水稻株高和抽穗期基因的定位和分离

利用241个重组自交系构成的群体,对水稻（Oryza sativaL.)株高和抽穗期进行基因定位,三年共定位到4个抽穗期的数量性状基因（QTLs)和4个株高OTLs,其中位于第7染色体C1023-R1440区间的QTL3年均可检测到,且效应大,同时影响株高和抽穗期。为了区分这个区间的QTL是一因多效还是紧密连锁的两个QTLs,从自交系群体里选取QTL区间来自明恢63,其他遗传背景与珍汕97高度相似的自交系RⅡ50,与珍汕97回交,获得含有363个单株的近等基因系BC1F2群体。考察株高和抽穗期。两个性状在群体里表现为双峰分布,它们的分离比符合期望的单基因盂德尔遗传分离比,BC1E2群体单株的株高和抽穗期基本表现为矮秆早抽穗,高秆迟抽穗,但是,6个单株表现相反的情况,以上结果证明,QTL能够作为盂德尔因子进行研究,在BC1F2群体里,株高和抽穗期是由单个基因控制的,第7染色体上是两个紧密连锁的基因分别控制株高和抽穗期。     

普通野生稻中增产相关QTL的发掘

普通野生稻(Oryza Rufipogon)是重要的遗传资源,发掘其优良等位基因将对水稻遗传改良产生重要影响。文章从以珍汕97为轮回亲本,普通野生稻为供体的BC2F1群体中选择一个与珍汕97表型明显不同的单株BC2F1-15,经过连续自交获得回交重组自交系BC2F5群体。均匀分布于12条染色体的126个多态性SSR(Simplesequence repeats)标记基因型分析,发现BC2F1-15单株在30%的标记位点为杂合基因型;利用该群体共检测到4个抽穗期、3个株高、4个每穗颖花数、2个千粒重和1个单株产量QTL。在第7染色体RM481-RM2区间,检测到抽穗期、每穗颖花数和产量QTL,野生稻等位基因表现增效作用;其他3个每穗颖花数QTL位点,野生稻等位基因也均具有增效作用。结果表明野生稻携带有增产相关的等位基因,这些有利等位基因无疑是水稻遗传改良可资利用的新资源。     

水稻显性感光抑制基因Su-E_1(t)的定位及遗传分析

利用粳稻品种Asominori和籼稻品种IR24衍生的重组自交系群体,在南京和海南2种自然环境下对水稻抽穗期QTL进行检测,分别检测到5个和6个影响抽穗期的QTL,其中位于第6染色体的qDTH-6在2种环境下都能被检测到,LOD值分别为6.28和12.93,贡献率分别为12.26%和17.18%。对以Asominori为背景、在qDTH-6处置换了IR24片段的染色体片段置换系CSSL45及背景亲本进行人工短日照处理,发现qDTH-6来自籼稻IR24的等位基因具有显性感光抑制效应。利用抽穗期基因型测验系和9311等一些常规稻与CSSL45杂交分析,进一步证实了qDTH-6的显性感光抑制功能,并初步判断其抑制对象为主效感光基因E_1(Ghd7),本研究将其命名为Su-E_1(t)。同时利用CSSL45×Asominori次级F2群体分别在人工短日照和自然长日照条件下对Su-E_1(t)进行了进一步定位,将其定位在SSR标记RM527附近。本研究对有效地解决水稻籼粳亚种间杂种生育期超亲晚熟的难题具有重要意义。     

水稻雄性不育系珍汕97A抽穗期的基因型分析

水稻雄性不育系珍汕97A是我国应用最大,使用最广泛的不育系,利用抽穗期基因型明确的秋光（e1e1e2e2e3e3se-1^eSe-1^e),越光（E1E1E2E2e3e3Se-1^eSe-1^e),日本晴（E1E1e2e2e3e3Se-1Se-1)和日光（E1E1E2E2e3e3Se-1Se-1)作测验品种,分析了水稻珍汕97B的抽穗期基因型,结果表明,珍汕97B的抽穗期感光基因型为：e1e1e2e2E3E3Se-1Se-1,同时还存在1对隐性感光抑制基因i-Se-1,进一步用QTL近等基因系NIL（Hd1),HIL(Hd2),NIL(Hd3),NIL(Hd5)和NIL（Hd6)进行的实验也验证了珍汕]97B 在1个显性的主效感光基因Se-1,以及其他感光修饰基因,如E3,Hd3(En-Se-1),Hd5和Hd6的基因的作用。因此,推测珍汕97A带有主效感光基因是其配制的灿型杂交稻抽穗期超亲表现的内因。     

