Roegneria kamoji Ohwi is a herb of the Roegneria genus of Triticeae Dumort in the family of Poaceae, which is widely distributed in China, Japan, Korea and other regions. There are more than 130 species of Roegneria kamoji Ohwi in the world, including about 79 species in China, mainly distributed in north China, northwest China and southwest China (Cai, 2002). It mostly grows on the slopes of 100~2 300 m above sea level and moist grassland. Many species of R. kamoji Ohwi have high yield, cold resistance, drought resistance, salt and alkali resistance, barren tolerance, high resistance to scab and other excellent characteristics (Xiao et al., 2008). In addition, it has abundant leaves, large grass yield, soft leaves and high edible ability. Horses, cattle, sheep, rabbits and geese like to eat, and it is rich in nutrition, good palatability, high crude protein content. It is an excellent pasture for grazing in summer and autumn and supplementary feeding in winter and spring for all kinds of livestock. In addition to its high economic value, it also provides a natural gene pool for forage breeding and crop improvement with a large number of high-quality stress-resistant genes (Sun et al., 2017). Sichuan and Chongqing region is located in the heart of southwest China. Its unique climate provides a good environment for the growth of various wild herbage and has abundant wild resources. However, the collection and breeding of wild forage germplasm resources in Sichuan and Chongqing region of China is far from enough. At present, domestic studies on genetic diversity are mainly focused on morphology (Shi et al., 2009), cytology (Yu et al., 2014) and isozyme (Zhang et al., 2006).

DNA molecular marker technology has the advantages of convenient use, low price, diverse functions and stable analysis (Liu et al., 2020), and has been widely applied in biology. By comparing the variation of nucleotide sequence directly, it can reduce the uncertainty that may be brought by using phenotype to infer genotype to some extent. It is a DNA-based polymorphism detection. Currently, the commonly used types of molecular markers are SSR (Simple sequence repeat), ISSR (Inter-simple sequence repeat), EST (Expressed sequences tags), AFLP (Amplified fragment length polymorphism), RAPD (Random amplification polymorphism DNA), SNP (Single nucleotide polymorphism) and so on. Zheng et al. (2018) and Zhu et al. (2018) used molecular markers to study genetic diversity in grasses such as Aegilops ovata and Sorghum Sudanense, respectively. Zhang et al. (2018) used ISSR markers to analyze Rhododendron simsii germplasm resources in dabie mountains, and showed that it is rich in genetic diversity. SSR markers were used to analyze the genetic diversity of eggplant (Solanum melongena) germplasm resources, and the results revealed the genetic relationship between eggplant germplasm (Yang et al., 2016). EST-SSR markers have also been used to analyze the genetic diversity of populations of Psammosilene tunicoides in recent years (Qiu et al., 2018). ISAP (Intron sequence amplified polymorphism) uses splicing-location of highly conserved sequences of introns as the core of primers. Primers upstream and downstream of ISAP are 18 bp, and primers are amplified through combination and pairing. The target gene sequence was first developed and utilized by Lu (2006, Huazhong Agricultural University, pp.21-29) in the molecular labeling of cotton (Gossypium barbadense) gene sequence. ISAP is a novel marker with many advantages, such as high polymorphism, good stability and strong purpose, and has extremely important potential value.

At present, the application of ISAP marker technique is relatively rare, and has only been used for the first time in the construction of cotton genetic linkage map (Lu, 2006, Huazhong Agricultural University, pp.21-29). Guo et al. (2015) used 19 pairs of ISAP primers to separate 44 tested Hemarthria compressa and analyzed the genetic and genetic relationships among the materials. Nie et al. (2016) used ISAP marker technology to study the genetic diversity of Miscanthus sinensis, but the related application of ISAP marker has not been reported yet. In this study, we analyzed the genetic diversity and population structure of 80 germplasm resources of wild R. kamoji Ohwi in Sichuan and Chongqing area by using ISAP molecular marker technology, aiming to provide theoretical basis for collection, evaluation and breeding of germplasm resources of R. kamoji Ohwi in the future, and to provide excellent gene resources for genetic improvement of wheat family crops.

