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. 2021 Oct 19;2021:7588652. doi: 10.1155/2021/7588652

Genetic Diversity of Shanlan Upland Rice (Oryza sativa L.) and Association Analysis of SSR Markers Linked to Agronomic Traits

Guofeng Yang 1, Yong Yang 1, Yali Guan 1, Zhixia Xu 1, Junyu Wang 1, Yong Yun 2, Xiaowei Yan 2,✉, Qingjie Tang 2,✉
PMCID: PMC8548095  PMID: 34712736

Abstract

Shanlan upland rice, a kind of unique rice germplasm in Hainan Island, was used to evaluate genetic diversity and association between SSR markers and agronomic traits. A total of 239 alleles were detected in 57 Hainan upland rice varieties using 35 SSR markers, and the number of alleles per locus was 2-19. The observed heterozygosity was 0.0655-0.3115. The Shannon diversity index was 0.1352-0.4827. The genetic similarity coefficient was 0.6736-0.9707, and 46 varieties were clustered into one group, indicating that the genetic base of the Shanlan upland rice germplasm was narrow. A total of 25 SSR markers significantly related to plant height, effective panicle number per plant, panicle length, total grain number, filled grain number, seed rating rate, and 1000-grain weight were obtained (P < 0.01), with the percentage of the total variations explained ranging from 0.12% to 42.62%. RM208 explained 42.62% of the total variations in plant height of Shanlan upland rice. RM493 was significantly associated with 6 agronomic traits. We can speculate that RM208 may flank QTLs responsible for plant height and RM493 may flank QTLs playing a fundamental role in the intertwined regulatory network of agronomic traits of Shanlan upland rice.

1. Introduction

Shanlan upland rice (Oryza sativa L.) is a type of landrace adapted to the tropical dryland climate, with strong drought resistance and good taste quality [1–3], distributed in the central and western regions of Hainan Island where Li and Miao people live. Shanlan liquor made from Shanlan glutinous rice is known as “Moutai of Li people” and well received by local people. In our previous study, the coefficients of variation of the agronomic traits including plant height, panicle length, seed setting rate, and 1000-grain weight were all more than 10%, and the coefficients of variation of the traits including effective panicle number per plant, total number of grains, and number of filled grains reached about 30%, indicating that the Shanlan upland rice germplasm has a relatively rich diversity of agronomic traits. Many excellent Shanlan upland rice varieties were found out, including 7 varieties with panicle length exceeding 30.0 cm, 3 varieties with total number of grains being more than 200.0, 10 varieties with seed setting rate exceeding 90.0%, and 23 varieties with 1000-grain weight being more than 30.0 g, which would provide excellent genetic resources for the high-yield breeding of rice [4].

Based on linkage disequilibrium (LD), the association between target traits and genetic markers or candidate gene mutations in the natural population can be identified. It is widely used in association analysis between molecular and phenotypic variation, and discovery, location, and functional analysis of genes of interest [5–7]. Simple sequence repeat (SSR) is composed of a set of 1 to 6 base sequences (motif) repeated in tandem, with high polymorphism, abundant quantity, good repeatability, and codominance [8, 9]. The Gramene website (http://www.gramene.org) has published more than 19,000 SSR markers in rice, which are commonly used in rice genetic diversity studies, germplasm evaluation, genetic map construction, target trait gene location, and cloning.

In previous studies, only few Shanlan upland rice varieties were used in the analyses of the genetic diversity [1, 10]. No report on association analysis between SSR markers and agronomic traits of the Shanlan upland rice germplasm was found. The objectives of this present study were to use 57 Shanlan upland rice varieties to evaluate genetic diversity and analyze association between SSR markers and agronomic traits.

2. Materials and Methods

2.1. Materials and Experimental Site

A collection consisting of 57 Shanlan upland rice accessions was used in this study, which including landraces and other breeding varieties collected from the central and western regions of Hainan Island during 2013–2017 (see Table 1). From 2015 to 2017, all accessions were grown in the Yongfa Base of Hainan Academy of Agricultural Sciences in Chengmai County, Hainan Province, and Tropical Crop Field in Yinggen Town, Qiongzhong County, Hainan Province, and were planted around the Dragon Boat Festival in a direct-seeding way, with shallow soil cover. 100 plants of each accession were planted with 25 cm of row spacing and 30 cm of plant spacing. The conventional management of upland rice planting was performed.

Table 1.

Source and subspecies of 57 Shanlan upland rice accessions.