云南元江普通野生稻株高和抽穗期QTL定位研究

以云南元江普通野生稻为供体亲本,在特青的遗传背景下构建了一套BC3高代回交群体。利用117个SSR标记分析383个BC3F2株系的基因型,采用单标记分析法对控制元江普野株高和抽穗期的QTL进行分析。在北京和合肥两个地点试验结果表明,控制株高的QTL分布在第1染色体上,在RM104附近有一个QTL,与sd-1位置相当,其对表现型变异的贡献率在两个地点分别为27％和28％,其加性效应值分别为26．24cm和26．28cm,来自野生稻的等位基因显著提高回交群体的株高;在第1、3、7、8、11染色体共检测到6个控制抽穗期QTL,其中第8染色体RM25附近控制抽穗期的QTL在两个地点的贡献率分别为13％和15％,加性效应值为4．60d和3．65d,来自野生稻的等位基因使回交群体抽穗期延迟。     

水稻F2不育和抽穗期QTL分析

对台中65（粳稻）/Bhadua（籼稻）杂交F2代群体构建了RFLP连锁图谱,含94个分布较为均匀的标记。对F2小穗不育性状进行单点分析和区间分析的结果基本一致：有两个F2小穗不育QTL座位分别位于染色体1的XNpb113～XNpb346之间和染色体8的G187～XNpb397之间,而且该两个QTL均为新检测出的座位;检测出5个抽穗期TQL,其中3个座位在单点分析和区间分析中的结果一致,分别位于染色体1的XNpb113～XNpb346,染色体4的C891～C335,染色体的8的C166～C1121,另外,染色体6的XNpb27为单点分析结果,染色体10的R716～C405为区间分析结果。由于染色体1上的F2不育QTL和抽穗期QTL重叠,该QTL座位是由于遗传效应所至还是由于环境因素（迟抽穗）所至有待构建近等基因系进一步研究。;位于染色体1和10上的抽穗期QTL座位为新检测的座位。对新检测的F2不育和抽穗期QTL座位正在建立相应的近等基因系以精确定位和克隆上述基因。     

应用中国和欧洲油菜建立的双二倍体群体对3个重要农艺性状的QTL定位以及与环境的互作分析

以中国的高油分自交系“高油”和欧洲高含油量品种“Sollux”的F1产生的282个株系组成的双二倍体(DH)群体为材料,在125个SSR标记座位构建的连锁图谱基础上,根据在中国和欧洲四个不同环境下的表型鉴定结果,采用混合线性模型基础上的QTL分析软件,对油菜3个重要农艺性状:株高,开花期和成熟期进行了数量性状基因座位(QTL)的联合定位分析,估测了这些QTL的加性、上位性以及与环境的互作效应。结果表明各性状均受多个加性、加加上位以及与环境互作的QTL控制。株高受多个QTL影响(12个位点具有加性或兼有环境互作效应,5个位点具有互作效应),以加性效应为主,加性效应总和可解释定位群体表型变异的75%左右,并多兼有上位性效应。12个主效QTL中,9个是“高油”等位基因相对“Sollux”有降低株高的作用,大多数加性×环境互作QTL的有效等位基因具有环境选择特异性。7个ae基因座位中,5个“高油”等位基因在杭州种植环境下,除一例外所有在德国环境下的互作基因座中,“Sollux”等位基因起着增加株高的作用,加加上位性主效总和为加性主效总和的三分之一。7个控制花期和8个控制成熟期的主效QTL中,分别有6个和5个是来自“高油”的等位基因相对“Sollux”具有提前开花和成熟的效应,这些QTL的效应总和占到性状表型变异的60%左右。5个位于第2和第12连锁群中的2个大效应QTL可能和已多次报导的VFN1和VFN3基因相近或相同。开花期和成熟期两性状均检测到显著的ae互作效应,双亲等位基因的效应在各环境下呈离散分布。位于14和19连锁群上的两个主效株高QTL同时也是控制开花期和油分含量的基因位点,因而利用这两个位点进行标记辅助筛选时要考虑到对油分含量的影响。控制成熟期的8个主效QTL中有3个同时也是控制开花期的基因座位,证实了开花期和成熟期高度正相关的遗传基础,两个生育性状均表现有较弱的QTL间加加上位互作,但以主效QTL的作用为主。     