1 Results and Analysis

1.1 ISAP polymorphism and genetic diversity analysis

A total of 102 clearly identifiable bands were detected in 20 pairs of primers from 80 wild R. kamoji Ohwi resources (Figure 1). Amplification results (Table 1) showed that there were 7 non-polymorphic bands and 95 polymorphic bands, with a polymorphism band ratio of 93.14%. The amplifying bands of each pair of primers ranged from 2 to 10, and the polymorphic bands ranged from 2 to 10, with an average of 5.1 bands amplified and 4.75 bands polymorphic. The PIC range of all ISAP loci was 0.093 to 0.468, and the mean value of PIC for each ISAP loci was 0.255.

Popgene 1.32 was used to calculate the genetic parameters of 80 germplasm resources of wild R. kamoji (Table 2). The results showed that there were 79 polymorphic bands in Minjiang river basin, and the percentage of polymorphic bands (PPB) was the highest (77.45%). There were 57 polymorphic bands in Jialing river basin, and the polymorphism ratio (PPB) was the lowest (55.88%). Minjiang river basin had the highest genetic diversity (0.286 4), accounting for 28.31% of the total genetic diversity. Jialing river basin had the lowest genetic diversity (0.230 3), accounting for 22.76% of the total genetic diversity. The average genetic diversity index of Yalong river basin and Chongqing populations was 0.247 5, which was slightly lower than that of the four populations (0.252 9). The Shannon information index was the highest in Minjiang river basin, which was 0.423 3. The Shannon information index in Jialing river basin was the lowest, which was 0.334 3. The total mean Nie's genetic diversity index was 0.252 9, and the mean Shannon information index was 0.372 9.

The results of AMOVA showed (Table 3) that 64% of the total genetic variation obtained by ISAP markers existed within the germplasm resources of wild R. kamoji Ohwi, and 36% of the variation existed between populations.  There were significant differences within and between groups (p<0.01), which were statistically significant.

1.2 Cluster analysis of 80 wild R. kamoji Ohwi resources in Sichuan and Chongqing areas

Based on the genetic similarity index, cluster analysis was performed on 80 wild R. kamoji Ohwi using NTSYS-PC 2.10e (Figure 2). The GS ranged from 0.77 to 0.98, with an average of 0.812 6. The genetic similarity coefficients of R26901 and R47902, R27301 and R27306, R27403 and R27404, R24201 and R24202 were the largest, and the genetic similarity coefficients of the four pairs of wild R. kamoji materials all reached 0.983 1.

As can be seen from the results of the cluster diagram (Figure 2), at the genetic similarity index of 0.815, the 80 germplasm resources of wild R. kamoji Ohwi can be divided into three categories. According to the geographical sources of the materials, the I group was almost all from Yalong river basin. In the II category, more than half of the 21 materials were from Minjiang river basin, in addition, 8 materials were mixed from Jialing river basin. The materials of class III are all from Chongqing area.

1.3 Principal component analysis of 80 wild R. kamoji materials in Sichuan and Chongqing area

According to the genetic similarity coefficient, principal component analysis was conducted on 80 wild R. kamoji materials (Figure 3). The results showed that the contribution rate of the first principal component was 81.6%, and that of the second principal component was only 3.7%. The materials from different geographical locations can be divided by the first principal component. The materials from Minjiang river basin are mainly concentrated in region I. The materials from Yalong river mainly concentrated in the second region. The materials from Chongqing area are mainly concentrated in area III. The 9 materials from Jialing river basin and the materials from Minjiang river basin were distributed together, and the overall distribution was relatively concentrated. The results of principal component analysis showed that there were some genetic variations within populations as well as some differences among populations.