No. Source Subspecies No. Source Subspecies
M1 Qiongzhong County Japonica M30 Qiongzhong County Indica
M2 Qiongzhong County Japonica M31 Qiongzhong County Indica
M3 Baisha County Japonica M32 Qiongzhong County Japonica
M4 Qiongzhong County Japonica M33 Qiongzhong County Indica
M5 Baisha County Indica M34 Qiongzhong County Indica
M6 Baisha County Japonica M35 Wuzhishan City Japonica
M7 Qiongzhong County Japonica M36 Wuzhishan City Japonica
M8 Qiongzhong County Indica M37 Wuzhishan City Japonica
M9 Qiongzhong County Japonica M38 Ledong County Japonica
M10 Qiongzhong County Indica M39 Ledong County Japonica
M11 Qiongzhong County Indica M40 Ledong County Japonica
M12 Qiongzhong County Indica M41 Ledong County Indica
M13 Qiongzhong County Japonica M42 Ledong County Japonica
M14 Qiongzhong County Indica M43 Ledong County Japonica
M15 Qiongzhong County Japonica M44 Ledong County Japonica
M16 Qiongzhong County Japonica M45 Dongfang City Indica
M17 Qiongzhong County Indica M46 Dongfang City Indica
M18 Baisha County Indica M47 Dongfang City Indica
M19 Qiongzhong County Japonica M48 Dongfang City Indica
M20 Qiongzhong County Japonica M49 Dongfang City Indica
M21 Qiongzhong County Japonica M50 Dongfang City Indica
M22 Baisha County Japonica M51 Dongfang City Indica
M23 Qiongzhong County Japonica M52 Dongfang city Indica
M24 Qiongzhong County Japonica M53 Baoting County Japonica
M25 Ledong County Japonica M54 Baoting County Japonica
M26 Ledong County Japonica M55 Baoting County Japonica
M27 Baisha County Indica M56 Ledong County Japonica
M28 Baisha County Indica M57 Ledong County Japonica
M29 Qiongzhong County Indica
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2.2. Agronomic and Molecular Methods in the Study

Ten plants were selected at random from each accession and evaluated for 7 agronomic traits including plant height, effective panicle number per plant, panicle length, total number of grains per panicle, number of filled grains per panicle, seed setting rate, and 1000-grain weight. Analysis of variance (ANOVA) was performed using SPSS 19.0 software.

A total of 48 SSR markers distributed on 12 chromosomes of rice were used to survey the Shanlan upland rice germplasm for genetic diversity (see Table 2). The forward fluorescent primers of SSR markers were filled with FAM (blue) fluorescent dye, and synthesized by the BGI (Guangzhou) Company. The reverse nonfluorescent primers were synthesized by the Shenggong (Shanghai) Company.

Table 2.

SSR markers used in study.

