欢迎访问作物学报，今天是
作物学报

作物学报 ›› 2024, Vol. 50 ›› Issue (7): 1669-1683.doi: 10.3724/SP.J.1006.2024.31073

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

两个RIL群体中小麦籽粒品质相关性状QTL定位及KASP标记开发

毕俊鸽1,2,**(), 曾占奎1,2,**(), 李琼1,2, 洪壮壮1,2, 颜群翔1,2, 赵越1,2, 王春平1,2,*()   

  1. 1河南科技大学农学院 / 河南省旱地作物种质资源利用工程研究中心, 河南洛阳 471000
    2神农种业实验室, 河南郑州 450000
  • 收稿日期:2023-11-30 接受日期:2024-01-31 出版日期:2024-07-12 网络出版日期:2024-03-02
  • 通讯作者: *王春平, E-mail: chunpingw@163.com
  • 作者简介:毕俊鸽, E-mail: bijungee@163.com;
    曾占奎, E-mail: zengzhankui0301@163.com

    **同等贡献

  • 基金资助:
    河南省重大科技专项“小麦营养基因组学解析及功能食品创制与产业化”项目(231100110300);神农种业实验室“一流课题”项目(SN01-2022-01)

QTL mapping and KASP marker development of grain quality-relating traits in two wheat RIL populations

BI Jun-Ge1,2,**(), ZENG Zhan-Kui1,2,**(), LI Qiong1,2, HONG Zhuang-Zhuang1,2, YAN Qun-Xiang1,2, ZHAO Yue1,2, WANG Chun-Ping1,2,*()   

  1. 1College of Agriculture, Henan University of Science and Technology / Henan Dryland Crop Germplasm Resources Utilization Engineering Research Center, Luoyang 471000, Henan, China
    2Shennong Laboratory, Zhengzhou 45000, Henan, China
  • Received:2023-11-30 Accepted:2024-01-31 Published:2024-07-12 Published online:2024-03-02
  • Contact: *E-mail: chunpingw@163.com
  • About author:

    **Contributed equally to this work

  • Supported by:
    Major Science and Technology of Henan Province Project “The Wheat Nutrigenomics Analysis and Functional Food Creation and Industrialization Fund Project”(231100110300);Shennong Laboratory “First-Class Subject” project(SN01-2022-01)

RichHTML

39

PDF

560

摘要：

本研究利用小麦55K SNP (55K single-nucleotide polymorphism)芯片和DArT (diversity array technology)标记对Avocet/Chilero和Avocet/Huites构建的两个F6重组自交系群体(recombinant inbred line, RIL)进行了小麦籽粒蛋白质含量(grain protein content, GPC)、湿面筋含量(wet gluten content, WGC)和沉降值(sedimentation value, SV)的QTL (quantitative trait loci)定位。共鉴定到68个与小麦籽粒蛋白质含量、湿面筋含量和沉降值相关的QTL, 表型贡献率为3.60%~22.53%, 其中, 位于3A(2)、4D、5D(2)、6A(8)和7B染色体上的14个QTL可在多环境下被重复检测到。此外, 在3A、3D、4B、5D、6A(2)和7B染色体上检测到7个QTL簇, 位于3AS染色体9.32~60.01 Mb和6AS染色体38.47~82.95 Mb的稳定QTL簇C3A和C6A.2, 同时与小麦籽粒蛋白质含量、湿面筋含量和沉降值显著相关, 分别解释了6.55%~14.21%和3.83%~22.53%的表型变异。同时, 在2个QTL簇中筛选到16个可能与籽粒蛋白质含量相关的候选基因, 并根据候选基因开发了可供育种利用的KASP标记CGPC-6A-KASP-1和CGPC-6A-KASP-2。本研究为小麦籽粒品质相关性状的遗传改良提供了新的QTL位点和KASP标记, 为分子标记辅助育种提供依据与参考。

关键词: 小麦, 籽粒蛋白质含量, QTL定位, KASP标记

Abstract:

We utilized a 55K single-nucleotide polymorphism (55K SNP) array and diversity array technology (DArT) to identify QTLs for grain protein content (GPC), wet gluten content (WGC), and sedimentation value (SV) in two F6 recombinant inbred lines derived from Avocet/Chilero and Avocet/Huites. Sixty-eight QTLs were identified related to grain protein content, wet gluten content, and settlement value, explaining 3.60%-22.53% of the phenotypic variances. Fourteen QTLs were found to be present in multiple environments, located on chromosomes 3A(2), 4D, 5D(2), 6A(8), and 7B, respectively. Additionally, seven QTLs clusters were detected on chromosomes 3A, 3D, 4B, 5D, 6A(2), and 7B, respectively. Two stable QTL clusters, C3A and C6A.2, identified in the physical intervals of 9.32-60.01 Mb and 38.47-82.95 Mb, respectively, were significantly associated with grain protein content and wet gluten content. These clusters accounted for 6.55%-14.21% and 3.83%-22.53% of the phenotypic variances for grain protein content, wet gluten content, and sedimentation value. Meanwhile, a total of 16 candidate genes associated with grain protein content were predicted within the two stable QTL clusters. Moreover, two KASP marker, CGPC-6A-KASP-1 and CGPC-6A-KASP-2, were developed based on the candidate genes. The findings of this study provide support for the identification of new QTL and KASP markers that can contribute to the genetic improvement of grain quality-related traits in wheat. These results also offer valuable insights for marker-assisted breeding in wheat.

Key words: wheat, grain protein content, QTL mapping, KASP marker

表1

不同环境下两个F6 RIL群体及亲本中籽粒品质相关性状表型变异分析"

