mapping quantitative trait loci influencing panicle-related traits from chinese common wild rice...

Mapping quantitative trait loci influencing panicle-related traits from Chinese

common wild rice (Oryza rufipogon) using introgression lines

X. LUO1, F. T IAN

1 , Y. FU1, J . YANG

2 and C. SUN1 , 3

1State Key Laboratory of Plant Physiology and Biochemistry, National Evaluation Central for Agricultural Wild Plant (Rice),Laboratory of Crop Heterosis and Utilization of Ministry of Education, Department of Plant Genetics and Breeding, ChinaAgricultural University, Beijing, 100094, China; 2State Key Laboratory of Genetic Engineering, Morgan-Tan InternationalCenter for Life Sciences, School of Life Sciences, Fudan University, Shanghai 200433, China; 3Corresponding author,E-mail: [email protected]

With 2 figures and 3 tables

Received February 22, 2008/Accepted October 20, 2008Communicated by M. Yano

Abstract

Panicle-related traits are important agronomic traits which directly

associated with grain yield. In this study, we investigated quantitative

trait loci (QTLs) associated with panicle-related traits using a set of

265 introgression lines (ILs) of common wild rice (Oryza rufipogon

Griff.) in the background of Indica high-yielding cultivar Guichao 2

(O. sativa L.). A total of 39 QTLs associated with panicle-related traits

including panicle length (PL), primary branch number (PBN),

secondary branch number (SBN), spikelet number per panicle (SPP)

and spikelet density (SD), were detected in the ILs with single-point

analysis. The alleles of 20 QTLs derived from wild rice showed positive

effects, and some QTLs, such as, QPl1b for PL, QPbn8 for PBN, QSd4

and QSd11b for SD and QSpp4 for SPP showed larger positive effects,

providing good candidates and useful information for marker-aided

improvement of yield potential of rice. Most of the QTLs controlling

SPP, SBN and SD were located in cluster or closely linked on

chromosomes, and the directions of their additive effects were

consistent, which explained the genetic basis of significant correlations

between their phenotypic characters.

Key words: common wild rice — introgression lines —quantitative trait locus — panicle-related traits

Grain yield is one of most important traits in rice breeding,and breeders always expected to develop high-yielding varie-ties. However, because grain yield is a complex trait andinfluenced by many processes and factors, direct analysis of

grain yield did not give ideal results. It will be helpful to makeproper dissection and focused studies on yield components,instead of yield itself as a whole. Panicle-related traits, as

important yield components, had been studied by manyresearchers (Kato and Takeda 1996, Xu et al. 2004, Yamagishiet al. 2004, Mei et al. 2005b, Ando et al. 2008, Xie et al. 2008).

Currently, rice breeding faces the problem of yield plateaus,caused by narrow genetic basis of parental materials (Rangelet al. 1996, Tanksley and McCouch 1997). Thus, new breedingresource must be exploited from unused local varieties or

exotic germplasm like wild rice to broaden the geneticdiversity. Common wild rice (Oryza rufipogon Griff.), as thewild ancestor species of cultivated rice (O. sativa L.) (Second

1982, Oka 1988, Wang et al. 1992), constitute a major genepool for rice improvement. During the course of domestica-tion from wild rice to cultivated rice, profound changes of

agronomic traits and genetic diversity occurred, and thenumber of alleles of cultivated rice was only 60% that of wild

rice, and many alleles were lost, leading to lower genetic

diversity of the cultivated rice (Sun et al. 2001). In recentyears, a number of trait-enhancing quantitative trait loci(QTL) alleles derived from wild rice have been reported (Xiaoet al. 1996, Moncada et al. 2001, Li et al. 2002, Septiningsih

et al. 2003, Thomson et al. 2003, He et al. 2006, Tian et al.2006a). However, there were few reports about the identifica-tion of favourable QTL of panicle-related traits from common

wild rice. Mapping QTL influencing panicle-related traits, wasbenefit to not only uncover the low yield genetic basis of wildrice, but also understand the evolutionary mechanism of

panicle-related traits from wild rice to cultivated rice.Introgression lines (ILs) are the results of using marker-

assisted selection (MAS) to introgress small chromosomal

segments from the donor into the recurrent parent byconsecutive backcrossing and selfing (Eshed and Zamir1994, 1995). Any phenotypic difference between such an ILand its recurrent parent should be due to the QTL located on

the introgressed segments of the donor. It was demonstratedthat ILs are a powerful tool for identification of new genes(Eshed and Zamir 1994, 1995, Chetelat and Meglic 2000,

Kubo et al. 2002, Ashikari et al. 2005, Tian et al. 2006a,b,Ando et al. 2008, Xie et al. 2008, Xing et al. 2008), distin-guishing pleiotropy vs. linkage as well as pseudo-overdomi-

nance vs. true-dominance (Yamamoto et al. 1998, Monforteand Tanksley 2000), and eliminating the linkage drag andmap-based cloning of QTL (Alpert and Tanksley 1996,

Grandillo et al. 1996, Yamamoto et al. 2000, Yano et al.2000, Takahashi et al. 2001, Ashikari et al. 2005). In ourlaboratory, a set of 159 ILs derived from the cross betweenGuichao 2, a high-yielding commercial �Indica� cultivar

(O. sativa), as the recurrent parent and an accession ofcommon wild rice collected from Dongxiang county, JiangxiProvince, China, as the donor, were constructed and QTL

analysis for yield-related traits in this population based onphenotypic evaluations of multiple years and sites wasconducted (Tian et al. 2006a).