No. SSR marker Sequence (5′ to 3′) Annealing temperature (°C) Size of common polymorphic fragments (bp)
1 RM583 Forward: agatccatccctgtggagag
Reverse: gcgaactcgcgttgtaatc		 55 179, 189, 192, 195, 198
2 RM7l Forward: ctagaggcgaaaacgagatg
Reverse: gggtgggcgaggtaataatg		 55 121, 139, 148, 213
3 RM85 Forward: ccaaagatgaaacctggattg
Reverse: gcacaaggtgagcagtcc		 55 79, 94, 100, 103
4 RM471 Forward: acgcacaagcagatgatgag
Reverse: gggagaagacgaatgtttgc		 55 104, 106, 114
5 RM274 Forward: cctcgcttatgagagcttcg
Reverse: cttctccatcactcccatgg		 55 149, 161
6 RM190 Forward: ctttgtctatctcaagacac
Reverse: ttgcagatgttcttcctgatg		 55 107, 119, 121
7 RM336 Forward: cttacagagaaacggcatcg
Reverse: gctggtttgtttcaggttcg		 55 141, 144, 151, 154, 160, 163, 165, 192
8 RM72 Forward: ccggcgataaaacaatgag
Reverse: gcatcggtcctaactaaggg		 55 149, 159, 162, 165
9 RM2l9 Forward: cgtcggatgatgtaaagcct
Reverse: catatcggcattcgcctg		 55 194, 196, 215, 221
10 RM311 Forward: tggtagtataggtactaaacat
Reverse: tcctatacacatacaaacatac		 55 160, 166, 170, 182
11 RM209 Forward: atatgagttgctgtcgtgcg
Reverse: caacttgcatcctcccctcc		 55 125, 132, 151, 153, 160
12 RM19 Forward: caaaaacagagcagatgac
Reverse: ctcaagatggacgccaaga		 55 216, 247, 250, 253
13 RM1195 Forward: atggaccacaaacgaccttc
Reverse: cgactcccttgttcttctgg		 55 142, 144, 146, 148, 150, 152
14 RM208 Forward: tctgcaagccttgtctgatg
Reverse: taagtcgatcattgtgtggacc		 55 162, 164, 172, 176, 178
15 RM232 Forward: ccggtatccttcgatattgc
Reverse: ccgacttltcctcclgacg		 55 141, 150, 156, 159, 161
16 RM119 Forward: catccccctgctgctgctgctg
Reverse: cgccggatgtgtgggactagcg		 67 166, 169
17 RM267 Forward: tgcagacatagagaaggaagtg
Reverse: agcaacagcacaacttgatg		 55 136, 138, 153, 155
18 RM253 Forward: tccttcaagagtgcaaaacc
Reverse: gcattgtcatgtcgaagcc		 55 213, 245
19 RM481 Forward: tagctagccgattgaatggc
Reverse: ctccacctcctatgttgttg		 55 135, 138, 141, 144, 147, 177, 188
20 RM339 Forward: gtaatcgatgctgtgggaag
Reverse: gagtcatgtgatagccgatatg		 55 140, 146, 158
21 RM278 Forward: gtagtgagcctaacaataatc
Reverse: tcaactcagcatctctgtcc		 55 59, 139, 141, 143
22 RM258 Forward: tgctgtatgtagctcgcacc
Reverse: tggcctttaaagctgtcgc		 55 128, 132, 136, 146
23 RM224 Forward: atcgatcgatcttcacgagg
Reverse: tgctataaaaggcattcggg		 55 120, 128, 131, 143, 153, 155, 157
24 RM17 Forward: tgccctgttattttcttctctc
Reverse: ggtgatcctttcccatttca		 55 153, 158, 182, 184
25 RM493 Forward: tagctccaacaggatcgacc
Reverse: gtacgtaaacgcggaaggtg		 55 221, 236, 245
26 RM561 Forward: gagctgttttggactacggc
Reverse: gagtagctttctcccacccc		 55 60, 185, 187, 193, 268, 270
27 RM8277 Forward: agcacaagtaggtgcatttc
Reverse: atttgcctgtgatgtaatagc		 55 165, 187, 190, 193, 196
28 RM551 Forward: agcccagactagcatgattg
Reverse: gaaggcgagaaggatcacag		 55 182, 184, 186, 188, 192, 194, 196
29 RM598 Forward: gaatcgcacacgtgatgaac
Reverse: atgcgactgatcggtactcc		 55 153, 156, 162
30 RMl76 Forward: cggctcccgctacgacgtctcc
Reverse: agcgatgcgctggaagaggtgc		 67 133, 136
31 RM432 Forward: ttctgtctcacgctggattg
Reverse: agctgcgtacgtgatgaatg		 55 166, 178, 186
32 RM331 Forward: gaaccagaggacaaaaatgc
Reverse: catcatacatttgcagccag		 55 63, 92, 150, 152, 158, 172
33 OSR28 Forward: agcagctatagcttagctgg
Reverse: actgcacatgagcagagaca		 55 136, 174, 177, 180, 183
34 RM590 Forward: catctccgctctccatgc
Reverse: ggagttggggtcttgttcg		 55 136, 143
35 RM21 Forward: acagtattccgtaggcacgg
Reverse: gctccatgagggtggtagag		 55 128, 132, 147, 158, 160
36 RM3331 Forward: cctcctccatgagctaatgc
Reverse: aggaggagcggatttctctc		 50 110, 122, 124, 126
37 RM443 Forward: gatggttttcatcggctacg
Reverse: agtcccagaatgtcgtttcg		 55 115, 119, 121, 123
38 RM490 Forward: atctgcacactgcaaacacc
Reverse: agcaagcagtgctttcagag		 55 93, 99, 103
39 RM424 Forward: tttgtggctcaccagttgag
Reverse: tggcgcattcatgtcatc		 55 240, 277, 280
40 RM423 Forward: agcacccatgccttatgttg
Reverse: cctttttcagtagccctccc		 55 269, 286, 293, 299
41 RM571 Forward: ggaggtgaaagcgaatcatg
Reverse: cctgctgctctttcatcagc		 55 54, 180, 189, 191
42 RM231 Forward: ccagattatttcctgaggtc
Reverse: cacttgcatagttctgcattg		 55 178, 180, 182, 184, 186, 188
43 RM567 Forward: atcagggaaatcctgaaggg
Reverse: ggaaggagcaatcaccactg		 55 244, 246, 248, 250, 252
44 RM289 Forward: ttccatggcacacaagcc
Reverse: ctgtgcacgaacttccaaag		 55 87, 106
45 RM542 Forward: tgaatcaagcccctcactac
Reverse: ctgcaacgagtaaggcagag		 55 87, 89, 111
46 RM316 Forward: ctagttgggcatacgatggc
Reverse: acgcttatatgttacgtcaac		 55 165, 182, 184, 186, 196, 198, 200, 213
47 RM332 Forward: gcgaaggcgaaggtgaag
Reverse: catgagtgatctcactcaccc		 55 164, 167, 169, 176
48 RM7102 Forward: taggagtgtttagagtgcca
Reverse: tcggtttgcttatacatcag		 55 170, 175, 187
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Using the Plant Genomic DNA Rapid Extraction Kit produced by the Shenggong (Shanghai) Company, the genomic DNA was extracted from 50 to 100 mg of the fresh tender leaves collected and sampled from individual plants of the accessions at the seedling stage as a template. The PCR reactions were carried out in a reaction solution of 10 μL containing 1 μL of the template DNA (50~100 ng), 0.2 μL of each primer (10 μmol/L), 5 μL of the 2x EasyTaq® PCR SuperMix produced by TransGen Biotech Company, and 3.6 μL of ddH2O. The PCR amplification reactions were performed at the following cycle profile: initial denaturation at 94°C for 4 min, 30 cycles of 45 s denaturation at 94°C, 45 s annealing at 50~67°C, 1 min extension at 72°C, followed by 8 min at 72°C for the final extension. The amplified products were submitted to the BGI (Wuhan) Company for capillary electrophoresis by the ABI 3730xl Genetic Analyzer, and the original data was collected using Data Collection software.

