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作物学报 ›› 2018, Vol. 44 ›› Issue (8): 1248-1255.doi: 10.3724/SP.J.1006.2018.01248

• 研究简报 • 上一篇    下一篇

不同环境基于高密度遗传图谱的稻米外观品质QTL定位

彭强(),李佳丽(),张大双,姜雪,邓茹月,吴健强,朱速松()   

  1. 贵州省农业科学院水稻研究所, 贵州贵阳 550006
  • 收稿日期:2018-03-14 接受日期:2018-06-12 出版日期:2018-08-10 网络出版日期:2018-06-19
  • 通讯作者: 彭强,李佳丽,朱速松
  • 基金资助:
    贵州省科技支撑计划项目(黔科合支撑[2018]2298号);贵州省科研机构服务企业行动计划项目(黔科合服企[2014]4005号);贵州省科技计划项目(黔科合平台人才[2017]5719号);贵州省现代产业体系项目(GZCYTX2017-0602);贵州省农业科学院青年基金项目(黔农科院青年基金[2018]18号)资助

QTL Mapping for Rice Appearance Quality Traits Based on a High-density Genetic Map in Different Environments

Qiang PENG(),Jia-Li LI(),Da-Shuang ZHANG,Xue JIANG,Ru-Yue DENG,Jian-Qiang WU,Su-Song ZHU()   

  1. Guizhou Rice Research Institute, Guizhou Academy of Agricultural Sciences, Guiyang 550006, Guizhou, China
  • Received:2018-03-14 Accepted:2018-06-12 Published:2018-08-10 Published online:2018-06-19
  • Contact: Qiang PENG,Jia-Li LI,Su-Song ZHU
  • Supported by:
    the Science and Technology Support Project of Guizhou Province (QKHZC20182298);the Research Institution Service Enterprise Action Plan Project of Guizhou Province (QKHFQ20144005);the Science and Technology Plan Project of Guizhou Province (QKHPTRC20175719);the Modern Industry System Project of Guizhou Province(GZCYTX2017-0602);the Youth Fund Project of Guizhou Academy of Agricultural Sciences (QNKYQN201818).

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摘要：

为解析稻米外观品质遗传基础, 挖掘稳定存在的控制稻米外观品质性状的QTL, 本研究以籼稻品种V20B和爪哇稻品种CPSLO17作为亲本, 构建包含150个重组自交家系(recombinantion inbred line, RIL)的RIL作图群体, 进行外观品质性状QTL定位分析。利用特定位点扩增长度测序(SLAF-seq)技术, 构建了一个由12个连锁群包含8602个标记, 平均间距为0.29 cM的高密度遗传图谱。采用IciMapping 4.0软件的ICIM-ADD方法在3种环境(贵阳、贵定、三亚)对4个外观品质性状(粒长、粒宽、垩白度和垩白粒率)进行QTL (quantitative trait locus)定位分析。结果表明: 3种环境共检测到9个粒长QTL、6个粒宽QTL、3个垩白度QTL和4个垩白粒率QTL; 有5个QTL在多个环境被重复检测到, 其中3种环境都定位到的粒宽QTL qGW5-1和垩白度QTL qCha5-1为同一定位区间(第5染色体的Marker1642127-Marker1514505); 此外, 垩白度QTL qCha5-2的定位区间(Marker1554573-Marker1554589)和垩白粒率QTL qCGP5-2也是一样的。序列比对发现QTL qCha5-1定位区间仅51.5 kb, 是新的垩白性状主效QTL。本研究结果不仅为挖掘新的外观品质性状基因奠定基础, 也有助于开发新的分子标记进行水稻外观品质性状遗传改良。

关键词: 水稻, 外观品质, QTL, 高密度遗传图谱, 高通量测序

Abstract:

