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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea
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Korean. J. Breed. Sci. : Korean Journal of Breeding Science

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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea


Published online: February 28, 2014

1농림축산식품부 국립종자원 재배시험과

1Variety Testing Division, Korea Seed & Variety Service, Ministry of Agriculture, Food and Rural Affairs, Suwon 443-400, Korea

2동아대학교 생명자원과학대학 유전공학과

2Department of Genetic Engineering, College of Natural Resources and Life Science, Dong-A University, Busan 604-714, Korea

3농림축산식품부 국립종자원 제주지원

3Jeju Office, Korea Seed & Variety Service, Ministry of Agriculture, Food and Rural Affairs, Seogwipo 699-946, Korea

4전북농업기술원 원예산업과

4Horticulture Division, Jeollabuk-do Agricultural Research and Extension Services, Iksan 570-704, Korea

5국립원예특작과학원 채소과

5Vegetable Research Division, National Institute of Horticultural & Herbal Science, Suwon 441-440, Korea

*Corresponding author (E-mail: hongjh19@korea.kr, Tel: +82-31-8008-0221, Fax: +82-31-203-7431)
• Received: December 18, 2013   • Revised: February 25, 2014   • Accepted: March 3, 2014

© The Korean Society of Breeding Science

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Blueberry (Vaccinium spp.) is a member of Ericaceae and the recent important small fruit crop. This study was to construct a DNA marker database for blueberry varieties in Korea using simple sequence repeat (SSR) markers. A set of 49 SSR primer pairs was tested to select polymorphic SSR marker in 6 varieties. With 49 primer pairs, seventeen primer pairs showed polymorphism, reproducibility and band clearance. The genetic relationship among 34 varieties by using 17 SSR markers was analyzed. A total of 115 polymorphic amplified fragments were obtained by 17 SSR markers. Two to fifteen SSR alleles were detected for each locus with an average of 6.8 alleles per locus. Average polymorphism information content (PIC) was 0.671, ranging from 0.248 to 0.888. A total of 115 SSR marker loci were used to calculate Jaccard’s distance coefficients for cluster analysis by unweighted pair-group method with arithmetical average (UPGMA). Genetic distance ranged from 0.31 to 0.81 in 34 varieties and the dendrogram at a similarity 0.40 gave 3 main clusters according to blueberry species. Totally 34 varieties were identified by 17 SSR markers. Out of 17 SSR markers, a set of 3 minimum SSR markers was also enabled the identification of 34 varieties. Hence, we concluded that these SSR markers will be available for identifying blueberry varieties and alternative choice to distinctness, uniformity, stability (DUS) examination in blueberry along with valid phenotypic data.
블루베리(Vaccinium spp.)는 진달래과(Ericaceae), Vaccinium 속, Cyanococcus아속에 속하며, Vaccinium속에는 약 400개 종이 있는 것으로 보고 되었다(Ratnaparkhe 2007). 블루베리 의 원산지는 북아메리카이고 주요 생산국은 미국과 캐나다이 며 황산화제, 비타민 C의 효능이 있는 기능성 과수로 알려져 있다(Matzner 1967). 상업적으로 재배되는 블루베리는 하 이부쉬 블루베리(V. corymbosum), 로우부쉬 블루베리(V. angustifolium), 래빗아이 블루베리(V. ashei), 하프 하이부쉬 블루베리(V. angustifolium x V. corymbosum)가 있으며, 이 중에 하이부쉬 블루베리가 전세계적으로 가장 많이 재배된다 고 보고된 바 있다(Ratnaparkhe 2007). 블루베리는 2012년 1 월 7일부터 품종보호 대상작물로 지정되어 품종보호 출원된 품종이 14품종(하이부쉬 10, 래빗아이 3, 하프 하이부쉬 1), 생산수입판매신고 건수가 784건(2013년 11월)을 차지하며 (http://www.seed.go.kr) 기능성 과수로 많은 홍보가 되면서 국내 수입과 재배면적이 급속히 증가하고 있다(http://www.rda.go.kr). 따라서 품종보호 출원품종과 가장 유사한 대조품종의 선정, 국내 유통품종과 농가 재배품종의 품종 진위성 확인 요구에 대비하기 위해서는 품종을 식별할 수 있는 DNA 마커의 선발 과 이를 이용한 데이터베이스 구축이 필요하다. 식물신품종보 호동맹(UPOV, International Union for the Protection of New Varieties of Plants)이 제안하는 DNA 마커 중 하나인 simple sequence repeat (SSR) 마커는 다중대립유전자, 게놈 의 위치 특이적, 높은 다형성 및 재현성 등으로 품종식별에 효과적인 것으로 보고 되었다 (Agawal et al. 2008, Parida et al. 2009). 최근에는 SSR 마커를 이용하여 자동염기서열분석 기로 품종에 따른 DNA 단편의 크기를 정확하게 측정하여 장 미(Hong et al. 2013), 사과(Hong et al. 2013), 오이(Kwon & Choi 2013) 등의 작물에 대하여 품종별 DNA 프로파일 데 이터베이스를 구축하고 이를 품종보호 재배심사와 종자분쟁 등과 같은 분야에 실용적으로 활용하고 있는 추세이다. 분자 표지를 활용한 블루베리의 국외 연구 동향을 살펴보면, 캐나다 에서는 random amplification of polymorphic DNA (RAPD) 마커를 활용하여 로우부쉬 블루베리 26개 유전자원에 대한 유연관계를 분석하였고(Burgher et al. 2002), 미국에서는 RAPD 마커를 이용하여 래빗아이 블루베리 19품종에 대한 품종식별 연구를 수행하였으며(Aruna et al. 1995), RAPD와 SSR 마커를 이용하여 블루베리 18품종의 식별 연구를 수행 한 결과도 보고되고 있다(Levi & Rowland 1997). 또한 expressed sequence tag (EST) - PCR 마커를 개발하여 블루 베리의 유전자원 특성 평가 및 품종식별 등 다양한 연구결과 가 보고되고 있다(Bell et al. 2008, Boches et al. 2006, Rowland et al. 2003). 그러나 국내에 최근에 수집된 블루베 리 주요 품종과 국내에 품종보호 출원된 품종을 대상으로 UPOV에서 제안된 DNA 검정방법인 SSR 마커를 이용하여 각 품종별로 정밀도 높은 DNA 프로파일 데이터베이스 구축 은 완료되지 못한 상황이다.
따라서, 본 연구에서는 블루베리의 품종보호를 위한 재배 심사, 국내 유통품종의 식별을 통한 유통관리 등에 SSR 마커 의 활용 가능성에 대한 기초 자료를 얻기 위하여 품종식별에 효과적인 SSR 마커를 선발 및 품종간 유전적 유연관계 분석 등에 대한 일련의 연구결과를 보고하는 바이다.
공시재료 및 DNA 추출
국립종자원 서부지원 및 전북농업기술원에서 수집된 34품 종(하이부쉬 29품종, 래빗아이 4품종, 하프 하이부쉬 1품종) 의 잎을 채취하여 분석을 위한 재료로 활용하였다(Table 1). 공시품종의 DNA는 NucleoSpin®PlantII(Macherey-Nagel Cat. 740 770.250) 키트를 이용하여 추출하였다. 추출된 DNA 는 분광광도계(NanoDrop2000, Thermo Scientific, USA)를 활용하여 DNA 농도를 확인한 후 μl당 20 ng의 농도로 맞추 어 PCR 분석에 사용하였다.
Table 1
Blueberry varieties used for variety identification by SSR markers
Table 1
No. Varieties Classification No. Varieties Classification