群体
Population		 性状
Trait		 环境
Env.		 亲本Parents RIL家系 广义遗传力
H2		 基因型
Genotype
(G)		 环境
Environment
(E)		 基因型×
环境
G × E
Avocet Chilero Huites 范围
Range		 平均值±标准误
Mean ± SD		 偏度
Skewness		 峰度
Kurtosis		 变异系数
CV (%)
AC
Population		 GPC
(%)		 E1 13.88** 14.95** - 12.19-17.16 14.52±0.90 0.14 ‒0.06 6.20 0.82 431.42** 6,867.82** 97.12**
E2 13.94** 14.93** - 13.78-18.51 15.66±0.88 0.62 0.90 5.62
E3 14.90* 15.42* - 12.42-18.94 15.27±1.29 0.20 ‒0.21 8.45
E4 13.62** 16.05** - 12.49-16.80 14.87±0.86 ‒0.11 ‒0.20 5.78
WGC
(%)		 E1 29.57** 33.15** - 26.50-36.85 31.99±2.17 ‒0.38 ‒0.31 6.78 0.85 338.43** 3,464.10** 59.57**
E2 30.48** 33.39** - 29.57-39.80 34.24±2.01 0.27 0.33 5.87
E3 31.48* 34.29* - 26.04-40.40 32.78±2.86 0.03 ‒0.28 8.72
E4 30.53** 35.03** - 26.33-36.63 32.48±2.08 ‒0.55 ‒0.18 6.40
SV
(%)		 E1 25.74** 35.61** - 21.76-39.02 30.36±3.53 ‒0.18 ‒0.19 11.63 0.84 233.56** 1,648.79** 42.91**
E2 27.90** 34.13** - 24.27-43.47 32.95±3.22 0.12 0.39 9.77
E3 29.47** 38.65** - 22.29-46.82 33.21±4.86 0.06 ‒0.24 14.63
E4 31.81** 39.49** - 22.74-40.29 32.62±3.67 ‒0.49 ‒0.11 11.25
AH
Population		 GPC
(%)		 E5 14.68* - 15.29* 12.56-16.73 14.83±0.88 0.08 ‒0.58 5.93 0.88 952.79** 1,077.77** 132.19**
E6 15.12** - 16.04** 12.10-18.66 14.99±1.34 0.25 ‒0.08 8.94
E7 14.69** - 16.03** 13.13-17.89 14.83±0.92 0.33 ‒0.13 6.20
WGC
(%)		 E5 30.26 - 30.27 26.89-36.27 31.98±2.03 ‒0.04 ‒0.61 6.35 0.90 446.82** 285.39** 49.13**
E6 31.71** - 34.76** 25.64-39.26 32.06±2.80 0.13 ‒0.35 8.73
E7 31.06** - 34.86** 28.30-38.52 32.31±2.06 0.13 ‒0.39 6.38
SV
(%)		 E5 39.43* - 43.24* 19.39-43.24 31.68±3.79 0.04 0.80 11.96 0.83 272.28** 1,075.43** 54.59**
E6 34.52* - 36.38* 22.55-46.57 33.83±4.96 0.22 ‒0.28 14.66
E7 29.78* - 37.07* 24.81-43.81 33.89±3.57 ‒0.08 ‒0.14 10.53

图1

AC群体(a)和AH群体(b)籽粒品质相关性状的频率分布 不同的填充形状和线条表示不同的环境; BLUE为最佳线性无偏估计。缩写同表1。"

图2

AC群体(a)和AH群体(b)中不同环境下籽粒品质相关性状的相关系数 白色到黑色的渐变表示从正相关到负相关; E1GPC、E1WGC、E1SV、E2GPC、E2WGC、E2SV、E3GPC、E3WGC、E3SV、E4GPC、 E4WGC、E4SV、E5GPC、E5WGC、E5SV、E6GPC、E6WGC、E6SV、E7GPC、E7WGC和E7SV分别为在E1、E2、E3、E4、E5、 E6和E7环境下的籽粒蛋白质含量、湿面筋含量和沉降值; *表示在P < 0.05水平差异显著。"

表S1

AC群体籽粒品质相关性状的QTL"

性状
Trait		 QTL 环境
Environment		 遗传位置
Genetic position (cM)		 侧翼标记
Flanking marker		 LOD值
LOD value		 表型贡献率
PVE (%)		 加性效应
Additive		 物理区间
Physical intervals (Mb)		 优势等位基因
Favorable allele
GPC QGPC.haust-AC-1B E4 6.00 AX-94871279-AX-111525685 6.20 15.70 ‒0.33 670.39-670.78 Chilero
QGPC.haust-AC-2B E4 46.00 AX-109885265-AX-108951217 4.76 11.77 ‒0.27 782.02-799.25 Chilero
QGPC.haust-AC-3A BLUE 271.00 AX-111543258-AX-111142459 3.54 8.77 ‒0.22 27.88-57.73 Chilero
QGPC.haust-AC-3D.1 E1 94.00 AX-108729781-AX-110834100 8.83 13.98 ‒0.44 537.29-552.24 Chilero
QGPC.haust-AC-3D.2 E3 189.00 AX-110808052-AX-95632197 2.69 5.57 ‒0.33 533.94-2.63 Chilero
QGPC.haust-AC-6A.1 E1 12.00 AX-109042664-AX-108939533 6.11 8.95 0.40 61.56-61.89 Avocet
E4 13.00 AX-109042664-AX-108939533 4.08 9.88 0.30 61.56-61.89 Avocet
QGPC.haust-AC-6A.2 E3 42.00 AX-94591230-AX-111122628 9.74 21.05 0.61 38.47-71.43 Avocet
BLUE 42.00 AX-94591230-AX-111122628 8.92 22.53 0.35 38.47-71.43 Avocet
QGPC.haust-AC-7B E3 54.00 AX-110412930-AX-108833738 3.82 7.52 ‒0.38 643.48-653.98 Chilero
BLUE 54.00 AX-110412930-AX-108833738 3.70 8.67 ‒0.22 643.48-653.98 Chilero
WGC QWGC.haust-AC-3A.1 E2 274.00 AX-111543258-AX-111142459 4.22 10.12 ‒0.77 27.88-57.73 Chilero
QWGC.haust-AC-3A.2 E3 237.00 AX-89583101-AX-109397508 5.98 10.64 ‒0.96 29.03-25.05 Chilero
BLUE 237.00 AX-89583101-AX-109397508 5.50 14.21 ‒0.62 29.03-25.05 Chilero
QWGC.haust-AC-3D.1 E1 96.00 AX-108729781-AX-110834100 5.91 16.34 ‒0.87 537.29-552.24 Chilero
QWGC.haust-AC-3D.2 E3 163.00 AX-110056468-AX-109831081 3.60 6.50 ‒0.74 349.68-342.70 Chilero
QWGC.haust-AC-4A E4 78.00 AX-110907767-AX-109440196 3.45 5.32 0.54 618.93-619.31 Avocet
QWGC.haust-AC-4B E3 24.00 AX-109986770-AX-110076607 5.11 9.22 ‒0.94 12.49-11.43 Chilero
QWGC.haust-AC-5D.1 E4 1.00 AX-108775585-AX-111011707 7.74 13.80 ‒0.83 556.11-547.81 Chilero
QWGC.haust-AC-5D.2 E4 76.00 AX-110476332-AX-109394742 7.62 13.32 ‒0.81 6.39-12.58 Chilero
QWGC.haust-AC-6A E3 42.00 AX-94591230-AX-111122628 9.39 17.62 1.22 38.47-71.43 Avocet
E4 42.00 AX-94591230-AX-111122628 4.05 6.24 0.54 38.47-71.43 Avocet
BLUE 42.00 AX-94591230-AX-111122628 7.65 20.45 0.74 38.47-71.43 Avocet
QWGC.haust-AC-6B E2 161.00 AX-109306114-AX-110400029 3.30 8.79 0.71 11.98-681.42 Avocet
SV QSV.haust-AC-1D E1 47.00 AX-111561523-AX-111535968 3.70 9.10 1.19 418.20-484.43 Avocet
QSV.haust-AC-2B.1 E4 134.00 AX-110064360-AX-111012832 5.19 7.22 ‒1.21 569.13-554.92 Chilero
QSV.haust-AC-2B.2 BLUE 94.00 AX-108837623-AX-89735721 4.69 11.69 ‒0.96 705.68-725.96 Chilero
QSV.haust-AC-3A.1 E2 278.00 AX-111543258-AX-111142459 3.17 10.27 ‒0.98 27.88-57.73 Chilero
QSV.haust-AC-3A.2 E3 236.00 AX-110520445-AX-89583101 3.10 9.30 ‒1.23 37.35-29.03 Chilero
BLUE 237.00 AX-89583101-AX-109397508 4.74 11.92 ‒0.98 29.03-25.05 Chilero
QSV.haust-AC-4B E3 24.00 AX-109986770-AX-110076607 3.52 10.64 ‒1.39 12.49-11.43 Chilero
QSV.haust-AC-6A.1 E1 42.00 AX-94591230-AX-111122628 5.50 13.30 1.21 38.47-71.43 Avocet
E2 42.00 AX-94591230-AX-111122628 3.46 9.92 0.94 38.47-71.43 Avocet
E3 42.00 AX-94591230-AX-111122628 4.70 14.38 1.52 38.47-71.43 Avocet
BLUE 42.00 AX-94591230-AX-111122628 5.91 15.09 1.09 38.47-71.43 Avocet
QSV.haust-AC-6A.2 E4 11.00 AX-111504079-AX-109974361 4.35 5.72 1.22 59.69-60.97 Avocet
QSV.haust-AC-7A.1 E4 173.00 AX-109473518-AX-109364614 8.14 11.43 ‒1.56 692.77-701.31 Chilero
QSV.haust-AC-7A.2 E4 204.00 AX-109947373-AX-111089494 11.07 16.16 1.78 731.14-708.47 Avocet
QSV.haust-AC-7B E1 17.00 AX-109306944-AX-95098493 5.07 12.30 1.17 54.79-708.12 Avocet
QSV.haust-AC-7D E2 55.00 AX-109301921-AX-111607406 2.68 7.56 ‒0.83 12.57-16.88 Chilero

