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Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes

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  • Dichondra (Dichondra repens) is an important ground cover plant and is also used as a herbal medicine in China. Objectives of this study were to evaluate phenotypic and genetic diversities among 33 genotypes by using 18 simple sequence repeat (SSR) markers and to further identify the drought tolerance of these germplasms based on five physiological parameters. Results showed that natural variations in phenotypes including plant height, leaf area, leaf thickness, and petiole length were observed among 33 genotypes under well-watered conditions. All 18 SSR primer pairs were found to be polymorphic and significant genetic variation was found in these genotypes. In addition, there were obvious differences in leaf relative water content (RWC), electrolyte leakage (EL), chlorophyll (Chl) content, photochemical efficiency (Fv/Fm), and performance index on absorption basis (PIABS) among 33 genotypes in response to a prolonged period of drought stress (46 d). Drought tolerance of 33 genotypes was then ranked by using subordinate function value analysis (SFVA) and the most drought-tolerant or -sensitive genotypes were identified as Dr5 or Dr29, respectively. Principal component analysis (PCA) further classified 33 genotypes into group I (drought-tolerant), group II (drought-sensitive), and group III (medium types). Current findings showed that 18 selected SSR primers could be potentially used to analyze genetic diversity and varietal identification in dichondra species. Drought-tolerant wild dichondra resources provide a rich genetic base for breeding of new cultivars.
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  • Table S1 SSR primer sequences.
  • [1]

    Harrington KC, Hartley MJ, Rahman A, James TK. 2005. Long term ground cover options for apple orchards. New Zealand Plant Protection 58:164−68

    doi: 10.30843/nzpp.2005.58.4323

    CrossRef   Google Scholar

    [2]

    Shaabani SM, Hatamzadeh A, Biglouei MH. 2018. Improving drought tolerance of two species of cover crop dichondra and lysimachia by spraying trinexapac-ethyl. Acta Horticulturae 1190:163−70

    doi: 10.17660/actahortic.2018.1190.28

    CrossRef   Google Scholar

    [3]

    Hartley MJ, Rahman A, Harrington KC, James TK. 2000. Assessing ground covers in a newly planted apple orchard. New Zealand Plant Protection 53:22−27

    doi: 10.30843/nzpp.2000.53.3643

    CrossRef   Google Scholar

    [4]

    Harrington KC, Anderson BJ, Cameron EA. 2002. Establishment techniques for dichondra ground covers in orchards. New Zealand Plant Protection 55:202−6

    doi: 10.30843/nzpp.2002.55.3890

    CrossRef   Google Scholar

    [5]

    Harrington K, Zhang T, Osborne M, Rahman A. 1999. Orchard weed control with Dichondra micrantha ground covers. Twelfth Australian Weeds Conference, Australian, 1999. pp. 250−54

    [6]

    Sheu MJ, Deng JS, Huang MH, Liao JC, Wu CH, Huang SS, Huang GJ. 2012. Antioxidant and anti-inflammatory properties of Dichondra repens Forst and its reference compounds. Food Chemistry 132:1010−18

    doi: 10.1016/j.foodchem.2011.09.140

    CrossRef   Google Scholar

    [7]

    Yao Q, Wang Y, Dong Z, Lai C, Chang B, et al. 2020. Dichondra repens J.R.Forst. and G.Forst.: A review of its traditional uses, chemistry, pharmacology, toxicology and applications. Frontiers in Pharmacology 11:608199

    doi: 10.3389/fphar.2020.608199

    CrossRef   Google Scholar

    [8]

    Wu J, Qiu P, Yong L, Yang X, Lin L, et al. 2009. Essential oil composition and antibacterial activity of Dichondra repens. Chemistry of Natural Compounds 45:572

    doi: 10.1007/s10600-009-9370-6

    CrossRef   Google Scholar

    [9]

    Fahad S, Bajwa AA, Nazir U, Anjum SA, Farooq A, et al. 2017. Crop production under drought and heat stress: plant responses and management options. Frontiers in Plant Science 8:1147

    doi: 10.3389/fpls.2017.01147

    CrossRef   Google Scholar

    [10]

    Garcia AA, Benchimol LL, Barbosa AM, Geraldi IO, Souza Jr CL, et al. 2004. Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies in tropical maize inbred lines. Genetics and Molecular Biology 27:579−88

    doi: 10.1590/S1415-47572004000400019

    CrossRef   Google Scholar

    [11]

    Morgante M, Hanafey M, Powell W. 2002. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nature Genetics 30:194−200

    doi: 10.1038/ng822

    CrossRef   Google Scholar

    [12]

    Varshney RK, Chabane K, Hendre PS, Aggarwal RK, Graner A. 2007. Comparative assessment of EST-SSR, EST-SNP and AFLP markers for evaluation of genetic diversity and conservation of genetic resources using wild, cultivated and elite barleys. Plant science 173:638−649

    doi: 10.1016/j.plantsci.2007.08.010

    CrossRef   Google Scholar

    [13]

    Powell W, Morgante M, Andre C, Hanafey M, Vogel J, et al. 1996. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Molecular Breeding 2:225−38

    doi: 10.1007/BF00564200

    CrossRef   Google Scholar

    [14]