1.4 Population genetic structure analysis

According to the genetic linkage map data constructed by ISAP molecular markers, the population structure of this population was analyzed. According to the method of Evanno et al. (2005), the optimal population number was determined by ΔK (Figure 4). The results showed that when K=3, ΔK reached the maximum value, and K=3 was regarded as the optimal group. When K=3, the mean value of α is 0.03, which is low, indicating that most materials have a single ancestral origin.

Population structure analysis results (Figure 5) showed that G1 in individuals only 1 mixed blood of the individual, G2 in individuals with mixed blood a few individuals, G3 all individuals do not have mixed blood, G1 15 individuals and G3 33 individual body is from the Yalong river basin and Chongqing area of wild R. kamoji material. All these are consistent with the results of cluster analysis.

2 Discussion

With the continuous development and progress of biotechnology, the types of DNA molecular markers are also increasing (Huang et al., 2013), from the earliest molecular hybridization as the core of molecular markers to polymerase chain reaction as the core of molecular markers, and then to many new molecular markers such as SNP and EST. ISAP is a novel intron amplification polymorphic molecular marker closely linked to the target gene, while SSR, ISSR, AFLP and other commonly used sequences are amplified outside the coding region or randomly amplified in the genome. In this study, ISAP was used for the first time to study the diversity of germplasm resources of wild R. kamoji. The results showed that the polymorphism rate of ISAP molecular markers in 80 wild R. kamoji resources in Sichuan and Chongqing areas was 93.14%, which was higher than that of 83.20% using ISSR markers (Xiao et al., 2007). In addition, 20 pairs of ISAP primers were used in this experiment to completely distinguish 80 samples of Sichuan and Chongqing wild R. kamoji plants, indicating that ISAP molecular marker technology is a highly effective and highly discriminative DNA fingerprinting technology. In addition, compared with common SSR, ISSR and AFLP, ISAP markers are more reproducible and closely combined with target genes, which makes it more suitable for genetic and breeding research.

Genetic improvement of species is based on germplasm resources (Li et al., 2015), and the index of genetic diversity plays a crucial role in collection of germplasm resources and crop breeding. In this study, the results of cluster analysis, principal component analysis and population Structure analysis showed that there were genetic variation and various geographical sources in 80 wild R. kamoji samples. The Yalong river basin and Chongqing are located in separate geographical locations, and the results of cluster analysis and principal component analysis showed that the materials of the two populations were separated separately. Minjiang river basin and Jialing river basin are geographically close and both tributaries of the upper reaches of the Yangtze River. Cluster analysis and principal component analysis showed that the materials of these two populations were mixed, which may be due to the continuous drift of their seeds along the river, thus forming gene flow between the two populations. In conclusion, there was an obvious correlation between the genetic relationships among the total materials and their geographical sources, which was the same as the results of SSR and ISSR (Xiao et al., 2007). Yang et al. (2006) analyzed the seed gliadin of Roegniera kamoji in Sichuan river basin and found that the genetic diversity of Roegniera kamoji was related to its geographical distribution. Dong et al. (2012, Shandong Normal University, pp.21-29) used SSR molecular markers to analyze the wild R. kamoji resources of Roegneria ciliaris, and found that the genetic diversity of Roegneria ciliaris was greatly affected by geographical location, showing a certain geographical distribution pattern. The differences in the geographical environment of plants can directly or indirectly affect the reproduction and development of plants, and even cause the changes of genetic material in plants during long-term adaptation. Of course, genetic relationships between materials can also be affected by factors such as gene mutation, genetic drift, gene flow and selection (Slatkin, 1987; Schaal et al., 1998).

Based on the results of genetic diversity analysis of wild R. kamoji in Sichuan and Chongqing region by using ISAP molecular marker technology, on the one hand, the polymorphism, effectiveness and identification ability of the new ISAP marker technology can be detected. This study, on the other hand, through the ISAP molecular marker technology will view of 80 selected wild R. kamoji material nuclear genome variation information is analyzed, the results showed abundant genetic polymorphism, and goose grass has rich genetic resources, then the concept of all wild R. kamoji material phenotype and resistance evaluation, so as to accelerate the species of wheat crop breeding process. In addition, R. kamoji itself is also an excellent perennial pasture. Next, R. kamoji resources with high quality, high yield and strong stress resistance will be further screened from the genetic population (Lin et al., 2019).

