Introduction
Soybean cyst nematode (SCN) is an
obligate parasite, and its host specialization is obvious. The diversity of SCN
is evaluated either by the race determination scheme (Golden et al. 1970; Riggs and Schmitt 1988) or
HG Type classification scheme (Niblack et
al. 2002).
The Race determination scheme was developed in 1970 (Golden et al. 1970); where four differential
soybean lines including Pickett, Peking, PI 88788 and PI 90763 and the
susceptible cultivar Lee 68 was used to characterize the heterogeneity
of H. glycines. Based on this scheme,
16 potential races were proposed (Riggs and Schmitt 1988). Currently, it had
become international scheme for classifying H.
glycines virulence. Of the 16 races, race 11 and race 13 have not been
found yet, and race 16 was reported only once. There are 13 races
in the United States, including race 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14 and
15 (Kim et al. 1997; Xu et al. 2010). Nine races 1, 2, 3, 4, 5, 6, 7, 9 and 14 had
been found in China with 1, 3 and 4 being the most widely distributed (Song et al. 2016). In 2017, a new SCN
population (called race X12) was detected in Shanxi province, China (Lian et al. 2017). With more and
more new SCN populations identified and reported, the race scheme became not
sufficient to classify the virulence profile in SCN. Therefore, a new scheme
for the virulence phenotype-HG Type classification was proposed (Niblack et al. 2002). HG Type testing enables
more accurate management recommendations than the Race scheme does (Winter et al. 2006). Since the scheme was
formally proposed at the national soybean cyst nematode conference in 2008, it
has been widely accepted and used. Virulence phenotypes of H. glycines had been surveyed with HG Type in some U.S. states
(Niblack et al. 2003; Zheng et al. 2006; Mitchum et al. 2007; Colgrove and Niblack 2008;
Rzodkiewicz 2010; Acharya et al. 2016;
Howland et al. 2018) and also in Korea
(Kim et al. 2013). In China, the race scheme has always been
used, and the application of HG scheme is relatively less (Wang et al. 2014; Chen et al. 2015; Cui et al.
2018).
In China, most soybeans are produced in Jilin province and the SCN disease
spreads widely in this area. The lack of distribution and phenotypic diversity
surveys hinder the efficient management of SCN. The only study on the
distribution of SCN in Jilin province was reported in 1988 (Liu and Wu 1988);
In the past 30 years, there was no report about SCN distribution and genetic
diversity of SCN population in Jilin Province, which seriously restricted the
progress of soybean resistance breeding against cyst nematode. There are only a
few resistant varieties bred from limited resistant sources available on the
market, e.g., Bainong 8, Bainong 9 and Bainong 10 derived from Peking.
Once SCN disease breaks out, only a few resistant varieties would not be
enough.
The objective of this study is to
determine the distribution, density, as well as the diversity of virulence
phenotypes of H. glycines in Jilin
province, thus to provide theoretical foundation for introducing and breeding
suitable resistant varieties in the region.
Materials
and Methods
Soil
sample collection
Soil samples were collected
from soybean fields in Jilin province. A total of 141 fields from 38 cities
(counties, towns) were sampled after harvest (Table 1) via multi-point random sampling within the circumference of the
soybean roots. The soil samples were divided into
two parts, one for counting to determine the density of the cysts, the other
were planted with the SCN-susceptible soybean Jiyu 86 to
increase population densities for studying virulence phenotypes of SCN.
SCN
populations
Soil samples with population of
more than 5 cysts/100 mL
soil were further tested for distribution of virulence phenotypes by race
scheme and HG Type scheme.
Soybean
differential lines
The four indicator lines Pickett, PI 548402(Peking), PI 88788 and PI 90763 and susceptible cultivar Lee 74 were from Soybean Research Institute, Jilin Academy of Agricultural Sciences. The other indicator lines PI 548402, PI 437654, PI 209332, PI 89772 and PI 548316, were from Nematology Institute of Northern China, Shenyang Agricultural University. Cyst
isolation
The isolation of cyst was carried
out as described previously (Liu 1995). In brief, 100 mL soil sample was mixed
in 300 mL water in a 1000 mL measuring cup. Soil suspensions were mixed well by
stirring. The floating particles and suspensions were filtered through 180-μm-pore and 450-μm-pore
sieves, 3 times. The residue on a 180-μm-pore
sieve was rinsed with a fine water flow into a beaker, filtered with a screen
cloth, and dried. Each soil sample was prepared 3 times.
Preparation
of egg suspension
Under a stereomicroscope, full
cysts were placed in a Petri dish and crushed, releasing eggs and juveniles
(J2). The eggs and juveniles (J2) were transferred to a breaker and diluted to
a final density of 1×106·L-1.
Inoculation
Plastic cups (6.4-cm diameter,
17-cm high) with bottom punched were filled with sterilized soil and sand (1:
3). For germination, surface-sterilized seeds of each soybean line were placed
on filter paper under dark conditions for 48 h. One 2–3 cm long soybean
seedling was then sown into each pre-irrigated plastic cup. After 3 days, a
2-mL egg suspension was injected into a 3-cm hole around the root of the
seedling. There were 5 replicate cups for each line. The cups were placed in
large plastic boxes according to sample origin and these boxes were placed in a
greenhouse at 27–29°C. Plants were watered daily.