水稻回交世代中两个抗纹枯病主效数量基因的鉴定与标记辅助选择

对水稻品种特青与Lemont杂交组合的F2 单株无性系群体,进行 2年有重复的抗水稻纹枯病QTLs定位,在特青的第 9号染色体和Lemont的第 11号染色体上分别定位到了 1个主效抗纹枯病QTL,各自命名为qSB 9和qSB 11。从该F2 定位群体中,根据位点双侧标记带型,选取 2个位点均为感病等位基因纯合的 2个单株作为双感亲本,均为抗病等位基因纯合的 1个单株作为双抗亲本,分别与轮回亲本特青和Lemont进行回交。标记辅助选择始于BC2F1 及以后的各回交世代,并于BC2F1 和BC4F1 世代进行了病原菌人工接种鉴定。鉴定结果表明,qSB 9和qSB 11确实存在于原定位区间,各等位基因也在回交过程中被成功选择。BC3F2 采用秧田期大群体标记检测,从中选取符合要求的单株,分别混合得到特青背景下的双感纯合系, Lemont背景下的双感、双抗纯合系,将这些纯合系连同轮回亲本同时种植于扬州大学农学院试验田和江苏里下河农科所试验田, 2次重复,随机区组设计,进行接种实验。结果表明: 1 )相同背景下的不同纯合系间在发病程度上存在极显著的差异,不同纯合系的病情严重程度依次为:Lemont双感系>特青双感系>Lemont>特青 >Lemont双抗系; 2 )2个位点上的抗性等位基因qSB 9和qSB 11单独存在时,分别可减轻病级 1 2级左右,同时存在时可减轻病级 2级左右;     

水稻显性早熟材料D64B的发现、遗传分析和分子标记定位

D64B是从籼型杂交稻保持系D63B中发现的一个无色早熟突变株。用不育系、保持系、恢复系以及早稳型水稻品种与之杂交,F1的抽穗期多数与早熟亲本D64B相同或相近,部分偏向早熟亲本。这些结果表明D64B具有显性早熟特性。将D64B在海南陵水短日照和温江长日照下分期种植,观察到两地点因生长发育期间温度变化引起的抽穗期的变化的程度是一致的,并且在一定范围内随着生长发育期间温度升高,D64B抽穗缩短,可知D64B不感光,感温性中等。种植D64B与蜀恢527的正反交F2和回交一代BC1,三者的抽穗期均呈双峰分布,并且峰谷处于同一位置,以峰谷值103d为转折点进行分组,早熟与迟熟植株的分离比经x^2检验分别符合3：1和1：1,表明D64B的早熟特性主要受一对显性早熟核基因控制。用356对微卫星引物对亲本D64B和蜀恢527进行多态性分析,并用多态性引物扩增蜀恢527／D64B的F2早熟和迟熟近等基因池,找到多态引物RM279,进一步用RM279附近的微卫星引物扩增F2早熟和迟熟近等基因池、迟熟植株,筛到多态性引物RM71。用MAPMAKER／EXP3．0软件分析,将该早熟基因定位于第2染色体的短臂端,位于RM179和RM71之间,遗传距离分别为12．6cM和13．3cM,该基因拟名EF-3(t)。在育种实践中用D64B育成早熟不育系D64A。     

基于染色体置换系的野生稻抽穗期及紫色性状QTL的鉴定

利用一套以9311为背景的普通野生稻染色体片段置换系群体为研究材料,进行野生稻相关QTL的定位与基因的鉴定。在多年多点的抽穗期调查数据基础上,结合200多个分子标记引物的基因型鉴定结果,定位到11个与抽穗期相关的QTL;选取携带相关QTL导入片段的两个置换系进一步研究,发现2个抽穗期主效QTL均为已克隆基因的等位基因。利用叶鞘、稃尖、柱头颜色与9311差异显著的一个单片段置换系定位到来自野生稻的紫色性状基因Or C,初步鉴定与栽培稻的等位基因功能不同。这些结果再次表明染色体片段置换系是行之有效的QTL定位以及基因发掘的遗传群体。通过对抽穗期、紫色性状相关QTL的定位与基因的鉴定,为进一步的功能研究提供了基因资源。     