3 Materials and Methods

3.1 Test materials

In this study, more than 80 samples of Roegniera Kamoji Ohwi were collected in Sichuan and Chongqing, and later transplanted to Chongzhou Grass Experimental Base of Sichuan Agricultural University (30°56′N, 103°66′E, altitude 560 m). Material number, code, collection place (Table 4). 

3.2 DNA extraction

Take R. kamoji healthy young leaves, rinse with distilled water after drying. DNA kit (Tiangen Biotech Co., Ltd) was used to extract genomic DNA from R. kamoji. The specific steps are as follows: (1) put the leaves into EP tube, cut them into pieces and add steel balls into liquid nitrogen for refrigeration, then grind them with grinding instrument, and then add them into 65℃ water bath preheated in advance for half an hour, and shake them evenly every 2 minutes during the process; (2) After the water bath, take out the sample, add 500 μL of chloroform and isoamyl alcohol mixture, absorb 500 μL of supernatant and then add the same amount of chloroform isoamyl alcohol. After the above operation is repeated, add 50 μL 3 mol/L NaAc solution and 500 μL precooled isopropyl alcohol. (3) Centrifuge for 8 min to stratify the solution, remove the supernatant, wash it with 75% ethanol and 95% ethanol, dry it, pick out THE DNA, dissolve it in 200 μL TE (TE buffer solution), and store it in a refrigerator at 4℃ for later use.

3.3 Primer design and PCR amplification

Referring to the principle of designing ISAP primers based on rice gene sequence proposed by Lu (2006, Huazhong Agricultural University, pp.21-29), rice BACs in NCBI database were randomly selected, and gene sequences verified by cDNA sequence were selected from BACs. Then intron boundary sequences conforming to the following rules were selected from the gene sequences. That is, the donor end is 5′-A/CA-GGTAA-3′ or the acceptor end is 5′-TTGCAG-3′, and the 7 bases in the 5' upstream of the acceptor end sequence contain at least 4 purines. Then, the boundary sequence of the intron was extracted to make the total length of the primer be 18 bases. The sequences containing secondary structure and other unsuitable primers were removed, and the primers conforming to the primer design principle were selected as upstream and downstream primers. A total of 72 pairs of primers were synthesized, including 9 upstream primers and 8 downstream primers (Table 5). Primers with good specificity were selected from all primers, and then PCR was performed on all materials. PCR reaction system was 20 μL, including: 2×Taq PCR Master Mix 15.4 μL; 60 ng/μL DNA template 3 μL; 10 μmol/L Primer-F and Primer-R 0.8 μL each. The amplification procedure was as follows: pre-denaturation at 94℃ for 5 min; Then denaturation at 94℃ for 1 min, annealing at 35℃ for 1 min, chain extension at 72℃ for 1 min, 5 cycles; Denaturation at 94℃ for 1 min, annealing at 50℃ for 1 min, chain extension at 72℃ for 1 min, 35 cycles; Finally, the chain was extended for 10 min at 72℃, preserve at 4℃.

The amplified products were detected on 8% polyacrylamide gel. After the gel for electrophoresis was prepared, 10 μL sample was added to each point sample well with Borack company's D2000 Marker as the control electrophoresis at 350 V constant voltage for 1.5 h.

After dyeing with silver in 0.1% AgNO₃ solution for 15 min, the color was developed in NaOH solution. The gel was placed under light and photographed with a digital camera for later analysis (Dai and Wu, 2011).