In this study, a larger population consisting of 265 ILsincluding the 159 ILs described previously by Tian et al.(2006a) and 106 new selected ILs from BC3F4 of the samecross by genotyping of 160 polymorphic simple sequence

repeats (SSR) loci was used. A total of 39 QTLs associatedwith five panicle-related traits were detected in the ILs with

www3.interscience.wiley.com

Plant Breeding 128, 559—567 (2009) doi:10.1111/j.1439-0523.2008.01607.x� 2009 The AuthorsJournal compilation � 2009 Blackwell Verlag, Berlin

single-point analysis, and the alleles of 20 QTLs derived fromwild rice showed positive effects.

Materials and Methods

Experimental populations: A set of ILs consisting of 265 lines carrying

variant introgressed segments of Chinese common wild rice (O. rufipo-

gon), collected from Dongxiang county, Jiangxi Province, in the

background of an �Indica� (O. sativa) cultivar, Guichao 2, were used.

These 265 lines represented 81.5% of the genome of O. rufipogon and

included the 159 lines representing 67.5% of the genome ofO. rufipogon

described in Tian et al. (2006a) and 106 new lines selected from BC3F4

of the same cross by genotyping of 160 polymorphic SSR loci.

Field trial and phenotypic evaluation: Field trials of the 265 ILs, and

their parents Dongxiang wild rice and Guichao 2 were conducted at

Sanya (18�N, 109�E, Hainan Province, China)–Experimental Station

of China Agricultural University. The germinated seeds were sown in

seedling nursery on 29 November, 2004 at Sanya. Seedlings were

transplanted to paddy fields on 22 December at Sanya with single plant

per hill spaced at 13.2 · 26.2 cm. Three-row plots with 11 plants per

row were planted in a randomized complete block design with two

replications. The field management was similar to that under normal

rice production conditions. The five plants in the middle of the central

row were selected, whose main-stem was marked with a little plastic

brand at its seedling stage and harvested at its maturity stage for

evaluating five panicle-related traits as follows. Panicle length (PL) was

measured as the average number of centimeter from the panicle neck to

the panicle tip (excluding awn) based on an evaluation of five main-

stem panicles. Primary branch number (PBN), secondary branch

number (SBN) and spikelet number per panicle (SPP) were evaluated

as the mean measurement from the five main-stem panicles. Spikelet

density (SD) was calculated as the average spikelets per centimeters

from the spikelets per panicle divided by the PL.

Genetic markers and genotyping: Simple sequence repeat markers were

selected from the previous publication (Temnykh et al. 2000, McCouch

et al. 2002) to evenly cover 12 chromosomes. A total of 160 polymor-

phic markers with confirmed linkage were finally chosen in this study

(Fig. 2). SSRmarker order was based on the rice linkage map described

by Temnykh et al. (2000) and McCouch et al. (2002) and Gramene

(http://www.gramene.org/db/markers/marker_view).All of 265 ILs and

their parents, Dongxiang wild rice and Guichao 2 were genotyped using

160 SSR markers using the methods described by Tian et al. (2006a).

QTL analysis: Based on the structure of ILs, QTL can be mapped on

chromosome segments introgressed. Concretely, one representative

marker for the particular introgressed segment was defined as a QTL.

To identify QTL associated with five panicle-related traits, the direct

trait measurement values of ILs for five panicle-related traits were

used. The association between the phenotypic data and 160 SSR

markers data was investigated by single-point analysis using the

software package Map Manager QTXb17 (Manly et al. 2001). The

statistical threshold was P ¼ 0.01 (the probability that loci had no

effect on the trait) for main effect loci. If a group of near markers were

associated to the same trait with similar effect (for both magnitude and

direction). The marker (or locus) with least P-value was chosen as the

locus associated to the traits. Main effect QTLs (M-QTLs) were named

following the popular nomenclature (McCouch et al. 1997) but using

alphabetic order for QTL on same chromosome.

ResultPolymorphism of markers

A total of 460 SSR markers from the 12 chromosomes wereused in the polymorphism survey. Of these, 160 (34.8%) werepolymorphic between Dongxiang common wild rice

(O. rufipogon) and Guichao 2 (O. sativa). This was higherthan that previously reported for O. rufipogon/O. sativa cross(Xiao et al. 1998).

Characterization of the introgression lines

The ILs obtained represented 81.5% of the genome of

O. rufipogon on the marker base, and carried 698 homozygousintrogressed segments and 113 heterozygous ones. Each ofthese ILs had 0–11 homozygous introgressed segments and/or

0–4 heterozygous introgressed ones, with an average of threesegments per IL (Fig. 1).A total of 811 introgressed segments were detected among

the 265 ILs, the sizes ranged from 0.15 to 60.25 cM, with an

average of 11.72 cM. Most introgressed segments were detectedby a single SSR marker. The majority of introgressed segments(54.9%) were <10 cM; another 40.5% were between 10 and

30 cM; and the proportions of large segments (>30 cM) wereonly 4.6%, and consistent with the result described by Tianet al. (2006a).

It was also found that of 811 O. rufipogon segments detected,435 (53.6%) were terminal, defined as including distance lessthan 15 cM from the end of the chromosome, and 376 (46.4%)

were interstitial, suggesting that the distribution of theintrogressed segments along the chromosomes was notrandom, and the majority of O. rufipogon introgressedsegments were often at terminal positions (Tian et al. 2006a).

Performance of the ILs for panicle-related traits

The summary statistics for the panicle-related traits were givenin Table 1. The performance of the two parents was signifi-cantly different for all traits measured, and the phenotypic

values of all panicle-related traits of Guichao 2 were signifi-cantly larger than that of Dongxiang common wild rice. TheILs showed normal distribution with tremendous variation and

transgressive segregation for all the traits (data not shown).