    Kumar M, Choi JY, Kumari N, Pareek A, Kim SR. 2015. Molecular breeding in Brassica for salt tolerance: importance of microsatellite (SSR) markers for molecular breeding in Brassica. Frontiers in Plant Science 6:688

    doi: 10.3389/fpls.2015.00688

    CrossRef   Google Scholar

    [15]

    Maqbool MA, Aslam M, Ali H, Shah TM. 2016. Evaluation of advanced chickpea (Cicer Arietinum L.) accessions based on drought tolerance indices and SSR markers against different water treatments. Pakistan Journal of Botany 48:1421−29

    Google Scholar

    [16]

    Li Z, Geng W, Tan M, Ling Y, Zhang Y, et al. 2022. Differential responses to salt stress in four white clover genotypes associated with root growth, endogenous polyamines metabolism, and sodium/potassium accumulation and transport. Frontiers in Plant Science 13:896436

    doi: 10.3389/fpls.2022.896436

    CrossRef   Google Scholar

    [17]

    Li Z, Tang M, Hassan MJ, Zhang Y, Han L, et al. 2021. Adaptability to high temperature and stay-green genotypes associated with variations in antioxidant, chlorophyll metabolism, and γ-aminobutyric acid accumulation in creeping bentgrass species. Frontiers in Plant Science 12:750728

    doi: 10.3389/fpls.2021.750728

    CrossRef   Google Scholar

    [18]

    Ajtahed SS, Rezaei A, Hosseini Tafreshi SA. 2021. Identifying superior drought-tolerant Bermudagrass accessions and their defensive responses to mild and severe drought conditions. Euphytica 217:91

    doi: 10.1007/s10681-021-02821-z

    CrossRef   Google Scholar

    [19]

    Yu X, Bai G, Liu S, Luo N, Wang Y, et al. 2013. Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions. Journal of Experimental Botany 64:1537−51

    doi: 10.1093/jxb/ert018

    CrossRef   Google Scholar

    [20]

    Kumar SPJ, Susmita C, Sripathy KV, Agarwal DK, Pal G, et al. 2022. Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers. Molecular Biology Reports 49:2129−40

    doi: 10.1007/s11033-021-07030-4

    CrossRef   Google Scholar

    [21]

    Sharopova N, McMullen MD, Schultz L, Schroeder S, Sanchez-Villeda H, et al. 2002. Development and mapping of SSR markers for maize. Plant Molecular Biology 48:463−81

    doi: 10.1023/a:1014868625533

    CrossRef   Google Scholar

    [22]

    Taheri S, Lee Abdullah T, Yusop MR, Hanafi MM, Sahebi M, et al. 2018. Mining and development of novel SSR markers using next generation sequencing (NGS) data in plants. Molecules 23:399

    doi: 10.3390/molecules23020399

    CrossRef   Google Scholar

    [23]

    Varshney RK, Sigmund R, Börner A, Korzun V, Stein N, et al. 2005. Interspecific transferability and comparative mapping of barley EST-SSR markers in wheat, rye and rice. Plant Science 168:195−202

    doi: 10.1016/j.plantsci.2004.08.001

    CrossRef   Google Scholar

    [24]

    Kuleung C, Baenziger PS, Dweikat I. 2004. Transferability of SSR markers among wheat, rye, and triticale. Theoretical and Applied Genetics 108:1147−50

    doi: 10.1007/s00122-003-1532-5

    CrossRef   Google Scholar

    [25]

    Saha MC, Mian MAR, Eujayl I, Zwonitzer JC, Wang L, et al. 2004. Tall fescue EST-SSR markers with transferability across several grass species. Theoretical & Applied Genetics 109:783−91

    doi: 10.1007/s00122-004-1681-1

    CrossRef   Google Scholar

    [26]

    de Oliveira EJ, Morgante CV, de Tarso Aidar S, de Melo Chaves AR, Antonio RP, et al. 2017. Evaluation of cassava germplasm for drought tolerance under field conditions. Euphytica 213:188

    doi: 10.1007/s10681-017-1972-7

    CrossRef   Google Scholar

    [27]

    Iseki K, Takahashi Y, Muto C, Naito K, Tomooka N. 2018. Diversity of drought tolerance in the genus Vigna. Frontiers in Plant Science 9:729

    doi: 10.3389/fpls.2018.00729

    CrossRef   Google Scholar

    [28]

    Liu Y, Bowman BC, Hu Y, Liang X, Zhao W, et al. 2017. Evaluation of agronomic traits and drought tolerance of winter wheat accessions from the USDA-ARS national small grains collection. Agronomy 7:51

    doi: 10.3390/agronomy7030051

    CrossRef   Google Scholar

    [29]

    Torres RO, McNally KL, Cruz CV, Serraj R, Henry A. 2013. Screening of rice Genebank germplasm for yield and selection of new drought tolerance donors. Field Crops Research 147:12−22

    doi: 10.1016/j.fcr.2013.03.016

    CrossRef   Google Scholar

    [30]

