Genetic Diversity Analysis of Rice Germplasm in Tripura State of Northeast India Using Drought and Blast Linked Markers

doi:10.1016/j.rsci.2016.07.003

Abstract

Abstract:

We genotyped 74 rice germplasms including Tripura’s local landraces, improved varieties, cultivars and breeding lines and other rice varieties using molecular markers for genetic diversity, drought QTLs, and blast resistance genes. The number of alleles per locus ranged from 2 to 5 with an average of 2.9. The polymorphic information content value per locus ranged from 0.059 (RM537) to 0.755 (RM252) with an average of 0.475. Cluster analysis based on 30 simple sequence repeat markers revealed 5 clusters and also indicated the presence of variability within the rice accessions. The drought QTL qDTY2.1 was found in 56.0% of germplasms and qDTY1.1 was detected in only 6.8% of the germplasms. Out of seven rice blast resistance genes screened, only two rice varieties, RCPL-1-82 and Buh Vubuk (Lubuk), were positive for four blast resistance genes while only Releng possessed two blast resistance genes. Among 74 rice germplasms, only three accessions, Releng, RCPL1-82 and Buh Vubuk (Lubuk), possessed both drought-related QTLs and blast resistance genes. Overall, the 74 indigenous rice genotypes showed low level of genetic diversity, which is in contrast to high level of genetic diversity among rice varieties in northeast India, where highlights the good farming practice, conservation of germplasms and the limitation of molecular markers employed in this study. The presence of both drought related QTLs and blast resistance genes in some of the germplasms can be useful in future breeding programmes.

Key words: drought, blast disease, quantitative trait locus, genetic diversity, gene, molecular marker, rice, germplasm

Anupam Alpana, Imam Jahangir, Mohammad Quatadah Syed, Siddaiah Anantha, Prasad Das Shankar, Variar Mukund, Prasad Mandal Nimai. Genetic Diversity Analysis of Rice Germplasm in Tripura State of Northeast India Using Drought and Blast Linked Markers[J]. Rice Science, 2017, 24(1): 10-20.

