Korean Journal of Plant Resources (한국자원식물학회지)

The Plant Resources Society of Korea (한국자원식물학회)
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A Statistical Analysis of Phenotypic Diversity Based on Genetic Traits in Barley Germplasms

특성평가 정보를 활용한 보리 유전자원 형태적 형질 다양성의 통계적 분석

  • 유동수 (농촌진흥청 국립농업과학원) ;
  • 신명재 (농촌진흥청 국립농업과학원) ;
  • 박진천 (농촌진흥청 국립식량과학원) ;
  • 강만정 (농촌진흥청 국립농업과학원)
  • Received : 2022.07.21
  • Accepted : 2022.09.06
  • Published : 2022.10.01
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Abstract

The biodiversity research of barley, a functional food, is proceeding to conserve germplasms and develop new cultivar of barley to improve its functional effects. In this study, with 25,104 barley germplasms in the National Agrobiodiversity Center, South Korea, the biodiversity index of species was much lower (1.17) than the origins (24.73) because of the presence of a biased species, Hordeum vulgare subsp. vulgare, but the species and origin of germplasms were significantly different with regard to genetic traits. In the clustering analysis based on genetic traits, we found that 97% barley germplasms could mostly be distributed between 1~7 clusters out of a total of 15 clusters; 'normal and uzu type', 'lodging', and 'loose smut' were commonly represented in the 1~7 clusters and some clusters showed specific differences in five genetic traits including 'growth habit'. In correlation of each genetic trait, the infection of 'barley yellow mosaic virus' was highly correlated to 'number of grains per spike'. '1000 grain weight' was weakly correlated with seven genetic traits including 'number of grains per spike'. Our analysis for barley's biodiversity can provide a useful guide to the species' phenotypes that need to be collected to conserve biodiversity and to breed new barley varieties.

보리는 베타글루칸, 폴리페놀, 안토시아닌 등을 이용한 건강식품 소비 증가로 최근 관심이 높아지고 있다. 따라서 보리에 대한 수요자의 기호에 맞춘 기능성 품종개발과 소재로서 유전자원 활용성을 증대시키기 위해서는 자원의 특성 분석과 종, 원산지과의 관계, 군집화(Clustering)을 통한 유사성과 대표성, 형질 간의 상호관계 등과 같은 유전자원의 다양성 연구가 선행되어야 할 것이다. 본 연구는 농업유전자원센터에서 보존하고 있는 보리 25,104 유전자원(25종, 국적미상을 포함한 102개 원산지)을 대상으로 종과 원산지에 따른 다양성 분석을 수행하였다. 특히 종에 대한 작물 유효수(ENCS)는 1.17로 원산지(24.73)에 비해 매우낮게 나타났다. 이는 보존하고 있는 보리 유전자원의 대부분이 Hordeum vulgare subsp. vulgare 로 확인되었는데, 원산지에 비해 보존 자원이 특정 종에 편중된것을 알 수 있지만, 형태적으로 구분한 20가지 특성평가 항목에 대하여 종과 원산지에 따라 유의적인 차이(P-value < 0.05)가 검정되었다. 비록 종 다양성은 낮지만 종과 종간의 차이와 종 내에서도 다양한 특성이 존재함을 추정할 수 있었으며, 이를 토대로 특성평가 항목을 이용한 군집화를 통해서 특성에 대한 다양성을 확인하였다. 특성평가 항목을 바탕으로 cacGMS 알고리즘을 이용한 군집 분석을 수행했을 때, 전체 97%의 자원이 분류된 1번~7번 군집에서 병와성, 도복, 깜부기병 항목이 공통적으로 동일한 형질을 보였다. 반면에 군집 별 특이성에서는 특성평가 항목에 대한 조합의 차이와 함께 생장습성, 망활, 한해, 파성, 보리누른모자이크병에서 다른 군집과 차별되는 특이성이 확인되었다. 이러한 특성평가 항목에 의한 대표성과 특이성, 그리고 각 군집에 따른 특성의 조합은 특성 간의 상호적 관계와 관련이 있을 것으로 추정되어 상관관계를 분석하였다. 그 결과 1수립수와 보리누른모자이크병이 높은 상관성(상관계수 0.79)을 보였고, 종자연구에서 중요한 지표로 사용되고 있는 천립중은 낮은 상관계수이지만 이삭조성(0.31), 이삭길이(0.23), 병와성(0.24), 이삭모양(0.28), 보리누른모자이크병(0.23), 1수립수(0.43), 조단백함량(0.29)과 관련이 있을 것으로 추정된다. 본 연구에서 사용된 연구방법과 결과는 신품종개발, 육종산업에 활용가능한 정보를 제공하고, 이를 통해 농업유전자원의 활용성 제고와 연구 선진화에 기여할 수 있을 것으로 기대한다.

