Mol Breeding (2016)36:145
DOI 10.1007/s11032-016-0566-8
Development and validation of candidate gene-specific
markers for the major fertility restorer genes, Rf4 and Rf3
in rice
K. Pranathi . B. C. Viraktamath . C. N. Neeraja . S. M. Balachandran . A. S. Hari prasad .
P. Koteswara Rao . P. Revathi . P. Senguttuvel . S. K. Hajira . C. H. Balachiranjeevi .
S. Bhaskar Naik . V. Abhilash . M. Praveen . K. Parimala . S. R. Kulkarni . M. Anila .
G. Rekha . M. B. V. N. Koushik . B. Kemparaju . M. S. Madhav . S. K. Mangrauthia .
G. Harika . T. Dilip . R. R. Kale . V. Vishnu Prasanth . V. Ravindra Babu . R. M. Sundaram
Received: 27 June 2016 / Accepted: 3 October 2016
Ó Springer Science+Business Media Dordrecht 2016
Abstract Two major nuclear genes, Rf3 and Rf4, are
known to be associated with fertility restoration of
wild-abortive cytoplasmic male sterility (WA-CMS)
in rice. In the present study, through a comparative
sequence analysis of the reported putative candidate
genes, viz. PPR9-782-(M,I) and PPR762 (for Rf4) and
SF21 (for Rf3), among restorer and maintainer lines of
rice, we identified significant polymorphism between
the two lines and developed a set of PCR-based
codominant markers, which could distinguish maintainers from restorers. Among the five markers
K. Pranathi and R. M. Sundaram have contributed equally to
this work.
Electronic supplementary material The online version of
this article (doi:10.1007/s11032-016-0566-8) contains supplementary material, which is available to authorized users.
K. Pranathi B. C. Viraktamath C. N. Neeraja
S. M. Balachandran A. S. Hari prasad
P. Koteswara Rao P. Revathi P. Senguttuvel
S. K. Hajira C. H. Balachiranjeevi S. Bhaskar Naik
V. Abhilash M. Praveen K. Parimala
S. R. Kulkarni M. Anila G. Rekha M.
B. V. N. Koushik B. Kemparaju M. S. Madhav
S. K. Mangrauthia G. Harika T. Dilip
R. R. Kale V. Vishnu Prasanth V. Ravindra Babu
R. M. Sundaram (&)
Crop Improvement Section, Indian Institute of Rice
Research, Rajendranagar, Hyderabad 500030, India
e-mail: rms_28@rediffmail.com
developed targeting the polymorphisms in PPR9782-(M,I), the marker RMS-PPR9-1 was observed to
show clear polymorphism between the restorer
(n = 120) and maintainer lines (n = 44) analyzed.
Another codominant marker, named RMS-PPR762
targeting PPR762, displayed a lower efficiency in
identification of restorers and maintainers, indicating
that PPR9-782-(M,I) is indeed the candidate gene for
Rf4. With respect to Rf3, a codominant marker, named
RMS-SF21-5 developed targeting SF21, displayed
significantly lower efficiency in identification of
restorers and non-restorers as compared to the Rf4specific markers. Validation of these markers in a F2
mapping population segregating for fertility restoration indicated that Rf4 has a major influence on
fertility restoration and Rf3 is a minor gene. Further,
the functional marker RMS-PPR9-1 was observed to
be very useful in identification of impurities in a seed
lot of the popular hybrid, DRRH3. Interestingly, when
RMS-PPR9-1 and RMS-SF21-5 were considered in
conjunction with analysis, near-complete, marker–
trait co-segregation was observed, indicating that
deployment of the candidate gene-specific markers
both Rf4 and Rf3, together, can be helpful in accurate
identification of fertility restorer lines and can facilitate targeted transfer of the two restorer genes into
elite varieties through marker-assisted breeding.
Keywords Fertility restoration Rf4 Rf3 WACMS Gene-specific markers Hybrid seed purity
123
145
Page 2 of 14
Introduction
Breeding rice for higher yield remains the key priority
for developing nations such as India, which needs to
produce *125 million tonnes of rice by 2030 to feed
its burgeoning population. Hybrids in rice have yield
superiority of about 15–20 % over the best commercial inbred varieties under similar conditions (Virmani
1996) and large-scale adoption of hybrid rice production is one of the feasible options to meet the food
security challenges in India. Hybrid based on wildabortive cytoplasmic male sterility (WA-CMS) system has been extensively used in commercial rice
hybrids production in most of the Asian countries
including India (Lin and Yuan 1980; Virmani and
Wan 1988), and so far, 75 hybrids based on WA-CMS
system have been released for commercial cultivation
in India (AS Hariprasad, personal communication).
The utility of the CMS lines in hybrid rice breeding is
determined by the availability of characterized and
effective fertility restoration lines. A total of 17 alleles
for fertility restoration have been identified in rice, and
all except rf17 are dominant in rice. Among these, at
least two genes, viz. Rf3 (located on chromosome 1)
and Rf4 (located on chromosome 10), are known to
control fertility restoration of WA cytoplasm (Zhang
et al. 1997; Yao et al. 1997). Various attempts have
been made to fine-map and characterize the candidate
genes underlying Rf4 and Rf3 (Ahmadikhah and
Karlov 2006; Sheeba et al. 2009; Ngangkham et al.
2010; Balaji et al. 2012). Ngangkham et al. (2010)
proposed that a gene encoding a pentatricopeptide
repeat (PPR) motif-containing protein, named PPR3,
located on the long arm of chromosome 10 is the
candidate gene for Rf4, while recently, another study
(Tang et al. 2014) identified another candidate, PPR9782 (M,I), located in the same region as PPR3 as the
candidate for Rf4 gene. With respect to Rf3, Balaji
et al. (2012) reported that a gene, named SF21,
encoding a pollen-specific protein to be putative
candidate for the gene.
