASP) marker was developed and used to validate its effect in an F2:3 population consisting of 136 lines. The results showed the presence of this resistance allele could explain up to 39.66% of phenotypic variance compared to its counterparts. In addition, quantitative real-time polymerase chain reaction showed that two candidate genes of Qfcr.sicau.1B-4 were differently expressed after inoculation. Our study provided useful information for improving FCR resistance in wheat.

Full text

Vol.:(0123456789)
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Theoretical and Applied Genetics (2023) 136:101
https://doi.org/10.1007/s00122-023-04289-y
ORIGINAL ARTICLE
Genome‑wide association analysis ofFusarium crown rot resistance
inChinese wheat landraces
ShuaiHou1,2· YuLin1,2· ShifanYu1,2· NingYan1,2· HaoChen1,2· HaoranShi3· CaixiaLi1,2· ZhiqiangWang1,2·
YaxiLiu1,2
Received: 6 September 2022 / Accepted: 28 December 2022
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023
Abstract
Key message A novel locus for Fusarium crown rot (FCR) resistance was identified on chromosome 1B at 641.36–
645.13Mb using GWAS and could averagely increase 39.66% of FCR resistance in a biparental population.
Abstract Fusarium crown rot can cause considerable yield losses. Developing and growing resistance cultivars is one of the
most effective approaches for controlling this disease. In this study, 361 Chinese wheat landraces were evaluated for FCR
resistance, and 27 with the disease index lower than 30.00 showed potential in wheat breeding programs. Using a genome-
wide association study approach, putative quantitative trait loci (QTL) for FCR resistance was identified. A total of 21 putative
loci on chromosomes 1A, 1B, 2B, 2D, 3B, 3D, 4B, 5A, 5B, 7A, and 7B were significantly associated with FCR resistance.
Among these, a major locus Qfcr.sicau.1B-4 was consistently identified among all the trials on chromosome 1B with the
physical regions from 641.36 to 645.13Mb. A polymorphism kompetitive allele-specific polymerase (KASP) marker was
developed and used to validate its effect in an F2:3 population consisting of 136 lines. The results showed the presence of this
resistance allele could explain up to 39.66% of phenotypic variance compared to its counterparts. In addition, quantitative
real-time polymerase chain reaction showed that two candidate genes of Qfcr.sicau.1B-4 were differently expressed after
inoculation. Our study provided useful information for improving FCR resistance in wheat.
Introduction
Fusarium crown rot (FCR), caused by the fungal pathogen
Fusarium spp., is a chronic and severe disease in wheat
worldwide (Kazan and Gardiner 2018). FCR has influenced
the quality and yield of wheat seriously now. FCR was dis-
covered in Australia in 1951 and has been one of the primary
Communicated by Evans Lagudah.
Shuai Hou and Yu Lin contributed equally to this work.
* Yaxi Liu
liuyaxi@sicau.edu.cn; yaxi.liu@outlook.com
Shuai Hou
houshuai1220@hotmail.com
Yu Lin
linuuu@outlook.com
Shifan Yu
1608231625@qq.com
Ning Yan
1299262161@qq.com
Hao Chen
1764456964@qq.com
Haoran Shi
542561234@qq.com
Caixia Li
493338068@qq.com
Zhiqiang Wang
frank.wang1991@hotmail.com
1 State Key Laboratory ofCrop Gene Exploration
andUtilization inSouthwest China,
Wenjiang,Chengdu611130, China
2 Triticeae Research Institute, Sichuan Agricultural University,
Wenjiang,Chengdu611130, China
3 Chengdu Academy ofAgriculture andForestry Sciences,
Wenjiang,Chengdu611130, China

Theoretical and Applied Genetics (2023) 136:101
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101 Page 2 of 12
diseases in wheat production for many years (Mcknight and
Hart 1966; Murray and Brennan 2009). In recent years, FCR
has become more prevalent in the USA (Poole etal. 2012;
Moya-Elizondo and Jacobsen 2016), Turkey (Gebremariam
etal. 2017), Iraq (Matny etal. 2012), Canada (Fernández
etal. 2011), Italy (Balmas etal. 2015), Argentina (Laraba
etal. 2017), and China (Li etal. 2012; Zhang etal. 2015;
Ji etal. 2016). FCR pathogens survive in crop residue for
subsequent crops in the following seasons, which makes it
difficult to effectively manage the damage using traditional
methods such as crop rotation and spraying pesticides.
Therefore, growing wheat varieties with enhanced FCR
resistance has long been recognized as one of the most effec-
tive approaches to managing its damage.
Significant efforts have been placed in identifying puta-
tive QTL conferring FCR resistance. So far, quantitative trait
loci (QTL) of FCR resistance have been identified on almost
all chromosomes, including several major loci on chromo-
somes 2A, 2D, 3B, 4B, and 5D (Ma et el. 2010; Zheng etal.