To analyze the genetic basis of appearance quality of rice, explore QTL which controlled rice appearance quality related traits stably existing, a mapping population of 150 lines (recombination inbred lines, RIL), derived from a cross between rice varieties V20B and CPSLO17, was applied to analysis QTL location of appearance quality trait. The specific locus amplified fragment sequencing (SLAF-seq) technology was employed to construct a high-density genetic map in rice (Oryza sativa L.). A genetic map included 8602 markers on the 12 linkage groups was successfully constructed, which with an average distance of 0.29 cM between adjacent markers. The ICIM-ADD method of IciMapping 4.0 software was used to analyze QTL location for four appearance quality traits, including grain length (GL), grain width (GW), chalky grain rate, and chalkiness degree in three environmental conditions (Guiyang, Guiding, and Sanya). A total of nine QTLs for grain length (GL), six QTLs for grain width (GW), four QTLs for chalkiness size, three QTLs for chalkiness degree traits were detested in three environments. Five QTLs were repeatedly detected in multiple environments, of which the QTL qGW5-1 and qCha5-1 with the same localization interval (Marker1642127-Marker1514505 on chromosome 5) were repeatedly located in all three environments. In addition, the positioning interval of chalkiness QTL qCha5-2 (Marker1554573-Marker1554589) is the same as the chalkiness size QTL qCGP5-2. The sequence alignment found that the location interval of QTL qCha5-1 was only 51.5 kb, which was a new main effect QTL for chalkiness trait. These results lay the foundation for further exploiting candidate gene of appearance quality, which also contribute to the development of new molecular markers for rice appearance quality traits genetic improvement.

Key words: rice, appearance quality, QTL, high-density genetic map, high throughput sequencing

图1

3种环境下RIL群体中稻米外观品质性状分布 GL: 粒长; GW: 粒宽; CGP: 垩白粒率。"

表1

RIL群体在3个环境下的外观品质性状表现"

性状
Trait		 环境
Environment		 亲本 Parents 均值
Mean		 幅度
Variance		 标准误
SE		 偏度
Skewness		 峰度
Kurtosis		 W-test P-value
V20B CPSLO17
粒长
Grian length
(mm)		 贵州贵阳 Guiyang, Guizhou 6.9317 7.5079 7.1104 0.3837 0.6194 0.2445 -0.4229 0.9770 0
贵州贵定 Guiding, Guizhou 6.8986 7.4041 7.0370 0.3853 0.6207 -0.0375 0.2419 0.9885 0
海南三亚 Sanya, Hainan 6.8264 7.6673 7.0589 0.3469 0.589 0.1212 -0.6511 0.9725 0
粒宽
Grain width
(mm)		 贵州贵阳 Guiyang, Guizhou 2.7864 1.9939 2.4299 0.0383 0.1956 -0.005 0.1085 0.9844 0
贵州贵定 Guiding, Guizhou 2.8194 2.1133 2.4330 0.0305 0.1746 -0.4667 -0.2171 0.9588 0
海南三亚 Sanya, Hainan 2.9044 2.1920 2.5347 0.0341 0.1846 -0.3713 -0.3784 0.9602 0
垩白度
Chalkiness
(%)		 贵州贵阳 Guiyang, Guizhou 23.0488 0 9.0864 81.8183 9.0453 1.0115 0.5006 0.8656 0.2495
贵州贵定 Guiding, Guizhou 23.4848 0 6.0706 54.2400 7.3648 1.5925 2.0456 0.7781 0.8978
海南三亚 Sanya, Hainan 23.4286 0 8.9570 74.5756 8.6357 1.0951 0.8017 0.8732 0.0977
垩白粒率
Chalky grain
percentage (%)		 贵州贵阳 Guiyang, Guizhou 26.2500 0 14.5078 90.7359 9.5255 0.6304 1.1792 0.9337 0.6898
贵州贵定 Guiding, Guizhou 25.0000 0 10.6941 78.7201 8.8724 0.7583 -0.0918 0.8983 0.0019
海南三亚 Sanya, Hainan 25.6250 0 11.9539 71.8795 8.4782 0.7945 0.7856 0.9134 0.0030

表2

亲本的SLAF数量及其覆盖深度"

样品
Sample		 SLAF数量
SLAF number		 读取数
Reads number		 平均深度
Average depth (×)
V20B 58473 2889072 49.41
CPSLO17 51837 2760145 53.25
合计 Total 110310 193277 51.21

表3

12连锁群基本信息统计"