In WA-CMS-based hybrid breeding (also called
three-line system of hybrid rice breeding), identification of potential restorers among the diverse rice
germplasm lines is of significant importance, as
genetically diverse restorer lines can be helpful in
breeding hybrids with higher magnitude of heterosis.
The traditional method of identifying restorers by
breeders involves test crossing the prospective lines
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Mol Breeding (2016)36:145
with selected WA-CMS lines and evaluating the F1
progenies for pollen and spikelet fertility. Lines with
progenies showing[70 % pollen and spikelet fertility
are then designated as restorers (Govinda Raj and
Virmani 1988). Molecular mapping of Rf3 and Rf4 can
reduce the time and effort involved in identification of
fertility restorer lines (Sattari et al. 2007; Sheeba et al.
2009). Further, molecular markers specific for Rf3 and
Rf4 can aid in targeted transfer of the two Rf genes into
elite genetic backgrounds and also facilitate accurate
estimation of genetic impurities in hybrid seed lots
(Nandakumar et al. 2004; Sundaram et al. 2008).
Many markers have been developed for Rf4 (Ahmadikhah and Karlov 2006; Ngangkham et al. 2010;
Balaji et al. 2012), and a few have been developed for
Rf3 (Nas et al. 2003). However, these markers display
limited efficiency in accurate identification of restorers, as all of them are linked markers and not specific
for the putative candidate genes underlying either Rf3
or Rf4. The present study was carried out with the
objective to analyze the sequence polymorphism in the
genomic region underlying the reported candidate
genes for Rf3 and Rf4, develop candidate genespecific, PCR-based codominant markers, validate
them among a large set of known maintainer and
restorer lines and a mapping population segregating
for the trait of fertility restoration and finally demonstrate the utility of the candidate gene-specific marker
in accurate identification of impurities in seed lot of a
commercial rice hybrid.
Materials and methods
Plant materials
The plant materials in the study included a total of 120
restorer and 44 non-restorer lines (i.e., maintainers) of
indica-type rice for WA-CMS cytoplasm (Table 1),
which were used for validation of the gene-specific
markers developed for Rf3 and Rf4. The developed
markers were also validated in a segregating population consisting of 1252 F2 individuals derived from the
cross between the WA-CMS line, IR58025A and the
restorer line, KMR3R, which were phenotyped for
spikelet fertility. A set of 71 wild rice lines (Supplementary Table 1) was analyzed for their amplification
pattern with respect to the gene-specific marker for
Rf4. In addition, a seed lot of the popular rice hybrid
Classification of
genotype along
with its source
1
RPHR-612-1
Restorer-indica
61
RNR-17420
Restorer-indica
1
APMS6B
Maintainer-indica
2
EPLT 104
Restorer-indica
62
RNR-17472
Restorer-indica
2
IR58025B
Maintainer-indica
3
EPLT 109
Restorer-indica
63
JGL-11118
Restorer-indica
3
IR68897B
Maintainer-indica
4
EPLT 107
Restorer-indica
64
RNR-2465
Restorer-indica
4
IR68888B
Maintainer-indica
5
RPHR 118
Restorer-indica
65
JGL-1798
Restorer-indica
5
PUSA5B
Maintainer-indica
6
RPHR 124
Restorer-indica
66
IR 40750
Restorer-indica
6
IR79156B
Maintainer-indica
7
RPHR-611-1
Restorer-indica
67
IR66
Restorer-indica
7
IR80555B
Maintainer-indica
8
RPHR 517
Restorer-indica
68
IR36
Restorer-indica
8
IR80561B
Maintainer-indica
9
RPHR-619-2
Restorer-indica
69
CN 1966-4-9
Restorer-indica
9
DRR5B
Maintainer-indica
10
RPHR619
Restorer-indica
70
Pusa 5001-6-3-2
Restorer-indica
10
DRR6B
Maintainer-indica
11
AYT-21
Restorer-indica
71
GQ-25
Restorer-indica
11
DRR9B
Maintainer-indica
12
RPBIO-491950-10
Restorer-indica
72
RPBIO-50-13
Restorer-indica
12
DRR10B
Maintainer-indica
13
RPBIO4919-5-1
Restorer-indica
73
IR46
Restorer-indica
13
DRR3B
Maintainer-indica
14
IR48725
Restorer-indica
74
NDR 3026
Restorer-indica
14
CRMS32B
Maintainer-indica
15
BR 827-35
Restorer-indica
75
RPHR1005
Restorer-indica
15
CR 2655-18-2-3
Maintainer-indica
16
RPHR2
Restorer-indica
76
MTU-9992
Restorer-indica
16
SN 244
Maintainer-indica
17
BCW56
Restorer-indica
77
NRI-38
Restorer-indica
17
CRR 575-38-1-1
Maintainer-indica
18
C20R
Restorer-indica
78
DR714-1-2R
Restorer-indica
18
SM-156
Maintainer-indica
19
AJAYA
Restorer-indica
79
RPBIO-4919363-5
Restorer-indica
19
RNSK-1054-1
Maintainer-indica
20
RPBIO50-10
Restorer-indica
80
PNR 3158
Restorer-indica
20
RSK 1046
Maintainer-indica
21
SG-22-289-3
Restorer-indica
81
RPHR 1096
Restorer-indica
21
DR714-1-2R X TJ-53
Maintainer-indica
22
SG-25-74
Restorer-indica
82
IR72
Restorer-indica
22
WR-37-1-1-2
Maintainer-indica
23
SG-27-177
Restorer-indica
83
KMR-3R
Restorer-indica
23
CR3818-1-1-1-1-2
Maintainer-indica
24
NLR-33358
Restorer-indica
84
RPHR 1004
Restorer-indica
24
CHIR 5
Maintainer-indica
25
Akshayadhan
Restorer-indica
85
RPHR 111-3
Restorer-indica
25
TTB 404
Maintainer-indica
26
RNR-2781
Restorer-indica
86
GQ70
Restorer-indica
26
RPHR-1096 X TJ-4
Maintainer-indica
27
IR64
Restorer-indica
87
IR 10198
Restorer-indica
27
UPR 3786-17-2-1
Maintainer-indica
28
RNR-6378
Restorer-indica
88
IR 24
Restorer-indica
28
PUSA 1557-06-28-188-1-17
Maintainer-indica
S. no.
Rice genotype
Classification of
genotype along
with its source
S. no.
Rice genotype
Classification of
genotype
along with its source
145
Rice
genotype
Page 3 of 14
123
S.
no.