2014, 2015; Jin etal. 2020; Lin etal. 2022). For example,
using a biparental population derived from “CSCR6” and
“Lang,” two major FCR resistance QTL were mapped in
different genetic backgrounds designated as Qcrs.cpi-3B and
Qcsr.cpi-4B, explaining 48.8% and 22.8% of the phenotypic
variance, respectively (Ma et el. 2010). The locus Qcrs.
cpi-3B was further fine-mapped at an interval of 0.7cM
(Zheng etal. 2015). Using three recombinant inbred lines
populations derived from a common resistance parent “EGA
Wylie,” two major QTL were identified on chromosomes 2D
and 5DS, explaining 20.2% and 31.1% phenotypic variance,
respectively (Zheng etal. 2014). Besides, using the genome-
wide association study approach, a novel locus was identi-
fied on chromosome 5DL for FCR resistance in 358 Chinese
wheat, and it could increase by 25% FCR resistance in an
F2 population (Jin etal. 2020). In a natural population, four
major QTL were identified using a genome-wide associa-
tion study, and pyramiding analysis of these four major loci
could improve FCR resistance (Lin etal. 2022). Previous
studies have found that the pyramiding gene/QTL of FCR
resistance could improve FCR resistance in wheat (Liu and
Ogbonnaya. 2015; Zheng etal. 2017; Lin etal. 2022). Thus,
identifying more major loci of FCR resistance is necessary
for pyramiding breeding.
Chinese landrace known as farm species produced
through long-term natural and artificial selections obtained
rich genetic diversity, which are potential sources of novel
resistance with enriched genetic variation. Many superior
genes of agronomic importance (Liu etal. 2017; Lin etal.
2021), drought resistance (Jing etal. 2002; Lin etal. 2019),
and disease resistance (Cai etal. 2016; Long etal. 2021;
Wang etal. 2021a) were identified from Chinese wheat lan-
draces. For example, stripe rust resistance loci were identi-
fied in Chinese wheat landraces “Anyuehong” (Long etal.
2021) and “Dabaimai” (Wang etal. 2021a). The resistance
genes of powdery mildew PmHHXM and Pm61 were iden-
tified in Chinese wheat landraces “Honghuaxiaomai” (Sun
etal. 2018; Xue etal. 2021). Fusarium head blight resistance
genes Fhb4 and Fhb5 were identified in the high-resistance
variety “Wangshuibai,” a Chinese wheat landrace (Ma etal.
2020a). Chinese wheat landraces, which contain abundant
disease-resistance genes, are suitable for screening resist-
ance materials and identifying resistance loci to FCR.
This study evaluated FCR resistance for 361 Chinese
wheat landraces from ten agroecological zones. A genome-
wide association study was performed using 18,194 poly-
morphic markers. Our research aimed to: (1) identify
FCR resistance resources; (2) detect loci associated with
FCR resistance; (3) validate genomic regions identified by
genome-wide association analysis using an F2:3 segregat-
ing population; and (4) identify putative candidate genes
for major loci.
Materials andmethods
Plant materials
Three hundred and sixty-one Chinese wheat landraces from
ten agroecological zones were authenticated and assessed
for FCR resistance (TableS1). All the seeds were harvested
from the Chongzhou experimental plots of Sichuan Agri-
cultural University (30.62°N, 103.63°E) in 2020. A segre-
gating population consisting of 136 F2:3 lines derived from
“Shishoumai” and “Sanyuehuang” was used as the valida-
tion population. “Shishoumai” and “Sanyuehuang” were
FCR resistance and susceptibility landraces, respectively.
The F2 lines were planted in Chongzhou experimental plots
of Sichuan Agricultural University (30.62°N, 103.63°E)
in 2020. Mature seeds were harvested for each F2 plant to
construct the F2:3 family in 2021 and were used for FCR
inoculation and phenotype identification at a greenhouse.
The F2:3 families were used to back-score the corresponding
F2 plants.
Spawn inoculum preparation ofFCR
A highly aggressive F.pseudograminearum isolate, Fp.322,
was used in the FCR assessment. The methods of inoculums
preparation were slightly modified according to the method
published by Mitter etal. (2006). The specific procedure is
as follows: Fp.322 was put on plates of half-strength potato
dextrose agar, which were incubated for seven days in a bio-
chemical incubator at 25°C in darkness. When the white
mycelium grew on the plate and showed pink to dark red
pigmentation, one piece of 1 × 1cm culture medium contain-
ing mycelium was picked out from the edge of the plate and

Theoretical and Applied Genetics (2023) 136:101
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transferred into a conical flask with 100ml carboxymethyl
cellulose sporulation medium. The conical flask was put into
a shaking incubator at 180rpm and 25°C for approximately
six days, and the whole process was carried out in the dark-
ness. The sterilized double-layer gauze was used to filter
out the mycelium, the filtrate was centrifuged at 5000rpm
for 5min, and the spore suspension was collected into a
50-ml centrifuge tube. The spores were harvested, and the
concentration of spore suspension was adjusted to 1 × 106
spores/ml with sterile water. Tween 20 was added to the
spore suspension to a final concentration of 0.1% v/v before
use for inoculation.