    Li Z, Zhang Y, Zhang X, Peng Y, Merewitz E, et al. 2016. The alterations of endogenous polyamines and phytohormones induced by exogenous application of spermidine regulate antioxidant metabolism, metallothionein and relevant genes conferring drought tolerance in white clover. Environmental & Experimental Botany 124:22−38

    doi: 10.1016/j.envexpbot.2015.12.004

    CrossRef   Google Scholar

    [31]

    Ahmed M, Zeng Y, Yang X, Anwaar HA, Alghanem S. 2020. Conferring drought-tolerant wheat genotypes through morpho-physiological and chlorophyll indices at seedling stage. Saudi Journal of Biological Sciences 27:2116−23

    doi: 10.1016/j.sjbs.2020.06.019

    CrossRef   Google Scholar

    [32]

    Dhanda SS, Sethi GS, Behl RK. 2010. Indices of drought tolerance in wheat genotypes at early stages of plant growth. Journal of Agronomy and Crop Science 190:6−12

    doi: 10.1111/j.1439-037x.2004.00592.x

    CrossRef   Google Scholar

    [33]

    Anjum SA, Xie X, Wang L, Saleem MF, Man C, et al. 2011. Morphological, physiological and biochemical responses of plants to drought stress. African Journal of Agricultural Research 6:2026−32

    Google Scholar

    [34]

    Appenroth KJ, Stöckel J, Srivastava A, Strasser RJ. 2001. Multiple effects of chromate on the photosynthetic apparatus of Spirodela polyrhiza as probed by OJIP chlorophyll a fluorescence measurements. Environmental Pollution 115:49−64

    doi: 10.1016/S0269-7491(01)00091-4

    CrossRef   Google Scholar

    [35]

    Hendrickson L, Förster B, Pogson BJ, Chow WS. 2005. A simple chlorophyll fluorescence parameter that correlates with the rate coefficient of photoinactivation of Photosystem II. Photosynthesis Research 84:43−49

    doi: 10.1007/s11120-004-6430-4

    CrossRef   Google Scholar

    [36]

    Viljevac M, Dugalić K, Mihaljević I, Šimić D, Sudar R, et al. 2013. Chlorophylls content, photosynthetic efficiency and genetic markers in two sour cherry (Prunus cerasus L.) genotypes under drought stress. Acta Botanica Croatica 72:221−35

    doi: 10.2478/botcro-2013-0003

    CrossRef   Google Scholar

    [37]

    Nouri-Ganbalani A, Nouri-Ganbalani G, Hassanpanah D. 2009. Effects of drought stress condition on the yield and yield components of advanced wheat genotypes in Ardabil, Iran. Journal of Food Agriculture and Environment 7:228−34

    Google Scholar

    [38]

    Liu C, Yang Z, Hu Y. 2015. Drought resistance of wheat alien chromosome addition lines evaluated by membership function value based on multiple traits and drought resistance index of grain yield. Field Crops Research 179:103−12

    doi: 10.1016/j.fcr.2015.04.016

    CrossRef   Google Scholar

    [39]

    Badr A, El-Shazly HH, Tarawneh RA, Börner A. 2020. Screening for drought tolerance in maize (Zea mays L.) germplasm using germination and seedling traits under simulated drought conditions. Plants 9:565

    doi: 10.3390/plants9050565

    CrossRef   Google Scholar

    [40]

    Hoagland DR, Arnon DI. 1950. The water culture method for growing plants without soil. California Agricultural Experiment Station Circular 347:357−59

    Google Scholar

    [41]

    Barrs HD, Weatherley PE. 1962. A re-examination of the relative turgidity technique for estimating water deficits in leaves. Australian Journal of Biological Sciences 15:413−28

    doi: 10.1071/BI9620413

    CrossRef   Google Scholar

    [42]

    Blum A, Ebercon A. 1981. Cell membrane stability as a measure of drought and heat tolerance in wheat. Crop Science 21:43−47

    doi: 10.2135/cropsci1981.0011183X002100010013x

    CrossRef   Google Scholar

    [43]

    Arnon D. 1949. Copper enzymes in isolated chloroplasts polyphenoloxidase in Beta vulgaris. Plant Physiology 24:1−15

    doi: 10.1104/pp.24.1.1

    CrossRef   Google Scholar

    [44]

    Zeng W, Hassan MJ, Kang D, Peng Y, Li Z. 2021. Photosynthetic maintenance and heat shock protein accumulation relating to γ-aminobutyric acid (GABA)-regulated heat tolerance in creeping bentgrass (Agrostis stolonifera). South African Journal of Botany 141:405−13

    doi: 10.1016/j.sajb.2021.05.028

    CrossRef   Google Scholar

    [45]

    Zhao N, Yu X, Jie Q, Li H, Li H, Hu J, Zhai H, He S, Liu Q. 2013. A genetic linkage map based on AFLP and SSR markers and mapping of QTL for dry-matter content in sweetpotato. Molecular Breeding 32:807−20

    doi: 10.1007/s11032-013-9908-y

    CrossRef   Google Scholar

    [46]

    Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. 2013. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. Molecular Biology & Evolution 30:2725−29

    doi: 10.1093/molbev/mst197

    CrossRef   Google Scholar

  • Cite this article

    Tan M, Ling Y, Peng Y, Li Z. 2022. Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes. Grass Research 2:8 doi: 10.48130/GR-2022-0008
    Tan M, Ling Y, Peng Y, Li Z. 2022. Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes. Grass Research 2:8 doi: 10.48130/GR-2022-0008

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ARTICLE   Open Access    

Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes

Grass Research  2 Article number: 8  (2022)  |  Cite this article

Abstract: Dichondra (Dichondra repens) is an important ground cover plant and is also used as a herbal medicine in China. Objectives of this study were to evaluate phenotypic and genetic diversities among 33 genotypes by using 18 simple sequence repeat (SSR) markers and to further identify the drought tolerance of these germplasms based on five physiological parameters. Results showed that natural variations in phenotypes including plant height, leaf area, leaf thickness, and petiole length were observed among 33 genotypes under well-watered conditions. All 18 SSR primer pairs were found to be polymorphic and significant genetic variation was found in these genotypes. In addition, there were obvious differences in leaf relative water content (RWC), electrolyte leakage (EL), chlorophyll (Chl) content, photochemical efficiency (Fv/Fm), and performance index on absorption basis (PIABS) among 33 genotypes in response to a prolonged period of drought stress (46 d). Drought tolerance of 33 genotypes was then ranked by using subordinate function value analysis (SFVA) and the most drought-tolerant or -sensitive genotypes were identified as Dr5 or Dr29, respectively. Principal component analysis (PCA) further classified 33 genotypes into group I (drought-tolerant), group II (drought-sensitive), and group III (medium types). Current findings showed that 18 selected SSR primers could be potentially used to analyze genetic diversity and varietal identification in dichondra species. Drought-tolerant wild dichondra resources provide a rich genetic base for breeding of new cultivars.

    • Dichondra (Dichondra repens) is a perennial convolvulaceous plant that is wildly used as a ground cover for landscaping, ecological restoration, and weed control due to its ability to form a dense and low-growing sward[1, 2]. Previous studies have demonstrated that dichondra was able to establish a denser greensward for weed suppression than other ground cover plants such as creeping red fescue (Festuca rubra) and white clover (Trifolium repens) in an apple orchard[3, 4], but did not cause reduction in fruit yield[5]. In addition, dichondra is also a main constituent in many traditional herbal beverages in China and its extracts including n-butanol, vanillin, umbelliferone, and scopoletin exhibit antinociceptive effect, antibacterial activity, and anti-inflammation for treatment of icterohepatitis, dysentery, hydrops, or other diseases[68]. There are more than five species of the genus Dichondra in the world and most of them are distributed in the Americas. Up to now, only one wild species is found in China[8]. Requirement for new dichondra cultivars to be used for park and home landscaping is increasing in virtue due to their creeping growth habit and no need for mowing. However, the breeding of dichondra species is far behind other ground cover plants.

      Global warming aggravates the frequency of extreme weather events such as high temperature and drought worldwide. Drought stress causes a lack of water availability in plants resulting in growth retardation and a decline in utility value[9]. Screening and evaluation of relative drought-tolerant genotypes play pivotal roles in breeding for stress-tolerant new cultivars. Multiple molecular markers including microsatellite or simple sequence repeat (SSR), restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), and random-amplified polymorphic DNA (RAPD) markers have been applied for selection and evaluation of diverse plant resources[10]. Among them, SSR markers exhibit outstanding characteristics of chromosome-specific location, co-dominant inheritance, and better interspecific transferability, and has become an important tool for molecular breeding[11]. Earlier studies by Varshney et al. and Powell et al. proved that SSRs were found to be more polymorphic than other molecular markers[12, 13]. Kumar et al. reviewed the importance of SSR markers for molecular breeding of salt-tolerant Brassica genotypes[14]. Maqbool et al. evaluated drought tolerance of 40 chickpea (Cicer arietinum) genotypes based on the change in seed yield and genetic diversity via SSR markers, which provided basic information for breeding of drought-tolerant chickpea genotypes[15].

      Understanding of genetic diversity and drought tolerance of different dichondra genotypes could help geneticists or breeders to interpret germplasm architecture or breed new cultivars. In addition, selection and utilization of drought-tolerant dichondra genotypes could be propitious to decrease in maintenance and management costs in the field. Objectives of this study were to evaluate morphological variation, genetic diversity via SSRs, and drought tolerance based on changes in five physiological parameters including leaf relative water content (RWC), electrolyte leakage (EL), chlorophyll (Chl), photosystem II photochemical efficiency (Fv/Fm), and performance index on absorption basis (PIABS) of 33 dichondra genotypes (three cultivars and 30 wild genotypes collected from southwest China). These physiological parameters have been widely used for evaluating stress tolerance in various plant species, since they indicate water status, cell membrane stability, and photosynthetic capacity[1619]. Current findings will provide potential materials for breeding program and further exploration of drought-resistant mechanism by using drought-tolerant and -sensitive dichondra genotypes.