Mol Breeding (2016)36:145
Table 1 List of plant materials used in the study
145
S.
no.
Rice
genotype
Classification of
genotype along
with its source
S. no.
29
Bhadrakali
Restorer-indica
89
30
RNR-17438
Restorer-indica
90
BK-64-116
Restorer-indica
30
PUSA 1557-06-2-9-159-3-2
Maintainer-indica
31
NP-6226
Restorer-indica
91
BK-36-167
Restorer-indica
31
SM-75
Maintainer-indica
Rice genotype
Classification of
genotype along
with its source
S. no.
Rice genotype
Classification of
genotype
along with its source
IR29723
Restorer-indica
29
RPHR 1005 X FBR-1
Maintainer-indica
WGL-640
Restorer-indica
92
BK 39-179
Restorer-indica
32
SN-15
Maintainer-indica
33
6527
Restorer-indica
93
BK-52-104
Restorer-indica
33
CRR 574-38-1-1
Maintainer-indica
34
NLR-145
Restorer-indica
94
BK-44-78
Restorer-indica
34
FGK-1
Maintainer-indica
35
CSR-23
Restorer-indica
95
BK-49-76
Restorer-indica
35
SN-322 T
Maintainer-indica
36
WGL-665
Restorer-indica
96
BK-49-43
Restorer-indica
36
CR 3818-1-1-1-1-2-1
Maintainer-indica
37
RNR-898
Restorer-indica
97
BK-49-77
Restorer-indica
37
TTB 404-1
Maintainer-indica
38
WGL-573
Restorer-indica
98
BK-49-120
Restorer-indica
38
CHIR 5-2
Maintainer-indica
39
NLR-40058
Restorer-indica
99
BK-49-80
Restorer-indica
39
RSK 1046-1
Maintainer-indica
40
41
Pushyami
TM07275
Restorer-indica
Restorer-indica
100
101
BK-35-155
BK-49-78
Restorer-indica
Restorer-indica
40
41
RMSB-514
KAUMK157
Maintainer-indica
Maintainer-indica
42
TCP 349
Restorer-indica
102
BK-49-76
Restorer-indica
42
TCP 1193
Maintainer-indica
43
KCD-1
Restorer-indica
103
SG-27-105
Restorer-indica
43
SM-202
Maintainer-indica
44
PNR-89
Restorer-indica
104
RNR-15351
Restorer-indica
44
KSLRV-221
Maintainer-indica
45
PNR-72
Restorer-indica
105
RNR-15038
Restorer-indica
46
PNR-71
Restorer-indica
106
RNR-10291
Restorer-indica
47
PNR-79
Restorer-indica
107
WGL-347
Restorer-indica
48
PNR-80
Restorer-indica
108
WGL-283
Restorer-indica
49
PNR-81
Restorer-indica
109
RNR-15048-1
Restorer-indica
50
PNR-82
Restorer-indica
110
RNR-15038-1
Restorer-indica
51
PNR-83
Restorer-indica
111
MTU-1081
Restorer-indica
52
PNR-84
Restorer-indica
112
WGL-285
Restorer-indica
53
PNR-85
Restorer-indica
113
RNR-11636
Restorer-indica
54
PNR-86
Restorer-indica
114
KAVYA
Restorer-indica
55
PNR-87
Restorer-indica
115
TCM-80-M
Restorer-indica
56
57
PNR-88
PNR-74
Restorer-indica
Restorer-indica
116
117
PRR78
HHZ5-SAL10DT3-Y2
Restorer-indica
Restorer-indica
58
RNR-15028
Restorer-indica
118
PNR-73
Restorer-indica
Mol Breeding (2016)36:145
32
Page 4 of 14
123
Table 1 continued
Mol Breeding (2016)36:145
Page 5 of 14
145
Classification of
genotype
along with its source
DRRH3 consisting of 400 seeds was also included for
analysis of efficiency of gene-specific marker for Rf4
in accurate identification of genetic impurities. All the
plant materials utilized in the study were collected
from Hybrid Rice Section of ICAR-Indian Institute of
Rice Research (ICAR-IIRR), Hyderabad.
Restorer-indica
Restorer-indica
HHZ12-Y4-Y1-DT1
vajram
120
119
RNR-17494
60
Restorer-indica
C-26
59
Restorer-indica
Rice
genotype
S.
no.
Table 1 continued
Classification of
genotype along
with its source
S. no.
Rice genotype
Classification of
genotype along
with its source
S. no.
Rice genotype
Analysis of gene sequences of Rf3 and Rf4
The candidate genes PPR9-782-(M,I) (Tang et al.