Microscopic
examination
After 30–35 days, the tops of the
seedlings were removed. The soil and roots in the plastic cups were poured into
a pot and then sprayed with a strong stream of water to dislodge the cysts. The
cysts were isolated as described above and counted using a stereomicroscope.
Identification
Virulence differentiation of SCN
population was based on the difference in reproductive ability on indicator
lines. Based on the average number of cysts formed on the indicator lines,
Female Indices (FI) was calculated, FI ≥ 10 meant ‘+’, FI < 10 meant
‘-’. Virulence phenotypes were identified by the race scheme and HG Type
scheme. The formula of the female index (FI):
%20735-741_files/image002.png){kind=small}
Statistical
analysis
The correlation analysis among
indicator lines was performed using IBM S.P.S.S. Statistics 21.
Results
Distribution
and Density of SCN in Jilin province
Out of the
141 samples, 104 samples from all 38 cities (counties, town) were positive for
SCN (73.76%) (Fig. 1). 100% of
soil samples from Gongzhuling, Baishan, Yanji, Taonan, Tongyu and other 9
counties (cities) were positive for SCN.
Table 1: Densities of Heterodera glycines
in Jilin province
|
Sampling point city (County) |
Number of samples |
Number of samples with SCN |
Effective sample number ( ≥ 5cyst/100 mL soil) |
Cyst density (cysts/100 mL soil) |
||
|
City |
County(town) |
|
||||
|
Baishan |
Baishan |
5 |
2 |
0 |
0.4 |
|
|
Jingyu |
2 |
2 |
2 |
15 |
|
|
|
Fusong |
4 |
3 |
0 |
1.75 |
|
|
|
Changbai Korean Autonomous County |
4 |
3 |
1 |
2 |
|
|
|
Tonghua |
Meihekou |
3 |
2 |
2 |
12.67 |
|
|
Liuhe |
3 |
1 |
0 |
1 |
|
|
|
Liaoyuan |
Dongliao |
3 |
1 |
1 |
1.67 |
|
|
Dongfeng |
3 |
1 |
0 |
0.67 |
|
|
|
Baicheng |
Baicheng |
3 |
3 |
3 |
14.67 |
|
|
Taonan |
4 |
4 |
4 |
36.25 |
|
|
|
Tongyu |
3 |
3 |
3 |
18.33 |
|
|
|
Daan |
4 |
3 |
1 |
2.5 |
|
|
|
Siping |
Gongzhuling |
5 |
5 |
4 |
19.8 |
|
|
Shuangliao |
3 |
3 |
3 |
11.33 |
|
|
|
Lishu |
4 |
3 |
2 |
3.75 |
|
|
|
Yitong |
4 |
2 |
0 |
1.5 |
|
|
|
Songyuan |
Fuyu |
4 |
3 |
1 |
2.5 |
|
|
Changling |
4 |
3 |
1 |
3.25 |
|
|
|
Qian’an |
4 |
3 |
1 |
2 |
|
|
|
Jilin |
Jilin |
2 |
2 |
2 |
15.5 |
|
|
Jiaohe |
2 |
2 |
2 |
11.5 |
|
|
|
Huadian |
4 |
2 |
0 |
1.25 |
|
|
|
Yongji |
4 |
4 |
2 |
4 |
|
|
|
Panshi |
3 |
3 |
3 |
12.67 |
|
|
|
Yanbian Korean Autonomous
Prefecture |
Dunhua |
6 |
5 |
2 |
3.33 |
|
|
Wangqing |
4 |
3 |
0 |
1.75 |
|
|
|
Antu |
4 |
3 |
2 |
3.75 |
|
|
|
Helong |
4 |
3 |
1 |
2.25 |
|
|
|
Yanji |
3 |
3 |
0 |
2 |
|
|
|
Tumen |
4 |
4 |
2 |
3.5 |
|
|
|
Hunchun |
5 |
3 |
0 |
1.2 |
|
|
|
Longjing |
3 |
3 |
3 |
13.67 |
|
|
|
Changchun |
Yushu |
4 |
2 |
1 |
2.25 |
|
|
Changchun |
4 |
4 |
2 |
4.75 |
|
|
|
Dehui |
4 |
3 |
0 |
1.75 |
|
|
|
Nongan |
4 |
3 |
1 |
2.75 |
|
|
|
Jiutai |
4 |
1 |
0 |
0.25 |
|
|
|
Shuangyang |
4 |
1 |
1 |
1.25 |
|
|
|
Total/Average |
141 |
104 |
53 |
6.33 |
|
|
The average cyst density of all soil samples was
6.33 cyst/100 mL. There were more than 10 cysts/100 mL soil in 24 soil samples
from 11 cities (counties, towns),
especially in samples from the cities of Taonan, Baicheng, Gongzhuling and
Jilin, as well as Tongyu county. The cyst density in Taonan county was 28
cysts/100 mL soil. There were more than 5 cysts/100 mL soils in 53 soil samples
from 27 cities (counties, towns).