The relationships between the mean trait values of ILs

Table 2 shows phenotypic correlation and determinationcoefficients in IL populations. Significant positive correlationamong panicle traits each other except between PL and SD

were observed, and the correlation coefficients of them were allover 0.3936 (P < 0.001), suggesting strikingly close relativefor panicle-related traits. Interestedly, the correlation between

SPP and other four traits in descending order wasSBN > SD >> PBN > PL. Notably, the determinationcoefficient between the IL performance for SPP and SBNreached 0.9518, implying that SBN is the most important

contributor to SPP.

QTLs for five panicle-related traits

The number, location and effect of QTL detected for thepanicle traits are summarized in Table 3 and Fig. 2. For traits

that were also studied between O. sativa and O. rufipogon(Xiao et al. 1998, Xiong et al. 1999, Cai and Morishima 2002,Jing et al. 2005, Tian et al. 2006a,b), between O. sativa and O.

nivara (Li et al. 2006), and between O. sativa and O. sativa (Xuet al. 2001, 2004, Mei et al. 2005b), the number and location ofthe QTL are compared (Table 3).

560 Lu o , T ian , Fu , Y ang and Sun

Fig. 1: Graphical representation of the introgression lines developed in this study. Each row represented a candidate introgression line and eachcolumn represented a SSR locus. The black regions indicated the regions homozygous for Oryza rufipogon; the white regions indicated the regionshomozygous for Guicao 2 alleles; the shaded regions indicated heterozygous regions

Mapping panicle-related QTL from wild rice 561

A total of 39 M-QTLs were identified for five panicle-relatedtraits, and 20 (51.3%) of them contributed positive additiveeffects (Table 3). There was a similar result in ratio of trait-enhancing QTL previously reported for common wild rice (O.

rufipogon)/cultivated rice (O. sativa) cross (Xiao et al. 1998).These M-QTLs were mapped to all of the rice chromosomesexcept chromosome 10 (Fig. 2).

Panicle length

Six QTLs were detected for PL on chromosome 1, 2, 3, 6 and 9,

respectively, which jointly explained 50.0% of the total varia-tion. The QTL QPl1b, accounting for 19.0% of the totalvariation, located in a locus nearly reported by Xiong et al.

(1999). Another QTL, QPl9, was located near OSR29 onchromosome 9 where a QTL for PL was mapped in previousstudies (Xu et al. 2001, Li et al. 2006). The remaining QTL

appeared tobenew loci forPL thatwere not reportedpreviously.

Primary branch number

Six QTLs for PBN, explaining 51.0% of the total variation,were identified on chromosome 1, 2, 8, 11 and 12, respectively.Three QTLs, QPbn1, QPbn2 and QPbn8, explaining 9.0%,

6.0% and 17.0% of the variation, respectively, have beenreported in previous studies (Xu et al. 2001, Yamagishi et al.2004, Jing et al. 2005).

Secondary branch number

Nine QTLs for SBN were detected on chromosome 1, 2, 4, 5, 7,

11 and 12, respectively, which jointly explained 80.0% of totalvariation. Of nine QTLs, five were mapped at similar loci asthe ones reported previously for this trait (Table 3).

Spikelet number per panicle

Nine QTLs for SPP, explaining 88.0% of total variation, were

located on chromosome 1, 2, 4, 5, 7, 11 and 12, respectively.

The previous studies involving O. rufipogon, O. nivara and O.sativa detected over 10 QTLs for SPP, and both this study and

previous studies identified five loci (QSpp1a, QSpp1b, QSpp4,QSpp7 and QSpp11b) in similar location on the chromosome1, 4, 7 and 11, respectively (Table 3).

Spikelet density

Nine QTLs for SD were detected on chromosome 1, 3, 4, 5, 7,

9, 11 and 12, respectively, which accounted for 77.0% of thetotal variation. Three QTLs, QSd1, QSd3 and QSd11b, werethe similar loci as the ones reported previously for this trait

(Table 3). The remaining six QTLs, containing three QTLswith P-value ¼ 0.0001 and over 10% contribution rates, havenot been reported previously for SD.

Summary of the QTL mapping

The variation explained by individual QTL ranged from a low

of 4.0% to a high of 19.0%, with the majority of themexplaining less than 10% of the variation. Comparison of theseQTLs with published results showed that 18 QTLs detected in

this study for five panicle-related traits corresponded to thoseidentified in previous studies, while the remaining 21 QTLshave not been reported previously.

Interestingly, 29 out of 39 QTLs detected appeared toclustering distribution for various traits examined in thisstudy. Concretely, nine genomic regions on seven chromo-somes contained QTLs influencing more than three panicle

traits, respectively (Table 3, Fig. 2). For instance, two regions,near RM84 on chromosome 1 and RM20A on chromosome12, respectively, were simultaneously detected for PBN, SBN,

SPP and SD, and the alleles of Dongxiang common wild riceat these QTLs on the two regions contributed negative effectfor the four traits. Furthermore, five regions, near RM335 on

chromosome 4, RM31 on chromosome 5, RM224 on chro-mosome 11, RM481 on chromosome 7, OSR1 on chromosome11, respectively, were simultaneously identified for SBN, SPP

and SD, and these QTL in previous three regions all appearedto be positive effective for SBN, SPP and SD, in contrast,remaining QTLs on other two regions all appeared to benegative effective for the three traits. Otherwise, two regions

near RM212 on chromosome 1 and RM279 on chromosome 2were also simultaneously detected for PL, SNB and SPP,respectively, and all contributed positive effective for the three

traits.These QTL regions above contributed in the same direc-

tion to all phenotypic performance, partially explaining the

highly positive correlation among SBN, SPP and SD,respectively.