1 Rebel Highbush (S)z 18 Jersey Highbush (N)
2 Brigittar Highbush (N)y 19 Collins Highbush (N)
3 Suziblue Highbush (S) 20 Reka Highbush (N)
4 Aurora Highbush (N) 21 Spartan Highbush (N)
5 Liberty Highbush (N) 22 Bluecrop Highbush (N)
6 Blueray Highbush (N) 23 Earliblue Highbush (N)
7 Duke Highbush (N) 24 Elizabeth Highbush (N)
8 Nelson Highbush (N) 25 Bluejay Highbush (N)
9 Chandler Highbush (N) 26 Sierra Highbush (N)
10 Elliot Highbush (N) 27 Huron Highbush (N)
11 Sunrise Highbush (N) 28 Draper Highbush (N)
12 O'Neal Highbush (S) 29 Misty Highbush (S)
13 Lancocas Highbush (N) 30 Northsky Half highbushx
14 Patriot Highbush (N) 31 Blueshower Rabbiteyew
15 Bluetta Highbush (N) 32 Delite Rabbiteye
16 Dixi Highbush (N) 33 Ochlockonee Rabbiteye
17 Coville Highbush (N) 34 Alapaha Rabbiteye

zHighbush (S) : Southern highbush (Vaccinium corymbosum × Vaccinium darrowi, Vaccinium ashei)

yHighbush (N) : Northern highbush (Vaccinium corymbosum)

xHalf highbush (Vaccinium corymbosum × Vaccinium angustifolium)

wRabbiteye (Vaccinium ashei)