Race
identification
%20735-741_files/image004.png)
Fig. 1: Distribution of
soybean cyst nematode (Heterodera
glycines) in Jilin province
Virulence phenotypes of 53
populations with more than 5 cysts /100 mL soil were tested by race scheme.
Seven races were identified, i.e., 1, 3, 5, 6, 9, 10 and 14 (Table 2).
Race 3 was the most widely distributed, accounting for 62.26%, followed by race
1, accounting for 11.32%. Race 5 and 6 accounted for 9.43% respectively. The
SCN in one soil sample was race 10, and one was race 14; of these, race 10 was
first found in China.
HG Type
SCN
virulence phenotypes in 53 soil samples with more than 5 cysts/100 mL soil were
tested using HG Type scheme. We identified 12 HG Types 0, 2, 2.5, 2.7, 5.7, 7, 1.7, 1.3.7,
1.5.7, 2.4.7, 2.5.7, 3.4.5.7, (Table 2). HG Type 7 and 0
was predominant, accounting for 33.96% and 30.18%. Both HG Type 5.7 and HG Type
2.5.7 accounted for 7.55%. HG Type 2.5 and HG Type 2.7 accounted for 3.77% and
5.66%. The remaining types each accounted for 1.89%. HG Type 1.7 was first time
recorded in China and HG Type 3.4.5.7 was
the first found worldwide.
Table 2: Virulence phenotypes of Heterodera glycines in Jinlin province
|
|
No. |
City |
County(town) |
Pickett |
Peking(1) |
PI88788(2) |
PI90763(3) |
PI437654(4) |
PI209332(5) |
PI89772(6) |
PI548316(7) |
Race |
HG Type |
||||||||
|
West |
1 |
Songyuan |
Fuyu |
3.31 |
- |
2.71 |
- |
1.51 |
- |
0.60 |
- |
5.72 |
- |
7.83 |
- |
0.90 |
- |
6.63 |
- |
3 |
0 |
|
2 |
Changling |
3.55 |
- |
1.66 |
- |
7.58 |
- |
4.98 |
- |
1.90 |
- |
7.82 |
- |
2.61 |
- |
19.67 |
+ |
3 |
7 |
||
|
3 |
Qian’an |
7.47 |
- |
2.67 |
- |
6.93 |
- |
3.47 |
- |
0.80 |
- |
7.73 |
- |
4.00 |
- |
25.87 |
+ |
3 |
7 |
||
|
4 |
Baicheng |
Taonan |
41.80 |
+ |
3.28 |
- |
2.62 |
- |
25.25 |
+ |
13.93 |
+ |
11.48 |
+ |
3.93 |
- |
29.51 |
+ |
10 |
3,4,5,7 |
|
|
5 |
Taonan |
18.22 |
+ |
4.12 |
- |
2.82 |
- |
2.17 |
- |
0.43 |
- |
16.70 |
+ |
4.34 |
- |
37.96 |
+ |
6 |
5.7 |
||
|
6 |
Taonan |
1.33 |
- |
2.92 |
- |
2.92 |
- |
4.77 |
- |
4.51 |
- |
0.80 |
- |
2.12 |
- |
7.16 |
- |
3 |
0 |
||
|
7 |
Taonan |
8.41 |
- |
1.68 |
- |
6.25 |
- |
5.29 |
- |
2.16 |
- |
2.16 |
- |
4.33 |
- |
8.65 |
- |
3 |
7 |
||
|
8 |
Tongyu |
3.77 |
- |
2.08 |
- |
0.19 |
- |
2.26 |
- |
5.66 |
- |
4.91 |
- |
5.09 |
- |
23.58 |
+ |
3 |
7 |
||
|
9 |
Tongyu |
0.98 |
- |
3.58 |
- |
5.21 |
- |
4.56 |
- |
4.56 |
- |
2.28 |
- |
5.86 |
- |
6.51 |
- |
3 |
0 |
||
|
10 |
Tongyu |
8.20 |
- |
3.61 |
- |
7.87 |
- |
4.92 |
- |
1.97 |
- |
5.25 |
- |
2.62 |
- |
6.56 |
- |
3 |
0 |
||
|
11 |
Baicheng |
4.61 |
- |
1.05 |
- |
1.05 |
- |
1.26 |
- |