    • Figure 1 showed leaf sizes among 33 genotypes under normal conditions. There were significant variations in plant height, leaf area, leaf thickness, and petiole length among 33 genotypes (Fig. 2ad). Dr9 exhibited the highest plant height and the greatest leaf area, whereas Dr12 showed the shortest plant height and Dr28 had smallest leaf area compared to other genotypes (Fig. 2a & b). The value of leaf thickness of all genotypes was more than 0.1 mm except Dr20 (Fig. 2c). The biggest value of leaf thickness was also observed in Dr9 (Fig. 2c). Dr26 and Dr28 had smaller petiole lengths than other genotypes under normal condition (Fig. 2d). Table 1 showed amplification results using 18 SSR primers. A total of 256 bands were amplified by these SSR primers and the total number of polymorphic bands reached 228 (Table 1). Primer C24 or IBM13 exhibited the highest or lowest polymorphism information content (PIC) than other primers, respectively (Table 1). Cluster analysis found that the average variation range of genetic similarity coefficient was from 0.56 to 0.89 among 33 genotypes (Fig. 3). New cultivars 'Xiaoshao' (Dr32) and 'Duliujiang' (Dr33) had closer genetic relationship, and commercial cultivar 'Silver Falls' (Dr30) showed closer genetic relationship with Dr31 (Fig. 3).

      Figure 1. 

      Phenotypic differences in leaves of 33 Dichondra repens genotypes under normal conditions.

      Figure 2. 

      Differences in (a) plant height, (b) leaf area, (c) leaf thickness, and (d) petiole length among 33 Dichondra repens genotypes under normal conditions. Vertical bars represent standard errors of the mean (n = 10).

      Table 1.  Amplification results among 33 Dichondra repens using different SSR primers.

      Primer
      name
      Total number of
      amplified bands
      Number of
      polymorphic bands
      PPB (%)PIC
      C241818100.000.338
      C271919100.000.295
      C3017952.940.163
      C331313100.000.314
      C51111090.910.354
      C601818100.000.193
      C661313100.000.342
      C6788100.000.230
      C71231982.610.230
      Z25211362.900.163
      Z3733100.000.266
      Z57191684.210.266
      Z699888.890.215
      Z1131616100.000.292
      Z1351111100.000.279
      SSR111212100.000.305
      IBM1344100.000.111
      IBM445211885.710.292
      Total256228
      Average14.2212.6791.590.258

      Figure 3. 

      Cluster analysis of 33 Dichondra repens genotypes based on SSR markers.

    • Dr29 completely died after 46 d of drought stress, so no physiological parameters were detected (Figs 4 & 5). Obvious variations in RWC and EL among 33 genotypes were observed, as demonstrated by drought stress index (DSI) of RWC and EL (Fig. 4a & b). Dr5, Dr18, and Dr33 showed higher DSI of RWC than other genotypes, and smallest DSI of RWC was detected in Dr8 and Dr27 (Fig. 4a). Dr9 or Dr33 had the biggest or smallest DSI of EL than other genotypes, respectively (Fig. 4b). Dr5, Dr9, Dr3, and Dr4 exhibited higher DSI of Chl as compared to other genotypes, whereas Dr28, Dr27, Dr20, and Dr30 had lower DSI of Chl than other genotypes (Fig. 5a). DSI of Fv/Fm of Dr1, Dr2, Dr3, Dr4, or Dr5 was greater than 1.0, but DSI of Fv/Fm of Dr8, Dr14, or Dr27 was less than 0.5 (Fig. 5b). DSI of Fv/Fm of other genotypes ranged from 0.5 to 1.0 (Fig. 5b). The highest DSI of PIABS was detected in Dr5, and DSI of PIABS of Dr7, Dr8, Dr14, or Dr27 were close to 0.0 (Fig. 5c).

      Figure 4. 

      Differences in drought stress index of (a) relative water content (RWC) and (b) electrolyte leakage (EL) among 33 Dichondra repens genotypes. Vertical bars represent standard errors of the mean (n = 4).

      Figure 5. 

      Differences in drought stress index of (a) chlorophyll (Chl), (b) photosystem II photochemical efficiency (Fv/Fm), and (c) performance index on absorption basis (PIABS) among 33 Dichondra repens genotypes. Vertical bars represent standard errors of the mean (n = 4).

    • Drought tolerance among 33 genotypes was evaluated synthetically based on subordinate function value (SFV) (Table 2). Dr5 had the largest SFV of RWC, and the second or third largest SFV of RWC was found in Dr18 and Dr33, respectively. Dr33 (top), Dr31 (second), and Dr32 (third) showed bigger SFV of EL than other genotypes (Table 2). Maximum SFV of Chl was detected in Dr5. The top three genotypes with bigger SFV of Fv/Fm than other genotypes in the sequences were Dr3, Dr5, and Dr4. Dr5 had the maximum SFV of PIABS as compared to other genotypes, whereas Dr27 exhibited the minimum SFV of PIABS than other genotypes except Dr29. Comprehensive ranking showed Dr29, Dr28, and Dr27 exhibited lower drought tolerance than other genotypes. Out of the 33 genotypes, drought tolerance of Dr5, Dr33, or Dr3 ranked first, second, or third, respectively (Table 2). Heat map showed variations in five physiological parameters among 33 genotypes in response to drought stress (Fig. 6a). 33 genotypes could be divided into three groups based on principal component analysis (PCA) analysis (Fig. 6b). The first group included eight genotypes (Dr5, Dr33, Dr9, Dr1, Dr2, Dr32, Dr3, and Dr4) with better tolerance than other genotypes, and the second group consisted of four genotypes (Dr29, Dr27, Dr8, and Dr14) which had lower drought tolerance than other genotypes. The remaining 21 genotypes were aggregated to form the third group and their drought tolerance was intermediate between the first group and second group (Fig. 6b).