Figures/Tables 6

References 53

1	Anderson J A, Churchill G A, Autrique J E, Tanksley S D, Sorrells M E.1993. Optimizing parental selection for genetic linkage maps.Genome, 36(1): 181-186.
2	Bernier J, Kumar A, Ramaiah V, Spaner D, Atlin G.2007. A large-effect QTL for grain yield under reproductive-stage drought stress in upland rice.Crop Sci, 47(2): 507-516.
3	Bernier J, Kumar A, Venuprasad R, Spaner D, Verulkar S, Mandal N P, Sinha P K, Peeraju P, Dongre P R, Mahto R N, Atlin G.2009a. Characterization of the effect of a QTL for drought resistance in rice, qtl12.1, over a range of environments in the Philippines and eastern India.Euphytica, 166(2): 207-217.
4	Bernier J, Serraj R, Kumar A, Venuprasad R, Impa S, Gowda R P V, Oane R, Spaner D, Atlin G.2009b. The large-effect drought-resistance QTL qtl12.1 increases water uptake in upland rice.Field Crops Res, 110(2): 139-146.
5	Bhuyan N, Borah B K, Sarma R N.2007. Genetic diversity analysis in traditional lowland rice (Oryza sativa L.) of Assam using RAPD and ISSR markers.Curr Sci, 93(7): 967-972.
6	Borkakati R P, Borah P, Deka P C.2000. Genetic divergence in photoperiodin sensitive autumn rice germplasm of Northeast India. In: Khush G S, Brar D S, Hardy B. Advances in Rice Genetics. Los Banos, the Philippines: International Rice Research Institute: 74-76.
7	Choudhury B, Khan M L, Dayanandan S.2013. Genetic structure and diversity of indigenous rice varieties (Oryza sativa L.) in eastern Himalayan region of northeast India.Springer Plus, 2: 228-237.
8	Das A, Kesari V, Satyanarayana V M, Parida A, Rangan L.2011. Genetic relationship of curcuma species from northeast India using PCR-based markers.Mol Biotechnol, 49(1): 65-76.
9	DeWoody J A, Honeycutt R L, Skow L C.1995. Microsatellite markers in white-tailed deer.J Hered, 86(4): 317-319.
10	Dixit S, Swamy B P M, Vikram P, Ahmed H U, Sta Cruz M T, Amante M, Atri D, Leung H, Kumar A.2012. Fine mapping of QTLs for rice grain yield under drought reveals sub-QTLs conferring a response to variable drought severities.Theor Appl Genet, 125(1): 155-169.
11	Dixit S, Singh A, Sta Cruz M T, Maturan P T, Amante M, Kumar A.2014. Multiple major QTL lead to stable yield performance of rice cultivars across varying drought intensities.BMC Genet, 15: 16.
12	Doebley J F, Gaut B S, Smith B D.2006. The molecular genetics of crop domestication.Cell, 127(7): 1309-1321.
13	Doyle J J, Doyle J L.1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue.Phytochem Bull, 19: 11-15.
14	Ferreira M E, Grattapaglia D.1998. Introduction to the Use of Molecular Markers in Genetic Analysis. 2nd edn. Embrapa-Cenargen, Brasilia: 220.
15	Glaszmann J C, Benyayer P, Arnaud M.1989. Genetic divergence among rice from Northeast India. In: Rice Genetics Newsletter. Mishima, Japan: Genetic Resources Section, National Institute of Genetics: 63.
16	Gomez M, Babu R C, Shanmugasundaram P, Kumar S R, Suresh R, Biji K R, Boopathi N M, Jeyaprakash P, Gurumurthy S, Price A H.2005. QTL mapping and marker assisted selection for drought tolerance in rice (Oryza sativa L.). In: Proceedings of the 2nd International Conference on Integrated Approaches to Sustain and Improve Plant Production under Drought Stress. University of Rome, La Sapienza, Rome, Italy.
17	Hayashi K, Yoshida H, Ashikawa I.2006. Development of PCR-based allele speciﬁc and InDel marker sets for nine rice blast resistance genes.Theor Appl Genet, 113(2): 251-260.
18	Hore D K.2005. Rice diversity collection, conservation and management in north eastern India.Genet Resour Crop Evol, 52(8): 1129-1140.
19	Imam J, Alam S, Variar M, Shukla P.2013. Identification of rice blast resistance gene Pi9 from Indian rice landraces with STS marker and its verification by virulence analysis.Proc Natl Acad Sci, Ind Sec B: Biol Sci, 83(4): 499-504.
20	Imam J, Alam S, Mandal N P, Variar M, Shukla P.2014a. Molecular screening for identification of blast resistance genes in northeast and eastern Indian rice germplasm (Oryza sativa L.) with PCR based markers.Euphytica, 196(2): 199-211.
21	Imam J, Mahto D, Mandal N P, Maiti D, Shukla P, Variar M.2014b. Molecular analysis of Indian rice germplasm accessions with resistance to blast pathogen.J Crop Improv, 28(6): 729-739.
22	Imam J, Alam S, Mandal N P, Maiti D, Variar M, Shukla P.2015a. Molecular diversity and mating type distribution of the rice blast pathogen Magnaporthe oryzae in north-east and eastern India.Ind J Microbiol, 55(1): 108-113.
23	Imam J, Alam S, Mandal N P, Shukla P, Sharma T R, Variar M.2015b. Molecular identification and virulence analysis of Avr genes in rice blast pathogen, Magnaporthe oryzae from eastern India.Euphytica, 206(1): 21-31.
24	Jain S, Jain R K, McCouch S R.2004. Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently labelled microsatellite markers.Theor Appl Genet, 109(5): 965-977.
25	Jia Y L, Wang Z H, Singh P.2002. Development of dominant rice blast Pi-ta resistance gene markers.Crop Sci, 42(6): 2145-2149.
26	Jia Y L, Redus M, Wang Z H, Rutger J N.2004. Development of a SNLP marker from the Pi-ta blast resistance gene by tri-primer PCR.Euphytica, 138(1): 97-105.
27	Kalinowski S T, Taper M L.2006. Maximum likelihood estimation of the frequency of null alleles at microsatellite loci.Conserv Genet, 7(6): 991-995.
28	Kumar R, Venuprasad R, Atlin G N.2007. Genetic analysis of rainfed lowland rice drought tolerance under naturally occurring stress in eastern India: Heritability and QTL effects.Field Crops Res, 103(1): 42-52.
29	Kuroda Y, Sato Y I, Bounphanousay C, Kono Y, Tanaka K.2007. Genetic structure of three Oryza AA genome species (O. rufipogon, O. nivara and O. sativa) as assessed by SSR analysis on the Vientiane Plain of Laos.Conserv Genet, 8(1): 149-158.
30	Liu G, Lu G, Zeng L, Wang G L.2002. Two broad spectrum resistance genes, Pi9(t) and Pi2(t), are physically linked on rice chromosome 6.Mol Genet Genom, 267: 472-480.
31	Mahender A, Swain D M, Gitishree D, Subudhi H N, Rao G J N.2012. Molecular analysis of native Manipur rice accessions for resistance against blast.Afr J Biotechnol, 11(6): 1321-1329.
32	Mishra K K, Vikram P, Yadaw R B, Swamy B P M, Dixit S, Sta Cruz M T, Maturan P, Marker S, Kumar A.2013. qDTY12.1: A locus with a consistent effect on grain yield under drought in rice.BMC Genet, 14: 12.
33	Ngachan S V, Mohanty A K, Pattanayak A.2011. Status Paper on Rice in North East India: Rice in North East India. Rice Knowledge Management Portal: 82.
34	Nei M.1973. Analysis of gene diversity in subdivided populations.Proc Natl Acad Sci USA, 70: 3321-3323.
35	Pusadee T, Jamjod S, Chiang Y C, Rerkasem B, Schaal B A.2009. Genetic structure and isolation by distance in a landrace of Thai rice.Proc Natl Acad Sci USA, 106: 13880-13885.
36	Qu S H, Liu G F, Zhou B, Bellizzi M, Zeng L R, Dai L Y, Han B, Wang G L.2006. The broad spectrum blast resistance gene Pi9 encodes a nucleotide-binding site leucine-rich repeat protein and is a member of a multigene family in rice.Genetics, 172(3): 1901-1914.
37	Ram S G, Thiruvengadam V, Vinod K K.2007. Genetic diversity among cultivars, landraces and wild relatives of rice as revealed by microsatellite markers.J Appl Genet, 48(4): 337-345.
38	RoyChowdhury M, Jia Y, Jackson A, Jia M H, Fjellstrom R, Cartwright R.2012a. Analysis of rice blast resistance gene Pi-z using pathogenicity assays and DNA markers.Euphytica, 184(1): 35-46.
39	RoyChowdhury M, Jia Y, Jia M H, Fjellstrom B, Cartwright R.2012b. Identification of the rice blast resistance gene Pi-b in the national small grains collection.Phytopathol, 102(7): 700-706.
40	Sarma B K, Pattanayak A.2009. Rice Diversity of Northeast India. Guwahati, India: Millenium Publishers.
41	Sarma R N, Bahar B.2005. Genetic variation of bora rice (glutinous rice) of Assam as revealed by RAPDs.Plant Genet Resour Newsl, 144: 34-38.
42	Sneath P H A, Sokal R R.1973. Numerical Taxonomy. San Francisco, USA: W. H. Freeman and Company.
43	Swamy B P M, Ahmed H U, Henry A, Mauleon R, Dixit S, Vikram P, Tilatto R, Verulkar S B, Perraju P, Mandal N P, Variar M, Robin S, Chandrababu R, Singh O N, Dwivedi J L, Das S P, Mishra K K, Yadaw R B, Aditya T L, Karmakar B, Satoh K, Moumeni A, Kikuchi S, Leung H, Kumar A.2013. Genetic, physiological, and gene expression analyses reveal that multiple QTL enhance yield of rice mega-variety IR64 under drought.PLoS One, 8(5): e62795.
44	Thomson M J, Septiningsih E M, Suwardjo F, Santoso T J, Silitonga T S, McCouch S R.2007. Genetic diversity analysis of traditional and improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers.Theor Appl Genet, 14(3): 559-568.
45	Tu M, Lu B R, Zhu Y Y, Wang Y Y.2007. Abundant within-varietal genetic diversity in rice germplasm from Yunnan Province of China revealed by SSR fingerprints.Biochem Genet, 45(11): 789-801.
46	Variar M, Vera Cruz C M, Carrillo M G, Bhatt J C, Sangar R B S.2009. Rice blast in India and strategies to develop durably resistant cultivars. In: Wang G L, Valent B. Advances in Genetics, Genomics and Control of Rice Blast Disease. New York, USA: Springer: 359-373.
47	Vairavan S, Siddiq E A, Arunachalam V, Swaminathan M S.1973. A study on the nature of genetic divergence in rice from Assam and Northeast Himalayas.Theor Appl Genet, 43(5): 213-221.
48	Venuprasad R, Dalid C O, Del Valle M, Zhao D, Espiritu M, Sta Cruz M T, Amante M, Kumar A, Atlin G.2009. Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis.Theor Appl Genet, 120(1): 177-190.
49	Verulkar S B, Mandal N P, Dwivedi J L, Singh B N, Sinha P K, Mahato R N, Dongre P, Singh O N, Bose L K, Swain P, Robin S, Chandrababu R, Senthil S, Jain A, Shashidhar H E, Hittalmani S, Vera Cruz C, Paris T, Raman A, Haefele S, Serrai R, Atlin G, Kumar A.2010. Breeding resilient and productive genotypes adapted to drought-prone rainfed ecosystem of India.Field Crops Res, 117(2/3): 197-208.
50	Vikram P, Swamy B P M, Dixit S, Ahmed H U, Sta Cruz M T, Singh A K, Kumar A.2011. qDTY1.1, a major QTL for rice grain yield under reproductive-stage drought stress with a consistent effect in multiple elite genetic backgrounds.BMC Genet, 12: 89.
51	Xiao J H, Grandillo S N, Ahn S N, McCouch S R, Tanksley S D, Li J M, Yuan L P.1996. Genes from wild rice improve rice yield.Nature, 384: 223-224.
52	Yadav S, Singh A, Singh M R, Goel N, Vinod K K, Mohapatra T, Singh A K.2013. Assessment of genetic diversity in Indian rice germplasm (Oryza sativa L.): Use of random versus trait-linked microsatellite markers.J Genet, 92(3): 545-557.
53	Zhang T, Ni X L, Jiang K F, Deng H F, He Q, Yang Q H, Yang L, Wan X Q, Cao Y J, Zheng J K.2010. Relationship between heterosis and parental genetic distance based on molecular markers for functional genes related to yield traits in rice.Rice Sci, 17(4): 288-295.