1.05 |
- |
3.14 |
- |
0.84 |
- |
1.68 |
- |
3 |
5.7 |
||
|
12 |
Baicheng |
11.78 |
+ |
11.36 |
+ |
3.93 |
- |
7.02 |
- |
1.45 |
- |
15.50 |
+ |
2.48 |
- |
30.37 |
+ |
9 |
1.5.7 |
||
|
13 |
Baicheng |
4.86 |
- |
2.13 |
- |
3.04 |
- |
2.74 |
- |
3.95 |
- |
9.12 |
- |
2.43 |
- |
27.66 |
+ |
3 |
7 |
||
|
14 |
Daan |
14.60 |
+ |
2.54 |
- |
12.38 |
+ |
1.59 |
- |
0.63 |
- |
13.33 |
+ |
4.44 |
- |
20.95 |
+ |
5 |
2.5.7 |
||
|
East |
15 |
Yanbian Korean
Autonomous Prefecture |
Longjing |
13.24 |
+ |
11.35 |
+ |
1.89 |
- |
2.16 |
- |
1.08 |
- |
1.62 |
- |
0.00 |
- |
13.24 |
+ |
9 |
1,7 |
|
16 |
Longjing |
3.27 |
- |
0.30 |
- |
5.36 |
- |
2.38 |
- |
4.76 |
- |
3.27 |
- |
2.68 |
- |
23.21 |
+ |
3 |
7 |
||
|
17 |
Longjing |
2.32 |
- |
0.70 |
- |
3.25 |
- |
2.55 |
- |
2.32 |
- |
2.32 |
- |
2.55 |
- |
3.02 |
- |
3 |
0 |
||
|
18 |
Duhua |
8.82 |
- |
1.26 |
- |
1.76 |
- |
8.82 |
- |
4.03 |
- |
2.02 |
- |
8.06 |
- |
8.56 |
- |
3 |
0 |
||
|
19 |
Duhua |
7.21 |
- |
4.08 |
- |
0.31 |
- |
0.94 |
- |
0.00 |
- |
3.45 |
- |
7.21 |
- |
15.05 |
+ |
3 |
7 |
||
|
20 |
Helong |
12.70 |
+ |
2.78 |
- |
2.78 |
- |
7.14 |
- |
7.54 |
- |
7.94 |
- |
2.38 |
- |
9.13 |
- |
6 |
0 |
||
|
21 |
Antu |
11.18 |
+ |
13.21 |
+ |
4.47 |
- |
12.60 |
+ |
3.25 |
- |
7.72 |
- |
6.71 |
- |
34.96 |
+ |
14 |
1.3.7 |
||
|
22 |
Antu |
7.59 |
- |
1.31 |
- |
11.26 |
+ |
2.36 |
- |
4.97 |
- |
2.36 |
- |
0.79 |
- |
32.46 |
+ |
1 |
2.7 |
||
|
23 |
Tumen |
12.31 |
+ |
2.24 |
- |
19.78 |
+ |
5.60 |
- |
2.61 |
- |
28.36 |
+ |
4.10 |
- |
16.42 |
+ |
5 |
2.5.7 |
||
|
24 |
Tumen |
0.56 |
- |
2.52 |
- |
3.36 |
- |
2.80 |
- |
4.48 |
- |
5.04 |
- |
4.48 |
- |
15.41 |
+ |
3 |
7 |
||
|
Mid-region |
25 |
Jilin |
Jilin |
36.04 |
+ |
1.90 |
- |
2.17 |
- |
2.44 |
- |
1.36 |
- |
34.42 |
+ |
2.17 |
- |
27.37 |
+ |
6 |
5.7 |
|
26 |
Jilin |
15.58 |
+ |
3.90 |
- |
13.96 |
+ |
1.62 |
- |
11.36 |
+ |
6.17 |
- |
1.30 |
- |
20.45 |
+ |
5 |
2.4.7 |
||
|
27 |
Jiaohe |
3.27 |
- |
1.76 |
- |
1.01 |
- |
2.26 |
- |
0.75 |
- |
1.01 |
- |
2.76 |
- |
31.91 |
+ |
3 |
7 |
||
|
28 |
Jiaohe |
4.82 |
- |
1.29 |
- |
11.58 |
+ |
2.25 |
- |
6.11 |
- |
3.54 |
- |
9.32 |
- |
15.43 |
+ |
1 |
2.7 |
||
|
29 |
Yongji |
7.51 |
- |
3.18 |
- |
2.31 |
- |
4.34 |
- |
2.60 |
- |
8.96 |
- |
2.02 |
- |
6.07 |
- |
3 |
0 |
||
|
30 |
Yongji |
5.65 |
- |
4.32 |
- |
5.98 |
- |
4.32 |
- |
0.00 |
- |
3.65 |
- |
7.64 |
- |
8.31 |
- |
3 |
0 |
||
|
31 |
Panshi |
1.61 |
- |
0.64 |
- |
16.40 |
+ |
1.29 |
- |
0.64 |
- |
4.82 |
- |
2.89 |
- |
19.61 |
+ |
1 |
2 |
||
|
32 |
Panshi |
6.21 |
- |
3.92 |
- |
0.33 |
- |
3.59 |
- |
3.27 |
- |
1.96 |
- |
3.92 |
- |
26.80 |
+ |
3 |
7 |
||
|