A 1/0 matrix was constructed based on the presence and absence of alleles. The presence was denoted as 1 and absence as 0. The genetic diversity parameters such as number of alleles per locus, observed heterozygosity (Ho), and Shannon's diversity index (I) were estimated using the program Popgene 1.32. The genetic similarity coefficients among the accessions were calculated using NTSYS 2.1 software. The cluster analysis was carried out usying the UPGMA and SHAN methods. The population structure was estimated using Structure 2.2 software.

Association analyses were carried out using Tassel 2.1 software. The maximum of L(K) was identified as the optimum number of the subpopulation, and the structure matrix (Q) was extracted from the membership probability of each genotype for the mixed linear model (MLM) analysis.

3. Results

3.1. Genetic Diversity Analysis

35 polymorphic SSR markers selected from a total of 48 SSR markers were used to screen 57 Shanlan upland rice accessions. As shown in Table 3, a total of 239 alleles were detected. A couple of allele report images are shown in Figure 1. The number of alleles per locus varied from 2 to 19 with an average of 6.8. The observed heterozygosity ranged from 0.0655 to 0.3115 with an average of 0.1702. The Shannon diversity index ranged from 0.1352 to 0.4827 with an average of 0.2826.

Table 3.

Genetic diversity parameters of SSR loci used for genotyping in Shanlan upland rice accessions.

No. SSR loci Number of alleles Observed heterozygosity Shannon's diversity index
1 RM583 5.0 0.1855 0.3234
2 RM490 7.0 0.1378 0.2304
3 RM443 4.0 0.3115 0.4827
4 RM493 8.0 0.1032 0.1793
5 RM424 6.0 0.1270 0.2177
6 RM423 5.0 0.1999 0.3399
7 RM561 7.0 0.2134 0.3524
8 RM208 11.0 0.0847 0.1554
9 RM71 5.0 0.1629 0.2699
10 RM231 7.0 0.2015 0.3357
11 RM571 6.0 0.2269 0.3582
12 RM8277 6.0 0.1683 0.2887
13 RM85 4.0 0.1884 0.3094
14 RM567 9.0 0.1461 0.2425
15 RM551 10.0 0.1409 0.2473
16 RM471 3.0 0.2688 0.4192
17 RM274 2.0 0.2948 0.4573
18 RM267 5.0 0.1944 0.3270
19 RM190 5.0 0.1845 0.2956
20 RM253 5.0 0.1584 0.2498
21 RM432 4.0 0.2004 0.3204
22 RM481 19.0 0.0655 0.1352
23 RM336 13.0 0.0797 0.1608
24 RM331 7.0 0.1889 0.3235
25 RM72 5.0 0.1867 0.3151
26 RM316 10.0 0.2073 0.3366
27 OSR28 8.0 0.1231 0.2174
28 RM278 6.0 0.2505 0.3817
29 RM219 7.0 0.1322 0.2273
30 RM590 5.0 0.1482 0.2430
31 RM332 6.0 0.1448 0.2467
32 RM21 10.0 0.0935 0.1681
33 RM7102 5.0 0.1644 0.2708
34 RM3331 8.0 0.1191 0.2088
35 RM17 6.0 0.1540 0.2550
Mean 6.8 0.1702 0.2826
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Figure 1.