2014; Kazama and Toriyama 2014) and PPR762
(Balaji et al. 2012) reported to be specific for Rf4 on
chromosome 10 were considered for sequence analysis. The reported restorer sequences (PPR9-782M and PPR9-782-I) and non-restorer gene sequences
(PPR9-409 and PPR9-782-ZH) of PPR9 gene (Tang
et al. 2014) were downloaded from NCBI/GenBank
public database. The coordinates of PPR9-782M gene were identified in Nipponbare, a japonica
cultivar from (19,287,680 to 19,295,473 bp; Pseudo
http://rice.plantbiology.msu.edu/
molecule
6.1,
pseudomolecules) using BioEdit tool version 7.0.9
(Hall 2007). Using ClustalW multiple sequence
alignment tool (Higgins et al. 1994), two functional
restorer sequences and two non-restorer sequences
were compared to identify different polymorphic
regions (Supplementary Figure 1). Further, a 25-kb
region upstream and a 25-kb region downstream of
PPR9-782-M on chromosome 10 of Nipponbare
(19,290,587–19,340,587 bp) and chromosome 10 of
indica cultivar, 93–11 (17,749,895–17,799,895 bp)
were also aligned using ClustalW tool in order to
identify the polymorphic regions in the vicinity of the
candidate gene. Similar sequence analysis was performed for another reported candidate gene PPR762
specific for Rf4 (Balaji et al. 2012). The reported
amplicon sequences of DRCG-Rf4-14 marker (Balaji
et al. 2012) targeting PPR762 in restorer and nonrestorer sequences were also considered for polymorphism analysis.
With respect to Rf3, a pollen-specific protein, SF21,
located on chromosome 1 was identified earlier by
fine-mapping analysis to be the putative candidate
gene (Balaji et al. 2012). SF21 gene sequence
(LOC_Os01g09670) was downloaded from Gramene/NCBI public database. The coordinates of
SF21 gene were identified on chromosome 1 of
Nipponbare, japonica cultivar (Pseudo molecule 6.1,
http://rice.plantbiology.msu.edu/pseudomolecules)
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145
Page 6 of 14
Mol Breeding (2016)36:145
and in indica cultivar 93–11 (Beijing Rice Information
System http://rice.genomics.org.cn/rice) using BioEdit tool version 7.0.9 (Hall 2007). A 10-kb region
upstream and 10-kb region downstream of SF21 gene
from both japonica (4,917,224–4,992,046 bp) and
indica (5,350,773–5,371,596 bp) were aligned using
ClustalW alignment tool (Higgins et al. 1994) (Supplementary Figure 2) to identify polymorphic regions
in the vicinity of the SF21 gene.
Primer designing and PCR analysis
of the developed markers
The different polymorphic regions identified within
the PPR9-782-M and PPR-782-I gene and also in the
vicinity of gene (i.e., within 50 kb on either side) were
targeted for designing of five PCR-based codominant
markers specific for Rf4. Another codominant marker
specific for Rf4 was designed targeting the polymorphism within PPR762 gene. In addition, different
Table 2 List of Rf3 and
Rf4 markers developed in
the study
S. no.
Primer name
polymorphic regions identified based on alignment
between SF21 sequences from japonica and indica
were targeted for designing of five PCR-based
codominant markers specific for Rf3. All these primer
pairs were designed using Primer 3 online tool (http://
bioinfo.ut.ee/primer3-0.4.0), and the primer sequences of these markers specific to Rf3 and Rf4 are listed
in Table 2. In addition, the reported SSR markers
RM6100 (specific for Rf4) (Singh et al. 2005), DRCGRf4-14 (specific for Rf4) (Balaji et al. 2012) and
DRRM-Rf3-10 (specific for Rf3) (Balaji et al. 2012)
were also considered for analysis.
The total genomic DNA was isolated from young,
healthy leaves of all the restorer lines, maintainer lines
and individuals of the segregating F2 mapping population by following the method of Dellaporta et al.
(1983). The isolated DNA was used for PCR amplification with the codominant markers developed in the
study. PCR was performed in 20 ll reaction volumes
containing 1X PCR buffer [10 mM TrisHCI (pH 8.3),
Primer sequence
Position in
Japonica (bp)
RMS-PRR9-1
GAGTTTTGAATAGATTTACGTGTGGA
19,294,526
2
RMS-PPR9-2
AGTGTCCAGATTCGTAGTAATGC
GAATGGAAGATCCACCGAAG
19,292,205
3
RMS-PPR9-3
List of markers specific to Rf4
1
ATGACATTGGGCTTCACACC
GGTGTGAAGCCCAATGTC
19,291,628
GCAAAGCCCATGAAGGATTA
4
RMS-PPR9-4
AACGTTACTATTCACCTC
19,335,773
AGCTTTGCTAGTCTTCCAG
5
RMS-PPR9-5
6
RMS-PPR762
ATTGGTGTCTGAGGGGTCTG
19,318,121
TTGGCAGGTTTGCTAATTTTG
TTGCCAGCATGTTCTCAGTT
19,394,606
GCAAAGCCCATGAAGGATTA
List of markers specific to Rf3
1
RMS-SF21-1
2
RMS-SF21-2
ACAAAAGGCACACCCTG
4,985,388
GTTTGAGGGACCTAAGGAATG
ACGGAGGAGACATGGAGC
4,988,522
GCAAAATACTACTCCCTATC
3
RMS-SF21-3
4
RMS-SF21-4
GTCAGCCGTAGGATGATAT
CCGACTCAATATTGCCACG
4,979,591
GTCGTCAAGGTCGTCGTC
4,975,318
GAGGCGGCGGGGAAAGGC
5
RMS-SF21-5
GAGTTGGGGGTCGAGAAATC
CGTACGTGCGGCTAGGATCAA
123
4,977,751
Mol Breeding (2016)36:145
50 mM KCI, 1.5 mM MgCL2, 0.01 % (v/v) gelatin],
30–50 ng of template DNA, 5 pmol of each primer,
200 lM (each) deoxyribonucleotide and 1 unit of Taq
polymerase (Merck, India). PCR conditions included
an initial denaturation step at 94 °C for 5 min,
followed by 30 cycles of 94 °C for 30 s, 55 °C for
30 s and 72 °C for 1 min and a final extension at 72 °C
for 7 min. All amplified products were resolved in
2–3.5 % agarose gels (Lonza Inc., USA) along with
100-bp molecular marker (Merck, India). The codominant markers that showed clear polymorphism
between restorers and maintainers were validated in
the F2 segregating populations. The scores 1, 2 and 3
were given to codominant markers for parent 1 type
(P1) and parent 2 type (P2) and heterozygous (F1). The
segregation of codominant markers in the F2 population was studied by Chi-square test for the Mendelian
segregation ratio 1:2:1 as outlined by Gomez and
Gomez (1984).