33 |
Panshi |
3.79 |
- |
2.84 |
- |
4.73 |
- |
4.42 |
- |
3.15 |
- |
5.99 |
- |
4.73 |
- |
38.49 |
+ |
3 |
7 |
||
|
34 |
Siping |
Gongzhuling |
7.24 |
- |
4.91 |
- |
7.49 |
- |
7.75 |
- |
7.49 |
- |
5.94 |
- |
1.55 |
- |
14.21 |
+ |
3 |
7 |
|
|
35 |
Gongzhuling |
7.07 |
- |
10.61 |
+ |
5.14 |
- |
5.47 |
- |
7.07 |
- |
9.32 |
- |
7.72 |
- |
28.94 |
+ |
3 |
7 |
||
|
36 |
Gongzhuling |
3.97 |
- |
3.44 |
- |
4.76 |
- |
3.44 |
- |
4.23 |
- |
6.88 |
- |
7.94 |
- |
9.79 |
- |
3 |
0 |
||
|
37 |
Gongzhuling |
7.31 |
- |
6.15 |
- |
15.77 |
+ |
3.46 |
- |
5.77 |
- |
6.92 |
- |
4.23 |
- |
25.00 |
+ |
1 |
2.7 |
||
|
38 |
Lishu |
6.68 |
- |
1.73 |
- |
3.22 |
- |
3.96 |
- |
2.48 |
- |
14.11 |
+ |
3.22 |
- |
21.04 |
+ |
3 |
5.7 |
||
|
39 |
Lishu |
2.25 |
- |
2.46 |
- |
2.66 |
- |
3.89 |
- |
2.25 |
- |
0.41 |
- |
3.69 |
- |
30.12 |
+ |
3 |
7 |
||
|
40 |
Shuangliao |
0.00 |
- |
0.00 |
- |
3.59 |
- |
5.25 |
- |
1.66 |
- |
2.49 |
- |
5.25 |
- |
22.38 |
+ |
3 |
7 |
||
|
41 |
Shuangliao |
0.27 |
- |
0.00 |
- |
2.73 |
- |
6.01 |
- |
1.37 |
- |
3.28 |
- |
2.46 |
- |
3.55 |
- |
3 |
0 |
||
|
42 |
Shuangliao |
2.30 |
- |
0.29 |
- |
4.02 |
- |
2.30 |
- |
3.45 |
- |
2.01 |
- |
2.01 |
- |
4.02 |
- |
3 |
0 |
||
|
43 |
Changchun |
Changchun |
20.90 |
+ |
6.35 |
- |
11.64 |
+ |
2.65 |
- |
2.38 |
- |
17.72 |
+ |
6.35 |
- |
4.50 |
- |
5 |
2.5 |
|
|
44 |
Changchun |
3.61 |
- |
4.26 |
- |
6.56 |
- |
4.92 |
- |
7.21 |
- |
9.18 |
- |
4.92 |
- |
33.44 |
+ |
3 |
7 |
||
|
45 |
Shuangyang |
6.39 |
- |
1.53 |
- |
6.91 |
- |
6.91 |
- |
1.02 |
- |
3.32 |
- |
5.12 |
- |
19.44 |
+ |
3 |
7 |
||
|
46 |
Yushu |
2.97 |
- |
2.97 |
- |
6.53 |
- |
4.75 |
- |
1.19 |
- |
7.72 |
- |
5.93 |
- |
6.82 |
- |
3 |
0 |
||
|
47 |
Nong`an |
12.15 |
+ |
0.00 |
- |
3.43 |
- |
4.36 |
- |
0.62 |
- |
4.36 |
- |
4.36 |
- |
7.79 |
- |
6 |
0 |
||
|
48 |
Baishan |
Jingyu |
8.90 |
- |
4.71 |
- |
2.62 |
- |
4.71 |
- |
7.59 |
- |
4.45 |
- |
6.28 |
- |
8.12 |
- |
3 |
0 |
|
|
49 |
Jingyu |
0.85 |
- |
2.56 |
- |
14.25 |
+ |
0.57 |
- |
0.57 |
- |
15.67 |
+ |
3.70 |
- |
27.92 |
+ |
1 |
2.5.7 |
||
|
50 |
Changbai Korean
Autonomous |
3.77 |
- |
3.77 |
- |
3.19 |
- |
0.00 |
- |
5.80 |
- |
1.45 |
- |
1.74 |
- |
7.25 |
- |
3 |
0 |
||
|
51 |
Tonghua |
Meihekou |
13.33 |
+ |
4.67 |
- |
4.00 |
- |
5.33 |
- |
4.00 |
- |
5.67 |
- |
0.33 |
- |
22.00 |
+ |
6 |
7 |
|
|
52 |
Meihekou |
17.59 |
+ |
6.19 |
- |
16.29 |
+ |
0.98 |
- |
4.89 |
- |
3.26 |
- |
0.33 |
- |
33.55 |
+ |
5 |
2.5.7 |
||
|
53 |
Liaoyuan |
Dongliao |
2.67 |
- |
0.00 |
- |
13.07 |
+ |
2.67 |
- |
0.27 |
- |
12.27 |
+ |
4.27 |
- |
6.40 |
- |
1 |
2.5 |
|
Note: ‘+’: FI ≥ 10; ‘-’: FI < 10.