Table 1: Statistics on panicle-related traits of main-stem panicle

Trait

Dongxiangcommonwild rice Guichao 2 Difference

Introgression lines

Mean RangeStandarddeviation

PL 20.1 22.5 2.4 22.0 18.5–27.2 1.5PBN 7.0 12.2 5.2 11.2 7.0–18.0 1.4SBN 0.6 39.4 38.8 37.9 12.0–69.0 8.6SPP 43.6 224.8 181.2 213.1 78.6–379.2 45.3SD 2.2 10.0 7.8 9.7 4–14.4 1.9

PL, Panicle length; PBN, primary branch number per panicle; SBN, second branch number per panicle;SPP, spikelet number per panicle; SD, spikelet density.

Table 2: Phenotypic correlation (r) between five panicle-related traitsof main-stem panicle

PBN SBN SD SPP

r r r r

PL 0.3936*** 0.4292*** )0.0417 0.4673***PBN 0.5128*** 0.5185*** 0.5900***SBN 0.9270*** 0.9756***SD 0.9386***

See abbreviation in Table 1.*P ¼ 0.05; **P ¼ 0.01; ***P ¼ 0.001.


DiscussionMapping QTL using ILs

Overlapping of chromosomal segments in ILs was a powerfulstrategy to map QTL more precisely in a spot of genome andto validate QTL mapped in early generation or in genome-

wide segregating populations (Paterson et al. 1990, Eshedet al. 1992). ILs give a more reliable implication for geneticimprovement, mainly by getting profit from more precise

estimation of genetic effect under a relatively uniform andprobably elite background (Tanksley and Nelson 1996). Meiet al. (2005b) detected 14 loci influencing panicle size in two

sets of reciprocal ILs derived from Teqing (indica)/Lemont(japonica) cross. Ando et al. (2008) also identified 38 QTLs forpanicle architecture using a set of 39 chromosome segmentsubstitutions lines (CSSL) from a cross between Sasanishiki

(japonica) and Habataki (indica). And a large number of QTLsdetected in the CSSL were not reported from other popula-tions derived from the same cross-combination (Nagata et al.

2002). They suggest that CSSL population is highly suitablefor the genome-wide surveying of complex traits. Furthermore,

Tian et al. (2006a) detected 59 QTLs associated with yield andits component in 159 ILs derived from same cross with presentstudy. In this study, an average of 7.8 M-QTLs with over69.2% contribution rate was identified for each panicle trait,

revealing that ILs possess a powerful sensitiveness for M-QTLmapping in rice.With previous studies for genetic basis of rice (Li et al. 2001,

Luo et al. 2001, Mei et al. 2005a), epistatic effect approved tobe more and more important ever than main effect for traitperformance. In F2 or recombinant inbred lines (RIL) popu-

lation, epistatic effect-QTLs (E-QTLs) were found to havehigher contribution rate than M-QTL for more traits,especially for QTL influencing heterosis isolated in RILs and

their testcross or backcross hybrids. Then, Zhang et al. (2002)carried out quantitative genetic analyses of panicle-relatedtraits by using a doubled haploid population of rice derivedfrom an intersubspecific cross, found that multigenes affecting

SPP and SBN not appeared to interact. Furthermore, Andoet al. (2008) performed epistatic analysis for a SBN QTL anddid not detect any epistatic interaction between the one and

other chromosomal region yet. In this study, only less E-QTLs

Table 3: Main effect QTLs influencing five panicle-related traits of main-stem panicle, PL, PBN, SBN, SPP and SD

Trait QTL Chromosome Locus PV P-value aThe previous studies that reported

similar loci with this research

PL QPl1a 1 RM81A 8 0.001 )1.42QPl1b 1 RM212 19 0.000 2.33 Xiong et al. 1999QPl2 2 RM279 5 0.008 1.01QPl3 3 RM81B 7 0.002 )1.37QPl6 6 RM162 6 0.003 )1.12QPl9 9 OSR29 5 0.008 )0.69 Xu et al. 2001, Li et al. 2006

PBN QPbn1 1 RM84 9 0.000 )0.87 Jing et al. 2005; Ando et al. 2008QPbn2 2 RM240 6 0.002 2.11 Yamagishi et al. 2004QPbn8 8 RM210 17 0.000 3.42 Xu et al. 2001QPbn11 11 RM229 5 0.008 )1.82QPbn12a 12 RM20A 4 0.009 )0.60QPbn12b 12 RM247 10 0.000 1.20

SBN QSbn1a 1 RM84 10 0.000 )5.60 Mei et al. 2005b, Ando et al. 2008QSbn1b 1 RM212 8 0.002 7.25 Xiong et al. 1999, Mei et al. 2005bQSbn2 2 RM279 6 0.003 4.35 Mei et al. 2005bQSbn4 4 RM335 9 0.001 3.78QSbn5 5 RM31 6 0.004 3.37QSbn7 7 RM481 14 0.000 )9.04 Tian et al. 2006b, Li et al. 2006QSbn11a 11 OSR1 9 0.000 )5.00QSbn11b 11 RM224 9 0.000 6.43 Xu et al. 2004QSbn12 12 RM20A 9 0.000 )5.73

SPP QSpp1a 1 RM84 11 0.000 )30.82 Xiao et al. 1998, Xiong et al. 1999,Mei et al. 2005b, Ashikari et al. 2005;Ando et al. 2008

QSpp1b 1 RM212 7 0.003 39.27 Xiao et al. 1998, Mei et al. 2005bQSpp2 2 RM279 6 0.004 17.21