Spikelet fertility analysis
About 20-day-old seedlings of F2 individuals were
transplanted in the field. At reproductive stage of
growth, just before flowering, the panicles of main
tiller and two side tillers of each individual plant were
bagged with a paper bag to prevent cross-pollination.
The seed set in each panicle was counted, and spikelet
fertility was determined according to Sheeba et al.
(2009). All the plants in the population were classified
into four classes based on spikelet fertility percentage,
namely fertile (more than 71 % spikelet fertility),
partially fertile (31–70 %), partially sterile (1–30 %)
and sterile (0 %).
Analysis of impurities in a seed lot of DRRH3
using Rf4-specific codominant marker
Four hundred seedlings of the popular rice hybrid
DRRH3 from a seed lot were planted in a grow-out
plot in the experimental farm of ICAR-Indian Institute
of Rice Research, Hyderabad, India, during wet season
2015. DNA was isolated from 20-day-old seedlings of
the 400 coded plants, individually as per the procedure
of Zheng et al. (1995). Genotyping of the 400
seedlings was done using the Rf4-specific codominant
marker, RMS-PPR9-1, which exhibited polymorphism among the female (APMS6A) and male
(RPHR-1005) parents of DRRH3. The genotype
Page 7 of 14
145
inferred from the marker profile was compared with
the phenotype at maturity to verify the results derived
from marker analysis with grow-out test (as described
in Yashitola et al. 2002 and Sundaram et al. 2008).
Sequencing of PCR fragments
Amplified PCR product of RMS-PPR9-1 marker from
KMR3R and IR58025A was gel-purified (WizardÒ SV
PCR clean up kit, Promega), cloned into pDrive
cloning vector (Qiagen, USA) and sequenced using an
ABI Prism 3700 automated DNA sequencer (PerkinElmer, Wellesley, MA) as per the procedure
suggested in Rajendrakumar et al. (2007). Homology
search was performed by BLASTN algorithm
(Altschul et al. 1990) through the National Center
for Biotechnology Information (http://www.ncbi.nlm.
nih.gov/blast), and the amplicon sequences from
IR58025A and KMR3R were aligned using the software ClustalW to validate the in-del polymorphisms
which were identified through sequence analysis of
PPR9 genomic regions.
Results
Development and validation of candidate genespecific markers for Rf3 and Rf4
The sequence analysis of candidate gene PPR9-782M, PPR9-782-I (which are specific for Rf4) and the
non-restorer sequences PPR9-409 and PPR9-782-ZH
revealed the presence of three major in-dels within the
gene (Supplementary Figure 1). These include a 42-bp
in-del, identified in the first intronic region, a 105-bp
in-del and a 1476-bp in-del identified within second
exonic region. Targeting each of these in-del polymorphisms, codominant markers were designed and
validated. Two other major in-dels were also identified
in the upstream region of PPR9-782-M gene and
targeted for development of codominant markers. Out
of the five codominant markers specific for in-dels
within PPR9-782-M or in its vicinity, three markers,
viz. a marker targeting 42-bp in-del polymorphism
within PPR9 gene, i.e., RMS-PPR9-1, two codominant markers, viz. RMS-PPR9-4, RMS-PPR9-5 targeting polymorphisms in the upstream region of
PPR9-782-M gene displayed clear polymorphism
between IR58025A and KMR3R (Fig. 1; Table 3).
123
145
Page 8 of 14
Mol Breeding (2016)36:145
a
L1
b
1
2
3
4
c
L1
1
4
L2
d
3
e
1
2
3
Fig. 1 Amplification pattern of markers developed targeting
the candidate genes for Rf4, viz. PPR9-78-M and PPR762:
a RMS-PPR9-1 (targeting in-del within PPR9-782-M); b RMSPPR762 (targeting PPR762); c RMS-PPR9-4 marker (targeting
PPR9-782-M); d RMS-PPR9-5 marker (targeting PPR9-782Table 3 Expected
amplification sizes of the
markers developed in the
study
S. no.
Primer name
L1
4
1
1
2
3
2
3
4
L2
4
M); e RMS-SF21-5 marker (targeting SF21). L1 indicates
100-bp ladder, L2 indicates 50-bp ladder, 1 indicates IR58025A,
2 indicates IR58025B, 3 indicates KMR3R, and 4 indicates
KRH2 in the figure
Expected PCR
amplicon size (bp)
Expected PCR product size (bp) in
Restorer
Non-restorer
Hybrid
1
2
RMS-PRR9-1
RMS-PPR9-2
114/159
447/1923
114
447
159
1923
114,159
447,1923
3
RMS-PPR9-3
365/470
365
470
365,470
4
RMS-PPR9-4
129/160
129
160
129,160
5
RMS-PPR9-5
178/360
178
360
178,360
6
RMS-PPR762
280/385
280
385
280/385
7
RMS-SF21-1
183/131
183
131
183,131
8
RMS-SF21-2
312/415
312
415
312,415
9
RMS-SF21-3
196/165
196
165
196,165
10
RMS-SF21-4
101/113
101
113
101,113
11
RMS-SF21-5
172/127
172
127
172,127
The analysis of restorer and non-restorer amplicon
sequences of DRCG-RF4-14 marker targeting
PPR762 gene revealed existence of a 105-bp in-del
polymorphism. Targeting this, a codominant marker
RMS-PPR762 was designed and validated. RMSPPR762 showed clear polymorphism between
IR58025A and KMR3R (Fig. 1; Table 3). Thus, a
total of four polymorphic markers were designed and
123
2
validated in this study targeting the putative candidate
genes for Rf4 (i.e., PPR9-782-M and PPR762).
In addition to Rf4, the putative candidate gene for
Rf3 (another fertility restorer gene for WA-CMS), viz.