      Table 2.  Membership function values of five physiological parameters and comprehensive evaluation of drought tolerance among 33 Dichondra repens genotypes.

      Material No.RWCELChlFv/FmPIABSAverageOrder
      Dr50.8360.6410.9320.8790.6420.7861
      Dr330.7580.8550.7190.8490.4740.7312
      Dr30.6520.6180.8980.9040.4550.7063
      Dr40.6810.6120.8470.8680.4620.6944
      Dr320.6420.7060.6370.8230.4610.6545
      Dr20.5750.6130.7220.8390.4330.6366
      Dr10.5360.5720.7980.8420.3910.6287
      Dr180.8240.5770.7520.6580.3120.6258
      Dr310.5950.7660.6960.7420.2950.6199
      Dr90.4580.3280.9170.8510.4440.60010
      Dr60.6860.4340.5700.7640.4120.57311
      Dr250.5920.5450.7450.7230.2530.57212
      Dr170.7350.3140.7080.7270.3610.56913
      Dr160.4980.4400.7360.7570.2960.54514
      Dr220.6560.5690.5100.6520.2520.52815
      Dr190.5390.3960.7030.6430.3060.51716
      Dr100.6670.4520.7030.5920.1730.51717
      Dr120.5120.4300.6720.6710.2480.50618
      Dr230.5230.4530.5450.6790.2740.49519
      Dr210.6080.6170.4280.5730.2080.48720
      Dr240.5580.4220.4550.6340.2720.46821
      Dr70.7170.3710.5790.5390.1060.46222
      Dr150.4850.4440.5410.6050.2070.45623
      Dr300.5370.4840.3630.6470.2430.45524
      Dr260.4250.4550.5230.6350.2300.45325
      Dr130.4310.3910.7180.5470.1630.45026
      Dr110.5120.4830.6520.4600.1420.45027
      Dr200.6760.2900.1880.7000.2550.42228
      Dr80.3620.4120.5670.3290.1440.36329
      Dr140.4060.2810.6200.2780.1450.34630
      Dr280.5050.2710.2720.5140.1560.34431
      Dr270.3230.2950.3210.2940.1130.26932
      Dr290.0000.0000.0000.0000.0000.00033

      Figure 6. 

      Changes in (a) heat map and (b) principal component analysis (PCA) based on five different physiological parameters. RWC, relative water content; EL, electrolyte leakage; Chl, chlorophyll; Fv/Fm, photosystem II photochemical efficiency; PIABS, performance index on absorption basis.

    • Wild dichondra is widely distributed in southwest China, but the problem is that lack of enough research has slowed down breeding and utilization of these wild resources. In the past 30 years, SSRs have been widely used to evaluate genetic diversity in various plant species[2022]. In our current study, significant genetic variation was detected among 33 dichondra genotypes through using 18 selected SSR markers that were developed from convolvulaceous sweet potato (Dioscorea esculenta). Excellent transferability of SSR markers cross related species has been demonstrated in many previous studies. For example, SSR markers from barley (Hordeum vulgare) exhibited good interspecific transferability in wheat (Triticum aestivum) and rye (Secale cereale)[23]. Mutual transferability of SSR between wheat and rye was also very high[24]. In addition, tall fescue (Festuca arundinacea) SSR markers could be applied for evaluation of genetic relationships in meadow fescue (Festuca pratensis), tetraploid fescue (Festuca arundinacea), and ryegrass (Lolium perenne)[25]. Our study found that all 18 primers were found to be polymorphic when they were applied to 33 dichondra genotypes, which indicated these primer pairs could be used for analysis of genetic diversity and cultivar identification in dichondra species. In addition, phenotypic variations in plant height, leaf area, leaf thickness, and petiole length were also observed among 33 dichondra genotypes under well-watered condition. Diverse morphological variability and genetic variation are beneficial to screen suitable accessions for stress adaptation, because variation in morphological characters often indicates genetic differences in one particular plant species, which provides abundant gene resources for screening new cultivars differing in drought tolerance.