Virulence of SCN groups on
indicator lines
33 SCN populations in this study
were virulent on PI548316: 62.26% had a FI ≥ 10 on the indicator line
(#7), 26.42% FI ≥ 10 on Pickett, 20.75% FI ≥ 10 on PI88788 (#2) and
18.87% FI ≥ 10 on PI209332 (#5). PI89772 had the most resistance: 100%
populations had a FI < 10 on the line (#6). 3.78% had a FI ≥ 10 on PI
90763 (#3), PI 437654 (#4) and 7.55% on Peking (#1),
(Table 2).
A highly significant positive correlation (P < 0.01) was found between the FI on PI 90763 (#3) and PI
437654 (#4), as were correlations among Pickett, PI 90763 (#3) and PI 209332
(#5). Pickett and PI 437654 (#4) were positively correlated (P < 0.05). PI 88788 (#2) and PI209332
(#5) were also positively correlated (Table 3). Additional correlation was
found between Peking (#1) and PI548316 (#7) (Fig. 2).
Table 3: Correlation coefficients among soybean differential
lines with resistance to Heterodera
glycines based on female indices (FIs) from 53 populations in Jilin
province
|
Correlation
coefficients |
Pickett |
Peking |
PI88788 |
PI90763 |
PI437654 |
PI209332 |
PI89772 |
PI548316 |
|
Pickett |
1 |
.254 |
.038 |
.479** |
.301* |
.555** |
-.099 |
.253 |
|
Peking |
|
1 |
-.014 |
.202 |
.147 |
.106 |
.074 |
.295* |
|
PI88788 |
|
|
1 |
-.168 |
.013 |
.282* |
.002 |
.114 |
|
PI90763 |
|
|
|
1 |
.442** |
.071 |
.179 |
.142 |
|
PI437654 |
|
|
|
|
1 |
-.098 |
-.041 |
.110 |
|
PI209332 |
|
|
|
|
|
1 |
.015 |
.224 |
|
PI89772 |
|
|
|
|
|
|
1 |
-.024 |
|
PI548316 |
|
|
|
|
|
|
|
1 |
* P < 0.05, ** P < 0.01
Table 4: Correspondence between race and HG Type
|
Race |
HG Type |
||||||||||||||
|
1 |
2 |
2.4 |
2.5 |
2.6 |
2.7 |
2.4.5 |
2.4.6 |
2.4.7 |
2.5.6 |
2.5.7 |
2.6.7 |
2.4.5.6 |
2.4.5.7 |
2.5.6.7 |
2.4.5.6.7 |
|
2 |
1.2 |
1.2.4 |
1.2.5 |
1.2.6 |
1.2.7 |
1.2.4.5 |
1.2.4.6 |
1.2.4.7 |
1.2.5.6 |
1.2.5.7 |
1.2.6.7 |
1.2.4.5.6 |
1.2.4.5.7 |
1.2.5.6.7 |
1.2.4.5.6.7 |
|
3 |
0 |
4 |
5 |
6 |
7 |
4.5 |
4.6 |
4.7 |
5.6 |
5.7 |
6.7 |
4.5.6 |
4.5.7 |
5.6.7 |
4.5.6.7 |
|
4 |
1.2.3 |
1.2.3.4 |
1.2.3.5 |
1.2.3.6 |
1.2.3.7 |
1.2.3.4.5 |
1.2.3.4.6 |
1.2.3.4.7 |
1.2.3.5.6 |
1.2.3.5.7 |
1.2.3.6.7 |
1.2.3.4.5.6 |
1.2.3.4.5.7 |
1.2.3.5.6.7 |
1.2.3.4.5.6.7 |
|
5 |
2 |
2.4 |
2.5 |
2.6 |
2.7 |
2.4.5 |
2.4.6 |
2.4.7 |
2.5.6 |
2.5.7 |
2.6.7 |
2.4.5.6 |
2.4.5.7 |
2.5.6.7 |
2.4.5.6.7 |
|
6 |
0 |
4 |
5 |
6 |
7 |
4.5 |
4.6 |
4.7 |
5.6 |
5.7 |
6.7 |
4.5.6 |
4.5.7 |
5.6.7 |
4.5.6.7 |
|
7 |
2.3 |
2.3.4 |
2.3.5 |
2.3.6 |
2.3.7 |
2.3.4.5 |
2.3.4.6 |
2.3.4.7 |
2.3.5.6 |
2.3.5.7 |
2.3.6.7 |
2.3.4.5.6 |
2.3.4.5.7 |
2.3.5.6.7 |
2.3.4.5.6.7 |
|
8 |
3 |
3.4 |
3.5 |
3.6 |
3.7 |
3.4.5 |
3.4.6 |
3.4.7 |
3.5.6 |
3.5.7 |
3.6.7 |
3.4.5.6 |
3.4.5.7 |
3.5.6.7 |
3.4.5.6.7 |
|
9 |
1 |
1.4 |
1.5 |
1.6 |
1.7 |
1.4.5 |
1.4.6 |
1.4.7 |
1.5.6 |
1.5.7 |
1.6.7 |
1.4.5.6 |
1.4.5.7 |
1.5.6.7 |
1.4.5.6.7 |
|
10 |
3 |
3.4 |
3.5 |
3.6 |
3.7 |
3.4.5 |
3.4.6 |
3.4.7 |
3.5.6 |
3.5.7 |
3.6.7 |
3.4.5.6 |
3.4.5.7 |
3.5.6.7 |
3.4.5.6.7 |
|
11 |
1.2 |
1.2.4 |
1.2.5 |
1.2.6 |
1.2.7 |
1.2.4.5 |
1.2.4.6 |
1.2.4.7 |
1.2.5.6 |
1.2.5.7 |
1.2.6.7 |
1.2.4.5.6 |
1.2.4.5.7 |
1.2.5.6.7 |
1.2.4.5.6.7 |
|
12 |
1.3 |
1.3.4 |
1.3.5 |
1.3.6 |