FCR inoculation andphenotype identification
Identification of FCR resistance to all wheat lines was
performed under a controlled greenhouse environment at
Sichuan Agricultural University, Chengdu, China. For each
repetition, 20 healthy and plump seeds were selected to
disinfect with 10% sodium hypochlorite for 20min. With
rinsed under running distilled water for 3min, seeds were
germinated in 4 × 8 boxes on two layers of filter paper
saturated with water. Ten germinated seedlings that grew
to about 1cm were immersed in the spore suspension for
1min. Every two seedlings were planted into 5-cm-square
punnets of a tray containing autoclaved potting mix (25%
vermiculite and 75% peat). After inoculation, the seedlings
were kept wet for 24h in darkness with 100% humidity.
Then all plants were grown in glasshouses until the eval-
uation of the FCR response. Settings for the glasshouses
were: 16h of light (22°C) and 8h of darkness (16°C) at
60–80% humidity. All plastic containers were placed on
trays and watered from the bottom of the trays. The plant
was watered when wilted and appeared for FCR infection.
Three repetitions were performed for the natural population,
including 361 Chinese wheat landraces. For the validation
population, at least ten seedlings were inoculated for each
F2:3 line. The severity of FCR was assessed four weeks after
inoculation, with a scale from 0 (no obvious symptoms) to
5 (completely necrotic damage) (Li etal. 2008). A disease
index (DI) was calculated for each line following the formula
of DI = (∑nX/5N) × 100, where X is the scale value of each
plant, n is the number of plants in the category, and N is the
total number of plants assessed for each line.
Statistical analysis
Analysis of variance and Pearson correlation analysis were
conducted using IBM SPSS Statistics for Windows (IBM,
Chicago, IL). The correlation coefficient was determined
using each line's DI value for each accession. The best lin-
ear unbiased prediction (BLUP) values across three repeti-
tions were calculated using the MIXED procedure in SAS
v8.1 (Piepho etal. 2008). The BLUP values of heading date
and plant height from our previous study (Liu etal. 2017)
were used for performed correction analysis with DI values.
Broad-sense heritability (H2) was calculated using the fol-
lowing formula: H2 = VG/(VG + VE), where VG is an esti-
mate of the genetic variance, and VE is an estimate of the
environmental variance.
DNA extraction andgenotyping
The genomic DNA of 361 landraces was extracted from
the fresh leaf tissue from each accession using the modified
cetyltrimethylammonium bromide method (Saghai-Maroof
etal. 1984). The genomic DNA of the validation population
was extracted from the fresh leaf tissue of each F2 plant.
DNA samples were diluted to concentrations of 50–100ng/
μL with an A260/A280 ratio of 1.8–2.0. Three hundred
and sixty-one Chinese wheat landraces were genotyped by
sequence using an Illumina HiSeq 2500 system, and the
details of SNP calling were referred to in our previous study
(Ma etal. 2020b). SNPs with more than 20% missing value
were excluded, and only those with minor allele frequencies
(MAF) ≥ 0.05 were used for further analyses (Zhou etal.
2017, 2018). The F2 lines were further genotyped using a
developed kompetitive allele-specific polymerase (KASP)
marker (KASP1869).
Population structure analysis, Kinship, andGWAS
analysis
The population structure (Q matrix) was analyzed using
STRU CTU RE software v2.3.4 with a burn-in length of
10,000 and 10,000 Monte Carlo Markov Chain iterations
for each K (Pritchard etal. 2000). The K value was set from
1 to 10 with five independent runs. The best K value was
selected using the delta K method (Evanno etal. 2005). The
CLUMPP was used to determine the optimal alignment of
the five replicates (Jakobsson and Rosenberg 2007). Kin-
ship, representing the relationship among individuals, was
estimated using the Genome Association and Prediction
Integrated Tool (GAPIT) package (Lipka etal. 2012).
GWAS analysis was conducted with GAPIT based on
means values of each repetition of phenotypic trait values
(FCR1, means of DI values in the first repetition; FCR2,
means of DI values in the second repetition; FCR3, means
of DI values in the third repetition) and BLUP values were
used for further study analyses. The compressed mixed
linear model with optimal compression and variance com-
ponent estimation was used to identify marker-trait asso-
ciations based on Q + K, where the Q matrix was for the
fixed effect and the K matrix was for the random effect
(Yu and Buckler 2006). A threshold − log10(P) value > 3.0
was set to detect significant associations between markers

Theoretical and Applied Genetics (2023) 136:101
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101 Page 4 of 12
and traits. Manhattan plots were generated using the
“CMplot” package (https:// github. com/ YinLi Lin/ CMplot)
in R v3.0.3.
Validation oftheQTL effect inthe F2:3 population
Two SNPs significantly associated with FCR resistance
identified in GWAS analysis were transformed into KASP
markers. The polymorphic KASP marker (KASP1869)
was used for genotyping the F2 lines. KASP markers were
designed using PolyMarker (Ramirez-Gonzalez etal.