SSR 마커 분석
블루베리 품종식별에 효과적인 마커를 선발하기 위하여 국외 에서 개발된 49개의 SSR 마커를 이용하여 ‘Rebel’, ‘Suziblue’, ‘Huron’, ‘Liberty’, ‘Draper’, ‘Ochlockonee’ 품종을 대상으 로 유전자형을 분석하였다. PCR 반응은 블루베리 게놈 DNA 20 ng, 0.5 μM의 SSR primer, 2 μl dNTP mixture (2.5 mM), Taq polymerase 1 units, 2.5 μl의 10 × PCR buffer (50 mM KCl, 20 mM Tris-HCl, pH 8.0, 2 mM MgCl2) (Genet Bio, Korea)에 증류수를 첨가하여 총 반응액을 25 μl 로 맞추었다. PCR (C1000, BioRad, USA)은 40회 실시하며, pre-denaturation은 94°C에서 5분, denaturation은 94°C에서 30초, annealing은 50~60°C에서 30초, extension은 72°C에 서 45초, final-extension은 72°C에서 10분간 수행하였다. 유 전자 증폭 산물은 6% polyacrylamide gels을 이용하여 전기 영동 한 다음 silver sequence™ staining reagents (Promega, USA)으로 염색하였고 각 품종별 대립유전자의 차이를 분석 하여 다형성을 보이는 마커를 선발하였다.
다형성을 나타내는 마커 중 SSR 프로파일 데이터베이스 구축에 활용할 마커를 선정한 후 프라이머의 정방향에 FAM, VIC, NED, PET 중 한가지로 형광 표지하여 블루베리 34품 종을 PCR 하였다. 4 μl의 PCR 증폭산물을 2% 아가로스 젤 에서 전기영동하여 증폭 여부를 확인한 후 증류수 220 μl에 PCR 산물을 증폭량에 따라 1~3 μl씩 첨가하였다. 희석된 PCR 증폭 산물은 Hi-Di formamide와 size marker (LIZ500 size standard)를 첨가하여 94°C에서 2분간 denaturation 시 킨 후 자동염기서열 분석장치(Genetic Analyzer 3730XL, Applied Biosystem, USA)를 활용하여 전기영동하고, GeneMapper 프로그램(Applied Biosystem, USA)을 이용하여 대립유전자 크기를 분석하였다.
다형성 지수 및 유사도 분석
자동염기서열 분석장치를 통해 분석된 대립유전자의 유무 에 따라 피크가 있으면 ‘1’, 없으면 ‘0’으로 기록하여 엑셀파 일에 품종별 SSR 프로파일 대립유전자 크기에 대한 데이터 베이스를 구축하였다. SSR 마커의 다형성을 조사하기 위하여 아래 공식을 이용하여 polymorphism information content (PIC) 값을 산출하였다. Pij 는 마커 i의 밴드들 중에서 j번째 공통 밴드 패턴의 빈도수이다(Anderson et al. 1993).
PICi=1j=1nPij2
NTSYSpc (version 2.10b) (Rohlf 2000) 컴퓨터 프로그램 의 Jaccard (Sneath & Sokal 1973)방법에 따라 유전적 유사 도 값을 계산한 후 unweighted pair-group method with arithmetical average (UPGMA) (Sneath & Sokal 1973) 방 법을 통해 유연관계를 분석하였다. 품종식별에 효과적인 최소 마커를 선정하기 위하여 Mantel 분석(Mantel 1967)에 의해 상관관계를 분석하였다.
SSR 마커 분석
블루베리의 품종식별에 적합한 SSR 마커를 선발하고자 총 49개의 EST에서 유래된 SSR 마커(Boches 2005)와 ‘Rebel’, ‘Suziblue’, ‘Huron’, ‘Liberty’, ‘Draper’, ‘Ochlockonee’를 이용하여 품종간 다형성 정도를 조사하였을 때 공시품종내에서 다형성을 나타낸 비율은 61.2%를 나타내었다. Polyacrylamide gel에서 다형성을 보이는 30개 SSR 마커 중 PCR 증폭이 약 한 밴드는 제외하고, 밴드 패턴이 선명하고, 반복 실험간 뚜렷 한 재현성을 보이는 17개의 마커를 최종 선발하였다. 17개 프 라이머의 정방향에 FAM, VIC, NED, PET 중 한가지의 형 광 물질을 표지한 프라이머와 34품종을 PCR 한 다음 자동염 기서열 분석기로 전기영동하여 대립유전자 크기를 분석한 바 (Fig. 1), 총 17개 SSR 마커에 의해 분석된 대립유전자의 수 는 2~15개였고, 총 115개의 대립유전자가 분석되었으며 마 커 당 평균 대립유전자의 수는 6.8개로 나타났다(Table 2). SSR 마커를 이용한 다른 연구자의 분석결과를 살펴보면 하 이부쉬 블루베리의 경우 마커 당 평균 대립유전자의 개수는 7.7~8.2개(Boches 2006), EST-PCR 마커를 이용한 로우부쉬 블루베리의 마커 당 평균 대립유전자 개수는 4.8개 (Bell et al. 2008)로 보고되었다. 본 연구의 결과와 대립유전 자 수를 비교하면 Bell et al. (2008)의 대립유전자 수보다는 많았으나, Boches et al. (2006)의 대립유전자 수보다는 다소 적게 나타났는데, 본 연구에서 활용된 분자마커가 다르고 공 시품종들의 유전적인 다양성 정도가 다르기 때문인 것으로 사료된다.
Fig. 1.
SSR peaks of 3 blueberry varieties at the CA25F locus. The PCR products were separated using a Genetic Analyzer 3730XL(Applied Biosystem, USA) and detected using GeneMapper software(Applied Biosystem, USA). A: Blueshower, B: Spartan, C: Huron.
KJBS-46-58_F1.gif
Table 2
The informative SSR markers selected for identification of blueberry varieties
Table 2
No. Primer name Repeat motif Annealing temp. Product size No. of alleles PIC value Primer labeling
(°C) (bp)

1 CA23F (AGA)6 60 156~168 5 0.626 VIC
2 CA25F (TG)7 55 240~252 7 0.652 NED
3 CA169F (GAT)4 55 111~138 8 0.787 VIC
4 CA190R (TGC)5 55 237~243 3 0.635 NED
5 CA214F (TC)6 55 120~124 3 0.574 FAM
6 CA236Fz (TG)17 55 219~239 11 0.832 NED
7 CA278F (CCA)7 60 232~253 8 0.749 FAM
8 CA518F (CAC)6 55 177~183 3 0.248 FAM
9 CA664F (AG)6 55 120~128 5 0.530 VIC
10 CA1031Fz (CT)10 55 220~242 10 0.817 VIC
11 NA172 (CAT)5 55 292~307 5 0.687 FAM
12 NA222 (TG)8 55 303~307 3 0.604 PET
13 NA240 (TC)3 60 100~102 2 0.485 VIC
14 NA961 (TAC)5 55 182~194 5 0.751 NED
15 VCC_H9 (CT)13 55 195~224 15 0.888 VIC
16 VCC_I8z (TG)8 55 108~161 12 0.820 FAM
17 VCC_J3 (AAG)15 55 126~163 10 0.714 PET

Total 115 11.399

Mean 6.8 0.671

zMinimum markers.