表S2

AH群体籽粒品质相关性状的QTL"

性状
Trait		 QTL 环境
Environment		 遗传位置
Genetic position (cM)		 侧翼标记
Flanking marker		 LOD值
LOD value		 表型贡献率
PVE (%)		 加性效应
Additive		 物理区间
Physical interval (Mb)		 优势等位基因
Favorable allele
GPC QGPC.haust-AH-2A E6 800.00 DArT3958592-SNP1019498 3.16 5.98 ‒0.37 605.66-625.28 Huites
QGPC.haust-AH-2B.1 E7 647.00 DArT1128457-DArT3533008 4.24 9.29 ‒0.31 784.26-784.04 Huites
QGPC.haust-AH-2B.2 BLUE 242.00 DArT3021488-DArT1079407 2.64 5.44 ‒0.27 97.34-55.23 Huites
QGPC.haust-AH-3A.1 E5 530.00 DArT3064883-DArT1223327 5.61 15.48 ‒0.41 476.31-435.80 Huites
QGPC.haust-AH-3A.2 E6 581.00 DArT1254451-SNP980942 3.56 6.55 ‒0.39 46.17-46.00 Huites
QGPC.haust-AH-3A.3 E6 774.00 DArT3958575-DArT3946190 3.60 7.00 0.41 32.97-9.32 Avocet
QGPC.haust-AH-3A.4 E7 519.00 SNP1213892-SNP100357542 4.39 9.53 ‒0.31 521.30-544.19 Huites
QGPC.haust-AH-3A.5 BLUE 570.00 DArT100082954-DArT1013788 4.96 8.35 ‒0.34 60.01-54.94 Huites
QGPC.haust-AH-4D E7 25.00 DArT1107261-DArT1233229 2.71 5.34 ‒0.23 207.70-319.32 Huites
QGPC.haust-AH-5A.1 E5 394.00 SNP998276-SNP993328 3.41 9.48 0.32 569.66-570.19 Avocet
QGPC.haust-AH-5A.2 E6 117.00 DArT1205298-DArT1120172 3.76 7.03 ‒0.40 29.63-26.75 Huites
QGPC.haust-AH-6A.1 E6 363.00 SNP4910893-SNP1096119 4.98 10.15 0.54 76.63-77.89 Avocet
BLUE 364.00 SNP4910893-SNP1096119 6.99 12.26 0.45 76.63-77.89 Avocet
QGPC.haust-AH-6A.2 E7 313.00 DArT3946508-SNP1151487 4.81 11.45 0.41 586.30-202.91 Avocet
QGPC.haust-AH-6A.3 E7 431.00 SNP2358794-SNP1094001 2.83 6.23 ‒0.25 12.23-12.89 Huites
BLUE 426.00 DArT1233578-DArT4544113 3.51 5.84 ‒0.29 11.01-12.08 Huites
QGPC.haust-AH-7B BLUE 61.00 DArT1218440-SNP2253713 6.36 10.63 ‒0.38 1.38-1.44 Huites
WGC QWGC.haust-AH-1A BLUE 137.00 SNP1218247-DArT1665599 2.61 3.60 ‒0.48 500.84-499.81 Huites
QWGC.haust-AH-2A BLUE 394.00 SNP1240003-DArT2277504 4.36 8.01 ‒0.74 13.12-581.96 Huites
QWGC.haust-AH-2B E7 645.00 DArT1218607-DArT1128457 5.00 7.47 ‒0.65 776.57-234.76 Huites
QWGC.haust-AH-3A E7 519.00 SNP1213892-SNP100357542 6.70 9.47 ‒0.74 521.30-544.19 Huites
QWGC.haust-AH-3B BLUE 394.00 DArT1138136-DArT1695648 2.86 4.02 ‒0.50 123.60-113.98 Huites
QWGC.haust-AH-4D E5 63.00 DArT100270810-DArT1101297 3.80 12.80 ‒0.76 456.68-464.36 Huites
E7 75.00 DArT988923-DArT1111555 4.33 6.16 ‒0.59 469.43-479.62 Huites
BLUE 72.00 DArT1239874-DArT988923 5.08 7.57 ‒0.68 456.05-469.43 Huites
QWGC.haust-AH-5A BLUE 175.00 SNP4910949-DArT3941315 3.40 4.78 ‒0.55 415.19-430.25 Huites
QWGC.haust-AH-5B BLUE 242.00 DArT1100263-DArT1112093 6.61 9.71 0.78 658.56-658.45 Avocet
QWGC.haust-AH-5D E5 3.00 DArT3944272-DArT1695607 3.12 10.60 ‒0.71 5.79-25.49 Huites
E7 2.00 SNP1234827-DArT3944272 7.80 11.28 ‒0.81 4.36-5.79 Huites
BLUE 2.00 SNP1234827-DArT3944272 8.77 13.60 ‒0.94 4.36-5.79 Huites
QWGC.haust-AH-6A.1 E7 426.00 DArT1233578-DArT4544113 5.62 8.18 ‒0.70 11.01-12.08 Huites
QWGC.haust-AH-6A.2 E6 369.00 DArT3026247-DArT100000998 3.00 11.06 0.98 82.95-72.49 Avocet
E7 369.00 DArT3026247-DArT100000998 2.94 3.83 0.48 82.95-72.49 Avocet
QWGC.haust-AH-7B E7 61.00 DArT1218440-SNP2253713 6.32 8.79 ‒0.70 1.38-1.44 Huites
SV QSV.haust-AH-1A E7 123.00 DArT1207393-DArT4993415 2.60 8.90 ‒1.03 503.46-514.10 Huites
QSV.haust-AH-1B BLUE 825.00 SNP1090153-DArT3021227 3.04 8.08 ‒1.43 521.00-2.92 Huites
QSV.haust-AH-2B BLUE 29.00 SNP4988941-SNP1100485 2.59 9.29 ‒1.54 289.16-13.91 Huites
QSV.haust-AH-3B BLUE 150.00 SNP100526939-SNP4990292 3.03 5.61 ‒1.18 75.71-61.62 Huites
QSV.haust-AH-4A E6 664.00 DArT4537961-DArT1254189 3.04 7.98 ‒1.59 140.70-90.59 Huites
QSV.haust-AH-5D E7 0 SNP1234827-DArT3944272 3.54 11.89 ‒1.22 4.36-5.79 Huites
E5 4.00 DArT3944272-DArT1695607 4.22 9.91 ‒1.46 5.79-25.49 Huites
QSV.haust-AH-6A.1 E6 427.00 DArT1233578-DArT4544113 2.78 5.99 ‒1.41 11.01-12.08 Huites
QSV.haust-AH-6A.2 E6 365.00 SNP1096119-SNP100562777 6.33 14.90 2.93 77.89-138.23 Avocet
BLUE 364.00 SNP4910893-SNP1096119 3.81 6.90 1.43 76.63-77.89 Avocet
QSV.haust-AH-6B.1 E6 855.00 DArT3955224-SNP100542305 4.18 9.43 ‒1.75 298.01-715.70 Huites
QSV.haust-AH-6B.2 E5 53.00 DArT1159426-DArT4543423 3.59 10.77 ‒1.48 221.72-708.71 Huites
QSV.haust-AH-7B E5 75.00 SNP2253713-SNP2276097 2.81 15.01 ‒1.74 1.44-16.53 Huites