SNP QSpp4 4 RM335 11 0.000 21.48 Teng et al. 2002, Mei et al. 2005bQSpp5 5 RM31 6 0.002 18.51QSpp7 7 RM481 18 0.000 )44.10 Tian et al. 2006b, Li et al. 2006QSpp11a 11 OSR1 9 0.000 )28.12QSpp11b 11 RM224 12 0.001 30.14 Xu et al. 2004QSpp12 12 RM20A 8 0.000 )31.69

SD QSd1 1 RM84 12 0.000 )1.37 Xiong et al. 1999QSd3 3 RM114 8 0.001 1.00 Xiong et al. 1999QSd4 4 RM335 14 0.000 1.14QSd5 5 RM31 6 0.002 0.77QSd7 7 RM481 5 0.005 )1.86QSd9 9 OSR28 5 0.009 0.98QSd11a 11 OSR1 10 0.000 )1.11QSd11b 11 RM224 7 0.000 1.56 Xu et al. 2004QSd12 12 RM20A 10 0.000 )1.28

See Table 1 for abbreviations. PV, the phenotypic variance explained by the QTL; P-value, the probability that the marker genotype had no effecton the trait; a, additive effect of allele from O. rufipogon.


pairs for PL and PBN were observed (data not shown). Theresults show that epistatic effect could be not important onpanicle architecture.

A blemish in an otherwise perfect thing, about 18.5% of thedonor genome was not covered by the introgressed segments inthe set of ILs, would partly affect the results of QTL mapping.

In other words, some M-QTLs could not be identified fromDongxiang wild rice.

Usefulness of valuable QTLs derived from common wild rice for

panicle-related traits in rice breeding

There is great potential for the discovery and utilization ofwild rice in rice breeding. Khush et al. (1990) and Song et al.(1995) discovered and cloned Xa21 gene from O. longistam-inata, respectively. Subsequently, this gene was successfully

transferred into diverse varieties by MAS technique anddeveloped a few new varieties resistant to bacterial leaf blight.Xiao et al. (1996) identified two yield-enhancing QTLs, yld1.1

and yld2.1, from O. rufipogon, and these two QTLs were latertransferred to the elite rice restorer line Ce64-7, 93-11 andMinghui 63 by MAS and were confirmed to produce

significant yield-enhancing effects in field tests (Deng et al.2004). Li et al. (2002) also identified two yield-enhancingQTL, qGY2-1 and qGY11-2, from Dongxiang common wild

rice (O. rufipogon) using advanced backcross QTL analysis.Recently, Xie et al. (2008) fine-mapped a yield-enhancingQTL cluster using a series of BC3F4 nearly isogenic lines

derived from a cross between the Korean �japonica� cultivarHwaseongbyeo and O. rufipogon. The cluster contained sevenQTLs for 1000-grain weight, spikelets per panicle, grains per

panicle, PL, SD, heading date and plant height, and allelesfrom the low-yielding O. rufipogon parent were beneficial inthe Hwaseongbyeo background. The exploitation of favour-

able genes from wild rice might bring about a breakthroughin rice breeding for further improvement of tolerance tobiotic and abiotic stress, or yield and other importantagronomic traits. From our results, the Dongxiang common

wild rice (O. rufipogon) had been validated possessing largenumber of trait-enhancing genes (Li et al. 2002, Tian et al.2006a).

Panicle architecture is one of important traits for rice planttype because it can affect directly grain yield as a factor of sinksize. High correlation between grain yield and panicle-related

Fig. 2: Genetic locations of QTL influencing panicle-related traits in the ILs


traits, such as PL, PBN, SBN, spikelet number on bothprimary and second branch, and spikelets per panicle had beenvalidated (Wang et al. 2001). To increase the value of eachpanicle characteristic would be an effective strategy for

improving grain yield (Guan et al. 2004). To develop extremelyhigh-yielding varieties with a large number of spikelets is amajor direction in super rice breeding programmes (Donald

1968, Khush 1996, Yuan 1997). Spikelets per panicle, PBN andSBN had high heritabilities, and were determined by genotypesin relatively higher proportion, in comparison with the

environmental influence (Zhang et al. 2002). So it will beeffective to improve panicle characteristics by MAS in earlystage of breeding. In present study, we identified 39 additive

QTLs, and 20 QTLs (51.3%) appeared to have positive effect,suggesting that these loci derived from wild rice could improvepanicle architecture of cultivar. In particularly, five loci(QPl1b, QPbn8, QSpp4, QSpp11b and QSd4) explained over

10% total phenotypic variances and showed larger positiveadditive effects, respectively. Interestingly, five genomicregions (near RM212, RM335, RM31, RM279 and RM224)

containing valuable loci could consistently increase SBN, SPPand SD or PL. Notably, two regions near RM279 and RM224coincided with the two locations of qGY2-1 and qGY11-2,

respectively, yield-improved QTL mapped by Li et al. (2002)

using a BC4F2 population derived from the same cross above.Furthermore, He et al. (2006) narrowed qGY2-1 down a102.9 kb region by construct nearly isogenic lines that differonly in single QTL, and presumed that the leucine-rich-repeat

receptor kinase (LRK) gene cluster identified should bean excellent candidate for the source of the yield QTL.Taken together, these QTLs or genomic regions with positive

effects from wild rice provided good candidates and usefulinformation for marker-aided improvement of panicle archi-tecture and yield potential of rice. Further works such as

fine-mapping and cloning the QTLs for panicle-related traitswill facilitate the utilization of these traits in breedingprogrammes.

Acknowledgements

We thank Xianyou Sun for maintaining the rice materials.This research was supported by the Conservation and Utili-zation of Agricultural Wild Plants Project of the Ministry ofAgriculture of China, and a grant from China National High-

Tech Research and Development (�863�) Program (No.2006AA100101) and Program for Changjiang Scholars andInnovative Research Team in University Programme of

Introducing Talents of Discipline to Universities (111-2-03).