2015). “RR” alleles stand for homozygous resistance
genotype, and “rr” alleles stand for homozygous suscep-
tibility genotype. Heterozygous were rejected for further
phenotypic data collection. Each F2:3 family derived from
the corresponding homozygous F2 plant (“RR” or “rr”)
was evaluated for FCR severity. The FCR severity data of
the F2:3 family were used to back-score the disease perfor-
mance of corresponding F2 plants. Student t-test was used
to determine the significant difference between the two
groups (the “RR” allele group and the “rr” allele group).
Candidate gene analysis
High-confidence predicted genes located in the linkage
disequilibrium (LD) distance of QTL were selected and
used to annotate functions using WheatOmics (Ma etal.
2021). Disease-resistance-related genes were selected for
further quantitative real-time polymerase chain reaction
(qRT-PCR) analysis. Besides, predicted genes with SNP
changes in coding regions were also selected for qRT-PCR
analysis. The FCR resistance genotype “Shishoumai” and
susceptible genotype “Sanyuehuang” were used to validate
gene expressions. Samples of inoculation and mock-inoc-
ulation were harvested by cutting the shoot bases (2cm)
at four days post-inoculation (dpi), snap-frozen in liquid
nitrogen, and kept at − 80°C until processed. RNA was
extracted using the total RNA Extraction Kit (Biofit Bio-
technologies Co., Ltd., Chengdu, China). Total RNA was
diluted to 1μg/mL−1 for reverse transcription. Candidate
gene expressions were identified in a Bio-Rad CFX96
real-time system (Bio-Rad, Hercules, CA, USA) with
three technical replications. The Taq Pro Universal SYBR
qPCR Master Mix (Vazyme Biotech Co., Ltd, Nanjing,
China) was used, and the qRT-PCR reaction mixture was
the same as described in our study (Lin etal. 2019). The
average values from three technical replications were used
in gene expression analysis. SARDB (accession number
BE429982) and MetAP1 (accession number CA680072)
were used as internal reference genes to normalize the Ct
values of each reaction.
Results
Evaluation ofFCR resistance inChinese wheat
landraces
Three hundred and sixty-one Chinese wheat landraces
were evaluated for FCR resistance. DI values of 361 acces-
sions ranged from 10.00 to 87.50, with a mean value of
45.43–54.22 (Fig.1, Table1). It indicated significant dif-
ferences in 361 Chinese wheat landraces' response to FCR.
Frequency distributions of FCR severity were approxi-
mately normally distributed (Fig.2). Among the three
replications and BULP values, correlation coefficients
ranged from 0.89 to 0.99 (Table2). The broad-sense her-
itability (H2) of FCR resistance was 0.74, suggesting the
panel contains adequate levels of genetic variation for the
trait (Table1). Among the 361 Chinese wheat landraces,
27 (7.48%) showed less DI value than 30.00. Of the top
27 resistance landraces, 12 were collected from the Mid-
dle and Low Yangtze Valleys Autumn-sown Spring Wheat
Zone (YTS). Of 361 Chinese wheat landraces, 184 showed
that DI values were more than 50.00. The result showed
that the majority of genotypes were high-susceptibility
landraces. The BLUP values of DI, heading date, and plant
height were used to resolve their relationships. The result
showed that FCR resistance was not corrected with the
heading date and plant height (TableS2).
SNP marker statistics, population structure analysis,
andKinship
After filtering markers based on MAF < 0.05 or missing
data > 20%, 18,194 polymorphic markers were obtained
among the 361 Chinese wheat landraces, which were
mapped on the Chinese spring physical reference map
IWGSC RefSeq v2.0. Among these markers, 7050,
8400, and 2744 markers were located on the A, B, and
D subgenomes, respectively, with a total map length of
14,200.38Mb. The average marker density of the three
subgenomes was 0.70, 0.62, and 1.45Mb/marker. Of the
21 chromosomes, the number of markers on chromosome
2B was the largest (1636), and the density was the low-
est (one marker per 0.50Mb). The number of markers on
chromosome 4D was the least (100), and the density was
the highest (one marker per 5.14Mb) (Table3).