表2

两个F6 RIL群体QTL簇分析"

QTL簇
QTL cluster		 性状
Trait		 群体
Population		 QTL 连锁标记
Linkage marker		 平均LOD值
Average LOD value		 平均表型贡献率
Average PVE (%)		 环境
Environment		 优势等位基因
Favorable allele		 物理区间
Physical intervals (Mb)
C3A GPC/WGC/SV AC Pupulation QGPC.haust-AC-3A AX-111543258-AX-111142459 3.54 8.77 BLUE Chilero 9.32-60.01
AC Pupulation QWGC.haust-AC-3A.1 AX-111543258-AX-111142459 4.22 10.12 E2 Chilero
AC Pupulation QWGC.haust-AC-3A.2 AX-89583101-AX-109397508 5.74 12.43 E3/BLUE Chilero
AC Pupulation QSV.haust-AC-3A.1 AX-111543258-AX-111142459 3.17 10.27 E2 Chilero
AC Pupulation QSV.haust-AC-3A.2 AX-109397508-AX-110520445 3.92 10.61 E3/BLUE Chilero
AH Pupulation QGPC.haust-AH-3A.2 DArT1254451-SNP980942 3.56 6.55 E6 Huites
AH Pupulation QGPC.haust-AH-3A.3 DArT3958575-DArT3946190 3.60 7.00 E6 Avocet
AH Pupulation QGPC.haust-AH-3A.5 DArT100082954-DArT1013788 4.96 8.35 BLUE Huites
C3D GPG/WGC AC Pupulation QGPC.haust-AC-3D.1 AX-108729781-AX-110834100 8.83 13.98 E1 Chilero 537.29-552.24
AC Pupulation QWGC.haust-AC-3D.1 AX-108729781-AX-110834100 5.91 16.34 E1 Chilero
C4B WGC/SV AC Pupulation QWGC.haust-AC-4B AX-109986770-AX-110076607 5.11 9.22 E3 Chilero 11.43-12.49
AC Pupulation QSV.haust-AC-4B AX-109986770-AX-110076607 3.52 10.64 E3 Chilero
C5D WGC/SV AC Pupulation QWGC.haust-AC-5D.2 AX-110476332-AX-109394742 7.62 13.32 E4 Chilero 4.36-25.49
AH Pupulation QWGC.haust-AH-5D SNP1234827-DArT1695607 6.56 11.83 E5/E7/BLUE Huites
AH Pupulation QSV.haust-AH-5D SNP1234827-DArT1695607 3.88 10.90 E5/E7 Huites
C6A.1 GPC/WGC/SV AH Pupulation QGPC.haust-AH-6A.3 DArT1233578-SNP1094001 3.17 6.04 E7/BLUE Huites 11.01-12.89
AH Pupulation QWGC.haust-AH-6A.1 DArT1233578-DArT4544113 5.62 8.18 E7 Huites
AH Pupulation QSV.haust-AH-6A.1 DArT1233578-DArT4544113 2.78 5.99 E6 Huites
C6A.2 GPC/WGC/SV AC Pupulation QGPC.haust-AC-6A.1 AX-109042664-AX-108939533 5.10 9.42 E1/E4 Avocet 38.47-82.95
AC Pupulation QGPC.haust-AC-6A.2 AX-94591230-AX-111122628 9.33 21.79 E3/BLUE Avocet
AC Pupulation QWGC.haust-AC-6A AX-94591230-AX-111122628 7.03 14.77 E3/E4/BLUE Avocet
AC Pupulation QSV.haust-AC-6A.1 AX-94591230-AX-111122628 4.89 13.17 E1/E2/E3/BLUE Avocet
AC Pupulation QSV.haust-AC-6A.2 AX-111504079-AX-109974361 4.35 5.72 E4 Avocet
AH Pupulation QGPC.haust-AH-6A.1 SNP4910893-SNP1096119 5.99 11.21 E6/BLUE Avocet
AH Pupulation QWGC.haust-AH-6A.2 DArT3026247-DArT100000998 2.97 7.45 E6/E7 Avocet
AH Pupulation QSV.haust-AH-6A.2 SNP4910893-SNP1096119 3.81 6.90 BLUE Avocet
C7B GPC/WGC/SV AH Pupulation QGPC.haust-AH-7B DArT1218440-SNP2253713 6.36 10.63 BLUE Huites 1.38-16.53
AH Pupulation QWGC.haust-AH-7B DArT1218440-SNP2253713 6.32 8.79 E7 Huites
AH Pupulation QSV.haust-AH-7B SNP2253713-SNP2276097 2.81 15.01 E5 Huites

