Molecular Plant Breeding 2016, Vol.7, No.12, 1
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19
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plays important role in the variation of grain size related phenotypes. And also suggested that the highly
complicated genetic regulatory network involves in the development of grain characters of crop plants. Thus,
elucidating regulatory QTL networks underlying rice grain development, and understanding the mechanism of
those QTLs are of great significance for QTL pyramiding in grain yield breeding application. In breeding program,
the major effect QTLs are, of course, considered in priority for grain size modification. However, epistatic QTLs,
even if their LOD score low to undetectable, also be another choice for grain size modification in molecular
breeding design. All the epistatic QTLs and their combinations in breeding practice can produce diverse size of
rice grain to meet the different preferences of different regions of the world people.
3 Materials and Methods
3.1 Population development and field experiments
A set of 188-indiviual F
2
population was developed from a cross between large/long grain
indica
variety, NYZ
(1000-grain weight is 50.16 g), and medium/long grain variety, Ce253 (1000-grain weight is 24.91 g). In Spring of
2014, F
2
population and its parents were grown in Experimental Field of Guangxi University, Nanning, China.
Each seedling was transplanted to 1-row plot with 6 plants in each row in a 15 cm (between rows)
×
10 cm (within
rows) pattern. The leaves of each individual and their parents were collected at seedling stage and used for
molecular marker genotypic analysis (Luo et al., 2008). At crop maturity, each individual and parents were
harvested and naturally dried for grain size phenotypic evaluation.
3.2 Evaluation of grain size related traits
For the measurement of grain length and grain width, the 20 seeds of each plant were lined up in two rows and
taken the images by digital camera. The digital images were used to analyze and measure grain length and width
by using a Bio-image analyzer, Digimizer (Ver. 4.2.6.0). Grain thickness of each genotype was determined by the
average of the thickness values of 20 grains from each rice plant. The thickness of each grain was measured using
a Vernier caliper with three replications. One hundred grains from each genotype was weighted and converted to
1000-grain weight.
3.3 DNA preparation and DNA marker genotyping
The genomic DNA for individual plant was extracted from young leaf tissues using the CTAB method as
described by Murray and Thompson (1980). DNA was then dissolved in ddH
2
O and stored for subsequent analysis.
PCR reaction mixture (total volume 10 uL) contained 5 uL 2×Es Taq MasterMix (CWBIO, Cat# CW0690D), 50
ng template DNA, and 5uM primers. PCR reaction cycles was performed with an initial 2-min period at 94
℃
,
followed by 30 cycles of denaturing at 94
℃
(30 s), annealing at 58
℃
(30 s), extension at 72
℃
(1 min), and a
final 2-min extension step at 72
℃
. PCR products were analyzed by 2.5
～
3% agarose electrophoresis and stained
with GelRed (Biotium, Cat# 41 003) for visualization.
SSR markers were obtained from the Gramene database
. The IN/DEL markers were
developed using genomic DNA sequences of Nipponbare and 9 311 as references (Supplement Table 1). The
primers were synthesized by Sunbiotech (Beijing, China) and SBS Genetech (Shanghai, China), respectively. All
the primers were used for identifying the polymorphic DNA markers between NYZ and Ce253 by PCR.
3.4 Linkage map construction and QTL analysis
QTL IciMapping 4.0 (Wang et al., 2014) was used to construct genetic linkage map and QTL analysis. The total of
110 polymorphic DNA markers (41 SSR and 69 IN/DEL), which well-distributed on 12 chromosomes, were
genotyped for genetic linkage map construction. According to the manual of QTL IciMapping 4.0, the genotypes
of DNA markers were defined as follows, the band of male parent (NYZ) was coded as 2, the band of female
parent (Ce253) was coded as 0, and heterozygote was coded as 1, missing genotypes were coded as -1. In QTL
analysis, the statistical method, Inclusive Composite Interval Mapping (ICIM-ADD, ICIM-EPI) was used for
genome-wide identification of grain size associated QTLs by combining phenotypic data and genetic linkage map.
A threshold of LOD≥2.5 was used to indicate the significant main effect QTL (
P
≤
0.001), and a threshold of