Population structure analysis used 2000 markers that
were randomly selected. According to our structure analy-
sis, the largest value of ΔK was observed at K = 2, which
indicates that 361 Chinese wheat landraces were divided
into two groups (Q1, Q2). Eighty-five landraces (23.55%)
were divided into the Q1 group, and 276 landraces

Theoretical and Applied Genetics (2023) 136:101
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Page 5 of 12 101
Fig. 1 Photograph of phenotype evaluation of Chinese wheat lan-
draces after inoculation. a three resistance landraces (left) and three
susceptibility landraces (right); b resistance landraces (stem); c sus-
ceptibility landraces (stem); d typical FCR symptoms on seedlings in
greenhouse experiments, scaling from 0 to 5
Table 1 Phenotypic variation
and broad-sense heritability
(H2) of DI in 361 Chinese wheat
landraces
SD standard deviation; CV coefficient of variation; H2, broad-sense heritability; FCR1 means of DI values
in the first repetition; FCR2 means of DI values in the second repetition; FCR3 means of DI values in the
third repetition; BLUP best linear unbiased predictions
Variables Minimum Maximum Mean SD CV (%) H2 (%)
FCR1 26.00 87.50 54.22 12.65 23.33
FCR2 22.50 87.50 49.52 12.45 25.14
FCR3 10.00 75.00 45.43 11.96 26.33
BLUP 22.28 85.26 49.58 12.15 24.51 0.74
Fig. 2 Phenotypic distribu-
tion of FCR resistance based
on three repetitions and BLUP
FCR1, means of DI values
in the first repetition; FCR2,
means of DI values in the
second repetition; FCR3, means
of DI values in the third repeti-
tion; BLUP, best linear unbiased
predictions

Theoretical and Applied Genetics (2023) 136:101
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101 Page 6 of 12
(76.45%) were divided into the Q2 group (TableS1). The
Q1 group mainly contains the Qinghai-Tibetan Plateau
Spring Winter Wheat Zone, the Southwestern Autumn-
sown Spring Wheat Zone (SWAS), and YTS agroecologi-
cal zones, and the Q2 group mainly contains the Yellow
and Huai River Valleys Facultative Wheat Zone, SWAS,
and YTS agroecological zones. Interestingly, 70.37%
of resistance landraces (DI < 30.00) were from the Q2
population.
FCR resistance loci revealed bygenome‑wide
association analysis
A total of 41 SNPs located on chromosomes 1A (1), 1B
(19), 2B (2), 2D (2), 3B (4), 3D (1), 4B (7), 5A (1), 5B
(1), 7A (1) and 7B (2) representing 21 putative QTL were
significantly associated with FCR resistance based on
BLUP. Of these 21 putative QTL, the one Qfcr.sicau.1B-4
located on chromosome 1B at 641.36–645.13Mb was
detected in all repetitions (Table4, Fig.3). The genomic
region of Qfcr.sicau.1B-4 included 12 significantly associ-
ated SNPs. SNP1869 and SNP1901 explained the highest
phenotypic variation (8.29%). These SNPs are located in a
physical interval of about 3.77Mb on chromosome 1B at
641.36–645.13Mb (Table4). In addition, 19 and 15 puta-
tive QTL were associated with heading date and plant height
revealed by genome-wide association analysis (Tables S3,
S4). However, no locus overlapped with the QTL of FCR
resistance.
Development ofKASP marker tovalidate Qfcr.
sicau.1B‑4
To validate the effects of Qfcr.sicau.1B-4 in the F2:3 popu-
lation derived from “Shishoumai” (DI = 23.09) and “Sany-
uehuang” (DI = 80.80). The KASP marker (KASP1869)
was successfully developed based on the significant marker
SNP1869 (TableS5) and was used for genotyping all F2 lines
of the F2:3 population. 35 and 38 F2 lines were homozygous
with the “RR” alleles and “rr” alleles. The F2:3 family cor-
responding to these homozygous lines was used to identify
the FCR severity. DI values of 35 homozygous F2:3 lines
ranged from 5.00 to 60.00, and DI values of 38 homozy-
gous F2:3 lines ranged from 5.00 to 87.50. The DI values
of “RR” allele lines with showed a significant difference
(P < 0.01) from those of “rr” allele lines (Fig.4). The result
also showed that Qfcr.sicau.1B-4 could decrease 39.66% the
FCR severity (Fig.4).
Putative candidate genes forQfcr.sicau.1B‑4
onchromosome 1B
Twelve SNPs were located in the interval of Qfcr.
sicau.1B-4. The SNP SNP1883 is located in the gene-
coding region of TraesCS1B03G1106600 and caused
the amino acid sequence change. Thus, it was treated
as a putative candidate gene for qRT-PCR analysis.
Besides, ten disease-related genes were selected as
the candidate for qRT-PCR analysis from 180 high-
confidence genes (TableS6). The results showed that
TraesCS1B03G1106600 and TraesCS1B03G1088300
were significantly induced after FCR inoculated at
four dpi in the resistance genotype “Shishoumai.”
The expression level of TraesCS1B03G1106600 and
TraesCS1B03G1088300 was significantly higher between
Table 2 Pearson correlations of FCR in three repetitions and BLUP
FCR1 means of DI values in the first repetition; FCR2 means of DI
values in the second repetition; FCR3 means of DI values in the third
repetition; BLUP best linear unbiased predictions
**Significant at P < 0.01 level
Repetition FCR1 FCR2 FCR3 BLUP
FCR1 1
FCR2 0.95** 1
FCR3 0.89** 0.95** 1
BLUP 0.97** 0.99** 0.97** 1
Table 3 Molecular marker distribution in the A, B, D, and whole genomes
Number of markers Map length (Mb) Marker density (Mb/marker)
Chromosome A B D Total ABDTotal ABDTotal
1 914 1169 469 2552 597.07 697.74 494.60 1789.41 0.65 0.60 1.05 0.70
2 1407 1636 704 3747 787.71 812.51 655.63 2255.85 0.56 0.50 0.93 0.60
3 655 1255 344 2254 754.01 850.60 619.24 2223.85 1.15 0.68 1.80 0.99
4 935 505 100 1540 753.93 672.36 513.89 1940.18 0.81 1.33 5.14 1.26
5 903 1198 270 2371 711.23 714.51 568.99 1994.73 0.79 0.60 2.11 0.84
6 1007 1294 454 2755 621.71 730.94 495.06 1847.71 0.62 0.56 1.09 0.67
7 1229 1343 403 2975 744.34 763.41 640.90 2148.65 0.61 0.57 1.59 0.72
All 7050 8400 2744 18,194 4970.00 5242.07 3988.31 14,200.38 0.70 0.62 1.45 0.78

Theoretical and Applied Genetics (2023) 136:101
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the resistance genotype “Shishoumai” and the susceptibil-
ity genotype “Sanyuehuang” after FCR inoculated (Fig.5).