Fig. 2: Continued


References

Alpert, K., and S. D. Tanksley, 1996: High-resolution mapping and

isolation of a yeast artificial chromosome contig containing fw2.2: a

major fruit-weight quantitative trait locus in tomato. Proc. Natl

Acad. Sci. USA 93, 15503—15507.

Ando, T., T. Yamamoto, T. Shimizu, X. F. Ma, A. Shomura,

Y. Takeuchi, S. Y. Lin, and M. Yano, 2008: Genetic dissection and

pyramiding of quantitative traits for panicle architecture by using

chromosomal segment substitution lines in rice. Theor. Appl. Genet.

116, 881.

Ashikari, M., H. Sakakibara, S. Y. Lin, T. Takashi, A. Nishimura,

E. R. Angeles, Q. Qian, H. Kitano, and M. Matsuoka, 2005:

Cytokinin oxidase regulates rice grain production. Science 309,

741—745.

Cai, H. W., and H. Morishima, 2002: QTL clusters reflect character

associations in wild and cultivated rice. Theor. Appl. Genet. 104,

1217—1228.

Chetelat, R. T., and V. Meglic, 2000: Molecular mapping of

chromosome segments introgressed from Solanum lycopersicoides

into cultivated tomato (Lycopersicon esculentum). Theor. Appl.

Genet. 100, 232—241.

Deng, Q. Y., L. P. Yuan, F. S. Liang, J. M. Li, X. Q. Li, L. G. Wang,

and B. Wang, 2004: Studies on yield-enhancing genes from wild rice

and their marker-assisted selection in hybrid rice. Hybrid Rice 19,

6—10. (In Chinese).

Donald, C. M., 1968: The breeding of crop ideotypes. Euphytica 17,

385—403.

Eshed, Y., and D. Zamir, 1994: Introgressions from Lycopersicon

pennellii can improve the soluble-solids yield of tomato hybrids.

Theor. Appl. Genet. 88, 891—897.

Eshed, Y., and D. Zamir, 1995: Introgression line population of

Lycopersicon pennellii in the cultivated tomato enables the identi-

fication and fine mapping of yield associated QTL. Genetics 141,

1147—1162.

Eshed, Y., M. Abu-Abied, Y. Saranga, and D. Zamir, 1992:

Lycopersicon esculentum lines containing small overlapping intro-

gressions from L. pennellii. Theor. Appl. Genet. 83, 1027—1034.

Grandillo, S., H. M. Ku, and S. D. Tanksley, 1996: Characterization

of fs8.1, a major QTL influencing fruit shape in tomato. Mol. Breed.

2, 251—260.

Guan, X., W. F. Chen, Z. J. Xu, Z. X. Li, and J. W. Sun, 2004:

Analysis of evolution on the panicle characteristics of rice varieties.

J. Shenyang Agricult. Univ. 35, 81—84. (In Chinese).

He, G. M., X. J. Luo, F. Tian, K. G. Li, W. Su, Z. F. Zhu, X. Y. Qian,

Y. C. Fu, X. K. Wang, C. Q. Sun, and J. S. Yang, 2006: Haplotype

variation in structure and expression of a gene cluster associated

with a quantitative trait locus for improved yield in rice. Genome

Res. 16, 618—626.

Jing, Y. H., C. Q. Sun, L. B. Tan, Y. C. Fu, P. J. Zhang, Z. J. Xu,

W. F. Chen, and X. K. Wang, 2005: Mapping QTLs controlling

vascular bundle and panicle-related traits from Yuanjiang common

wild rice (Oryza rufipogon Griff.). Acta Genet. Sin. 32, 178—182.

(In Chinese).

Kato, T., and K. Takeda, 1996: Associations among characters

related to yield sink capacity in spaced-planted rice. Crop Sci. 36,

1135—1139.

Khush, G. S., 1996: Prospects of and approaches to increasing the

genetic yield potential of rice. In: R. E. Evenson, R. W. Herdt, and

M. Hossain (eds), Rice Research in Asia: Progress and Priorities,

59—71. CAB International, in association with the International

Rice Research Institute University Press, Cambridge, UK.

Khush, G. S., E. Bacalangco, and T. Ogawa, 1990: A new gene for

resistance to bacterial blight from O. longistaminata. Rice Genet.

Newsl. 7, 121—122.

Kubo, T., Y. Aida, K. Nakamura, H. Tsunematsu, K. Doi, and

A. Yoshimura, 2002: Reciprocal chromosome segment substitution

series derived from Japonica and Indica cross of rice (Oryza sativa

L.). Breed. Sci. 52, 319—325.

Li, Z. K., L. J. Luo, H. W. Mei, Q. Y. Shu, R. Tablen, D. B. Zhong,

C. S. Ying, J. W. Stansel, G. S. Khush, and A. H. Paterson, 2001:

Overdominant epistatic loci are the primary genetic basis of

inbreeding depression and heterosis in rice. I. Biomass and grain

yield. Genetics 158, 1737—1753.

Li, D. J., C. Q. Sun, Y. C. Fu, L. Chen, Z. F. Zhu, C. Li, H. W. Cai,

and X. K. Wang, 2002: Identification and mapping of genes for

improving yield from Chinese common wild rice (O. rufipogon

Griff.) using advanced backcross QTL analysis. Chin. Sci. Bull. 18,

1533—1537.

Li, C. B., A. L. Zhou, and T. Sang, 2006: Genetic analysis of rice

domestication syndrome with the wild annual species, Oryza nivara.

New Phytol. 170, 185—194.