Gene	Chr	Marker	Primer sequence		AT (ºC)	ES (bp)	Reference
Gene	Chr	Marker	Forward (5′-3′)	Reverse (5′-3′)	AT (ºC)	ES (bp)	Reference
Piz	6	Z56592	GGACCCGCGTTTTCCACGTGTAA	AGGAATCTATTGCTAAGCATGAC	60	292	Hayashi et al (2006)
Piz-t	6	Zt56591	TTGCTGAGCCATTGTTAAACA	ATCTCTTCATATATATGAAGGCCAC	60	257	Hayashi et al (2006)
Pita/Pita-2	12	YL155/YL87	AGCAGGTTATAAGCTAGGCC	CTACCAACAAGTTCATCAAA	55	1042	Jia et al (2002, 2004)
Pi2	6	pB8	CCCAATCTCCAATGACCCATAAC	CCGGACTAAGTACTGGCTTCGATA	55	700	Liu et al (2002)
Pib	2	Pb28	GACTCGGTCGACCAATTCGCC	ATCAGGCCAGGCCAGATTTG	60	388	Hayashi et al (2006)
Pi9	6	195R-1	ATGGTCCTTTATCTTTATTG	TTGCTCCATCTCCTCTGTT	56	2000	Qu et al (2006)
Chr, Chromosome; AT, Annealing temperature; ES, Expanded size.