Figure 1

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Allele report based on capillary electrophoresis. (a) SSR marker RM85 was used to survey Shanlan upland rice accession M36. Two alleles were detected and denoted as 79 and 103. (b) SSR marker RM336 was used to survey Shanlan upland rice accession M31. Two alleles were detected and denoted as 125 and 154.

3.2. Genetic Similarity Coefficient and Cluster Analysis

The genetic similarity coefficients of 57 Shanlan upland rice accessions ranged from 0.6736 to 0.9707 with an average of 0.7889. The dendrogram resulting from the distance-based analysis of 57 accessions with Jaccard's genetic distance is shown in Figure 2. 57 accessions were classified into 3 clades with a genetic similarity coefficient of 0.75. Clade 1 included 46 accessions, such as M1, M3, and M6, which were classified into 6 subclades. The accession M31 constituted Clade 2 alone. Clade 3 included 10 accessions, such as M5, M7, and M53.

Figure 2.

Figure 2

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Neighbor-joining cluster analysis for Shanlan upland rice accessions. Subclade 1A: M1, M3, M6, M19, M26, M34, M25, and M32. Subclade 1B: M2, M21, M4, M14, M23, M24, M35, and M39. Subclade 1C: M8, M10, M11, M17, M29, M16, M9, M13, M27, M28, M41, M42, M44, M15, M22, M12, M33, M18, and M20. Subclade 1D: M30 and M43. Subclade 1E: M38. Subclade 1F: M36, M37, M57, M40, M50, M51, M49, and M56. Clade 2: M31. Clade 3: M5, M7, M53, M54, M46, M47, M45, M55, M48, and M52.

3.3. Population Structure Analysis

The likelihood value of this analysis is shown in Figure 3. The likelihood was maximum at 2 of K value and then decreased, after which it became almost constant. Therefore, the structure results of K = 2 were considered the best possible partition. Using Structure 2.2 software, the posterior probability of each accession was calculated, and 57 Shanlan upland rice accessions were divided into 2 subpopulations. The population structure diagram is shown in Figure 4. Subpopulation 1 included 37 accessions: M1, M2, M3, M4, M6, M8, M9, M10, M11, M12, M13, M14, M15, M16, M17, M18, M19, M20, M21, M22, M23, M24, M25, M26, M27, M28, M29, M30, M32, M33, M34, M35, M39, M41, M42, M43, and M44. Subpopulation 2 included 20 accessions: M5, M7, M31, M36, M37, M38, M40, M45, M46, M47, M48, M49, M50, M51, M52, M53, M54, M55, M56, and M57.

Figure 3.

Figure 3

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Estimation of population in Shanlan upland rice accessions.

Figure 4.

Figure 4

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Population structure of Shanlan upland rice accessions.

Comparing the results of population structure analysis with cluster analysis, it was found that the accessions contained in Subpopulation 1 were consistent with those contained in Subclade 1A, Subclade 1B, Subclade 1C, and Subclade 1D. Subclade 1E, Subclade 1F, Clade 2, and Clade 3 belonged to Subpopulation 2.

3.4. Association Analysis

The details of the agronomic traits of 57 Shanlan upland rice accessions are shown in Table 4. The analysis of variance revealed significant differences (P < 0.05) among 57 accessions for 7 agronomic traits, respectively.

Table 4.

Details of agronomic traits of Shanlan upland rice accessions.