Luo, L. J., Z. K. Li, H. W. Mei, Q. Y. Shu, R. Tablen, D. B. Zhong,

C. S. Ying, J. W. Stansel, G. S. Khush, and A. H. Paterson, 2001:

Overdominant epistatic loci are the primary genetic basis of

inbreeding depression and heterosis in rice. II. Grain yield compo-

nents. Genetics 158, 1755—1771.

Manly, K. F., J. R. H. Cudmore, and J. M. Meer, 2001: Map Manager

QTX, cross-platform software for genetic mapping. Mamm.

Genome 12, 930—932.

McCouch, S. R., Y. G. Cho, M. Yano, E. Paul, M. Blinstrub,

H. Morishima, and T. Kinoshita, 1997: Report on QTL nomencla-

ture. Rice Genet. Newsl. 14, 11—13.

McCouch, S. R., L. Teytelman, Y. Xu, K. B. Lobos, K. Clare,

M. Walton, B. Fu, R. Maghirang, Z. Li, Y. Xing, Q. Zhang,

I. Kono, M. Yano, R. Fjellstrom, G. DeClerck, D. Schneider,

S. Cartinhour, D. Ware, and L. Stein, 2002: Development of 2,240

new SSR markers for rice (Oryza sativa L.). DNA Res. 9, 199—207.

Mei, H. W., Z. K. Li, Q. Y. Shu, L. B. Guo, Y. P. Wang, X. Q. Yu,

C. S. Ying, and L. J. Luo, 2005a: Gene actions of QTLs affecting

several agronomic traits resolved in a recombinant inbred rice

population and two backcross populations. Theor. Appl. Genet.

110, 649—659.

Mei, H. W., J. L. Xu, Z. K. Li, X. Q. Yu, L. B. Guo, Y. P. Wang, C. S.

Ying, and L. J. Luo, 2005b: QTLs influencing panicle size detected

in two reciprocal introgressive lines (IL) populations in rice (Oryza

sativa L.). Theor. Appl. Genet. 112, 648—656.

Moncada, P., C. P. Martinez, J. Borrero, M. Chatel, H. Gauch,

E. Guimaraes, J. Tohme, and S. R. McCouch, 2001: Quantitative

trait loci for yield and yield components in an Oryza sativa · Oryza

rufipogon BC2F2 population evaluated in an upland environment.


Monforte, A. J., and S. D. Tanksley, 2000: Fine mapping of a

quantitative trait locus (QTL) from Lycopersicon hirsutum chromo-

some 1 affecting fruit characteristics and agronomic traits: breaking

linkage among QTLs affecting different traits and dissection of

heterosis for yield. Theor. Appl. Genet. 100, 471—479.

Nagata, K., Y. Fukuta, H. Shimizu, T. Yagi, and T. Terao, 2002:

Quantitative trait loci or sink size and ripening traits in rice (Oryza

sativa L.). Breed. Sci. 52, 259—276.

Oka, H. I., 1988: Origin of Cultivated Rice. Developments in Crop

Science, 14. Japanese Scientific Society Press/Elsevier, Tokyo.

Paterson, A. H., J. W. DeVerna, B. Lanini, and S. D. Tanksley, 1990:

Fine mapping of quantitative trait loci using selected overlapping

recombinant chromosomes, in an interspecies cross of tomato.

Genetics 124, 735—742.

Rangel, P. H., E. P. Guimaraes, and P. C. F. Neves, 1996: Base

genetica das cultivares de arroz (Oryza sativa L.) irrigado do Brasil.

Pesq. Agropec. Bras. 31, 349—357.

Second, G., 1982: Origin of the genetic diversity of cultivated rice

(Oryza spp.), study of the polymorphism scored at 40 isozyme loci.

Jpn. J. Genet. 57, 25—57.

Septiningsih, E. M., J. Prasetiyono, E. Lubis, T. H. Tai, T. Tjubaryat,

S. Moeljopawiro, and S. R. McCouch, 2003: Identification of

quantitative trait loci for yield and yield components in an advanced

backcross population derived from theOryza sativa variety IR64 and

the wild relative O. rufipogon. Theor. Appl. Genet. 107, 1419—1432.


Song, W. Y., G. L. Wang, L. L. Chen, H. S. Kim, L. Y. Pi, T. Holsten,

J. Gardner, B. Wang, W. X. Zhai, L. H. Zhu, C. Fauquet, and P.

Ronald, 1995: The rice disease resistance gene, Xa21, encodes a

receptor kinase-like protein. Science 270, 1804—1806.

Sun, C. Q., X. K. Wang, A. Yoshimura, and N. Iwata, 2001:

Comparison of the genetic diversity of common wild rice (Oryza

rufipogon Griff.) and cultivated rice (O. sativa L.) using RFLP

markers. Theor. Appl. Genet. 102, 157—162.

Takahashi, Y., A. Shomura, T. Sasaki, and M. Yano, 2001:Hd6, a rice

quantitative trait locus involved in photoperiod sensitivity, encodes

the a subnit of protein kinase CK2. Proc. Natl Acad. Sci. USA 98,

7922—7927.

Tanksley, S. D., and S. R. McCouch, 1997: Seed banks and molecular

maps: unlocking genetic potential from the wild. Science 277,

1063—1066.

Tanksley, S. D., and J. C. Nelson, 1996: Advanced backcross QTL

analysis: a method for the simultaneous discovery and transfer of

valuable QTLs from unadapted germplasm into elite breeding lines.


Temnykh, S., W. D. Park, N. Ayres, S. Cartinhour, N. Hauck,

L. Lipovich, Y. G. Cho, T. Ishii, and S. R. McCouch, 2000:

Mapping and genome organization of microsatellite sequences in

rice (Oryza sativa L.). Theor. Appl. Genet. 100, 697—712.