Gene	Chr	Marker	Primer sequence		AT (ºC)	ES (bp)	Reference
Gene	Chr	Marker	Forward (5′-3′)	Reverse (5′-3′)	AT (ºC)	ES (bp)	Reference
Piz	6	Z56592	GGACCCGCGTTTTCCACGTGTAA	AGGAATCTATTGCTAAGCATGAC	60	292	Hayashi et al (2006)
Piz-t	6	Zt56591	TTGCTGAGCCATTGTTAAACA	ATCTCTTCATATATATGAAGGCCAC	60	257	Hayashi et al (2006)
Pita/Pita-2	12	YL155/YL87	AGCAGGTTATAAGCTAGGCC	CTACCAACAAGTTCATCAAA	55	1042	Jia et al (2002, 2004)
Pi2	6	pB8	CCCAATCTCCAATGACCCATAAC	CCGGACTAAGTACTGGCTTCGATA	55	700	Liu et al (2002)
Pib	2	Pb28	GACTCGGTCGACCAATTCGCC	ATCAGGCCAGGCCAGATTTG	60	388	Hayashi et al (2006)
Pi9	6	195R-1	ATGGTCCTTTATCTTTATTG	TTGCTCCATCTCCTCTGTT	56	2000	Qu et al (2006)
Chr, Chromosome; AT, Annealing temperature; ES, Expanded size.