SF21 (Balaji et al. 2012), was analyzed through
comparative sequence analysis of restorer and nonrestorer genotypes and five major in-del polymorphisms were identified in the vicinity of gene.
Mol Breeding (2016)36:145
Targeting each of these, a codominant marker was
designed and validated. However, only one codominant marker, RMS-SF21-5, displayed clear polymorphism between the WA-CMS lines IR58025A and the
restorer line, KMR3R (Fig. 1; Table 3).
Marker–trait co-segregation analysis
The candidate gene-specific markers for Rf4 and Rf3
which have shown clear polymorphism between
IR58025A and KMR3R were analyzed for their cosegregation with the trait of fertility restoration in a F2
population derived from the cross IR58025A/KMR3R
(Supplementary Table 2). All the codominant markers
displayed a Mendelian segregation ratio of 1:2:1 in the
F2 mapping population and the candidate gene-specific marker for Rf4, RMS-PPR9-1 was observed to be
significantly associated with the trait at P \ 0.01. The
markers RM6100 (Singh et al. 2005) and DRCG-Rf414 (Balaji et al. 2012) were also observed to be
associated with trait phenotype, but to a lesser extent.
The earlier reported marker DRCG-Rf4-14 (Balaji
et al. 2012) and the marker RMS-PPR762 developed
in this study, targeting the same 105-bp polymorphism
in PPR762 gene, displayed identical association with
the trait phenotype, but at a slightly lesser level of
association as compared to RMS-PPR9-1 targeting
PPR9-782-M. RMS-PPR762 showed clear and robust
resolution of the restorer-specific and non-restorerspecific alleles when compared to the earlier designed
marker, DRCG-Rf4-14. With respect to Rf3, the
earlier reported SSR marker DRRM-Rf3-10 (Balaji
et al. 2012) and RMS-SF21-5, the marker developed in
this study, displayed same level of association with the
trait phenotype (Supplementary Table 2) with the
newly designed marker showing clear resolution of
alleles as compared to DRRM-Rf3-10 (Supplementary
Figure 3).
Assessment of prediction efficiency of the markers
targeting Rf4 and Rf3
To validate the efficiency of these markers in accurately predicting the fertility restoration trait, they
were analyzed with a set of 120 known restorers and
44 known non-restorers. The selection efficiency of
the candidate gene-specific markers, RMS-PPR9-1
and RMS-PPR762 developed in this study, was 91 and
82 %, respectively (Supplementary Table 3; Fig. 2).
Page 9 of 14
145
As expected, the earlier reported marker, DRCG-Rf414, and the newly designed marker, RMS-PPR762,
displayed same selection efficiency of 82 %, as they
targeted the same polymorphism. The selection efficiency of candidate gene-specific marker for Rf3,
RMS-SF21-5 and the earlier reported marker
DRRMRf3-10 in identification of restorers and nonrestorers was identical (i.e., 57 %; Supplementary
Table 3; Fig. 3). The combined selection efficiency of
the best markers for Rf4 and Rf3, viz. RMS-PPR91 ? RMS-SF21-5, was as high as 94 %. Particularly,
the candidate gene-specific marker for Rf4, RMSPPR9-1, was observed to show polymorphism among
all the male and female parents of commercial rice
hybrids based on WA-CMS system analyzed in this
study (Supplementary Figure 4). When these markers
(viz. RMS-PPR9-1, RMS-SF21-5) were analyzed in a
set of wild rice accession belonging to O. nivara and
O. rufipogon (Supplementary Table 1), it was
observed that many O. nivara accessions showed the
presence of restoring allele with respect to Rf4.
Utility of gene-specific markers for Rf4
in detection of impurities in hybrid/parental seed
lots
The candidate gene-specific marker for Rf4 locus,
RMS-PPR9-1, was deployed for identification of
impurities in a seed lot of the hybrid DRRH3. With
the help of the marker, a total of seven impurities were
identified in the seed lot (Supplementary Figure 5),
and a perfect correlation was observed between the
marker analysis data and grow-out test (GOT) data.
Discussion
Wild-abortive (WA)-type CMS-based hybrids contribute significantly to the total rice cultivated area
worldwide. Inheritance of fertility restoration for the
WA-CMS system has been extensively investigated
and two major loci, Rf4 and Rf3 are known to control
the trait (Young and Virmani 1984; Li and Yuan 1986;
Virmani et al. 1986; Govinda Raj and Virmani 1988;
Bharaj et al. 1991; 1995; Teng and Shen1994).
However, efforts to delineate the candidate genes
underlying Rf4 and Rf3 are very limited. Recently,
Ngangkham et al. (2010) and Balaji et al. (2012)
identified that PPR3 and PPR762 are the putative
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145
Page 10 of 14
Mol Breeding (2016)36:145
BCW56
AJAYAR
IL5010R
EPLT109
EPLT104
SG-25-74
SG-27-177
SG-52-2-1
NRI38
CRR 575-38-1-1
SM-156
RNSK 1046
WR-37-1-1-2
UPR 3786-17-2-1
SM-75
SN-15
CRR 574-38-1-1
FGK-1
BK35-155
GQ70
RPHR1004
RPHR2
C20R
RPHR1096
RPHR619
RPHR517
BK49-80
BK49-45
BR829-35
DR714-1-2R
RPHR1005
KMR3R
IR58025A
50bp ladder
Restorers
CR 2655-18-2-3
CRMS32B
DRR10B
DRR9B
DRR6B
DRR5B
DRR4B
IR79155B
IR80156B
PUSA5B
IR68888B
IR68897B
APMS6B
IR58025A
KMR3R
50bp ladder
Non-Restorers
Fig. 2 Amplification pattern of RMS-PRR9-1, the candidate
gene-specific marker for Rf4 (targeting in-del within PPR9-782M) in a set of restorers and non-restorers (i.e., maintainers) in the
above lanes, IR58025A (WA-CMS) and KMR3R (restorers) are
used to standard checks
candidate genes for Rf4, while two independent groups
cloned and characterized another putative candidate
gene PPR9-782(M,I), for Rf4 loci (Tang et al. 2014;
Kazama and Toriyama 2014). According to the report
of Tang et al. (2014), there are diverse functional Rf4/
rf4 alleles based on their donor source, PPR9-782M allele from MH63 and PPR9-782-I from IR24 and
two types of non-functional rf4 alleles, PPR9-409
(rf4-i from indica) and PPR9-782-ZH (rf4-j from
japonica). With respect to Rf3, a putative candidate
gene, SF21 has been identified (Balaji et al. 2012).