No. PH (cm) PN PL (cm) TG FG SR (%) TW (g)
M1 134.8 9.5 24.5 91.9 78.9 85.9 30.8
M2 147.8 8.4 25.6 94.6 85.7 90.6 27.5
M3 147.0 6.7 28.0 146.1 122.9 84.1 30.2
M4 154.0 8.2 26.3 126.4 116.6 92.2 29.0
M5 152.0 9.1 26.6 103.1 92.2 89.4 30.6
M6 136.2 8.4 25.9 102.5 87.9 85.8 30.3
M7 141.8 10.2 25.3 90.0 76.5 85.0 31.9
M8 156.6 12.6 28.3 103.5 85.9 83.0 33.2
M9 136.5 8.3 26.9 112.4 99.1 88.2 34.5
M10 148.7 9.7 25.8 87.3 69.4 79.5 28.2
M11 168.3 9.0 29.7 144.4 131.0 90.7 27.2
M12 164.0 11.7 26.3 137.0 121.8 88.9 31.4
M13 170.7 12.0 24.3 85.6 78.4 91.6 25.2
M14 175.0 11.0 25.9 104.3 84.6 81.1 28.7
M15 169.7 9.8 27.4 104.0 96.0 92.3 32.1
M16 156.3 10.3 29.4 140.9 105.9 75.2 30.6
M17 160.0 8.1 24.9 102.8 83.6 81.3 27.8
M18 137.3 6.0 29.0 95.2 61.0 64.1 24.2
M19 154.3 8.0 24.6 104.0 93.6 90.0 29.0
M20 159.7 8.0 28.6 108.6 95.4 87.8 27.4
M21 160.7 9.0 23.2 94.2 79.2 84.1 27.0
M22 144.3 7.0 26.6 133.0 104.4 78.5 28.0
M23 146.7 10.0 28.8 112.4 75.2 66.9 30.4
M24 151.0 8.0 29.0 115.2 97.2 84.4 29.0
M25 148.3 6.0 33.2 153.6 102.8 66.9 28.9
M26 152.7 7.0 30.2 124.0 75.4 60.8 29.0
M27 158.7 11.0 27.0 113.8 82.4 72.4 25.6
M28 160.7 9.0 27.8 131.0 70.0 53.4 28.0
M29 139.0 9.0 28.2 99.2 86.8 87.5 31.4
M30 155.7 7.0 27.2 195.8 131.4 67.1 24.2
M31 158.3 13.0 29.4 151.6 125.6 82.8 26.2
M32 162.7 11.0 27.4 118.8 92.6 77.9 30.0
M33 152.7 7.0 26.2 99.6 71.4 71.7 26.4
M34 162.0 11.0 29.2 144.6 129.8 89.8 25.8
M35 157.8 8.0 27.4 118.2 113.0 95.6 25.4
M36 135.8 14.0 28.3 196.0 162.0 82.7 17.7
M37 159.2 6.0 29.4 163.2 78.2 47.9 24.0
M38 143.2 7.0 28.7 170.6 107.0 62.7 30.6
M39 157.2 4.0 26.4 124.5 113.3 91.0 20.5
M40 153.1 5.0 31.4 189.2 166.4 87.9 23.6
M41 142.1 6.0 26.0 107.7 90.0 83.6 32.0
M42 156.1 5.0 27.3 174.8 151.2 86.5 31.4
M43 139.2 4.0 32.0 243.0 115.0 47.3 31.4
M44 149.5 5.0 24.8 141.8 101.4 71.5 30.4
M45 132.0 6.0 24.8 119.7 60.5 50.6 22.0
M46 145.0 5.0 26.5 184.2 148.2 80.5 34.8
M47 167.1 10.0 29.5 177.2 161.2 91.0 29.0
M48 139.2 9.0 29.3 180.0 157.4 87.4 31.2
M49 133.5 8.0 23.1 239.6 226.0 94.3 23.1
M50 157.5 6.0 31.3 182.7 111.3 60.9 33.5
M51 133.0 8.0 22.9 150.3 129.4 86.1 22.8
M52 147.5 4.0 34.1 188.5 107.0 56.8 24.0
M53 99.2 10.0 21.0 164.8 123.3 74.8 23.3
M54 123.0 7.0 25.1 205.9 153.3 74.5 23.2
M55 173.5 11.0 25.8 128.3 95.1 74.1 36.1
M56 86.3 5.0 19.0 84.2 67.6 80.3 21.0
M57 100.0 3.0 19.6 62.4 54.8 87.8 23.1
P 0.000 0.046 0.000 0.000 0.000 0.000 0.000
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PH: plant height; PN: effective panicle number per plant; PL: panicle length; TG: total number of grains; FG: number of filled grains; SR: seed setting rate; TW: 1000-grain weight; P: levels of probability for significant differences between data within each column.

A total of 25 SSR markers significantly associated with agronomic traits such as plant height, effective panicle number per plant, panicle length, total grain number, filled grain number, seed setting rate, and 1000-grain weight were detected, with the percentage of total variations explained ranging from 0.12% to 42.62% (P < 0.01) (see Table 5). Of them, RM208 explained 42.62% of total variations in plant height of Shanlan upland rice. The locations of the associated SSR markers on 12 chromosomes of rice are shown in Figure 5 according to Cornell SSR 2001 (https://archive.gramene.org/). The SSR markers significantly associated with each agronomic trait of the Shanlan upland rice germplasm were all distributed on multiple chromosomes. There were many SSR markers significantly linked to 2 or more agronomic traits, respectively. For example, 8 markers were significantly associated with 2 traits, 3 markers with 3 traits, and 3 markers with 4 traits. In particular, RM493 was significantly associated with 6 traits.

Table 5.

Percentage of total variations explained by SSR markers linked to agronomic traits of Shanlan upland rice accessions (%).