染色体
Chr.		 长度
Length (cM)		 标记数量
Marker number		 标记间距 Marker interval (cM) Spearman相关系数?
Spearman correlation coefficient ?
平均值 Mean 最大值 Max
1 365.11 1334 0.27 2.45 0.9996
2 184.38 818 0.23 6.00 0.9999
3 262.99 438 0.60 10.50 0.9995
4 241.09 908 0.27 3.67 0.9956
5 105.26 504 0.21 3.36 0.9996
6 363.05 1028 0.35 2.91 0.9900
7 149.03 817 0.18 3.09 0.9831
8 157.91 386 0.41 3.58 0.9996
9 130.07 525 0.25 7.04 0.9632
10 103.98 415 0.25 4.92 0.9791
11 245.23 782 0.31 2.82 0.9913
12 200.54 647 0.31 4.83 0.9978
合计 Total 2508.65 8602 0.29 10.50

图2

稻米外观品质性状的QTL在遗传图谱上的分布"

表4

不同环境下稻米外观品质性状QTL分析"

性状
Trait		 环境Environments 基因座
QTL		 染色体
Chr.		 位置
Position (cM)		 标记区间
Marker interval		 LOD 表型贡献率PVE (%) 加性效应
Add.
粒长
Grain length		 贵州贵阳Guiyang, Guizhou qGL1-2 1 361 Marker693317-Marker532394 4.13 5.87 -0.1498
qGL3-1 3 60 Marker910209-Marker823024 5.25 7.28 0.1693
qGL3-3 3 127 Marker891931-Marker771788 4.03 5.42 0.1466
qGL7-1 7 118 Marker275670-Marker347375 4.85 6.95 -0.1628
qGL8-1 8 115 Marker201080-Marker118092 17.97 31.18 0.3496
qGL8-2 8 119 Marker191958-Marker143502 7.88 11.87 -0.2175
qGL10-1 10 19 Marker34448-Marker23092 9.60 15.71 0.2592
贵州贵定Guiding,Guizhou qGL1-1 1 266 Marker587391-Marker688101 3.91 10.15 -0.1972
qGL3-2 3 63 Marker922818-Marker757283 5.08 13.38 0.2283
海南三亚
Sanya, Hainan		 qGL1-2 1 361 Marker693317-Marker532394 3.05 8.10 -0.1673
qGL3-1 3 60 Marker910209-Marker823024 3.79 10.22 0.1908
粒宽
Grain width		 贵州贵阳Guiyang, Guizhou qGW5-1 5 27 Marker1642127-Marker1514505 14.34 28.66 0.1051
qGW7-2 7 114 Marker343862-Marker239518 6.18 10.49 0.0632
qGW11-2 11 120 Marker1741595-Marker1645826 4.45 7.81 0.0545
贵州贵定Guiding, Guizhou qGW5-1 5 27 Marker1642127-Marker1514505 8.46 16.96 0.0721
qGW7-1 7 106 Marker322410-Marker237275 6.83 13.24 0.0638
海南三亚
Sanya, Hainan		 qGW5-1 5 27 Marker1642127-Marker1514505 5.84 12.59 0.0657
qGW11-1 11 114 Marker1750082-Marker1683589 4.34 8.93 0.0550
qGW12-1 12 71 Marker1486720-Marker1380718 4.09 8.88 -0.0567
垩白度Chalkiness 贵州贵阳Guiyang, Guizhou qCha5-1 5 27 Marker1642127-Marker1514505 4.69 12.63 0.0322
贵州贵定Guiding, Guizhou qCha5-1 5 27 Marker1642127-Marker1514505 5.05 14.77 0.0284
海南三亚
Sanya, Hainan		 qCha4-1 4 147 Marker403659-Marker472670 3.98 7.71 0.0241
qCha5-1 5 27 Marker1642127-Marker1514505 8.55 17.83 0.0366
qCha5-2 5 102 Marker1554573-Marker1554589 3.75 7.46 0.0241
垩白粒率Chalky grain percentage 贵州贵阳Guiyang, Guizhou qCGP2-1 2 1 Marker1152260-Marker1135261 3.91 9.95 2.9960
qCGP5-2 5 102 Marker1554573-Marker1554589 3.42 9.15 2.9475
海南三亚
Sanya, Hainan		 qCGP4-1 4 149 Marker472670-Marker400717 5.01 10.66 2.7694
qCGP5-1 5 25 Marker1611496-Marker1557594 5.82 12.50 3.0122
qCGP5-2 5 102 Marker1554573-Marker1554589 5.28 11.15 2.8968
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