3.4 Data statistics and processing

The bright bands or clear weak bands in the electrophoretic results of amplified products were counted to obtain basic data. Stripes are distributed in numbers “1, 0” "1" represents the position with stripes, "0" represents the position without stripes, and the original standard 0/1 matrix is established. The polymorphism band ratio (PPB) and primer polymorphism information content (PIC) were calculated, PICi=2fi(1-fi). Popgene 1.32 was used to calculate genetic parameters, GenAIEx 6.4 was used to calculate variation distribution within and between populations, NTSYS PC 2.10e software was used for cluster analysis and principal component analysis, and Structure 2.3 software was used for population Structure analysis.

Authors’ contributions

NG and WM are the designers and executors of this study. WM and LD completed the data analysis and wrote the first draft of the paper. YLM, LZC, SYN and XJQ participated in the experimental operation. NG was the architect and principal of the project, while ZXQ directed experimental design, data analysis, paper writing and revision. All authors read and approved the final manuscript.

Acknowledgments

This study was supported by the National Technology System of Modern Forage Industry (CARS-34), the Undergraduate Research Interest Training Program of Sichuan Agricultural University (NO.2018049), and the Innovative Training Program of Sichuan Agricultural University (S201910626072).

References

Cai L.B., 2002, Geographical distribution of Roegneria C. Koch (Poaceae), Xibei Zhiwu Xuebao (Acta Botanica Boreali-Occidentalia Sinica), 22(4): 913-923

Dai J., and Wu Y., 2011, Attention of SSR molecular maker in experiment, Zhongzi (Seed), 30(11): 122-123
https://doi.org/10.1167/11.11.122

Evanno G., Regnaut S., and Goudet J., 2005, Detecting the number of clusters of individuals using the software structure: a simulation study, Molecular Ecology, 14(8): 2611- 2620
https://doi.org/10.1111/j.1365-294X.2005.02553.x
PMid:15969739

Guo Z.H., Zhang X.Q., Ma X., Zhou C.J.,Wang X., Huang L.K.,Yan Y.H., Cheng Y.J.,Gu X.Y., and Liu X., 2015, Genetic diversity and relationship of hemarthria compressa clones from Southwest China revealed by ISAP markers, Caoye Xuebao (Acta Agrestia Sinica), 23(1): 156-166

Huang X., Zhang X.Q., Zhang Y., Jiang X.M., Zeng J., Liu H., Nie G., Zhang G., and Huang L.K., 2013, Genetic diversity of Hemarthria altissima and its relative species by SCoT markers, Redai Zuowu Xuebao (Chinese Journal of Tropical Crops), 34(11): 2192-2199

Li Y., Li Y.H., Yang Q.W., Zhang Ji.P., Zhang J.M., Qiu L.J., and Wang T.Y., 2015, Genomics-based crop germplasm research: advances and perspectives, Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 48(17): 3333-3353

Lin Z.S., Liu G.M., and Xu Q.G., 2019, Analysis of genetic diversity of new rice lines by SRAP markers, Jiyinzuxue Yu Yingyong Shengwuxue (Genomics and Applied Biology), 38(4): 1683-1688

Liu X.Q., Zhao H.B., Li X.L., and Zhang Y.M., 2020, Research advance on applications of molecular markers and genomes in perenial ryegrass, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 18(2): 473-481

Nie G., Huang L.K., Zhang X.Q., Taylor M., Jiang Y.W., Yu X.Q., Liu X.C., Wang X.Y., and Zhang Y.J., 2016, Maker-trait association for biomass yield of potential bio-fuel feedstock Miscanthus sinensis from Southwest China, Front. Plant Sci., 7(1): 802
https://doi.org/10.3389/fpls.2016.00802

Qiu F., Lei H., Chen J., Yang S.C., Bai B., Liu C., Ye P., Gao L.Y., and Xin P.Y, 2018, EST-SSR analysis of genetic diversity of Psammosilene tunicoides in Yunnan-Guizhou provincial region, Zhongcaoyao (Chinese Traditional and Herbal Drugs), 49(16): 3895-3898