No. SSR marker Agronomic traits
PH PN PL TG FG SR TW
1 OSR28 17.93 12.45
2 RM17 10.20 11.40 24.11
3 RM190 9.50 10.42
4 RM208 42.62 20.63 10.26
5 RM21 10.28 16.56 23.19
6 RM219 10.31 12.71
7 RM253 17.93 12.45 18.09 12.88
8 RM267 9.71
9 RM278 11.59
10 RM331 10.43
11 RM332 12.36 22.52
12 RM3331 9.54
13 RM336 14.43
14 RM423 15.81
15 RM424 10.31
16 RM481 28.67 12.43 19.16 13.55
17 RM493 11.97 11.74 13.22 15.10 14.21 19.64
18 RM567 17.93 12.45 11.95 24.61
19 RM571 20.66
20 RM583 0.12
21 RM590 14.80 16.98
22 RM71 17.93 12.45
23 RM7102 11.59
24 RM72 12.66 14.27
25 RM85 24.18 9.44
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PH: plant height; PN: effective panicle number per plant; PL: panicle length; TG: total number of grains; FG: number of filled grains; SR: seed setting rate; TW: 1000-grain weight.

Figure 5.

Figure 5

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Map locations of the SSR markers linked to agronomic traits of Shanlan upland rice accessions. PH: plant height. PN: effective panicle number per plant. PL: panicle length. TG: total number of grains. FG: number of filled grains. SR: seed setting rate. TW: 1000-grain weight.

4. Discussion

Shanlan upland rice is a kind of unique rice germplasm in Hainan Island. So, it is essential to analyze its genetic diversity and explore its application in rice breeding. Through the sequence analysis of SSII, ITS, Ehd1, ndhC-trnV, and cox3 genes, Yuan et al. have found that the genetic diversity of 14 Shanlan upland rice varieties was lower than that of Asian cultivated rice and the common wild rice [1]. Wang et al. have analyzed the genetic diversity of 23 Shanlan upland rice varieties using 22 RAPD primers and found that the genetic similarity coefficients ranged from 0.881 to 0.952 [10]. In this study, a total of 239 alleles were detected in 57 Hainan upland rice varieties using 35 SSR markers, and the number of alleles per locus varied from 2 to 19 with an average of 6.8. The genetic similarity coefficient of 57 Shanlan upland rice varieties ranged from 0.6736 to 0.9707 with an average of 0.7889, and 46 varieties were clustered into one group, indicating that the genetic base of the Shanlan upland rice germplasm is narrow, which is similar to the results of previous studies [1, 10]. The low genetic diversity of the Shanlan upland rice germplasm may be caused by factors such as the relatively single geographic origin and the long-term continuous selection of Li and Miao people.

In this study, 57 accessions were classified into 3 clades, and Clade 1 was further classified into 6 subclades through cluster analysis. Through population structure analysis, 57 accessions were divided into 2 subpopulations. Subclade 1A, Subclade 1B, Subclade 1C, and Subclade 1D belonged to Subpopulation 1. Subclade 1E, Subclade 1F, Clade 2, and Clade 3 belonged to Subpopulation 2. Subclade 1A included 8 accessions, all of which belonged to the japonica subspecies except for M34. Subclade 1B included 8 accessions, all of which belonged to the japonica subspecies except for M14. Subclade 1C included 19 accessions, of which 8 accessions belonged to the japonica subspecies and 11 accessions belonged to the indica subspecies. Subclade 1D included 2 accessions, one of which belonged to the japonica subspecies and the other belonged to the indica subspecies. Subclade 1E included 1 accession, which belonged to the japonica subspecies. Subclade 1F included 8 accessions, of which 5 accessions belonged to the japonica subspecies and 3 accessions belonged to the indica subspecies. Clade 2 included 1 accession, which belonged to the indica subspecies. Clade 3 included 10 accessions, of which 4 accessions belonged to the japonica subspecies and 6 accessions belonged to the indica subspecies. Most of the accessions of some subclades belonged to the japonica subspecies. However, the indica subspecies and the japonica subspecies were mixed in most clades and subclades. From the perspective of geographic origin, clades and subclades were not concentratedly distributed, and the difference in their geographic origin was not obvious. Zheng et al. have used five indicators such as glume hair, grain phenol reaction, 1 to 2 internode length below the spike, grain length/width ratio, and chaff color at heading to detect the species margin of Shanlan upland rice accessions and found that most of the accessions belong to the japonica subspecies [11]. We can speculate that the subspecies structure of Shanlan upland rice has changed in the past two decades, and the proportion of the indica subspecies has increased. The area of Hainan Island is not large, and the geographical and climatic conditions, such as altitude, temperature, and sunshine, are very similar in the areas where Shanlan upland rice is cultivated. In addition, the frequent exchanges between the Li and Miao ethnic groups have made the geographical boundaries of different Shanlan upland rice accessions increasingly blurred.