In the present study, we analyzed the sequences of
the above mentioned putative candidate genes, which
have been earlier implicated with Rf4 and Rf3
controlled fertility restoration, identified sequence
polymorphisms within the candidate genes and targeting these polymorphic regions, designed codominant markers and validated them in a mapping
population and also in a large set of restorers and
non-restorers lines. Based on marker–trait co-segregation analysis and analysis of selection efficiency of
markers, we confirmed the candidacy of PPR9-782M gene to be specific for Rf4. Our study is the first
report on development of the candidate gene-specific
marker, named RMS-PPR9-1 targeting PPR9-782-M,
and PPR9-782-I gene specific for Rf4 and another
candidate gene-specific marker named RMS-SF21-5
targeting SF21 gene specific for Rf3. Among these two
candidate gene-specific markers developed in this
study, RMS-PPR9-1, specific for Rf4 has displayed
higher selection efficiency of 91 % in terms of
identification of all the known major restorer lines
(Supplementary Table 2), as compared to the RMSSF21-5 marker, which is specific for Rf3 showing only
57 % selection efficiency. These findings support the
general understanding that a good restorer would
possess Rf4 gene alone or Rf4 gene along with Rf3
gene, while lines possessing Rf3 alone might not be
good restorers. Thus, Rf4 has a stronger influence on
the trait than Rf3 as observed earlier by several groups
(Yao et al. 1997; Sattari et al. 2008; Cai et al.
2013, 2014). However, a few exceptions were also
found in this study. Two of the known restorer lines
IR66 and IR40750R were observed to possess only Rf3
and not Rf4 and another two known restorers PNR
3158 and AYT 21 do not possess both Rf3 and Rf4. The
possible explanation could be that IR66, IR40750R
may not be very good restorers and/or may not possess
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Mol Breeding (2016)36:145
Page 11 of 14
145
RPHR1005/FBR-1
SN-15
SM-75
CR3818-1-1-1-1-2
RPHR1096/TJ4
RSK 1046
RNSK-1054-1
CRR575-38-1-1
CRMS 32B
DRR4B
IR80561B
DRR10B
DRR9B
IR80555B
IR79156B
PUSA5B
IR68888B
IR68897B
APMS6B
IR58025B
IR58025A
KMR3R
100bp ladder
Non-Restorers
RPHR118
RPHR619
C20R
IBL-57
IR40750R
AJAYAR
RPHR517
SGQ25
DR714-1-2R
RPHR1005
KMR3R
IR58025B
IR58025A
100bp ladder
Restorers
Fig. 3 Amplification pattern of RMS-SF21-5, the candidate
gene-specific marker for Rf3 (targeting in-del upstream of SF21)
in a set of restorers and non-restorers (i.e., maintainers) in the
above lanes, IR58025A (WA-CMS) and KMR3R (restorer) are
used to standard checks
PPR9 gene (both PPR9-782-M and PPR9-782-I functional alleles) as RMS-PPR9-1 targets PPR9-782
(M,I) and might possess novel loci other than Rf3
and Rf4 for fertility restoration, as Kazama and
Toriyama (2014) reported that other fertility restoration genes could be associated with restoration of WACMS.
The process of screening for the trait of fertility
restoration is laborious and time-consuming as it
involves test crossing with a set of WA-CMS lines
followed by evaluation of the F1s for pollen and spikelet
fertility. Molecular markers targeting the candidate
gene associated with the trait are more efficient in
accurate identification of restorers among rice germplasm (Sheeba et al. 2009). Recently, our group
reported development of a functional marker, targeting
the candidate gene, WA352 for WA-CMS trait (Pranathi
et al. 2016). However, functional markers for the
fertility restoration trait were not available, when this
study was initiated and most of the markers available
were either linked markers or markers targeting nonvalidated putative candidate genes. To develop candidate gene-specific markers for fertility restoration trait,
we first attempted to identify candidate genes for Rf4
and Rf3. In a recent study, Tang et al. (2014) delineated
Rf4 locus to a 137-kb region on chromosome 10 and
identified three candidate genes, out of which PPR9782-M derived from an elite restorer line Minghui 63
(MH63, with Rf3 and Rf4) and PPR9-782-I from IR24
was confirmed as a causal gene through complementation assay. Further, the action of Rf4 on WA352 (orf
352) was confirmed by RNA blot analysis. The same
study reported two in-del markers (M19288, with a
23-bp in-del and M19280 with a 6-bp in-del). However,
it was observed that M19288 displays a dominant
fashion of amplification, while M19280 amplified
polymorphic fragments from restorers and maintainers
in our study. However, the reported primer binding sites
(F primer binding site-19,280,871 bp in japonica) of
M19280 in-del marker was observed to be not located
within the candidate gene (PPR9 with genomic region
from 19,287,680 to 19,295,473 bp) and the 6-bp in-del
was located at a distance of 6.8 kb upstream from the
gene. Further, as the marker targeted a 6-bp deletion,
the polymorphism detected by it was not robust and
required a higher percentage of agarose gels ([3.5 %)
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145
Page 12 of 14
for discrimination of the restorer and non-restorer
alleles and could not identify many known restorer lines
(data not shown), and hence, the marker may not be
useful in routine breeding programs. Kazama and
Toriyama (2014) identified the same gene (i.e., PPR9782-M,I) through fine-mapping of Rf4 locus that
corresponded to a 213-kb region of Nipponbare genome
in IR24 cultivar and demonstrated that the fertility
restoration is controlled sporophytically. Interestingly,
the sequence annotation study of reported candidate
genes specific for Rf4, PPR9-782(M,I) and PPR3
(Ngangkham et al. 2010) in Nipponbare genome shows
that both genes encode the same 782 amino acidcontaining
protein
(Os10g0495200
or
LOC_Os10g35240), where as another reported putative
candidate gene, PPR762 encodes a different protein
with 762 amino acids (BAD08213; protein sequence
alignment file as Supplementary Figure 6). Even
though we could observe a 105-bp polymorphism
between restorers and non-restorers with respect to
PPR9-782-M, on critical analysis of restorer and nonrestorer sequences of the three putative candidate genes
reported for Rf4 (mentioned above), we identified that
the 105-bp deletion is present in all the three putative
candidates PPR762, PPR9-782-(M,I) and PPR3 (alignment file as Supplementary Figure 7). Thus, this
polymorphic region may not be unique to a particular
candidate gene and hence is not be amenable for
development of candidate gene-specific marker. We
have identified a unique in-del region of 42 bp within
the candidate gene (i.e., PPR9-782-M) (Supplementary
Figure 1). Targeting this in-del polymorphism, we
designed and validated a codominant marker named
RMS-PPR9-1. The marker RMS-PPR9-1 displayed
very significant association with the trait phenotype (of
fertility restoration) and unequivocally distinguishes
almost all the major restorer lines from the nonrestorers of indica rice type (Supplementary Table 2).