총 17개 마커별 품종식별력 정도를 나타내주는 PIC 값은 0.248~0.888의 분포를 나타내었고, 평균값은 0.671로 높은 경향을 나타내었다. 기존에 보고된 다형성 정도 수치와 비교 할 때 기존연구에서는 PIC값에 대한 결과는 보고되지 않고, Shannon’s index (H) (Shannon & Weaver 1949)를 분석하 여 품종 간의 다형성을 비교한 바 있다(Boches 2005). 공시 재료의 대립유전자 수가 많을수록 Shannon’s index (H)값이 높은 경향을 나타내었고, 58개 유전자원과 13품종의 블루베 리의 다형성 정도는 재료의 다양성 정도에 따라 평균 7.7~ 9.8의 분포를 나타낸다고 보고하였다(Boches 2005). 본 연구 에서 최종 선발된 17개 SSR 마커 중에서 CA236F, CA1031F, VCC_H9 및 VCC_I8 마커는 PIC값이 0.80 이상으로 공시품 종 내에서 높은 다형성을 나타내었다. Hinrichsen et al. (2009)에 의하면 SSR 마커 CA344F, VCC_H9, CA794F 순 으로 블루베리 품종식별에 효과적인 것으로 보고하였다. 본 연구에서는 VCC_H9 마커의 PIC 값이 0.888로 높게 나타나 Hinrichsen et al. (2009)의 연구 결과를 확인할 수 있었으나 CA344F와 CA794F 마커의 경우 Hinrichsen et al. (2009)의 연구결과와 다르게 나타났는데 이에 대해서 공시품종이나 유 전자원 등을 다양하게 공시하여 깊이 있는 연구가 수행되어 야 할 것으로 사료된다.
공시품종 간 식별이 가능한 최소 마커 조합을 선정하기 위 하여 PIC 값이 높은 마커들을 이용하여 계통도를 작성한 결 과 PIC 값이 0.80 이상인 마커 중 총 3개 마커(CA236F, CA1031F, VCC_I8)를 이용하였을 때 17개 마커 조합을 이 용한 결과와 같이 34품종이 모두 식별이 되었다. 17개 SSR 마커와 3개 SSR 마커의 상관관계를 알아보기 위하여 Mantel 분석(Mantel 1967)을 수행한 결과 상관계수(r)는 0.744로 나 타났다. 따라서 블루베리 34품종의 식별에 3개의 최소 마커 를 활용한다면 17개 전체 마커를 활용한 효과를 얻을 수 있어 유전자 분석에 소요되는 시간과 경비를 절감할 수 있을 것으 로 사료된다.
블루베리는 12개의 염색체가 있고 2배체(2n=2X=24), 4배 체(2n=4X=48), 6배체(2n=6X=72)가 존재하여 배수성 작물 로 알려져 있다(Longley 1927). 본 연구에 활용된 하이부쉬 블루베리는 4배체이고, 래빗아이 블루베리는 6배체이며, 하프 하이부쉬 블루베리는 4배체로 보고된바 있다(Ratnaparkhe 2007). 배수체 작물의 경우 대립유전자 개수가 많기에 자동염 기서열분석기를 이용한 정밀한 유전자형 분석 연구가 필요하 다. 본 연구에서의 정밀한 유전자형 결과를 기반으로 향후 공 시품종에 대한 배수성 분석이 추가적으로 수행된다면 공시품 종의 염색체 수와 대립유전자 수간의 비교 분석 연구도 가능 할 것으로 사료된다.
유전적 유사도 분석
블루베리 품종식별을 위해 최종 선발된 17개의 마커를 이 용하여 34품종에 대한 유전적 유사도를 분석하였다(Fig. 2). 공시품종의 유사도 지수는 0.31~0.81의 범위로 나타났고, 34품종이 모두 식별되었다. 공시품종의 유연관계는 유사도 지수 0.40을 기준으로 할 때 3개의 그룹으로 구분되었다. 그 룹 I은 하이부쉬 블루베리, 그룹 II는 하프 하이부쉬 블루베 리, 그룹 III은 래빗아이 블루베리가 속하여 알려진 계통에 따 라 각각의 그룹을 형성하였다. Bidani et al. (2013)는 17개 SSR 마커를 이용하여 287개의 품종과 유전자원에 대한 유연 관계를 분석한 결과 래빗아이 품종의 경우 하나의 그룹을 형 성하였다고 보고한 바 있어 본 결과와 유사하였다. 래빗아이 품종이 하이부쉬 품종과 다른 그룹을 형성한 것은 종간의 유 전적 거리가 멀고, 염색체의 배수체 등이 다르기 때문에 나타 난 결과로 사료된다. 하프 하이부쉬 블루베리인 ‘Northsky’ 품종의 경우 Bidani et al. (2013)이 보고한 바에 따르면 래빗 아이 품종보다 하이부쉬 품종과 유전적 유사도가 높게 그룹 화 되었는데 본 연구에서도 ‘Northsky’ 품종은 래빗아이 품종 보다 하이부쉬 품종과 유사도가 높게 나타났다. Ratnaparkhe (2007)에 의하면 하프 하이부쉬 블루베리는 키가 큰 하이부 쉬 블루베리와 키가 작은 로우부쉬 블루베리의 교배로 육성 되었다고 보고했고 이로 인해 하프 하이부쉬와 하이부쉬의 유사도가 높게 나타난 것으로 추정된다. 한편 하이부쉬 블루 베리는 저온 요구도에 따라 북부 하이부쉬와 남부 하이부쉬 로 구분되는데 유사도 분석 결과 북부, 남부 하이부쉬 품종별 로 그룹을 형성하지 않고 하나의 그룹으로 묶였다. 남부 하이 부쉬 품종은 북부 하이부쉬로부터 따뜻한 남부기후에서 잘 재 배되도록 V. darrowi (Ratnaparkhe 2007)와 V. ashei (Lyrene 1990) 등과 교배하여 육성된 품종으로 저온 요구도에서 북부 하이부쉬와 큰 차이를 나타내고, 기타 특성은 비슷한 것으로 Boches (2005)에 의해 보고된 바 있다.
Fig. 2.
Genetic relationship of 34 blueberry varieties generated by 17 SSR markers. The scale at the bottom is Jaccard’s coefficient of similarity. I : Vaccinium corymbosum, II : Vaccinium corymbosum × Vaccinium angustifolium, III : Vaccinium ashei.
KJBS-46-58_F2.gif
공시품종 중 품종보호를 위해 출원된 품종인 하이부쉬 블루 베리 ‘Suziblue’, ‘Rebel’, ‘Aurora’, ‘Liberty’, ‘Huron’, ‘Draper’ 품종과 래빗아이 블루베리 ‘Ochlockonee’ 품종은 SSR 마커 에 의해 구분되었다. ‘Aurora’ 품종과 ‘Liberty’ 품종간의 유 전적 유사도는 0.813 (Table 3)으로 공시품종 중 가장 높게 나타났는데 육성 계통도를 조사해본 결과 두 품종 모두 ‘Brigitta’와 ‘Elliot’ 품종의 교배로 육성된 품종으로 양친이 동일하기 때문에 유사도가 높게 나타난 것으로 추정된다. 향 후 두 품종에 대한 형태적 특성 검정을 통해 유전자형과 표현 형의 품종간 최소거리에 대한 비교연구가 필요할 것으로 사 료된다.
Table 3
Genetic distance matrix derived from SSR analyses of 34 blueberry varieties using jaccard’s estimate of similarity
Table 3
1z 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