The expression level of other genes was not significantly
changed in either of the two varieties after inoculation.
Discussion
Evaluation andscreening ofFCR resistance
atChinese wheat landraces
Table 4 QTL for FCR resistance identified by genome-wide association analysis
PVE phenotypic variation explained; FCR1 means of DI values in the first repetition; FCR2 means of DI values in the second repetition; FCR3
means of DI values in the third repetition; BLUP best linear unbiased predictions
Marker Chromosome Position
(Mb)
− LOG10(P) PVE (%)
FCR1 FCR2 FCR3 BLUP FCR1 FCR2 FCR3 BLUP
Qfcr.sicau.1A-1 SNP59 1A 14.33 – 3.13 3.16 3.15 – 4.84 4.86 4.72
Qfcr.sicau.1B-1 SNP1110 1B 27.78 3.88 – – – 5.68 – – –
SNP1111 1B 28.00 3.58 – – – 5.31 – – –
SNP1118 1B 28.01 3.46 – – – 5.15 – – –
SNP1115 1B 28.66 3.46 – – – 5.15 – – –
Qfcr.sicau.1B-2 SNP1607 1B 530.24 4.15 3.24 – 3.79 6.02 5.00 – 5.51
SNP1610 1B 532.25 3.40 – – – 5.08 – – –
Qfcr.sicau.1B-3 SNP1766 1B 607.16 3.02 – 3.01 3.02 4.61 – 4.64 4.56
Qfcr.sicau.1B-4 SNP1868 1B 641.36 3.89 3.34 – 4.41 5.70 5.13 – 6.28
SNP1900 1B 641.36 3.94 3.48 – 4.50 5.76 5.32 – 6.40
SNP1869 1B 641.74 5.14 5.06 3.68 5.98 7.29 7.53 5.59 8.29
SNP1901 1B 641.74 5.14 5.06 3.68 5.98 7.29 7.53 5.59 8.29
SNP1870 1B 643.48 4.54 4.32 3.30 5.17 6.51 6.49 5.05 7.25
SNP1879 1B 644.77 3.19 – – 3.05 4.82 – – 4.60
SNP1913 1B 644.77 3.20 – – 3.01 4.83 – – 4.55
SNP1882 1B 645.05 4.11 – – 3.84 5.97 – – 5.57
SNP1917 1B 645.05 3.49 – – 3.25 5.19 – – 4.84
SNP1883 1B 645.05 3.58 – – 3.34 5.30 – – 4.95
SNP1884 1B 645.13 – – – 3.25 – – – 4.84
SNP1918 1B 645.13 3.32 3.16 – 3.58 4.98 4.89 – 5.24
Qfcr.sicau.2B-1 SNP5583 2B 794.74 – – – 3.34 – – – 4.95
Qfcr.sicau.2B-2 SNP5655 2B 809.62 4.48 3.22 – 4.39 6.44 4.97 – 6.26
Qfcr.sicau.2D-1 SNP5957 2D 90.58 3.53 – – 3.16 5.24 – – 4.73
Qfcr.sicau.2D-2 SNP6065 2D 577.59 3.08 – – – 4.68 – – –
Qfcr.sicau.3B-1 SNP7310 3B 23.11 – 3.08 – – – 4.78 – –
Qfcr.sicau.3B-2 SNP7561 3B 126.92 3.50 – – 3.25 5.20 – – 4.84
Qfcr.sicau.3B-3 SNP7718 3B 262.57 3.24 3.08 – 3.02 4.88 4.79 – 4.56
Qfcr.sicau.3B-4 SNP7936 3B 582.01 3.02 – – – 4.61 – – –
Qfcr.sicau.3D-1 SNP8533 3D 5.30 3.29 – – – 4.95 – – –
Qfcr.sicau.4B-1 SNP9933 4B 50.13 – – 3.05 – – – 4.69 –
Qfcr.sicau.4B-2 SNP10193 4B 628.82 – 3.68 – 3.10 – 5.61 – 4.66
SNP10187 4B 628.82 – 3.44 – – – 5.27 – –
SNP10195 4B 629.22 – 3.44 – – – 5.27 – –
SNP10188 4B 629.22 – 3.44 – – – 5.27 – –
SNP10189 4B 629.22 – 3.44 – – – 5.27 – –
Qfcr.sicau.4B-3 SNP10261 4B 657.40 – – 3.36 – – – 5.14 –
Qfcr.sicau.5A-1 SNP11200 5A 620.15 3.36 – – – 5.02 – – –
Qfcr.sicau.5B-1 SNP11592 5B 76.60 – – 3.18 – – – 4.88 –
Qfcr.sicau.7A-1 SNP16572 7A 614.69 – 3.12 – – – 4.83 – –
Qfcr.sicau.7B-1 SNP17158 7B 49.03 – – 3.22 – – – 4.94 –
SNP17159 7B 49.03 – – 3.30 – – – 5.04 –

Theoretical and Applied Genetics (2023) 136:101
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101 Page 8 of 12
FCR is a chronic disease that causes great wheat losses (Smi-
ley etal. 2005). In China, FCR has become more prevalent
in wheat-planting regions such as Anhui, Henan, Hebei, and
Shandong (Zhang etal. 2015). Chinese researchers screened
many wheat cultivars or advanced lines to identify novel
sources of FCR resistance, but the result showed that only a
few were resistant (Zhang etal. 2009; Yang etal. 2019). Chi-
nese wheat landraces contain abundant disease-resistance
Fig. 3 The 21 chromosomes
carrying significant markers
detected by the compressed
mixed linear models. The
red dashed line indicated the
threshold −log10(P) value of
3.0. Significantly associated
markers are shown above the
lines. a FCR1, means of DI
values in the first repetition; b
FCR2, means of DI values in
the second repetition; c FCR3,
means of DI values in the third
repetition; d BLUP, best linear
unbiased predictions