Thus, RMS-PPR9-1 marker targeting a unique 42-bp
in-del within PPR9-782(M,I) gene can be considered as
the ideal candidate gene-specific marker for Rf4.
Further, we validated the 42-bp in-del polymorphism
through sequencing of RMS-PPR9-1 candidate genespecific marker amplicons from IR58025A (WA-CMS)
and popular restorer KMR-3R (restorer) lines (Supplementary Figure 8).
Another loci known to be controlling the trait of
fertility restoration in WA-CMS system is Rf3. Using
RAPD and RFLP markers Rf3 was earlier mapped on
123
Mol Breeding (2016)36:145
chromosome 1 (Yao et al. 1997; Zhang et al. 1997).
Till now, there are no reports on cloning and
characterization of the candidate gene(s) controlling
Rf3 loci. Balaji et al. 2012 reported a putative
candidate, a pollen-specific protein (SF21) encoding
gene to be specific for Rf3. Targeting the major
deletion in the upstream region of SF21 gene, RMSSF21-5, a codominant, gene-specific marker, was
designed and validated in our study. The newly
developed marker, RMS-SF21-5, and the earlier
reported SSR marker, DRRM-Rf3-10 (Balaji et al.
2012), displayed the same selection efficiency, as they
target the same candidate gene, SF21. However, the
newly designed marker RMS-SF21-5 was more
robust, showing clear polymorphism as compared to
DRRM-Rf3-10 (Supplementary Figure 3). Interestingly, when both the gene-specific markers RMSPPR9-1 (specific for Rf4) and RMS-SF21-5 (specific
for Rf3), used in conjunction, displayed increased
selection efficiency of 94 % as compared to deploying
them alone and also as compared to earlier reported
markers for fertility restoration trait. The gene-specific
markers developed in the study, notably RMS-PPR9-1
has higher efficiency in identifying all true F1s hybrids
in WA-CMS system (Supplementary Figure 4) and
also highly efficient in detection of impurities in
hybrid seed lots (Supplementary Figure 5), which was
clearly demonstrated in this study through analysis of
genetic impurities in a seed lot of the popular hybrid,
DRRH3. When the marker RMS-PPR9-1 (specific for
Rf4) was validated among 71 Indian accessions of O.
nivara and O. rufipogon (Pranathi et al. 2016), many
accessions displayed amplification of the restorerspecific allele and interestingly, most of the wild rice
accessions, which possess wild-abortive cytoplasm
and are still fertile, displayed Rf4-specific allele with
respect to RMS-PPR9-1 marker indicating the possibility of coevolution of WA-CMS and fertility
restoration traits in a few Indian wild rice accessions
of O. nivara and O. rufipogon.
In conclusion, through the present study, we
identified significant in-del polymorphisms within
and around each putative candidate gene specific for
Rf4 and Rf3 loci. Through marker–trait co-segregation
analysis and higher selection efficiency of genespecific marker targeting in-del polymorphism specific to PPR9-782-M, we confirmed the association of
earlier reported gene PRR9-782 (M,I) with Rf4 loci
(Tang et al. 2014) and we report the first gene-specific
Mol Breeding (2016)36:145
markers for major fertility restoration loci, Rf4 and
Rf3. The deployment of gene-specific marker for Rf4
(RMS-PPR9-1) and another gene-specific marker for
Rf3 (RMS-SF21-5) in conjunction displayed higher
selection efficiency compared to utilization of genespecific marker alone. Further validation of genespecific markers in F2 population and germplasm
established major influence of Rf4 than Rf3 on the trait.
The gene-specific markers, particularly RMS-PPR9-1
marker, can facilitate marker-assisted selection and
targeted transfer of Rf4 gene into elite backgrounds
and also provide highly accurate, rapid detection of
impurities in hybrid seed lots. Further efforts are
necessary for characterization of candidate gene(s) for
Rf3 loci.
Acknowledgments K. Pranathi would like to thank
Department of Science and Technology (DST), Government
of India, for the INSPIRE fellowship awarded for Ph.D. studies.
The authors would also like to thank the Indian Council of
Agricultural Research and Department of Biotechnology,
Government of India, for the generous funding support for the
research work presented in the study.
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