1z 1.000
2 0.500 1.000
3 0.452 0.386 1.000
4 0.395 0.364 0.298 1.000
5 0.415 0.381 0.255 0.813 1.000
6 0.452 0.356 0.512 0.419 0.372 1.000
7 0.405 0.439 0.333 0.475 0.462 0.463 1.000
8 0.340 0.465 0.362 0.465 0.452 0.362 0.512 1.000
9 0.444 0.477 0.404 0.512 0.432 0.435 0.488 0.511 1.000
10 0.327 0.444 0.347 0.585 0.500 0.467 0.391 0.478 0.458 1.000
11 0.476 0.409 0.500 0.378 0.333 0.465 0.419 0.477 0.489 0.426 1.000
12 0.467 0.404 0.426 0.535 0.488 0.558 0.477 0.568 0.543 0.479 0.511 1.000
13 0.465 0.400 0.455 0.500 0.452 0.455 0.409 0.610 0.619 0.511 0.585 0.605 1.000
14 0.550 0.476 0.432 0.348 0.395 0.400 0.356 0.383 0.396 0.396 0.422 0.447 0.413 1.000
15 0.362 0.422 0.383 0.561 0.512 0.512 0.537 0.426 0.500 0.468 0.535 0.556 0.457 0.375 1.000
16 0.489 0.489 0.447 0.457 0.413 0.511 0.500 0.489 0.532 0.532 0.568 0.698 0.556 0.568 0.511 1.000
17 0.396 0.457 0.88 0.489 0.512 0.388 0.650 0.489 0.440 0.412 0.468 0.490 0.400 0.380 0.614 0.510 1.000
18 0.386 0.419 0.476 0.419 0.341 0.442 0.429 0.488 0.535 0.435 0.432 0.523 0.524 0.465 0.413 0.581 0.417 1.000
19 0.467 0.435 0.426 0.500 0.455 0.489 0.444 0.643 0.543 0.511 0.545 0.674 0.643 0.417 0.522 0.521 0.490 0.523 1.000
20 0.417 0.511 0.408 0.619 0.535 0.468 0.558 0.578 0.622 0.659 0.489 0.609 0.578 0.458 0.565 0.744 0.531 0.643 0.609 1.000
21 0.442 0.442 0.286 0.476 0.463 0.370 0.488 0.548 0.457 0.523 0.455 0.581 0.512 0.488 0.467 0.683 0.468 0.465 0.581 0.667 1.000
22 0.378 0.442 0.370 0.590 0.538 0.465 0.525 0.512 0.489 0.634 0.391 0.478 0.444 0.524 0.500 0.533 0.533 0.500 0.478 0.628 0.524 1.000
23 0.463 0.463 0.419 0.463 0.381 0.419 0.553 0.432 0.477 0.512 0.550 0.467 0.500 0.442 0.488 0.595 0.457 0.419 0.500 0.619 0.512 0.550 1.000
24 0.435 0.571 0.426 0.467 0.488 0.426 0.625 0.568 0.578 0.479 0.478 0.600 0.533 0.447 0.556 0.622 0.659 0.558 0.600 0.762 0.545 0.545 0.535 1.000
25 0.452 0.419 0.476 0.525 0.413 0.512 0.463 0.600 0.610 0.500 0.537 0.634 0.641 0.432 0.477 0.581 0.511 0.590 0.718 0.683 0.537 0.537 0.488 0.718 1.000
26 0.512 0.512 0.467 0.413 0.432 0.375 0.455 0.545 0.556 0.458 0.523 0.511 0.581 0.489 0.438 0.500 0.440 0.435 0.543 0.553 0.457 0.457 0.477 0.614 0.535 1.000
27 0.380 0.08 0.321 0.408 0.367 0.346 0.417 0.532 0.574 0.480 0.479 0.531 0.565 0.365 0.404 0.551 0.434 0.400 0.531 0.540 0.578 0.449 0.468 0.531 0.556 0.510 1.000
28 0.467 0.375 0.96 0.404 0.422 0.595 0.477 0.438 0.479 0.449 0.417 0.469 0.468 0.417 0.429 0.460 0.377 0.396 0.440 0.480 0.388 0.511 0.467 0.440 0.489 0.479 0.415 1.000
29 0.465 0.432 0.422 0.370 0.326 0.422 0.512 0.571 0.478 0.388 0.477 0.468 0.500 0.413 0.367 0.458 0.400 0.362 0.500 0.420 0.413 0.413 0.432 0.408 0.422 0.511 0.412 0.500 1.000
30 0.373 0.321 0.291 0.321 0.283 0.291 0.327 0.404 0.415 0.293 0.358 0.434 0.490 0.358 0.298 0.426 0.351 0.392 0.434 0.418 0.440 0.333 0.373 0.434 0.420 0.442 0.411 0.357 0.431 1.000
31 0.264 0.264 0.214 0.264 0.250 0.259 0.245 0.276 0.286 0.263 0.232 0.304 0.273 0.380 0.291 0.321 0.254 0.236 0.327 0.271 0.278 0.302 0.288 0.259 0.259 0.220 0.226 0.237 0.296 0.283 1.000
32 0.321 0.373 0.224 0.373 0.388 0.315 0.327 0.404 0.339 0.364 0.263 0.333 0.281 0.412 0.345 0.375 0.305 0.291 0.382 0.393 0.412 0.440 0.346 0.357 0.340 0.316 0.317 0.357 0.327 0.311 0.453 1.000
33 0.345 0.321 0.293 0.276 0.263 0.316 0.217 0.283 0.339 0.295 0.10 0.333 0.305 0.462 0.279 0.397 0.227 0.271 0.311 0.302 0.310 0.333 0.298 0.250 0.250 0.317 0.317 0.290 0.328 0.292 0.500 0.448 1.000
34 0.333 0.333 0.305 0.288 0.276 0.305 0.230 0.317 0.350 0.306 0.300 0.302 0.317 0.368 0.311 0.339 0.297 0.283 0.344 0.313 0.300 0.345 0.267 0.302 0.305 0.280 0.288 0.281 0.339 0.323 0.431 0.458 0.607 1.000