Teng, S., Q. Qian, D. L. Zeng, Y. KuniHiro, D. N. Huang, and L. H.

Zhu, 2002: QTL analysis of rice peduncle vascular bundle system

and panicle traits. Acta Botan. Sin. 44, 301—306.

Thomson, M. J., T. H. Tai, A. M. McClung, X. H. Lai, M. E. Hinga,

K. B. Lobos, Y. Xu, C. P. Martinea, and S. R. McCouch, 2003:

Mapping quantitative trait loci for yield, yield components and

morphological traits in an advanced backcross population between

Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theor.

Appl. Genet. 107, 479—493.

Tian, F., D. J. Li, Q. Fu, Z. F. Zhu, Y. C. Fu, X. K. Wang, and

C. Q. Sun, 2006a: Construction of introgression lines carrying wild

rice (Oryza rufipogonGriff.) segments in cultivated rice (O. sativa L.)

background and characterization of introgressed segments associ-

ated with yield-related traits. Theor. Appl. Genet. 112, 570—580.

Tian, F., Z. F. Zhu, B. S. Zhang, L. B. Tan, Y. C. Fu, X. K. Wang,

and C. Q. Sun, 2006b: Fine mapping of a quantitative trait locus for

grain number per panicle from wild rice (Oryza rufipogon Griff.).


Wang, Z. Y., G. Second, and S. D. Tanksley, 1992: Polymorphism and

phylogenetic relationships among species in the genus Oryza as

determined by analysis of nuclear RFLPs. Theor. Appl. Genet. 83,

565—581.

Wang, S., Z. L. Qin, J. B. Yu, X. D. Xie, L. X. Wang, Z. Wang, and C.

Q. Chen, 2001: Effects of main agronomic characters of grain yield

of high-yield rice plant populations. J. Shenyang Agricult. Univ. 32,

250—252. (In Chinese).

Xiao, J., S. Grandillo, S. N. Ahn, S. R. McCouch, S. D. Tanksley,

J. Li, and L. Yuan, 1996: Genes from wild rice improve yield.

Nature 384, 223—224.

Xiao, J. H., J. M. Li, S. Grandillo, S. N. Ahn, L. P. Yuan,

S. D. Tanksley, and S. R. McCouch, 1998: Identification of trait-

Improving quantitative trait loci alleles from a wild rice relative,

Oryza rufipogon. Genetics 150, 899—909.

Xie, X. B., F. X. Jin, M. H. Song, J. P. Suh, H. G. Hwang, Y. G. Kim,

S. R. McCouch, and S. N. Ahn, 2008: Fine mapping of a yield-

enhancing QTL cluster associated with transgressive variation in an

Oryza sativa · O. rufipogon cross. Theor. Appl. Genet. 116,

613—622.

Xing, Y. Z., W. J. Tang, W. Y. Xue, C. G. Xu, and Q. Zhang, 2008:

Fine mapping of a major quantitative trait loci, qSSP7, controlling

the number of spikelets as a single Mendelian factor in rice. Theor.

Appl. Genet. 116, 789—796.

Xiong, L. Z., K. D. Liu, X. K. Dai, C. G. Xu, and Q. Zhang, 1999:

Identification of genetic factors controlling domestication-related

traits of rice using an F2 population of a cross between Oryza sativa

and O. rufipogon. Theor. Appl. Genet. 98, 243—251.

Xu, J. L., Q. Z. Xue, L. J. Luo, and Z. K. Li, 2001: QTL dissection

of panicle number per plant and spikelet number per panicle

in rice (Oryza sativa L.). Acta Genet. Sin. 28, 752—757.

(In Chinese).

Xu, J. L., S. B. Yu, L. J. Luo, D. B. Zhong, H. W. Mei, and Z. K. Li,

2004: Molecular dissection of the primary sink size and its related

traits in rice. Plant Breed. 123, 43—50.

Yamagishi, J., N. Miyamoto, S. Hirotsu, R. C. Laza, and K. Nemoto,

2004: QTLs for branching, floret formation, and pre-flowering floret

abortion of rice panicle in a temperate japonica tropical japonica

cross. Theor. Appl. Genet. 109, 1555—1561.

Yamamoto, T., Y. Kuboki, S. Y. Lin, T. Sasaki, and M. Yano, 1998:

Fine mapping of quantitative trait loci Hd-1, Hd-2 and Hd-3,

controlling heading date of rice, as single Mendelian factor. Theor.

Appl. Genet. 97, 37—44.

Yamamoto, T., H. Y. Lin, T. Sasaki, and M. Yano, 2000: Identifi-

cation of heading date quantitative trait loci Hd6 and characteriza-

tion of its epistatic interaction with Hd2 in rice using advanced

backcross progeny. Genetics 154, 885—891.

Yano, M., Y. Katayose, M. Ashikari, U. Yamanouchi, L. Monna,

T. Fuse, T. Baba, K. Yamamoto, Y. Umehara, Y. Nagamura, and

T. Sasaki, 2000: Hd1, a major photoperiod sensitivity quantitative

trait locus in rice, is closely related to the Arabidopsis flowering time

gene CONSTANS. Plant Cell 12, 2473—2483.

Yuan, L. P., 1997: Hybrid rice breeding for super high yield. Hybrid

Rice 12, 1—6. (In Chinese).

Zhang, Z. H., M. M. Chen, J. Tang, and Z. L. Hu, 2002: Genetic

analysis of neck-panicle vascular bundle and panicle characteristics

in rice (Oryza sativa L.). Acta Agron. Sin. 28, 86—89. (In Chinese).


mapping quantitative trait loci influencing panicle-related traits from chinese common wild rice...

Documents