拔节期与抽穗期玉米抗纹枯病相关QTL的初步定位

以玉米自交系R15(抗)×478(感)的F_2分离群体为作图群体,构建了包含146个SSR标记位点的遗传连锁图谱,覆盖玉米基因组1666 cM,平均图距11．4 cM。通过麦粒嵌入法对229个F_(2：4)家系进行人工接种纹枯病菌,于玉米拔节期和抽穗期进行纹枯病的抗性鉴定。应用复合区间作图法分析两个时期的抗病QTL及遗传效应。结果共检测到17个抗性QTL,其中以拔节期病情指数为指标共检测到9个QTL,分别位于第1、2、3、4、5、6、和10染色体上,可解释的表型变异为3．72%-9．26%;以抽穗期的病情指数为指标共在7条染色体上检测到10个抗玉米纹枯病的QTL,分布于第2、3、4、5、6、8和9染色体上。单个QTL可解释的表型变异为4．27%-9．27%。两个时期共检测出2个共同QTL,它们分别位于第2染色体的bnlgl662-bnlg1940区间和第6染色体的umc1006-umc1723区间。定位结果表明两个时期检测出的抗性QTL的差异表达与玉米不同发育时期基因的时空表达有密切关系,从而反映在纹枯病的抗性位点差异性上．这为玉米抗病选育提供新的信息。     

Mapping quantitative trait loci controlling seed dormancy and heading date in rice, Oryza sativa L., using backcross inbred lines

 To detect quantitative trait loci (QTLs) controlling seed dormancy, 98 BC₁F₅ lines (backcross inbred lines) derived from a backcross of Nipponbare (japonica)/Kasalath (indica)//Nipponbare were analyzed genetically. We used 245 RFLP markers to construct a framework linkage map. Five putative QTLs affecting seed dormancy were detected on chromosomes 3, 5, 7 (two regions) and 8, respectively. Phenotypic variations explained by each QTL ranged from 6.7% to 22.5% and the five putative QTLs explained about 48% of the total phenotypic variation in the BC₁F₅ lines. Except for those of the QTLs on chromosome 8, the Nipponbare alleles increased the germination rate. Five putative QTLs controlling heading date were detected on chromosomes 2, 3, 4, 6 and 7, respectively. The phenotypic variation explained by each QTL for heading date ranged from 5.7% to 23.4% and the five putative QTLs explained about 52% of the total phenotypic variation. The Nipponbare alleles increased the number of days to heading, except for those of two QTLs on chromosomes 2 and 3. The map location of a putative QTL for heading date coincided with that of a major QTL for seed dormancy on chromosome 3, although two major heading-date QTLs did not coincide with any seed dormancy QTLs detected in this study. Received: 10 October 1997 / Accepted: 12 January 1998     

Identification of quantitative trait loci associated with small brown planthopper (Laodelphax striatellus Fallén) resistance in rice (Oryza sativa L.)

F(2) and BC(1) populations derived from the cross between 02428 / Rathu Heenati were used to investigate small brown planthopper (SBPH) resistance. Using the F(2) population, three QTLs for antixenosis against SBPH were located on chromosomes 2, 5 and 6, and accounted for 30.75% of the phenotypic variance; three QTLs for antibiosis against SBPH were detected on chromosomes 8, 9 and 12. qSBPH5-c explaining 7.21% of phenotypic variance for antibiosis was identified on chromosome 5 using the BC(1) population. A major QTL, qSBPH12-a1, explained about 40% of the phenotypic variance, and a minor QTL, qSBPH4-a, was detected by the SSST method in both the F(2) and BC(1) populations. The QTLs indentified in the present study will be useful for marker assisted selection of SBPH resistance in rice.     