Rice agronomic traits are mostly quantitative traits, controlled by multiple genes. Known rice plant height QTLs exist on each chromosome of rice, and the mapping results and the effect value of the same QTL in different studies are different [12]. Currently, nearly 90 rice dwarf genes have been discovered, and most of them are phytohormone biosynthesis defective mutations or signal transduction defective mutations [13]. Liu et al. have cloned the THIS1 gene on rice chromosome 1 that affects tillering of rice [14]. Jiao et al. have mapped the rice tiller number QTL on chromosome 8, and finally cloned the IPA1 (WFP) gene that affects tillering of rice [15]. Yan et al. and Kong et al. have mapped the rice erect panicle QTL between RM3700 and RM7424 on chromosome 9, and then Huang et al. cloned the DEP1 gene, the mutation of which enhances the vigor of meristems and leads to the lengthening of internodes of inflorescence, the increase of panicle length and number of grains per panicle [16–18]. Ashikari et al. have cloned the Gn1a gene that controls the number of grains per panicle from rice chromosome 1. When Gn1a expression decreases, cytokinins would accumulate in the inflorescence meristems, thereby increasing the number of reproductive organs and grains per panicle [19]. Rice grain weight is greatly affected by grain shape. GW2, GS3, GL3, and other genes are the major genes that control rice grain weight [20–22].

In this study, a total of 25 SSR markers significantly related to plant height, effective panicle number per plant, panicle length, total grain number, filled grain number, seed rating rate, and 1000-grain weight were obtained (P < 0.01), with the percentage of total variations explained ranging from 0.12% to 42.62%. 12 SSR markers distributed on 9 chromosomes were significantly associated with plant height. RM208 explained 42.62% of the total variations in plant height. We can speculate that RM208 may flank QTLs responsible for plant height. Four SSR markers distributed on chromosomes 1, 2, 7, and 8 were significantly associated with the effective panicle number per plant that were similar to the results of Liu et al. and Jiao et al. partly [14, 15]. 10 SSR markers distributed on 8 chromosomes were significantly associated with panicle length. 15 SSR markers distributed on 10 chromosomes were significantly associated with the total number of grains or the number of filled grains. Five SSR markers distributed on chromosomes 9, 10, and 12 were significantly associated to 1000-seed weight. No marker associated with 1000-grain weight mentioned by previous reports was found on chromosomes 2 and 3 [20–22]. It may be related to the germplasm specificity of Shanlan upland rice and needs further study.

In this study, the SSR markers associated with each agronomic trait of Shanlan upland rice were all distributed on multiple chromosomes, which proves to a certain extent that these agronomic traits were regulated by multiple genes. On the other hand, this study also found that many SSR markers were significantly associated with 2 or more agronomic traits. RM493 was significantly associated with 6 agronomic traits. We can speculate that RM493 may flank QTLs playing a fundamental role in the intertwined regulatory network of agronomic traits of Shanlan upland rice. The genes encoding protein GFS12 (LOC4326972), protein transport protein SEC23 (LOC4326988), and probable 2-oxoglutarate-dependent dioxygenase AOP1.2 (LOC112939546), which may play a role in the regulation of the agronomic traits of Shanlan upland rice, are located in chromosome 1 close to RM493 [23–25]. These genes are worthy of further study.

5. Conclusion

A total of 239 alleles were detected in 57 Hainan upland rice varieties using 35 SSR markers, and the number of alleles per locus was 2-19. The observed heterozygosity was 0.0655-0.3115. The Shannon diversity index was 0.1352-0.4827. The genetic similarity coefficient was 0.6736-0.9707, and 46 varieties were clustered into one group, indicating that the genetic base of the Shanlan upland rice germplasm was narrow. A total of 25 SSR markers significantly related to plant height, effective panicle number per plant, panicle length, total grain number, filled grain number, seed rating rate, and 1000-grain weight were obtained (P < 0.01), with the percentage of the total variations explained ranging from 0.12% to 42.62%. RM208 explained 42.62% of total variations in plant height of Shanlan upland rice. RM493 was significantly associated with 6 agronomic traits. We can speculate that RM208 may flank QTLs responsible for plant height and RM493 may flank QTLs playing a fundamental role in the intertwined regulatory network of the agronomic traits of Shanlan upland rice.

Acknowledgments

This work was supported by the Technical Innovation Professional Project of the Provincial Scientific Research Institutes in Hainan Province (jscx202003), Hainan Province Natural Science Foundation of China (317117), Haikou Integration Station of China Agriculture Research System (CARS-01-94), and the Conservation Project of Species Resources (111821301354052033).

Contributor Information

Xiaowei Yan, Email: yxwei-888@163.com.

Qingjie Tang, Email: flyingfoxtqj@163.com.

Data Availability

Data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

There are no conflicts of interest to disclose.

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Data Availability Statement

Data used to support the findings of this study are available from the corresponding author upon request.

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