1.3.7 |
1.3.4.5 |
1.3.4.6 |
1.3.4.7 |
1.3.5.6 |
1.3.5.7 |
1.3.6.8 |
1.3.4.5.6 |
1.3.4.5.7 |
1.3.5.6.7 |
1.3.4.5.6.7 |
|
13 |
1 |
1.4 |
1.5 |
1.6 |
1.7 |
1.4.5 |
1.4.6 |
1.4.7 |
1.5.6 |
1.5.7 |
1.6.7 |
1.4.5.6 |
1.4.5.7 |
1.5.6.7 |
1.4.5.6.7 |
|
14 |
1.3 |
1.3.4 |
1.3.5 |
1.3.6 |
1.3.7 |
1.3.4.5 |
1.3.4.6 |
1.3.4.7 |
1.3.5.6 |
1.3.5.7 |
1.3.6.8 |
1.3.4.5.6 |
1.3.4.5.7 |
1.3.5.6.7 |
1.3.4.5.6.7 |
|
15 |
2.3 |
2.3.4 |
2.3.5 |
2.3.6 |
2.3.7 |
2.3.4.5 |
2.3.4.6 |
2.3.4.7 |
2.3.5.6 |
2.3.5.7 |
2.3.6.7 |
2.3.4.5.6 |
2.3.4.5.7 |
2.3.5.6.7 |
2.3.4.5.6.7 |
|
16 |
1.2.3 |
1.2.3.4 |
1.2.3.5 |
1.2.3.6 |
1.2.3.7 |
1.2.3.4.5 |
1.2.3.4.6 |
1.2.3.4.7 |
1.2.3.5.6 |
1.2.3.5.7 |
1.2.3.6.7 |
1.2.3.4.5.6 |
1.2.3.4.5.7 |
1.2.3.5.6.7 |
1.2.3.4.5.6.7 |
Discussion
%20735-741_files/image006.jpg)
Fig. 2: Heat map
for correlation between indicator lines
In a previous survey conducted in 1988, SCN was
distributed over 83% of Jilin province, especially in the counties of Zhenlai,
Yushu, Tongyu and Jingyu and in Baicheng city (Liu and Wu 1988). A total of
38 (100%) cities (counties, towns) were infested with SCN in this study.
Taonan, Baicheng, Gongzhuling, Jilin city and Tongyu county are the hotspots
for SCN distribution (Fig. 1), the same as previous survey, except Jilin city. Significantly, SCN was not detected in Jilin
and Longjing cities in the survey conducted in 1988 and cyst density of sample
from Gongzhuling increased, possibly due to the long-term cultivation of
soybeans and the lack of disease resistant varieties in these regions. As shown
in Fig. 1, the density of SCN was the highest and widely distributed in the
western of Jilin Province, which may be due to the most of saline-alkali land,
followed by the middle part, the lowest in the east.
According to similarities of cellular resistance response in tests,
soybean resistance to SCN was classified into two main types: the PI 88788-type,
including PI 209332 and PI 548316; and the Peking-type, including PI 90763, PI
89772 and perhaps, PI 437654 (Endo 1965; Kim et al. 1987; Halbrendt et al.
1992; Mahalingham and Skorupska 1996). The results of this study are similar to
and different from those of previous studies. The resistance of PI 209332 was similar to that of PI 88788
and PI 548316
(Anand 1992). H. glycines
reproduction on these three differentials was significantly positively
correlated (Zheng et al.
2006; Colgrove and Niblack 2008; Acharya et
al. 2016). In this study, PI 209332 (#5) and PI88788 (#2) had positive
correlation on FI (P < 0.05), but
not PI 548316 (#7) (Fig. 2). What's interesting was that significant correction
was found between PI 548316 and Peking in this study. PI 548316, originally assigned to
PI88788-type, now was classified into the Peking-type. Differentials PI 90763
(#3) and PI 437654 (#4) exhibited significant positive correlations on FI (P < 0.01), but not Peking. PI 90763
and PI 437654 were not classified into the Peking-type now. An observation of a
stage-related effect of resistance on juvenile development supports that the
resistance response may be different between the types (Halbrendt et al.