zThe numbers (1 to 34) at the upper and left refer to the list of varieties in Table 1.

UPOV 산하 기술위원회 중의 하나인 분자생물학 및 생화 학 실무작업반회의(BMT, Working Group on Biochemical and Molecular Techniques, and DNA-Profiling in Particular) 에서는 분자표지를 품종의 구별성(Distinctness, D), 균일성 (Uniformity, U), 안정성(Stability, S) 판단에 직접적으로 활 용하는 것은 인정하지 않으나 형태적 특성을 고려한 분자표 지의 활용은 제안하고 있다. 대표적인 예로 형태적 특성과 밀 접히 연관된 마커의 활용, 형태적 특성과 분자표지의 상관관 계가 높을 때 분자표지를 활용, 형태적 특성과 분자표지 성적 을 병합한 후 상관관계가 높을 때 분자표지를 활용하는 방안 을 제시하고 있다(UPOV 2011).
따라서 본 연구에서는 블루베리 34품종에 대해서 17개 SSR 마커를 이용하여 품종별 SSR 프로파일 데이터베이스를 구축하였고 향후 공시품종에 대한 특성조사를 통해 SSR 마 커와 형태적 특성의 상관관계가 밝혀진다면 블루베리 품종보 호 출원품종의 대조품종 선정과 구별성 심사, 국내 유통품종 의 진위성 검정 및 분쟁종자 대비시험에 매우 유용하게 활용 될 것으로 사료된다.
국내에서 수집된 블루베리 34품종의 식별을 위하여 SSR 마커를 이용하여 품종별 SSR 프로파일 데이터베이스를 구축 하였다. 블루베리 품종의 식별에 적합한 마커를 선정하기 위 하여 6개 품종을 대상으로 총 49개의 마커를 분석하였다. 6개 품종간에 높은 다형성과 재현성을 나타내고, 밴드패턴이 선명 한 17개의 마커를 선발하여 공시된 34품종을 분석하였을 때 총 115개의 대립유전자가 분석되었다. 대립유전자의 수의 분 포는 2~15개를 나타내었고, 마커당 평균 대립유전자의 수는 6.8개로 분석되었다. PIC 값은 0.248~0.888의 범위에 속하 였으며 평균값은 0.671로 나타났다. 115개의 대립유전자를 Jaccard 방법에 의해 유사도를 산출하고 비가중 산술방식에 의해 집괴 분석한 결과 공시품종의 유전적 거리는 0.31~ 0.81의 범위로 나타났고 계통도는 유사도 지수 0.40을 기준 으로 할 때 종에 따라 3개의 그룹으로 구분되었다. 17개 SSR 마커에 의해 34품종이 모두 식별되었고, 34품종을 식별할 수 있는 3개의 최소마커 조합을 선정하였다. 본 결과는 블루베리 품종식별과 신품종 보호 심사를 위한 유전자 분석 자료로 유 용하게 활용될 것으로 사료된다.
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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea
Korean. J. Breed. Sci.. ;46(1):58-65.   Published online March 31, 2014
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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea
Korean. J. Breed. Sci.. ;46(1):58-65.   Published online March 31, 2014
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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea
Image Image
Fig. 1. SSR peaks of 3 blueberry varieties at the CA25F locus. The PCR products were separated using a Genetic Analyzer 3730XL(Applied Biosystem, USA) and detected using GeneMapper software(Applied Biosystem, USA). A: Blueshower, B: Spartan, C: Huron.
Fig. 2. Genetic relationship of 34 blueberry varieties generated by 17 SSR markers. The scale at the bottom is Jaccard’s coefficient of similarity. I : Vaccinium corymbosum, II : Vaccinium corymbosum × Vaccinium angustifolium, III : Vaccinium ashei.