      Although many previous studies have been conducted to identify drought-tolerant plant genotypes in the field or under controlled conditions[2629], selection and identification of dichondra genotypes with better drought tolerance have not been reported so far. Leaf RWC and EL are two important indicators of drought tolerance, as the RWC reflects leaf water status and the EL indicates cell membrane stability when plants suffer from drought stress[30]. Both of them have been applied to evaluate plant drought tolerance. Ahmed et al. found that drought tolerance of wheat was positively related to higher RWC and cell membrane stability which could be used to screen drought-tolerant genotypes at the seedling stage[31]. Drought-tolerant bermudagrass (Cynodon dactylon) also showed higher RWC and lower EL than drought-sensitive accessions in response to drought stress[18]. Dhanda et al. reported that cell membrane stability was the most important trait for evaluation of drought tolerance among thirty wheat cultivars[32]. Our current study demonstrated that Dr5, Dr18, and Dr33 could maintain higher leaf RWC and lower EL than other dichondra genotypes, whereas Dr8 exhibited the lowest RWC and the highest EL under drought stress. Those genotypes with higher leaf RWC and lower EL in response to drought stress could be recognized as potential breeding materials for developing drought-tolerant varieties.

      Drought-tolerant plants could delay Chl degradation to maintain higher photosynthesis under water-deficit condition[33]. It has been found that the maintenance of higher Chl content is a common characteristic in drought-tolerant plant genotypes[18, 31]. Apart from Chl content, Fv/Fm and PIABS also are critical parameters for evaluation of stress tolerance in plant species, as Fv/Fm represents photosystem II photochemical efficiency and PIABS indicates health status of photosynthetic organs[34, 35]. It has been found that higher Chl content, Fv/Fm, or PIABS were the superior indicators with regard to better tolerance to heat stress in creeping bentgrass (Agrostis stolonifera) accessions[17], salt stress in white clover germplasm[16], and drought stress in sour cherry (Prunus cerasus) genotypes[36]. Dichondra genotypes exhibited significant variations in Chl content, Fv/Fm, and PIABS in response to a prolonged period of drought stress. Higher Chl content, Fv/Fm, and PIABS were found in Dr3, Dr4, Dr5, Dr9, and Dr33 which could be potential drought-tolerant genotypes.

      Drought tolerance evaluated by one particular parameter is often one-sided. Subordinate function value analysis (SFVA) has been applied to comprehensively evaluate drought tolerance of diverse plant accessions based on different parameters[28, 37, 38]. The most promising drought-tolerant dichondra genotypes (Dr5, Dr33, Dr3, Dr4, and Dr32) were screened based on the SFVA in our current study. In addition, those 33 dichondra genotypes were classified into three distinct groups according to the analysis of PCA. Group I included 8 genotypes (Dr1, Dr2, Dr3, Dr4, Dr5, Dr9, Dr32, and Dr33) which were identified to be drought-tolerant candidates and group II contained four genotypes (Dr8, Dr14, Dr27, and Dr29) which were recognized as drought-sensitive accessions. The remaining 21 dichondra genotypes were classified into group III, which was intermediate between group I and III for drought tolerance. Similar results were found in the study of Badr et al. who reported that PCA analysis could clearly separate out drought-tolerant maize (Zea mays) genotypes from 40 accessions[39]. Analytic results from SFVA were consistent with the findings based on the analysis of PCA. These selected drought-tolerant genotypes offer available materials for breeders to develop new dichondra cultivars.

    • A total of 18 SSR primer pairs were applied to evaluate genetic diversity of 33 dichondra genotypes and all primer pairs were found to be polymorphic. Natural variations in phenotypes including plant height, leaf area, leaf thickness, and petiole length were also observed among 33 genotypes under the well-watered condition. Drought tolerance of 33 genotypes was ranked by using SFVA, and the most tolerant genotype was Dr5 and most drought-sensitive genotype was Dr29. In addition, PCA analysis could classify 33 genotypes into group I (drought-tolerant), group II (drought-sensitive), and group III (medium types). Current findings showed that 18 selected SSR primer pairs could be used to potentially analyze genetic diversity and varietal identification in dichondra species. Selected drought-tolerant wild resources provide a rich genetic base for the breeding of new cultivars.

    • Thirty wild dichondra genotypes and three commercial cultivars 'Silver falls', 'Xiaoshao', and 'Duliujiang' were collected from the Field Gene Bank at Sichuan Agricultural University (Table 3) and transplanted into polyvinyl chloride (PVC) tubes (33 cm in length, and 11 cm in diameter). All PVC tubes were filled with same mixtures of soil and sand (v:v, 1:1). Plants were cultivated in a greenhouse from July 14th to August 30th, 2020 (average temperature about 27/18 °C day/night and 800 μmol m−2∙s−1 photosynthetically active radiation) and fertilized weekly with full Hoagland's solution[40]. For drought treatment, plants were then divided into two groups: one group was irrigated three times a week to avoid soil drought as well-watered control, and another group was subjected to drought stress by stop irrigating for 46 d. Leaves were collected for detecting physiological parameters and SSR markers. Each genotype was replicated four times (four tubes) under normal condition or drought stress.

      Table 3.  Test 33 Dichondra repens materials and their sources.