Keywords

Acknowledgement

본 연구는 농촌진흥청 연구과제 '유전자원 활용도 제고를 위한 DB화 및 서비스(PJ014226)'의 지원을 받아 수행하였습니다.

References

  1. Aguilar, J., G.G. Gramig, J.R. Hendrickson, D.W. Archer, F. Forcella and M.A. Liebig. 2015. Crop species diversity changes in the United States: 1978-2012. PLOS ONE 10(8):e0136580. https://doi.org/10.1371/journal.pone.0136580
  2. Bae, I.H., H.S. Kang, W.J. Jeong, J.H. Ryu, O.H. Lee and H. Chung. 2021. Characterization of phenotypic traits and application of fruit flesh color marker in melon (Cucumis melo L.) Accessions. Korean J. Plant Res. 34(5):478-490 (in Korean).
  3. Benesty, J., J. Chen, Y. Huang and I. Cohen. 2009. Pearson correlation coefficient. Noise Reduction in Speech Processing. Springer, Germany. pp. 1-4.
  4. Biselli, C., S. Urso, L. Bernardo, A. Tondelli, G. Tacconi, V. Martino, S. Grando and G. Vale. 2010. Identification and mapping of the leaf stripe resistance gene Rdg1a in Hordeum spontaneum. Theor. Appl. Genet. 120(6):1207-1218. https://doi.org/10.1007/s00122-009-1248-2
  5. Caierao, E. 2006. Effect of induced lodging on grain yield and quality of brewing barley. Crop. Breed. Appl. Biotechnol. 6: 215-222. https://doi.org/10.12702/1984-7033.v06n03a05
  6. Carver, T.L.W. and E. Griffiths. 1981. Relationship between powdery mildew infection, green leaf area and grain yield of barley. Ann. Appl. Biol. 99(3):255-266. https://doi.org/10.1111/j.1744-7348.1981.tb04794.x
  7. Cho, M.-C., M.-K. Huh, S.-H. Kim, K.-J. Cho and C.-W. Kang. 2009. Phenetic variability in leaf morphological characteristics of the Korean Rubus crataegifolius Populations. J. Life Sci. 19(10):1382-1388 (in Korean). https://doi.org/10.5352/JLS.2009.19.10.1382
  8. Dessau, R.B. and C.B. Pipper. 2008. "R"--project for statistical computing. Ugeskr. Laeg. 170(5):328-330.
  9. Ehrlich, P.R. and E.O. Wilson. 1991. Biodiversity studies: Science and policy. Science 253(5021):758-762. https://doi.org/10.1126/science.253.5021.758
  10. Hallsson, L.R. and M. Bjorklund. 2012. Selection in a fluctuating environment leads to decreased genetic variation and facilitates the evolution of phenotypic plasticity. J. Evol. Biol. 25(7):1275-1290. https://doi.org/10.1111/j.1420-9101.2012.02512.x
  11. Jakob, S.S., D. Rodder, J.O. Engler, S. Shaaf, H. Ozkan, F.R. Blattner and B. Kilian. 2014. Evolutionary history of wild barley (Hordeum vulgare subsp. spontaneum) analyzed using multilocus sequence data and paleodistribution Modeling. Genome Biol. Evol. 6(3):685-702. https://doi.org/10.1093/gbe/evu047
  12. Jarvis, D.I., C. Padoch and H.D. Cooper. 2010. Managing Biodiversity in Agricultural Ecosystems. Columbia University Press, NY (USA), pp. 19-29.