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Construction of SSR Profile Database for Variety Identification of Blueberry in Korea

Blueberry varieties used for variety identification by SSR markers

No. Varieties Classification No. Varieties Classification

1 Rebel Highbush (S)z 18 Jersey Highbush (N)
2 Brigittar Highbush (N)y 19 Collins Highbush (N)
3 Suziblue Highbush (S) 20 Reka Highbush (N)
4 Aurora Highbush (N) 21 Spartan Highbush (N)
5 Liberty Highbush (N) 22 Bluecrop Highbush (N)
6 Blueray Highbush (N) 23 Earliblue Highbush (N)
7 Duke Highbush (N) 24 Elizabeth Highbush (N)
8 Nelson Highbush (N) 25 Bluejay Highbush (N)
9 Chandler Highbush (N) 26 Sierra Highbush (N)
10 Elliot Highbush (N) 27 Huron Highbush (N)
11 Sunrise Highbush (N) 28 Draper Highbush (N)
12 O'Neal Highbush (S) 29 Misty Highbush (S)
13 Lancocas Highbush (N) 30 Northsky Half highbushx
14 Patriot Highbush (N) 31 Blueshower Rabbiteyew
15 Bluetta Highbush (N) 32 Delite Rabbiteye
16 Dixi Highbush (N) 33 Ochlockonee Rabbiteye
17 Coville Highbush (N) 34 Alapaha Rabbiteye

Highbush (S) : Southern highbush (Vaccinium corymbosum × Vaccinium darrowi, Vaccinium ashei)

Highbush (N) : Northern highbush (Vaccinium corymbosum)

Half highbush (Vaccinium corymbosum × Vaccinium angustifolium)

Rabbiteye (Vaccinium ashei)

The informative SSR markers selected for identification of blueberry varieties

No. Primer name Repeat motif Annealing temp. Product size No. of alleles PIC value Primer labeling
(°C) (bp)

1 CA23F (AGA)6 60 156~168 5 0.626 VIC
2 CA25F (TG)7 55 240~252 7 0.652 NED
3 CA169F (GAT)4 55 111~138 8 0.787 VIC
4 CA190R (TGC)5 55 237~243 3 0.635 NED
5 CA214F (TC)6 55 120~124 3 0.574 FAM
6 CA236Fz (TG)17 55 219~239 11 0.832 NED
7 CA278F (CCA)7 60 232~253 8 0.749 FAM
8 CA518F (CAC)6 55 177~183 3 0.248 FAM
9 CA664F (AG)6 55 120~128 5 0.530 VIC
10 CA1031Fz (CT)10 55 220~242 10 0.817 VIC
11 NA172 (CAT)5 55 292~307 5 0.687 FAM
12 NA222 (TG)8 55 303~307 3 0.604 PET
13 NA240 (TC)3 60 100~102 2 0.485 VIC
14 NA961 (TAC)5 55 182~194 5 0.751 NED
15 VCC_H9 (CT)13 55 195~224 15 0.888 VIC
16 VCC_I8z (TG)8 55 108~161 12 0.820 FAM
17 VCC_J3 (AAG)15 55 126~163 10 0.714 PET

Total 115 11.399

Mean 6.8 0.671

Minimum markers.

Genetic distance matrix derived from SSR analyses of 34 blueberry varieties using jaccard’s estimate of similarity