      Material No.OriginAltitude (m)
      Dr1Zhongjiang, Sichuan600
      Dr2Pingtang, Guizhou848
      Dr3Dushan, Guizhou1010
      Dr4Tianzhu, Guizhou350
      Dr5Naxi, Sichuan404
      Dr6Dayi, Sichuan310
      Dr7Bishan, Chongqing350
      Dr8Jining, Yunnan1890
      Dr9Xifeng,Guizhou990
      Dr10Xishui, Guizhou1169
      Dr11Sinan, Guizhou730
      Dr12Jiangkou, Guizhou475
      Dr13Tongren, Guizhou415
      Dr14Zhenyuan, Guizhou382
      Dr15Danzai, Guizhou894
      Dr16Sandu, Guizhou500
      Dr17Sandu, Guizhou780
      Dr18Dujun, Guizhou842
      Dr19Shuicheng, Guizhou1193
      Dr20Liuzhi, Guizhou1035
      Dr21Anshun, Guizhou1278
      Dr22Qinglong, Guizhou1393
      Dr23Jin’an, Guizhou1336
      Dr24Panzhou, Guizhou1532
      Dr25Xingren, Guizhou1336
      Dr26Anlong, Guizhou1250
      Dr27Wangmo, Guizhou653
      Dr28Ziyun, Guizhou1160
      Dr29Huishui, Guizhou980
      Dr30 (‘Silver Falls’)USA-
      Dr31Xichou, Yunnan1108
      Dr32 (‘Xiaoshao’)Yiliang, Yunnan1970
      Dr33 (‘Duliujiang’)Sandu, Guizhou600
    • A vernier caliper was used to measure leaf thickness and leaf area (S) which was calculated based on the formula S = π × [(length + width) / 4]2. Plant height and petiole length were measured by using a ruler, and 10 independent plants were selected randomly from each tube for the measurement of these phenotypic parameters. For leaf RWC, fresh leaves were cut from plants and weighted instantly to record fresh weight (FW). These leaves were then soaked in deionized water for 10 h and turgid weight (TW) was weighted. All leaves were put in an oven at 80 °C for 72 h to detect dry weight (DW). The RWC was calculated as RWC (%) = [(FW − DW) / (TW −DW)] × 100)[41]. To detect leaf EL, fresh leaves (0.15 g) were soaked in 40 mL of deionized water for 24 h at 25 °C and initial conductivity of solution (Cinitial) was measured by using a conductivity meter (YSI Model 32, Yellow Spring, OH). Max conductivity of solution (Cmax) was detected after leaves were autoclaved at 120 °C for 20 min. The EL was calculated as the ratio of Cinitial to Cmax[42]. For Chl content, leaves were soaked in 15 mL of dimethyl sulfoxide for 48 h and absorbance was detected at 645 and 663 nm with a spectrophotometer (Spectronic Instruments, Rochester, NY, USA)[43]. For Fv/Fm and PIABS, leaves were kept in darkness for 15 min and a fluorescence meter (Pocket PEA Chl Fluorimeter, Hansatech Instruments Ltd, UK) was used to record Fv/Fm and PIABS[44].

    • Total DNA was extracted from approximately 0.1 g of fresh leaf tissues by using an assay kit purchased from Tiangen Biotech Co., LTD, Beijing, China. A Hoefer Dyna Quant 200 (Amersham Biosciences, Piscataway, NJ, USA) was used to detect DNA concentration which was adjusted to 10 ng ∙ μL−1 of final concentration using purified water. PCR reaction was conducted by using 7.5 μL of 2× Mix (P2015, Dongsheng Biotech), 3 μL of DNA, 1.5 μL of 0.6 μmol∙L−1 each primer, and 3 μL of purified water. A total of 18 primer sequences which were developed from sweet potato and their annealing temperature were recorded in Supplmental Table S1[45]. PCR products were electrophoresed in 6% polyacrylamide denaturing gels under 200 V for 30 min and then 400 V for 1.5 h. For SSR bands detection, gels were silver-stained and then captured using a camera. Gel images were analyzed by using the software Gel Analyzer 19.1 (www.gelanalyzer.com) to estimate base pair size of bands. Polymorphism was determined based on absence or presence of SSR locus.

    • Variations in phenotypic and physiological parameters were analyzed by Statistix 8.1 (Tallahassee, FL, USA). PCA biplot analysis was performed by using SPSS 20 (IBM, Armonk, NY, USA). Drought tolerance was evaluated by using SFVA based on five physiological parameters (RWC, EL, Chl, Fv/fm, and PIABS)[17]. DSI was calculated according to the formula DSI = (value of parameter under drought stress) / (value of parameter under normal condition) × 100. Cluster analysis of 33 Dichondra micrantha genotypes based on SSR markers was conducted by using NTSYSPC2.10e and MEGA 6 (Tokyo Metropolitan University, Hachioji, Tokyo, Japan)[46].

    • We appreciate Prof. Youmin Gan who collected wild dichondra resources from southwest China and established the Field Gene Bank at Sichuan Agricultural University.

      • The authors declare that they have no conflict of interest.

      • Copyright: © 2022 by the author(s). Published by Maximum Academic Press, Fayetteville, GA. This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.
    Figure (6)  Table (3) References (46)
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    Tan M, Ling Y, Peng Y, Li Z. 2022. Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes. Grass Research 2:8 doi: 10.48130/GR-2022-0008
    Tan M, Ling Y, Peng Y, Li Z. 2022. Evaluation of genetic diversity and drought tolerance among thirty-three dichondra (Dichondra repens) genotypes. Grass Research 2:8 doi: 10.48130/GR-2022-0008

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