Schaal B.A., Hayworth D.A., Olsen K.M., Rauscher J.T., and Smith W.A., 1998, Phylogeographie studies in plants: problems and prospects, Molecular Ecology, 7(4): 465- 474
https://doi.org/10.1046/j.1365-294x.1998.00318.x

Shi J.W., Gao A.N., Liu J.G., Li L.H., Yang X.M., and Li X.Q., 2009, Diversity of morphological traits in Roegneria sinica. var. media Keng populations of triticeae, Zhiwu Yichuan Ziyuan Xuebao (Jounal of Plant Genetic Resources), 10(4): 547-552

Slatkin M., 1987, Gene flow and the geographic structure of natural, Science, 236(4803): 787- 792
https://doi.org/10.1126/science.3576198
PMid:3576198

Sun Z.H., Zhang Y., Deng M.Q., Jiang Z.X., Qiao Z.H., Zhou Y.H., and Zhang H.Q., 2017, Cytogenetic and morphological studies on seven populations of Roegneria kamoji Ohwi (Triticeae: Poaceae), Zhiwu Yichuan Ziyuan Xuebao (Jounal of Plant Genetic Resources), 18(6): 1032-1038

Xiao H.J., Xu Z., Li L.H., Ma Y.B., and Cao S.J., 2007, Genetic diversity of Roegneria genera studied by ISSR markers, Huabei Nongxuebao (Acta Agriculturea Boreali-Sinica), 22(4): 146-150

Xiao S., Zhang X.Q., Ma X., Zhang J.B., Yi Y.J, and Huang L.K., 2008, Effect of the photosynthetic characteristics under shade condition about Spuriopiminella brachycarpa, Beifang Yuanyi (Northern Horticulture), 9(8): 10-14

Yang L., Zhang X.Q., Yang W.Y., Li J., and Wei H.T., 2006, Genetic diversity of Roegniera kamoji between and within populations in the Mingjiang and Qingyijiang river valleys as revealed by gliadin, Caoye Xuebao (Acta Agrestia Sinica), 15(4): 12-20

Yang X., Liu F., Zhang Y., Cheng Y.F., Xue L.B., and Chen X.H., 2016, Study on the genetic diversity of eggplant germplasm with SSR markers, Jiyinzuxue Yu Yingyong Shengwuxue (Genomics and Applied Biology), 35(12): 3450-3457

Yu Y., Liu Y.H., Mu D.D., Gao J.D., and Zhang Y.M., 2014, Morphological and cytological observation of Roegneria cilia, Haerbin Shifan Daxue Ziran Kexue Xuebao (Natural Sciences Journal of Harbin Normal University), 30(4): 101-103

Zhang B.L., Ren J., Tian S.Y., Li Z.L., Gan J.P., and Wang S.Z., 2018, Genetic diversity of Rhododendron simsii populations located on dabie mountains based on ISSR markers, Beifang Yuanyi (Northern Horticulture), 24(9): 79-84

Zhang C., Zhou Y.H., Yu H.Q., Fan X., and Zhang H.Q., 2006, Studies on esterase isozymes among species of Roegneria, Elymus, Hystrix and Kengyilia in triticeae, Sichuan Nongye Daxue Xuebao (Journal of Sichuan Agricultural University), 24(2): 130-134, 151

Zheng K., Yi Y.J., Zhao L.B., Liu D.M., Xu K., Hao M., Zhang L.Q., Liu D.C., and Ning S.Z., 2018, Development of PCR Marker specific for subunit 1My of Aegilops ovata, Sichuan Nongye Daxue Xuebao (Journal of Sichuan Agricultural University), 36(6): 717-721

Zhu Y.Q., Peng D.D., Lin C.W., Nie G., Xu Z.W., Huang L.K., Luo F.X., Peng J.H., and Zhang X.Q., 2018, Development of SSR makers based on transcriptome sequence and analysis of genetic diversity in Sorghum sudanense, Caoye Xuebao (Acta Agrestia Sinica), 27(5): 178-189