图3

在两个RIL群体中关于籽粒蛋白质含量、湿面筋含量和沉降值的QTL簇 两条染色体上的蓝色区段表示QTL的物理区间, 实心矩形表示优势等位基因来自父本Chilero或Huites, 空心矩形表示优势等位基因来自母本Avocet。用不同的颜色表示来自不同群体不同性状的QTL。"

表S3

筛选获得的候选基因信息"

QTL簇
QTL cluster		 基因
Gene		 物理位置
Physical position (bp)		 基因注释
Gene annotation		 表达部位
expression location
C3A TraesCS3A02G027500 14764482-14766910 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G028600 15294546-15298077 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 籽粒 Grain
TraesCS3A02G028800 15302528-15304140 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 籽粒 Grain
TraesCS3A02G029300 15477245-15478646 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G029500 15603607-15604989 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G030000 15779481-15780912 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G031400 17257262-17258628 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G032200 17621292-17623525 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 穗部 Spike
TraesCS3A02G073400 45592602-45603876 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 籽粒 Grain
TraesCS3A02G077900 50382036-50384496 含NAC结构域的蛋白质 NAC domain-containing protein 籽粒 Grain
TraesCS3A02G079200 51280020-51291788 泛素家族蛋白 Ubiquitin family protein 籽粒 Grain
C6A.2 TraesCS6A02G086800 555455195-55550804 E3泛素蛋白连接酶 E3 ubiquitin-protein ligase 籽粒 Grain
TraesCS6A02G087100 55709408-55710595 多泛素 Polyubiquitin 籽粒 Grain
TraesCS6A02G089000 57680849-57684135 核糖体生物发生调节蛋白样蛋白 Ribosome biogenesis regulatory protein-like protein 籽粒 Grain
TraesCS6A02G108300 77097709-77100361 含NAC结构域的蛋白质，推定 NAC domain-containing protein, putative 叶部 Leaf
TraesCS6A02G112400 81257411-81259132 多泛素 Polyubiquitin 籽粒 Grain

表3

KASP分子标记引物序列"

KASP标记
KASP tag		 引物
Primer		 引物序列
Primer sequence (5′-3′)
CGPC-6A-KASP-1 通用反向引物
Universal reverse primers		 CCT TAT GCG CCA ATC TTT TAT ACA
特异性正向引物
Specific forward primers		 GAA GGT GAC CAA GTT CAT GCT TAG GGA GGC GTC CGT GGA A
GAA GGT CGG AGT CAA CGG ATT TAG GGA GGC GTC CGT GGA C
CGPC-6A-KASP-2 通用反向引物
Universal reverse primers		 GCA TGG TAA TTG CAT ACA CGG G
特异性正向引物
Specific forward primer		 GAA GGT GAC CAA GTT CAT GCT GCA TAA GGG CCA CTC ACA TAA C
GAA GGT CGG AGT CAA CGG ATT GCA TAA GGG CCA CTC ACA TAA T

图4

CGPC-6A-KASP-1 (a)和CGPC-6A-KASP-2 (b)在自然群体的等位基因分离及效应分析 黑色表示空白对照; 图4-a中橙色表示A等位基因, 蓝色表示C等位基因; 图4-b中橙色表示C等位基因, 蓝色表示T等位基因; E8和E9分别表示自然群体在2020-2021年和2021-2022年种植于河南科技大学农学院试验田; *和**分别表示在P < 0.05和P < 0.01水平差异显著。"

表4

前人研究在3A、4D、5D和6A染色体上检测到的籽粒品质相关性状QTL"