1z 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

1z 1.000
2 0.500 1.000
3 0.452 0.386 1.000
4 0.395 0.364 0.298 1.000
5 0.415 0.381 0.255 0.813 1.000
6 0.452 0.356 0.512 0.419 0.372 1.000
7 0.405 0.439 0.333 0.475 0.462 0.463 1.000
8 0.340 0.465 0.362 0.465 0.452 0.362 0.512 1.000
9 0.444 0.477 0.404 0.512 0.432 0.435 0.488 0.511 1.000
10 0.327 0.444 0.347 0.585 0.500 0.467 0.391 0.478 0.458 1.000
11 0.476 0.409 0.500 0.378 0.333 0.465 0.419 0.477 0.489 0.426 1.000
12 0.467 0.404 0.426 0.535 0.488 0.558 0.477 0.568 0.543 0.479 0.511 1.000
13 0.465 0.400 0.455 0.500 0.452 0.455 0.409 0.610 0.619 0.511 0.585 0.605 1.000
14 0.550 0.476 0.432 0.348 0.395 0.400 0.356 0.383 0.396 0.396 0.422 0.447 0.413 1.000
15 0.362 0.422 0.383 0.561 0.512 0.512 0.537 0.426 0.500 0.468 0.535 0.556 0.457 0.375 1.000
16 0.489 0.489 0.447 0.457 0.413 0.511 0.500 0.489 0.532 0.532 0.568 0.698 0.556 0.568 0.511 1.000
17 0.396 0.457 0.88 0.489 0.512 0.388 0.650 0.489 0.440 0.412 0.468 0.490 0.400 0.380 0.614 0.510 1.000
18 0.386 0.419 0.476 0.419 0.341 0.442 0.429 0.488 0.535 0.435 0.432 0.523 0.524 0.465 0.413 0.581 0.417 1.000
19 0.467 0.435 0.426 0.500 0.455 0.489 0.444 0.643 0.543 0.511 0.545 0.674 0.643 0.417 0.522 0.521 0.490 0.523 1.000
20 0.417 0.511 0.408 0.619 0.535 0.468 0.558 0.578 0.622 0.659 0.489 0.609 0.578 0.458 0.565 0.744 0.531 0.643 0.609 1.000
21 0.442 0.442 0.286 0.476 0.463 0.370 0.488 0.548 0.457 0.523 0.455 0.581 0.512 0.488 0.467 0.683 0.468 0.465 0.581 0.667 1.000
22 0.378 0.442 0.370 0.590 0.538 0.465 0.525 0.512 0.489 0.634 0.391 0.478 0.444 0.524 0.500 0.533 0.533 0.500 0.478 0.628 0.524 1.000
23 0.463 0.463 0.419 0.463 0.381 0.419 0.553 0.432 0.477 0.512 0.550 0.467 0.500 0.442 0.488 0.595 0.457 0.419 0.500 0.619 0.512 0.550 1.000
24 0.435 0.571 0.426 0.467 0.488 0.426 0.625 0.568 0.578 0.479 0.478 0.600 0.533 0.447 0.556 0.622 0.659 0.558 0.600 0.762 0.545 0.545 0.535 1.000
25 0.452 0.419 0.476 0.525 0.413 0.512 0.463 0.600 0.610 0.500 0.537 0.634 0.641 0.432 0.477 0.581 0.511 0.590 0.718 0.683 0.537 0.537 0.488 0.718 1.000
26 0.512 0.512 0.467 0.413 0.432 0.375 0.455 0.545 0.556 0.458 0.523 0.511 0.581 0.489 0.438 0.500 0.440 0.435 0.543 0.553 0.457 0.457 0.477 0.614 0.535 1.000
27 0.380 0.08 0.321 0.408 0.367 0.346 0.417 0.532 0.574 0.480 0.479 0.531 0.565 0.365 0.404 0.551 0.434 0.400 0.531 0.540 0.578 0.449 0.468 0.531 0.556 0.510 1.000
28 0.467 0.375 0.96 0.404 0.422 0.595 0.477 0.438 0.479 0.449 0.417 0.469 0.468 0.417 0.429 0.460 0.377 0.396 0.440 0.480 0.388 0.511 0.467 0.440 0.489 0.479 0.415 1.000
29 0.465 0.432 0.422 0.370 0.326 0.422 0.512 0.571 0.478 0.388 0.477 0.468 0.500 0.413 0.367 0.458 0.400 0.362 0.500 0.420 0.413 0.413 0.432 0.408 0.422 0.511 0.412 0.500 1.000
30 0.373 0.321 0.291 0.321 0.283 0.291 0.327 0.404 0.415 0.293 0.358 0.434 0.490 0.358 0.298 0.426 0.351 0.392 0.434 0.418 0.440 0.333 0.373 0.434 0.420 0.442 0.411 0.357 0.431 1.000
31 0.264 0.264 0.214 0.264 0.250 0.259 0.245 0.276 0.286 0.263 0.232 0.304 0.273 0.380 0.291 0.321 0.254 0.236 0.327 0.271 0.278 0.302 0.288 0.259 0.259 0.220 0.226 0.237 0.296 0.283 1.000
32 0.321 0.373 0.224 0.373 0.388 0.315 0.327 0.404 0.339 0.364 0.263 0.333 0.281 0.412 0.345 0.375 0.305 0.291 0.382 0.393 0.412 0.440 0.346 0.357 0.340 0.316 0.317 0.357 0.327 0.311 0.453 1.000
33 0.345 0.321 0.293 0.276 0.263 0.316 0.217 0.283 0.339 0.295 0.10 0.333 0.305 0.462 0.279 0.397 0.227 0.271 0.311 0.302 0.310 0.333 0.298 0.250 0.250 0.317 0.317 0.290 0.328 0.292 0.500 0.448 1.000
34 0.333 0.333 0.305 0.288 0.276 0.305 0.230 0.317 0.350 0.306 0.300 0.302 0.317 0.368 0.311 0.339 0.297 0.283 0.344 0.313 0.300 0.345 0.267 0.302 0.305 0.280 0.288 0.281 0.339 0.323 0.431 0.458 0.607 1.000

The numbers (1 to 34) at the upper and left refer to the list of varieties in Table 1.

Table 1 Blueberry varieties used for variety identification by SSR markers
Table 2 The informative SSR markers selected for identification of blueberry varieties
Table 3 Genetic distance matrix derived from SSR analyses of 34 blueberry varieties using jaccard’s estimate of similarity