Theoretical and Applied Genetics (2023) 136:101
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Page 9 of 12 101
genes and are suitable for screening resistance materials and
identifying resistance loci to FCR. Previous studies have
proved that many diseases resistance QTL or genes were
found in Chinese wheat landraces, such as stripe rust resist-
ance QTL and Fusarium head blight resistance genes (Yao
etal. 2019; Ma etal. 2020a; Wang etal. 2021b).
In this study, 361 Chinese wheat landraces from 10 agro-
ecological zones in China were used to evaluate resistance
against FCR. Twenty-seven landraces showed a stable FCR
resistance with DI less than 30.00. These 27 landraces have
great potential value in the FCR resistance improvement,
which is crucial for breeding varieties of FCR resistance
and controlling the spread of FCR. 70.37% of resistance lan-
draces were from the Q2 sub-population, suggesting that the
Q2 sub-population might be more resistant than those in the
Q1 sub-population. Among ten agroecological zones, most
of the resistance landraces (12) were from YTS. YTS covers
Jiangsu, Anhui, Henan, Hubei, Zhejiang, Hunan, Jiangxi,
and Shanghai. YTS plant area accounts for about 14% of
the Chinese wheat plant area, and the wheat yield accounts
for 13%. The previous research showed that Hunan, Jiangsu,
and Anhui were serious about FCR (Zhou etal. 2014), so
high incidence is beneficial to the generation and evolution
of resistant lines. Besides, the mainland type of YTS was
hills, causing difficulty in soil tillage (Zhao 2010). The soil
tillage method affected the development of FCR, especially
deep tillage can reduce the incidence of FCR (Bankina etal.
2013). Various land types and difficult soil tillage method
helps germs multiply and hide and help generate resistant
wheat. Thus, long-time natural selection finally caused YTS
to have more FCR resistance lines.
Qfcr.sicau.1B‑4 isanovel QTL
In the present study, 21 putative QTL were identified on
chromosomes 1A (1), 1B (4), 2B (2), 2D (2), 3B (4), 3D (1),
4B (3), 5A (1), 5B (1), 7A (1) and 7B (1). Previous studies
showed that FCR resistance genes/QTL were mapped on
almost all chromosomes (Su etal. 2021). Until now, only
three studies found FCR resistance QTL on chromosome
1B (Martin etal. 2014; Jin etal. 2020; Rahman etal.2020).
Two loci were located on the short arm of chromosome
1B, and only one was located at 430–574Mb on the long
arm of chromosome 1B (Rahman etal. 2020). However,
it showed a 67Mb distance from Qfcr.sicau.1B-4. Thus,
we suggested that Qfcr.sicau.1B-4 is a novel locus for FCR
resistance. Besides the major QTL Qfcr.sicau.1B-4, the
present study also identified minor QTL for FCR resist-
ance. Among 41 significant SNPs, five loci can be identi-
fied in at least two repetitions, including Qfcr.sicau.1A-1,
Qfcr.sicau.1B-2, Qfcr sicau.1B-3, Qfcr.sicau.2B-2, and
Qfcr.sicau.3B-3. The locus Qfcr.sicau.1A-1 was located at
14.33Mb on chromosome 1AS. Rahman etal. (2020) identi-
fied a QTL for FCR resistance at 9.67Mb on chromosome
Fig. 4 Effects analysis of Qfcr.sicau.1B-4 in the “Shishoumai”/
“Sanyuehuang” population. **Significant at P < 0.01
Fig. 5 Gene relative expression level of two selected genes in the
Chr. 1BL region in “Shishoumai” and “Sanyuehuang” based on qRT-
PCR analysis. aTraesCS1B03G1106600; bTraesCS1B03G1088300;
Fp-, mock-inoculated control; Fp + , inoculated with Fusarium pseu-
dograminearum. Different letters above boxes denote statistically sig-
nificant at P < 0.05

Theoretical and Applied Genetics (2023) 136:101
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101 Page 10 of 12
1A. It was 4.66Mb distance from Qfcr.sicau.1A-1. Based
on the LD decay of the Chinese wheat landrace (5.98Mb)
in Lin etal. (2019) reported, these two may be the same.