1992). In addition, Pickett is considered to be the
progeny of Peking and may carry similar
resistance genes. However, in this study, Pickett and PI
90763 (#3), PI 437654 (#4), PI 209332 (#5) were found to
have significant positive correlation
but not Peking. This result may be due to the high genetic diversity of the field
population. Pickett should be used to distinguish the virulence phenotypes of SCN field populations in Jilin province.
Virulence phenotypes of H. glycines populations were evaluated
by race scheme and HG Type scheme. A total of 7 races and 12 HG Types were
identified, and race 10 and HG Type 1.7 were first recorded in China. In 1988, race 10 was first discovered in Arkansas (Riggs
and Schmitt 1988). In 1996, the race was also identified in Ohio (Willson et al. 1996). HG Type 3.4.5.7 was first
found worldwide.
If Jilin Province is divided
into eastern, western and central regions, race 1, 3, 5, 6 are distributed in
all the three regions in common. Race
1 is dominantly distributed in the mid-region, while the other three races are
common. Race 9 was found sporadically in the east and west, but not in the
central Jilin Province. Race 10 and 14 distributed in one sampling point in the
West and East respectively.
A population`s HG Type name can clearly show invalid indicator plants. Any
cultivar that has a similar FI ≥10 should not be used in a field that has
an H. glycines population that is compatible with that indicator line.
In this student (Table 2), due to FI
≥10 on
PI 548316 and Pickett in most of populations, the use of PI 548316 and Pickett
as resistant parents should be minimized in Jilin province. The use of PI 88788
(#2) should be also reduced in the west. PI 89772, PI 437654 and PI 90763 are
better sources for resistance to SCN. Recently, multi resistant varieties, such
as Kangxian 3 (Cao et al. 2014),
Dongnong L-10 (Wu et al. 2016),
ZDD24656, a variety derived from PI 437654 and ZDD2315 (Lian et al. 2017), Andou 162, a descendant of
Franklin, Bedford and Hartwig (Wang et
al. 2019), Zhonghuang 26 and Zhonghuang 54, varieties
derived from PI 437654 (Wang and Wang 2016) can be used as source of
resistance.
When comparing the two
schemes, the same race corresponded to multiple HG types, e.g., race 3
corresponded to HG Type 7 and HG Type 5.7 in this study. Additionally, the same
HG type may also correspond to multiple races, e.g., HG Type 7
corresponded to race 3 and race 6, and HG Type 5.7 also corresponded to race 3
and race 6 in this study. In a previous study (Wang 2015), HG
Type 2.7 corresponded to race 1 and race 5. We considered the SCN population
with HG Type 2.7 (race 1) in this study was different from the population with
HG Type 2.7 (race 5) in the previous study (Wang 2015).
Possibly, that was the same as the population with HG Type 2.7 (race 1) in the
previous study. In this way, neither scheme could completely distinguish the
virulence phenotypes of SCN populations. HG Type testing is internationally
accepted because it is relatively accurate and easily expandable as new soybean
germplasm is released and deployed (Winter et al. 2006). The resistant line PI
438489B (Yue et al. 2001) was
added to the set of differentials used in the HG Type test in 2007 (Mitchum et
al. 2007).
However, as the number of identified hosts increases, HG type testing will
become more complex. Currently, HG Type + Race are used in SCN research fields (Han et al.
2015; Lin et al. 2016).
Although there is no one-to-one correspondence
between race and HG type, there are some corresponding relationships (Table 4).
Theoretically, 128 HG types are possible with HG Type testing. Each race
corresponded to 16 HG types, and each two races corresponded to the same HG
type, e.g., race 3 and race 6 corresponded to the same 16 HG Types.
Accordingly, in theory, 256 different SCN virulence types are possible with the
combination of the two methods, but the lack of characterization of them. More trials
are needed for further validation. According to this study, the combination of the
two methods was suitable for the study of genetic diversity of SCN in Jilin
province. Pickett which was removed in HG
scheme should be included not as an indicator line but just to separate
different races from the same HG type in Jilin province.
Conclusion
In this study, 104 soil samples
from 38 cites (cities, counties and towns) were positive for SCN across Jilin
province 7 races and 12 HG types were identified, with Race 3 and HG Type 7
being the most dominant genotypes. PI 90763, PI 437654 and PI89772 were
recommended as excellent sources against cyst nematode. It suggests that Peking-type
resistance sources were preferred to pi88788-type in Jilin province. The
combination of the race and HG scheme is recommended for studying the genetic
diversity of SCN in Jilin province. That is, Pickett should be included
not as an indicator line but just to separate different races from the same HG
type.
Acknowledgement
We acknowledge the financial supports of the National Key
Research and Development Program of China (Grant No. 2018YFD1000905).
Author Contributions
Xiujuan Yan and Yuxi Duan conceived and designed the
experiments; Qiang Qiu and Xiaofeng Zhu collected soil samples; Xiujuan Yan,
Jinwen Liu and Mingshu Li performed the experiments; Jinwen Liu analyzed the
data;Xiujuan Yan and Jinwen Liu wrote the paper.
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