性状
Trait		 染色体
Chr.		 QTL 连锁标记
Linkage marker		 物理位置
Physical position (Mb)		 平均表型贡献率
Average PVE (%)		 参考文献
Reference
GPC 6A QGpc.uhw-6A wsnp_Ex_c15268_23489498 535.52-583.20 — [15]
6A QGpc-6A-2 D-1112857-S-2362461 51.40-64.18 10.15 [16]
6A qGPC.XX-6A.1 AX-110368218-AX-110368140 595.06-595.18 4.19 [18]
6A QNGPC.cau-6A — 63.00-83.00 4.07 [44]
6A — BS00046964_51 4.42 [45]
WGC 3A QWGC.hau-3A.1 AX-111674404-AX-109456846 739.32-740.02 1.98 [17]
3A QLWGC.cau-3A.1 wsnp_BE426222A_Ta_2_1 191.53 2.77 [44]
3A QLWGC.cau-3A.2 wsnp_Ku_c44089_51445136 401.71 3.92 [44]
3A QLWGC.cau-3A.3 BobWhite_c28464_814 484.64 3.06 [44]
3A QNWGC.cau-3A BS00078430_51 374.87 3.40 [44]
4D qWGC.XX-4D.1 AX-109282550-AX-110572006 16.43-19.18 12.50 [18]
5D QWGC.hau-5D.1 AX-109684926-AX-109455090 98.26-100.94 3.06 [17]
6A QWGC.hau-6A.1 AX-109418600-AX-110992859 547.81-549.05 4.42 [17]
6A QWGC.hau-6A.2 AX-111504079-AX-109418640 59.69-81.31 6.92 [17]
6A QNWGC.cau-6A — 73.00-83.00 3.98 [44]
6A — BS00046964_51 4.42 — [45]
SV 3A Qsdss-3A AX-110439700-AX-109956297 580.2-649.4 2.47 [46]
5D Qsdss-5D INDEL1489469-INDEL8181683 1.50-8.20 8.11 [46]
6A QSv-6A-2.1 wPt-731556-D-3952327 50.35-50.34 13.34 [16]
6A QSv-6A-2.2 D-1112857-D-1092061 51.40-63.19 11.08 [16]
6A QSV.hau-6A.1 AX-109843320-AX-111089021 8.61-14.39 11.57 [17]
6A QSV.hau-6A.2 AX-109934181-AX-110547197 580.32-598.05 12.18 [17]
[1] Shiferaw B, Smale M, Braun H J, Duveiller E, Reynolds M, Muricho G. Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Secur, 2013, 5: 291-317.
[2] 韩文燕, 王凤成, 魏雪, 王晓玲. 小麦分级改善小麦及小麦粉品质的研究. 河南工业大学学报(自然科学版), 2022, 43(4): 85-91.
Han W Y, Wang F C, Wei X, Wang X L. Study on improving the quality of wheat and wheat flour by wheat grading. J Henan Univ Technol (Nat Sci Edn), 2022, 43(4): 85-91 (in Chinese with English abstract).
[3] Hernández Z J E, Figueroa J D C, Rayas-Duarte P, Martínez-Flores H E, Arámbula G V, Luna G B, Peña R J. Influence of high and low molecular weight glutenins on stress relaxation of wheat kernels and the relation to sedimentation and rheological properties. J Cereal Sci, 2012, 55: 344-350.
[4] 李晓丽, 姜兰芳, 马小飞, 王敏, 曹勇, 郝建宇, 张定一, 姬虎太. 基于主成分分析的强筋小麦加工品质综合评价. 麦类作物学报, 2022, 42: 1473-1483.
Li X L, Jiang L F, Ma X L, Wang M, Cao Y, Hao J Y, Zhang D Y, Ji H T. Comprehensive processing quality evaluation of strong gluten wheat based on principal component analysis. J Triticeae Crops, 2022, 42: 1473-1483 (in Chinese with English abstract).
[5] 沈业松, 王歆, 顾正中, 杨子博, 詹秋文. 296份黄淮麦区小麦品种资源在江苏淮北地区的品质分析. 浙江农业学报, 2018, 30: 1617-1623.
doi: 10.3969/j.issn.1004-1524.2018.10.01
Shen Y S, Wang X, Gu Z Z, Yang Z B, Zhan Q W. Quality analysis of 296 wheat varieties from the Huang-Huai wheat region planted in Huaibei area of Jiangsu. Acta Agric Zhejiangensis, 2018, 30: 1617-1623 (in Chinese with English abstract).
doi: 10.3969/j.issn.1004-1524.2018.10.01
[6] 李桂萍, 张根生, 巴青松, 张改生. 杂种小麦品质性状的性状相关和主成分分析. 浙江农业学报, 2016, 28: 1447-1453.
doi: 10.3969/j.issn.1004-1524.2016.09.01
Li G P, Zhang G S, Ba Q S, Zhang G S. Correlation analysis and principal component analysis on quality traits in hybrid wheat. Acta Agric Zhejiangensis, 2016, 28: 1447-1453 (in Chinese with English abstract).
[7] Ma M, Li Y, Xue C, Xiong W, Peng Z, Han X, Ju H, He Y. Current situation and key parameters for improving wheat quality in China. Front Plant Sci, 2021, 12: 638525.
[8] 黄梦豪, 刘天相, 强琴琴, 李春莲, 王中华. 基于SNP和SSR标记的小麦品质性状的QTL定位. 分子植物育种, 2019, 17: 3966-3973.
Hang M H, Liu T X, Qiang Q Q, Li C L, Wang Z H. QTL mapping of wheat quality traits based on SNP and SSR markers. Mol Plant Breed, 2019, 17: 3966-3973 (in Chinese with English abstract).
[9] Li J, Cui F, Ding A M, Zhao C H, Wang X Q, Wang L, Bao Y G, Qi X L, Li X F, Gao J R, Feng D S, Wang H G. QTL detection of seven quality traits in wheat using two related recombinant inbred line populations. Euphytica, 2012, 183: 207-226.
[10] Huang X Q, Cloutier S, Lycar L, Radovanovic N, Humphreys D G, Noll J S, Somers D J, Brown P D. Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.). Theor Appl Genet, 2006, 113: 753-766.
doi: 10.1007/s00122-006-0346-7 pmid: 16838135
[11] Doerge R W. Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet, 2002, 3: 43-52.
doi: 10.1038/nrg703 pmid: 11823790
[12] Echeverry-Solarte M, Kumar A, Kianian S, Simsek S, Alamri M S, Mantovani E E, McClean P E, Deckard E L, Elias E, Schatz B, Xu S S, Mergoum M. New QTL alleles for quality-related traits in spring wheat revealed by RIL population derived from supernumerary × non-supernumerary spikelet genotypes. Theor Appl Genet, 2015, 128: 893-912.
doi: 10.1007/s00122-015-2478-0 pmid: 25740563
[13] 胡文静, 裔新, 李东升, 张春梅, 高德荣, 张勇. 扬麦13/C615重组自交系籽粒蛋白质含量和硬度性状QTL分析. 麦类作物学报, 2021, 41: 930-936.
Hu W J, Yi X, Li D S, Zhang C M, Gao D R, Zhang Y. Genetic analysis and QTL mapping for grain protein content and grain hardness using the RIL population of Yangmai 13/C615. J Triticeae Crops, 2021, 41: 930-936 (in Chinese with English abstract).
[14] 郭利建, 王竹林, 汪世娟, 刘振华, 刘香利, 胡胜武, 赵惠贤. 基于SRAP和SSR标记的小麦品质相关性状的QTL定位. 麦类作物学报, 2016, 36: 1275-1282.
Guo L J, Wang Z L, Wang S J, Liu Z H, Liu X L, Hu S W, Zhao H X. QTL mapping of wheat grain quality traits based on SRAP and SSR marker. J Triticeae Crops, 2016, 36: 1275-1282 (in Chinese with English abstract).
[15] Fatiukha A, Filler N, Lupo I, Lidzbarsky G, Klymiuk V, Korol A B, Pozniak C, Fahima T, Krugman T. Grain protein content and thousand kernel weight QTLs identified in a durum × wild emmer wheat mapping population tested in five environments. Theor Appl Genet, 2020, 133: 119-131.