  13. Jo, S.-H., C.-Y. Cho, K.-S. Ha, E.-J. Choi, Y.-R. Kang and Y.-I. Kwon. 2013. The antioxidant and antimicrobial activities of extracts of selected barley and wheat Inhabited in Korean peninsula. J. Korean Soc. Food Sci. Nutr. 42(7):1003-1007 (in Korean). https://doi.org/10.3746/jkfn.2013.42.7.1003
  14. Jung, J., S. Choi, J. Oh, N. Kim, D. Kim, B. Son and Y. Park. 2015. Evaluation of horticultural traits and genetic relationship in melon germplasm. J. Plant Biotechnol. 42:401-408 (in Korean). https://doi.org/10.5010/JPB.2015.42.4.401
  15. Kang, H.C. and C.S. Kim. 2006. Clustering applications in data mining. J. of Basic Sciences, Cheju Nat'l Univ. 18(2):121-127 (in Korean).
  16. Kim, D.-j., J.-h. Roh, J.-g. Kim and J.I. Yun. 2013. The influence of shifting planting date on cereal grains production under the projected climate change. Korean J. Agric. For. Meteorol. 15(1):26-39 (in Korean). https://doi.org/10.5532/KJAFM.2013.15.1.026
  17. Kim, J.-G., J.-H. Lee, B.-R Sung, B.-R Ko, Y.-T. Lee and T. Kwon. 2012. Current state of barley industry and counterplan against the abolition of procurement system of barley - II. Problems in supply and demand of barley material for processing enterprises and counterplan as affected by abolition of the procurement system of barley -. Korean J. Intl. Agri. 24(5):507-510 (in Korean). https://doi.org/10.12719/KSIA.2012.24.5.507
  18. Kim, K.-M., C.-S. Kang, Y.-K. Kim, K.-H. Kim, J.-H. Park, Y.-M. Yoon, H.-H. Park, H.-Y. Jeong, C.-H. Choi, J. Park, Y.-J. Kim, Y.-K. Cheong, O.-K. Han and T.-I. Park. 2020a. Past and current status, and prospect of winter cereal crops research for food and forage in Korea. Korean J. Breed. Sci. 52:73-92 (in Korean). https://doi.org/10.9787/KJBS.2020.52.S.73
  19. Kim, K.-W., H.-K. Chung, G.-T. Cho, K.-H. Ma, D. Chandrabalan, J.-G. Gwag, T.-S. Kim, E.-G. Cho and Y.-J. Park. 2007. PowerCore: A program applying the advanced M strategy with a heuristic search for establishing core sets. Bioinformatics 23(16):2155-2162. https://doi.org/10.1093/bioinformatics/btm313
  20. Kim, Y.-J., J.-E. Lee, E. Yoo, S. Lee, W. Xiaohan, D.A. Awraris and H. Noh. 2022. Selection of excellent genetic resources based on comparison of caffeic and rosmarinic acid contents and antioxidant activity in Perilla Accessions. Korean J. Plant Res. 35(1):1-9 (in Korean).
  21. Kim, Y.-K., J.-H. Seo, J.-C. Park, J.-S. Choi, S.-D. Kim and J.-H. Lee. 2003. Growth characteristics and grain quality of naked barley infected by barley yellow mosaic virus. Korean J. Crop. Sci. 48(6):501-505.
  22. Kim, Y.-K., Y.-M. Yoon, J.-H. Park, K.-H. Kim, C.-S. Kang, T.-i. Park and S.-k. Oh. 2020b. Development of a covered barley (Hordeum vulgare L.) cultivar, 'Hohyang', with high yield and spring sowing adaptability. Korean J. Breed. Sci. 52(4) (in Korean).