Qfcr.sicau.1B-2 and Qfcr.sicau.1B-3 were located on the
long arm of chromosome 1B. Qfcr.sicau.1B-2 was located
at 530–532Mb and overlapped with the locus on chromo-
some 1B at 430–574Mb reported by Rahman etal. (2020).
Qfcr.sicau.1B-3 was located at 607.16Mb on chromosome
1B and should be a novel locus. Qfcr.sicau.2B-2 was located
at 809.62Mb on chromosome 2B and was far from the locus
at 451.30Mb on chromosome 2B reported by Bovill etal.
(2006). Qfcr.sicau.3B-3 was located at 262.57Mb on chro-
mosome 3B. In a previous study, a locus for FCR resistance
was reported at 827.72Mb on chromosome 3B, and it was
different with Qfcr.sicau.3B-3. Overall, the major locus Qfcr.
sicau.1B-4 and minor loci Qfcr.sicau.1B-2 Qfcr.sicau.1B-3,
and Qfcr.sicau.3B-3 were novel, and Qfcr.sicau.1A-1 and
Qfcr.sicau.1B-2 were overlapped with the previous study.
Putative candidate genes related toFCR forQfcr.
sicau.1B‑4
To further investigate the putative candidate genes for Qfcr.
sicau.1B-4, 11 high-confidence genes located within the
region of Qfcr.sicau.1B-4 were used for qRT-PCR analysis.
The result showed that two genes (TraesCS1B03G1106600
and TraesCS1B03G1088300) were differentially expressed.
The exon of TraesCS1B03G1106600 contains an SNP
SNP1883 (G/C). This SNP causes changes in amino acids
and may change protein function. Previous studies have
proved that a single base mutation can strengthen plant dis-
ease resistance. For example, the rice-spotted leaf 36 mutant
was caused by a single base substitution, and this variation
strengthens the mutant's disease resistance (Rao etal. 2021).
TraesCS1B03G1088300 contains the NB-ARC domain
and encodes the disease-resistance protein. The NB-ARC
domain is a functional ATPase domain whose nucleotide-
binding state is thought to control resistance protein activity.
Resistance proteins are involved in pathogen recognition and
subsequent innate immune response activation (Gerben etal.
2008). Besides, TraesCS1B03G1088300 is homologous to
Os11g11790 (named Pia) in rice. Os11g11790 was a rice
blast resistance gene consisting of two adjacent NBS-LRR
proteins (Okuyama etal. 2011). However, more evidence
is needed to prove their function, such as gene sequence
analysis and transgenic tests.
Conclusion
In this study, 361 Chinese wheat landraces were evaluated
for FCR resistance, and 27 showed a stable FCR resistance
with DI values of less than 30.00. Based on genotypic and
phenotypic data, GWAS analysis identified 21 putative
QTL. Among these QTL, Qfcr.sicau.1B-4 can be identified
in all repetitions and showed stable FCR resistance. Qfcr.
sicau.1B-4 was located at a region of 3.77Mb on chromo-
some 1B with the physical region from 641.36 to 645.13Mb.
The genetic effect of Qfcr.sicau.1B-4 was validated F2:3 pop-
ulation, and this locus could reduce 39.66% of FCR severity.
Two differentially expressed genes revealed by qRT-PCR
were identified as putative candidate genes. The 27 resist-
ance landraces identified in the present study provided novel
sources in wheat variety improvement of FCR resistance.
Our study also provides valuable QTL for FCR resistance
selection and useful information for cloning candidate genes.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00122- 023- 04289-y.
Author contribution statement SH, SY, NY, and HC performed the
phenotypic evaluation; YL conducted data analysis; SH performed
experiments and drafted the manuscript; YL, CL, ZW, and YL
revised the manuscript. All authors have read and approved the final
manuscript.
Funding This work was supported by the Key Program of Sichuan
Province Natural Science Foundation (2022NSFSC0015), the
Key Research and Development Program of Sichuan Province
(2021YFN0034 and 2021YFG0028),the Key Research of State
Key Laboratory of Crop Gene Exploration and Utilization in South-
west China (SKL-KF20221) and the Research of State Key Labora-
tory of Crop Gene Exploration and Utilization in Southwest China
(SKL-ZY202231).
Data availability The datasets used in the current study are available
from the corresponding author upon reasonable request.
Declarations
Conflict of interest The authors declare that they have no conflict of
interest.
Ethical approval The experiments were performed in compliance with
the current laws of China.
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