doi: 10.1007/s00122-019-03444-8 pmid: 31562566
[16] Guo Y, Zhang G, Guo B, Qu C, Zhang M, Kong F, Zhao Y, Li S. QTL mapping for quality traits using a high-density genetic map of wheat. PLoS One, 2020, 15: e0230601.
[17] 王姗. 小麦面团拉伸特性和淀粉特性相关性状的QTL定位. 河南农业大学硕士学位论文, 河南郑州, 2023.
Wang S. QTL Mapping for Traits Related to Dough Tensile Characteristics and Starch Characteristics of Wheat. MS Thesis of Henan Agricultural University, Zhengzhou, Henan, China, 2023 (in Chinese with English abstract).
[18] 周锋. 基于两个群体对小麦籽粒性状及其稳定性和品质性状的QTL分析. 西北农林科技大学硕士学位论文, 陕西咸阳, 2022.
Zhou F. QTL Analysis of Grain Traits and Stability Quality Traits of Wheat Based on Two RILs Populations. MS Thesis of Northwest Agriculture & Forestry University, Xianyang, Shaanxi, China, 2022 (in Chinese with English abstract).
[19] Kumar A, Jain S, Elias E M, Ibrahim M, Sharma L K. An overview of QTL identification and marker-assisted selection for grain protein content in wheat. In: Sengar R S, Ashu S, eds. Eco-Friendly Agro-biological Techniques for Enhancing Crop Productivity. Singapore: Springer Singapore Pte. 2018. pp 245-274.
[20] Uauy C, Distelfeld A, Fahima T, Blechl A, Dubcovsky J. A NAC gene regulating senescence improves grain protein, Zinc, and Iron content in wheat. Science, 2006, 314: 1298-1301.
doi: 10.1126/science.1133649 pmid: 17124321
[21] Jin X, Feng B, Xu Z, Fan X, Liu J, Liu Q, Zhu P, Wang T. TaAAP6-3B, a regulator of grain protein content selected during wheat improvement. BMC Plant Biol, 2018, 18: 71.
doi: 10.1186/s12870-018-1280-y pmid: 29685104
[22] Gadaleta A, Nigro D, Giancaspro A, Blanco A. The glutamine synthetase (GS2) genes in relation to grain protein content of durum wheat. Funct Integr Genom, 2011, 11: 665-670.
[23] Ravel C, Martre P, Romeuf I, Dardevet M, El-Malki R, Bordes J, Duchateau N, Brunel D, Balfourier F, Charmet G. Nucleotide polymorphism in the wheat transcriptional activator Spa influences its pattern of expression and has pleiotropic effects on grain protein composition, dough viscoelasticity, and grain hardness. Plant Physiol, 2009, 151: 2133-2144.
[24] Guo D, Hou Q, Zhang R, Lou H, Li Y, Zhang Y, You M, Xie C, Liang R, Li B. Over-expressing TaSPA-B reduces prolamin and starch accumulation in wheat (Triticum aestivum L.) grains. Int J Mol Sci, 2020, 21: 3257.
[25] Gao Y, An K, Guo W, Chen Y, Zhang R, Zhang X, Chang S, Vincenzo R, Jin F, Cao X, Xin M, Peng H, Hu Z, Guo W, Du J, Ni Z, Sun Q, Yao Y. The endosperm-specific transcription factor TaNAC019 regulates glutenin and starch accumulation and its elite allele improves wheat grain quality. Plant Cell, 2021, 33: 603-622.
[26] Li J, Xie L, Tian X, Liu S, Xu D, Jin H, Song J, Dong Y, Zhao D, Li G, Li Y, Zhang Y, Zhang Y, Xia X, He Z, Cao S. TaNAC100 acts as an integrator of seed protein and starch synthesis exerting pleiotropic effects on agronomic traits in wheat. Plant J, 2021, 108: 829-840.
[27] Shen L, Luo G, Song Y, Xu J, Ji J, Zhang C, Gregová E, Yang W, Li X, Sun J, Zhan K, Cui D, Liu D, Zhang A. A novel NAC family transcription factor SPR suppresses seed storage protein synthesis in wheat. Plant Biotechn J, 2021, 19: 992-1007.
[28] Jiang P, Zhang P, Wu L, He Y, Li C, Ma H, Zhang X. Linkage and association mapping and Kompetitive allele-specific PCR marker development for improving grain protein content in wheat. Theor Appl Genet, 2021, 134: 3563-3575.
doi: 10.1007/s00122-021-03913-z pmid: 34374830
[29] Sun L J, Liu M L, Xu L L, Li X F, Mao X D. Wheat sedimentation value determination based on Near Infrared Spectroscopy. Adv Mater Res, 2013, 605: 996-1000.
[30] 陈峰, 何中虎, 崔党群, 赵武善, 张艳, 王德森. 利用近红外透射光谱技术测定小麦品质性状的研究. 麦类作物学报, 2003, 23: 1-4.
Chen F, He Z H, Cui D Q, Zhao W S, Zhang Y, Wang D S. Measurement of wheat quality traits by Near Infrared Transmittance Spectrometer. J Triticeae Crops, 2003, 23: 1-4 (in Chinese with English abstract).
[31] 陈泠, 王文学, 陶越, 佟汉文. 近红外法测定小麦品质的准确性分析. 农业科学, 2020, 10(12): 5.
Chen L, Wang W X, Tao Y, Tong H W. Accuracy analysis of quality characteristics by near-infrared spectrometer. J Agric Sci, 2020, 10(12): 5 (in Chinese with English abstract).
[32] Wang Y, Zeng Z, Li J, Zhao D, Zhao Y, Peng C, Lan C, Wang C. Identification and validation of new quantitative trait loci for spike-related traits in two RIL populations. Mol Breed, 2023, 43: 64.
[33] Mccouch S, Cho Y, Yano M, Paul E, Blinstrub M, Morishima H, McCouch S R, Cho Y G, Yano M, Kinosita T. Report on QTL nomenclature. Rice Genet Newsl, 1997, 14: 11-13.
[34] Luo Q, Zheng Q, Hu P, Liu L, Yang G, Li H, Li B, Li Z. Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population. Theor Appl Genet, 2021, 134: 171-189.
[35] Ma S, Wang M, Wu J, Guo W, Chen Y, Li G, Wang Y, Shi W, Xia G, Fu D, Kang Z, Ni F. WheatOmics: a platform combining multiple omics data to accelerate functional genomics studies in wheat. Mol Plant, 2021, 14: 1965-1968.
doi: 10.1016/j.molp.2021.10.006 pmid: 34715393
[36] Zeng Z, Guo C, Yan X, Song J, Wang C, Xu X, Hao Y. QTL mapping and KASP marker development for seed vigor related traits in common wheat. Front Plant Sci, 2022, 13: 994973.
[37] Ren P, Zhao D, Zeng Z, Yan X, Zhao Y, Lan C, Wang C. Pleiotropic effect analysis and marker development for grain zinc and iron concentrations in spring wheat. Mol Breed, 2022, 42: 49.
[38] Avni R, Zhao R, Pearce S, Jun Y, Uauy C, Tabbita F, Slade A, Dubcovsky J, Distelfeld A. Functional characterization of GPC-1 genes in hexaploid wheat. Planta, 2014, 239: 313-324.