Marker	Na	He	PIC	Ne	Nr	Marker	Na	He	PIC	Ne	Nr
RM431	3	0.564	0.469	1.712	1	RM72	4	0.747	0.699	1.784	0
RM11943	2	0.480	0.365	1.824	0	RM5789	2	0.259	0.225	1.259	0
RM3825	3	0.666	0.592	1.943	0	RM189	2	0.498	0.374	1.602	0
RM5443	2	0.485	0.367	1.910	0	RM24393	3	0.548	0.470	1.713	0
RM555	3	0.652	0.577	1.892	0	RM24334	4	0.683	0.622	1.606	1
RM279	3	0.617	0.547	1.546	1	RM24421	3	0.511	0.395	1.660	1
RM236	3	0.706	0.648	1.740	1	RM24350	3	0.662	0.588	1.795	0
RM324	3	0.623	0.547	1.786	0	RM566	3	0.616	0.543	1.803	0
RM232	3	0.648	0.575	1.891	0	RM211	2	0.548	0.470	1.207	1
RM60	2	0.338	0.281	1.600	0	RM511	3	0.531	0.468	1.636	0
RM520	3	0.480	0.365	1.823	0	RM28166	3	0.605	0.530	1.761	0
RM537	2	0.061	0.059	1.056	1	RM28130	3	0.529	0.418	1.685	1
RM252	5	0.789	0.755	1.987	0	RM20A	3	0.481	0.392	1.572	1
RM518	3	0.591	0.523	1.654	0	Max	5	0.789	0.755	1.987	2
RM3558	2	0.482	0.366	1.939	0	Min	2	0.061	0.059	1.056	0
RM136	4	0.474	0.435	1.330	2	Mean	2.9	0.551	0.475	1.685
RM3	3	0.651	0.576	1.824	0
Na, Number of observed alleles; He, Nei’s gene diversity (Nei, 1973); PIC, Polymorphism information content; Ne, Number of effective alleles; Nr, Number of rare alleles.

Marker	Na	He	PIC	Ne	Nr	Marker	Na	He	PIC	Ne	Nr
RM431	3	0.564	0.469	1.712	1	RM72	4	0.747	0.699	1.784	0
RM11943	2	0.480	0.365	1.824	0	RM5789	2	0.259	0.225	1.259	0
RM3825	3	0.666	0.592	1.943	0	RM189	2	0.498	0.374	1.602	0
RM5443	2	0.485	0.367	1.910	0	RM24393	3	0.548	0.470	1.713	0
RM555	3	0.652	0.577	1.892	0	RM24334	4	0.683	0.622	1.606	1
RM279	3	0.617	0.547	1.546	1	RM24421	3	0.511	0.395	1.660	1
RM236	3	0.706	0.648	1.740	1	RM24350	3	0.662	0.588	1.795	0
RM324	3	0.623	0.547	1.786	0	RM566	3	0.616	0.543	1.803	0
RM232	3	0.648	0.575	1.891	0	RM211	2	0.548	0.470	1.207	1
RM60	2	0.338	0.281	1.600	0	RM511	3	0.531	0.468	1.636	0
RM520	3	0.480	0.365	1.823	0	RM28166	3	0.605	0.530	1.761	0
RM537	2	0.061	0.059	1.056	1	RM28130	3	0.529	0.418	1.685	1
RM252	5	0.789	0.755	1.987	0	RM20A	3	0.481	0.392	1.572	1
RM518	3	0.591	0.523	1.654	0	Max	5	0.789	0.755	1.987	2
RM3558	2	0.482	0.366	1.939	0	Min	2	0.061	0.059	1.056	0
RM136	4	0.474	0.435	1.330	2	Mean	2.9	0.551	0.475	1.685
RM3	3	0.651	0.576	1.824	0
Na, Number of observed alleles; He, Nei’s gene diversity (Nei, 1973); PIC, Polymorphism information content; Ne, Number of effective alleles; Nr, Number of rare alleles.

	Cluster I	Cluster II	Cluster III	Cluster IV	Cluster V
Cluster I	0.550	0.683	0.762	0.684	0.701
Cluster II		0.575	0.715	0.722	0.716
Cluster III			0.610	0.695	0.683
Cluster IV				0.596	0.684
Cluster V					0.612