QTL analysis of percentage of grains with chalkiness in Japonica rice (Oryza sativa)

Appearance quality of rice grains is a major problem for rice production in many areas of the world. We conducted a molecular marker-based genetic analysis of percentage of grains with chalkiness (PGWC), which is a determining factor for appearance quality; it strongly affects milling, eating and cooking quality. An F(8) recombinant inbred line population, which consists of 261 lines derived from a cross between Koshihikari (Japonica) and C602 (Japonica), was used for QTL mapping. Three QTLs related to PGWC were detected on chromosomes 5, 8 and 10, together explaining 50.8% of the genetic variation. The 'Koshihikari' alleles qJPGC-5, qJPGC-8 and the 'C602' alleles at qJPGC-10 were associated with reduced PGWC. The QTL contributions to phenotypic variance were 18.2, 9.6 and 25%, respectively. These QTL markers for PGWC could be used for developing improved varieties.     

Mapping QTLs for heading synchrony in a doubled haploid population of rice in two environments

Simultaneous heading of plants within the same rice variety, also refer to heading synchrony, is an important factor that affects simultaneous ripening of the variety. Understanding of the genetic basis of heading synchrony may contribute to molecular breeding of rice with simultaneous heading and ripening. In the present study, a doubled haploid （DH） population, derived from a cross between Chunjiang 06 and TN1 was used to analyze quantitative trait locus （QTL） for heading synchrony related traits, i.e., early heading date （EHD）, late heading date （LHD）, heading asynchrony （HAS）, and tiller number （PN）. A total of 19 QTLs for four traits distributed on nine chromosomes were detected in two environments. One QTL, qHAS-8 for HAS, explained 27.7% of the phenotypic variation, co-located with the QTLs for EHD and LHD, but it was only significant under long-day conditions in Hangzhou, China. The other three QTLs, qHAS-6, qHAS-9, and qHAS-10, were identified under short-day conditions in Hainan, China, each of which explained about 11% of the phenotypic variation. Two of them, qHAS-6 and qHAS-9, were co-located with the QTLs for EHD and LHD. Two QTLs, qPN-4 and qPN-5 for PN, were detected in Hangzhou, and qPN-5 was also detected in Hainan. However, none of them was co-located with QTLs for EHD, LHD, and HAS, suggesting that PN and HAS were controlled by different genetic factors. The results of this study can be useful in marker assisted breeding for improvement of heading synchrony.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Quantitative trait loci mapping of resistance to Laodelphax striatellus (Homoptera: Delphacidae) in rice using recombinant inbred lines

Laodelphax striatellus Fallén (Homoptera: Delphacidae), is a serious pest in rice, Oryza sativa L., production. A mapping population consisting of 81 recombinant inbred lines (RILs), derived from a cross between japonica' Kinmaze' and indica' DV85' rice, was used to detect quantitative trait loci (QTLs) for the resistance to L. striatellus. Seedbox screening test (SST), antixenosis test, and antibiosis test were used to evaluate the resistance response of the two parents and 81 RILs to L. striatellus at the seedling stage, and composite interval mapping was used for QTL analysis. When the resistance was measured by SST method, two QTLs conferring resistance to L. striatellus were mapped on chromosome 11, namely, Qsbph11a and Qsbph11b, with log of odds scores 2.51 and 4.38, respectively. The two QTLs explained 16.62 and 27.78% of the phenotypic variance in this population, respectively. In total, three QTLs controlling antixenosis against L. striatellus were detected on chromosomes 3, 4, and 11, respectively, accounting for 37.5% of the total phenotypic variance. Two QTLs expressing antibiosis to L. striatellus were mapped on chromosomes 3 and 11, respectively, explaining 25.9% of the total phenotypic variance. The identified QTL located between markers XNpb202 and C1172 on chromosome 11 was detected repeatedly by three different screening methods; therefore, it may be important to confer the resistance to L. striatellus. Once confirmed in other mapping populations, these QTLs should be useful in breeding for resistance to L. striatellus by marker-assisted selection of different resistance genes in rice varieties.     

