Classification and Identification of indica P/TGMS Lines in China

Zhang Mengchen, Wang Shan, Yan Jianfang, Sun Shuiyong, Xu Xin, Xu Qun, Yuan Xiaoping, Wei Xinghua, Yang Yaolong



Classification and Identification ofP/TGMS Lines in China

Zhang Mengchen1, Wang Shan1, Yan Jianfang2, Sun Shuiyong1, Xu Xin1, Xu Qun1, Yuan Xiaoping1, Wei Xinghua1, Yang Yaolong1

(State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, China; Seeds Administration Center of Zhejiang Province, Hangzhou 310016, China)

espite extensive studies on cultivated rice, the population structure and genetic diversity of thephotoperiod- and thermo-sensitive genic male sterility (P/TGMS) lines in China remains unclear. Using 48 simple sequence repeat (SSR) markers, we genotyped a panel of 208P/TGMS lines and confirmed three subgroups, named-I,-II and-III, inP/TGMS lines. Further diversity analysis indicated-II had the highest genetic diversity. The genetic differentiation between-II and-III was demonstrated as the largest among the three subgroups. Moreover,/component identification was detected that five P/TGMS lines possesscomponents less than 0.900. These results improve our knowledge on the genetic background for P/TGMS lines in China and will be beneficial for hybrid rice breeding programs.

The utilization of heterosis is a major approach to increase rice yield and has made a great contribution to food security in both China and many other countries (Cheng et al, 2007). Production of hybrid rice seeds is mainly based on the male sterility systems. The current hybrid rice breeding system includes three-line hybrid rice (cytoplasmic male sterile, CMS) and two-line hybrid rice (photoperiod- and thermo-sensitive genic male sterility, P/TGMS). Compared with the three-line hybrid system, the two-line hybrid system, which is based on the discovery and application of environmentally sensitive genic male sterile (EGMS) materials, has obvious advantages in breeding hybrid rice seeds (Yuan, 1994b; Liao and Yuan, 2000; Yang et al, 2007; Xu et al, 2011). Then, based on these advantages, P/TGMS lines have occupied millions of hectares of rice field in China for more than a decade (Yang et al, 2009). Despite the wide-range usage of P/TGMS lines in China, the knowledge of genetic components of P/TGMS lines is lacking. Hence, it is timely and valuable to ascertain the genetic background of the P/TGMS lines and to understand their relationships.

To improve our understanding on the genetic relationship of the sterile germplasms and make contribution to better utilization in rice breeding programs, we employed 48 simple sequence repeat (SSR) markers (NY/T1433-2014, 2014) (Supplemental Table 1) to genotype 208 ChineseP/TGMS lines (Supplemental Table 2) and to investigate the genetic structure, diversity and differentiation of them. With the genotype data, we firstly used STRUCTURE (Pritchard et al, 2000; Falush et al, 2003), a model-based approach, to calculate the genetic component of the 208P/TGMS lines and sub-divided them as clusters. We found that the LnP(D) value increased withfrom 1 to 8 (Fig. 1-A), but displayed peaks of Evanno’sDat= 3 (Fig. 1-B). Similar grouping results were observed at> 3 (Supplemental Fig. 1). Thus, we choseas 3 for the final analysis of the global accessions. Sequently, three major subgroups were apparently obtained, corresponding to-I (including 53 lines),-II (including 96 lines) and-III (including 59 lines) (Fig. 1-C). A neighbor-joining tree which was constructed based on’s genetic distance (Liu and Muse, 2005) revealed genetic relationships fairly consistent with the model-based membership assignment for most accessions (the color in the neighbor-joining tree aligns with it in the STRUCTURE-based model) (Fig. 2-A). However, a few P/TGMS lines appeared as transitional type that were distributed between two adjacent types, such as, accessions in admix-I are the transitional type between-I and-II groups. From the model-based approach, the genetic components of these ‘admixture’ rice accessions were determined less than 0.72 in any of the three subgroups (Supplemental Table 2). We further confirmed the population structure with principal component analysis (PCA) (Rohlf, 1997). The three major subgroups,-I,-II and-III were clearly separated based on the first two eigenvectors (PC1, 22.67%; PC2, 17.22%) (Fig. 2-B). Based on the first and the third/fourth (PC3, 7.88%; PC4, 6.42%) eigenvectors,-I were able to be distinguished from the other subgroups, while-II could be distinguished from the others based on the second and the third/fourth eigenvectors. Taken together, our results demonstrated three major subgroups inP/TGMS lines.

Fig. 1. Model-based population assignment using STRUCTURE analysis.

Average LnP(D) (A) and Δ(B) values over five repeats of simulations withfrom 1 to 8, and subgroup divisions of all accessions as= 3 (C).

Fig. 2. Population structure of 208 Chinese two-linehybrids.

A, Neighbor-joining tree based on’s genetic distance. B, Principal component analysis.