  23. Lee, J.-R., G.-T. Jo, D.-Y. Hyeon, M.-J. Shin, S.-H. Kim, G.-J. Lee and R. Sebastin. 2019. Multiplication and Characterization of Wheat, Barely and Carrot Germplasm. National Institute of Agricultural Sciences, The Republic of Korea, pp. 8-18 (in Korean).
  24. Lee, M., H.L. Kim, H.-C. Rhee, Y.-B. Kwack, H.M.P.C. Kumarihami and J.G. Kim. 2020. Evaluation of the genetic resources of kiwifruit with multivariate analysis. Hortic. Sci 38(4):569-581 (in Korean).
  25. Murtagh, F. and P. Legendre. 2011. Ward's hierarchical clustering method: Clustering criterion and agglomerative algorithm. ArXiv 1111.6285:1-20.
  26. Newman, M.E.J. 2006. Modularity and community structure in networks. Proc. Natl. Acad. Sci. U. S. A. 103(23):8577-8582. https://doi.org/10.1073/pnas.0601602103
  27. Olsson, U., F. Drasgow and N.J. Dorans. 1982. The polyserial correlation coefficient. Psychometrika 47(3):337-347. https://doi.org/10.1007/BF02294164
  28. Ozturk, Y., R. Avci, T. Kahraman, A. Tulek, R. Kaya and B. Tuna. 2014. Investigation of yield and some agronomical traits of the barley (Hordeum vulgare L) genotypes in Trakya region. Scientific works of Institute of agriculture-Karnobat 3(1):133-137.
  29. Park, H.-S. and C.-H. Jun. 2009. A simple and fast algorithm for K-medoids clustering. Expert Syst. Appl. 36(2):3336-3341. https://doi.org/10.1016/j.eswa.2008.01.039
  30. Park, J.-C., J.-D. Lee, J.-H. Seo, Y.-K. Kim, S.-G. Jeong and H.-M. Kim. 2004. Growth damage and alteration of cellular tissue of barley infected by barley yellow mosaic virus. Res. Plant Dis. 10(1):34-38 (in Korean). https://doi.org/10.5423/RPD.2004.10.1.034
  31. Park, J.-C., M.-J. Lee, I.-B. Choi, M.-J. Kim, C.-S. Park and J.-G. Kim. 2006. Growth and yield comparisons among barley varieties with different resistance to barley mosaic virus. Korean J. Crop. Sci. 51(5):477-482 (in Korean).
  32. Prematunga, R.K. 2012. Correlational analysis. Australian Critical. Care. 25(3):195-199. https://doi.org/10.1016/j.aucc.2012.02.003
  33. Rawal, S., S.C. Gupta and S. Singh. 2017. Predicting missing values in a dataset: challenges and approaches. Int. J. Recent Res. Asp. 4(3):34-38.
  34. Rommens, C.M. 2007. Intragenic crop improvement: Combining the benefits of traditional breeding and genetic engineering. J. Agric. Food Chem. 55(11):4281-4288. doi:10.1021/jf0706631.
  35. Tolbert, D.M., C.O. Qualset, S.K. Jain and J.C. Craddock. 1979. A diversity analysis of a world collection of barley. Crop. Sci. 19(6):789-794. https://doi.org/10.2135/cropsci1979.0011183X001900060011x
  36. Yu, D.S., and S.H. Yoo. 2015. VBioindex: A visual tool to estimate biodiversity. Genomics. Inform. 13(3):90. https://doi.org/10.5808/GI.2015.13.3.90
  37. Yu, D.S., M. Kang, N.-Y. Ro and O.-S. Hur. 2022. cacGMS: An algorithm clustering germplasm based on categorical genetic traits. Korean J. Breed. Sci. (in Korean).