Identification of Quantitative Trait Loci for Bacterial Blight Resistance Derived from Oryza meyeriana and Agronomic Traits in Recombinant Inbred Lines of Oryza sativa

Bacterial blight (BB) is one of the major diseases that affect rice productivity. In previous studies, BB resistance was transferred to cultivated rice Oryza sativa from wild rice Oryza meyeriana using asymmetric somatic hybridization. One of the resistant hybrid progenies (Y73) has also been shown to possess novel resistance gene(s) different from any of those previously associated with BB resistance. We have mapped quantitative trait loci (QTLs) for BB resistance in a recombinant inbred line (RIL) population derived from a cross between Y73 and a BB‐susceptible cv. IR24. Five QTLs were detected where Y73 alleles contributed to increased BB resistance. Three minor QTLs were identified on chromosomes 3, 10 and 11, and two major QTLs on chromosomes 1 and 5, respectively. QTL on chromosome 5, designated qBBR5, had the strongest effect on BB resistance, explaining approximately 37% of the phenotypic variance. Using the same RIL population, we also mapped QTLs for agronomic traits including plant height (PH), heading date (HD), plant yield (PYD) and PYD component traits. A total of 21 QTLs were identified, of which four were detected for PH, six for HD, three for panicle number per plant (PNPP), one for spikelets per panicle (SPP), six for 1000‐grain weight (TGW) and one for PYD. qPH1 (a QTL for PH) was found in the same interval as qBBR1 for BB resistance, and qHD11 for HD and qBBR11 for BB resistance also shared a similar interval. Additionally, BB resistance was significantly correlated with PH or HD in the RIL population. This suggests that the resistance genes may have pleiotropic effects on, or close linkage to, genes controlling PH or HD. These results will help deduce the resistance mechanisms of the novel resistance gene(s) and provide the basis for cloning them and using them in marker‐assisted breeding.     

Identification and molecular mapping of loci controlling fruit ripening time in tomato

Using RAPD marker analysis, two quantitative trait loci (QTLs) associated with earliness due to reduced fruit-ripening time (days from anthesis to ripening = DTR) were identified and mapped in an F₂ population derived from a cross between Lycopersicon esculentum’E6203’ (normal ripening) and Lycopersicon esculentum’Early Cherry’ (early ripening). One QTL, on chromosome 5, was associated with a reduction in both ripening time (5 days) and fruit weight (29.3%) and explained 15.8 and 13% of the total phenotypic variation for DTR and fruit weight, respectively. The other QTL, on chromosome 12, was primarily associated with a reduction only in ripening time (7 days) and explained 12.3% of the total phenotypic variation for DTR. The gene action at this QTL was found to be partially dominant (d/a=0.41). Together, these two QTLs explained 25.1% of the total phenotypic variation for DTR. Additionally, two QTLs associated with fruit weight were identified in the same F₂ population and mapped to chromosomes 4 and 6, respectively. Together, these two QTLs explained 30.9% of the total phenotypc variation for fruit weight. For all QTLs, the ’Early Cherry’ alleles caused reductions in both ripening time and fruit weight. The polymorphic band for the most significant RAPD marker (OPAB-06), linked to the reduced ripening time QTL on chromosome 12, was converted to a cleaved amplified polymorphism (CAP) assay for marker-aided selection and further introgression of early ripening time (DTR) into cultivated tomato. Received: 15 March 1999 / Accepted: 29 April 1999     

Mapping quantitative trait loci associated with arsenic accumulation in rice (Oryza sativa)

The quantitative trait loci (QTLs) associated with arsenic (As) accumulation in rice were mapped using a doubled haploid population established by anther culture of F1 plants from a cross between a Japonica cultivar CJ06 and an Indica cultivar TN1 (Oryza sativa). Four QTLs for arsenic (As) concentrations were detected in the map. At the seedling stage, one QTL was mapped on chromosome 2 for As concentrations in shoots with 24.4% phenotypic variance and one QTL for As concentrations in roots was detected on chromosome 3. At maturity, two QTLs for As concentrations in grains were found on chromosomes 6 and 8, with 26.3 and 35.2% phenotypic variance, respectively. No common loci were detected among these three traits. Interestingly, the QTL on chromosome 8 was found to be colocated for As concentrations in grain at maturity and shoot phosphorus (P) concentrations at seedling stage. These results provide an insight into the genetic basis of As uptake and accumulation in rice, and will be useful in identifying genes associated with As accumulation.