Genetic diversity is an indicator of biology diversity. According to genetic diversity, relationship between heterozygosity and population fitness could be expected (David and Richard, 2003). In this study, among the 48 SSR markers, the marker RM176 amplified one fragment, and the others generated polymorphic fragment. A total of 268 alleles were identified in these accessions based on the rest 47 markers. The average number of alleles per locus () for the 48 markers was 5.6, varying from 1 (RM176) to 12 (RM481) (Supplemental Table 3). The markers showed a high level of availability, ranging from 88% (RM332) to 100% (as many as 17 markers). Total(’s genetic diversity index) varied greatly among the loci from 0 at RM176 to 0.8243 at RM493 with a mean value of 0.5038 (Supplemental Table 3). The PIC values derived from allelic diversity and frequency among the genotypes were not uniform for the tested markers. The PIC values varied from 0 (RM176) to 0.8010 (RM493) with an average of 0.4541 (Supplemental Table 3). In terms of genetic diversity,-II had the highest level (= 4.6,= 0.4888, PIC = 0.4460), followed by-III (= 2.9,= 0.3130, PIC = 0.2701), and-I was the lowest (= 2.3,= 0.1875, PIC = 0.1650) (Supplemental Table 4). The results showed higher diversity than previous report using 12 elite TGMS lines (Singh et al, 2011). To evaluate the genetic diversity and differentiation in the three groups ofP/TGMS lines, we analyzed 150 non-admixed lines (with membership more than 72% in any one group based on the model-based approach, Supplemental Table 2). Pairwise(population differentiation statistic) varied from 0.0879 (-I vs-III) to 0.1541 (-II vs-III). To sum up, our results indicated-II had the highest level of genetic diversity and the differentiation between-II and-III was of top difference among the three subgroups.

In recent years, hybrid rice from the cross ofandparents is getting popular. It is inferred thathybrid rice with a certain proportion ofbackground could benefit root vigor at the later stage of hybrid rice growth, with leaf function period extended and lodging resistance improved (Yang et al, 2002; Yuan, 1994a). To evaluate the sub-group components of P/TGMS lines, we added 100 typicand 100 typiccultivars (Supplemental Table 5) to the tested 208 lines and performed structure analysis according to the STRUCTURE-based model (Fig. 3). When= 2, thecomponent for the 100reference accessions was no less than 0.991, and thecomponent for the 100reference accessions was no less than 0.992. For the tested 208P/TGMS lines, they were all divided into thegroup. However, we found that 23 lines possessedcomponent less than 0.991. Among the 23P/TGMS, 5 lines (1103S, 15S, Kang 3418S, P8hS and M Pei’ai 64S) were detected withcomponent less than 0.900. One hybrid rice, Liangyou 1193, derived from 1103S, possessed the promotion area of 6.7 × 103hm2in 2010 in Hubei Province of China. Four hybrids bred with 15S as the female parent, accumulated promotion area of 4.0 × 105hm2from 2012 to 2015 in Hubei Province of China.

In summary, we performed genetic analysis using 208P/TGMS lines. Forty-eight SSR markers detected 269 alleles, with the mean number of 5.6 per marker. Total’s genetic diversity index per locus () varied widely from 0 to 0.8243 with an average value of 0.5038. The PIC values varied from 0 to 0.8010 with an average value of 0.4541. Structure calculation identified three subgroups-I,-II and-III in the present population. The genetic differentiation between-II and-III was detected as the largest one among the three subgroups.-II had the highest level of genetic diversity (= 4.6,= 0.4888, PIC = 0.4460). For/component identification, five P/TGMS lines possessedcomponents less than 0.900, which means that the genetic components of these lines were mixed with part ofclan. These results can improve our understanding of the genetic background for P/TGMS lines and will be beneficial for exploitation and better utilization in rice breeding programs.

Fig. 3./component of 208two-line hybrids with 100andreferenceaccessions.

ACKNOWLEDGEMENTS

This work was supported by the Chinese Academy of Agricultural Sciences (Grant No. CAAS-ASTIP-201X-CNRRI) and the Major Scientific and Technological Project for New Varieties Breeding of Zhejiang Province, China (Grant No. 2016C02050-6-1).

SUPPLEMENTAL DATA

The following materials are available in the online version of this article at http://www.sciencedirect.com/science/journal/ 16726308; http://www.ricescience.org.

Supplemental File 1. Materials and methods used in this study.

Supplemental Table 1. Detail information of the 48 simple sequence repeat markers used in this study.

Supplemental Table 2. Information of the 208 Chinese two-line hybrids used in this study.

Supplemental Table 3. Number of alleles per locus (),’s genetic diversity index () and polymorphism information content (PIC) for 48 SSR markers in 208 Chinese two-linehybrids.

Supplemental Table 4. Genetic diversity index of each subgroup.

Supplemental Table 5. Information of the 200 reference accessions used in this study.

Supplemental Fig. 1. Model-based population assignment withfrom 2 to 8 using STRUCTURE analysis.

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http://dx.doi.org/10.1016/j.rsci.2019.01.003

15 October 2018;

8 January 2019

Yang Yaolong (yangxiao182@126.com); Wei Xinghua (weixinghua@caas.cn)

(Managing Editor: Wang Caihong)