doi: 10.1007/s00425-013-1977-y pmid: 24170335
[39] Harrington S A, Overend L E, Cobo N, Borrill P, Uauy C. Conserved residues in the wheat (Triticum aestivum) NAM-A1 NAC domain are required for protein binding and when mutated lead to delayed peduncle and flag leaf senescence. BMC Plant Biol, 2019, 19: 407.
doi: 10.1186/s12870-019-2022-5 pmid: 31533618
[40] Zhang G, Chen R Y, Shao M, Bai G, Seabourn B W. Genetic analysis of end-use quality traits in wheat. Crop Sci, 2020, 61: 1709-1723.
[41] Gao L, Meng C, Yi T, Xu K, Cao H, Zhang S, Yang X, Zhao Y. Genome-wide association study reveals the genetic basis of yield-and quality-related traits in wheat. BMC Plant Biol, 2021, 21: 144.
doi: 10.1186/s12870-021-02925-7 pmid: 33740889
[42] Kumari P, De N, Kumari A K A. Genetic variability, correlation and path coefficient analysis for yield and quality traits in wheat (Triticum aestivum L.). Int J Curr Microb Appl Sci, 2020, 9: 826-832.
[43] 张平平, 姚金保, 王化敦, 宋桂成, 姜朋, 张鹏, 马鸿翔. 江苏省优质软麦品种品质特性与饼干加工品质的关系. 作物学报, 2020, 46: 491-502.
doi: 10.3724/SP.J.1006.2020.91050
Zhang P P, Yao J B, Wang H D, Song G C, Jiang P, Zhang P, Ma H X. Soft wheat quality traits in Jiangsu province and their relationship with cookie making quality. Acta Agron Sin, 2020, 46: 491-502 (in Chinese with English abstract).
[44] Lou H, Zhang R, Liu Y, Guo D, Zhai S, Chen A, Zhang Y, Xie C, You M, Peng H, Liang R, Ni Z, Sun Q, Li B. Genome-wide association study of six quality-related traits in common wheat (Triticum aestivum L.) under two sowing conditions. Theor Appl Genet, 2021, 134: 399-418.
[45] Chen J, Zhang F, Zhao C, Lv G, Sun C, Pan Y, Guo X, Chen F. Genome-wide association study of six quality traits reveals the association of the TaRPP13L1 gene with flour colour in Chinese bread wheat. Plant Biotechnol J, 2019, 17: 2106-2122.
[46] Chang S, Chen Q, Yang T, Li B, Xin M, Su Z, Du J, Guo W, Hu Z, Liu J, Peng, H, Ni Z, Sun Q, Yao Y. Pinb-D1p is an elite allele for improving end-use quality in wheat (Triticum aestivum L.). Theor Appl Genet, 2022, 135: 4469-4481.
[47] Würschum T, Leiser W L, Kazman E, Longin C F H. Genetic control of protein content and sedimentation volume in European winter wheat cultivars. Theor Appl Genet, 2016, 129: 1685-1696.
doi: 10.1007/s00122-016-2732-0 pmid: 27225454
[48] 马冬云, 张艳, 夏先春, Morris C F, 何中虎. Puroindoline b位点近等基因系对小麦面粉及面包和馒头品质的影响. 作物学报, 2010, 36: 261-266.
doi: 10.3724/SP.J.1006.2010.00261
Ma D Y, Zhang Y, Xia X C, Morris C F, He Z H. Wheat flour, pan bread, and steamed bread qualities of common wheat near- isogenic lines differing in Puroindoline b alleles. Acta Agron Sin, 2010, 36: 261-266 (in Chinese with English abstract).
[49] Boehm J J D, Ibba M I, Kiszonas A, See D R, Skinner D Z, Morris C F. Identification of genotyping-by-sequencing sequence tags associated with milling performance and end-use quality traits in hard red spring wheat (Triticum aestivum L.). J Cereal Sci, 2017, 77: 73-83.
[50] Balyan H S, Gahlaut V, Kumar A, Jaiswal V, Dhariwal R, Tyagi S, Agarwal P, Kumari S, Gupta P K. Nitrogen and phosphorus use efficiencies in wheat: physiology, phenotyping, genetics, and breeding. Plant Breed Rev, 2016, 40: 167-234.
[51] Nigro D, Fortunato S, Giove S L, Paradiso A, Gu Y Q, Blanco A, Pinto A C D, Gadaleta A. Glutamine synthetase in durum wheat: genotypic variation and relationship with grain protein content. Front Plant Sci, 2016, 7: 971.
doi: 10.3389/fpls.2016.00971 pmid: 27468287
[52] Xu F Q, Xue H W. The ubiquitin-proteasome system in plant responses to environments. Plant Cell Environ, 2019, 42: 2931-2944.
[53] 陆海燕, 周玲, 林峰, 王蕊, 王凤格, 赵涵. 基于高通量测序开发玉米高效KASP分子标记. 作物学报, 2019, 45: 872-878.
doi: 10.3724/SP.J.1006.2019.83067
Lu H Y, Zhou L, Lin F, Wang R, Wang F G, Zhao H. Development of efficient KASP molecular markers based on high throughput sequencing in maize. Acta Agron Sin, 2019, 45: 872-878 (in Chinese with English abstract).
[54] 胡文静, 李东升, 裔新, 张春梅, 张勇. 小麦穗部性状和株高的QTL定位及育种标记开发和验证. 作物学报, 2022, 48: 1346-1356.
doi: 10.3724/SP.J.1006.2022.11055
Hu W J, Li D S, Yi X, Zhang C M, Zhang Y. Molecular mapping and validation of quantitative trait loci for spike-related traits and plant height in wheat. Acta Agron Sin, 2022, 48: 1346-1356 (in Chinese with English abstract).
[55] 杨青青, 唐家琪, 张昌泉, 高继平, 刘巧泉. KASP标记技术在主要农作物中的应用及展望. 生物技术通报, 2022, 38(4): 58-71.
doi: 10.13560/j.cnki.biotech.bull.1985.2021-1378
Yang Q Q, Tang J Q, Zhang C Q, Gao J P, Liu Q Q. Application and prospect of KASP marker technology in main crops. Biotechnol Bull, 2022, 38: 58-71 (in Chinese with English abstract).
[1] 彭小爱, 卢茂昂, 张玲, 刘童, 曹磊, 宋有洪, 郑文寅, 何贤芳, 朱玉磊. 基于55K SNP芯片的小麦籽粒主要品质性状的全基因组关联分析[J]. 作物学报, 2024, 50(8): 1948-1960.
[2] 高维东, 胡城祯, 张龙, 张艳艳, 张沛沛, 杨德龙, 陈涛. 小麦泛素结合酶TaUBC16基因的克隆与功能分析[J]. 作物学报, 2024, 50(8): 1971-1988.
[3] 梁进宇, 尹嘉德, 侯慧芝, 薛云贵, 郭宏娟, 王硕, 赵绮志, 张绪成, 谢军红. 干旱条件下深施肥对春小麦旗叶生态化学计量特征及其光合碳同化的影响[J]. 作物学报, 2024, 50(8): 2078-2090.
[4] 陈娟, 杨婷婷, 闫素辉, 雍玉东, 张士雅, 李文阳. 拔节期渍水对软质小麦淀粉粒度分布与糊化特性的影响[J]. 作物学报, 2024, 50(7): 1877-1884.
[5] 方宇辉, 齐学礼, 李艳, 张煜, 彭超军, 华夏, 陈艳艳, 郭瑞, 胡琳, 许为钢. 强光胁迫对转玉米C4型ZmPEPC+ZmPPDK基因小麦光合和生理特性的影响[J]. 作物学报, 2024, 50(7): 1647-1657.
[6] 韩丽, 汤胜胜, 李佳, 胡海斌, 刘龙龙, 吴斌. 燕麦SNP高密度遗传图谱构建及β-葡聚糖含量QTL定位[J]. 作物学报, 2024, 50(7): 1710-1718.
[7] 秦娜, 叶珍言, 朱灿灿, 付森杰, 代书桃, 宋迎辉, 景雅, 王春义, 李君霞. 谷子籽粒类黄酮含量和粒色的QTL定位[J]. 作物学报, 2024, 50(7): 1719-1727.
[8] 张智源, 周界光, 刘家君, 王素容, 王同著, 赵聪豪, 尤佳宁, 丁浦洋, 唐华苹, 刘燕林, 江千涛, 陈国跃, 魏育明, 马建. 基于遗传解析新模式的小麦寡分蘖QTL的鉴定和验证[J]. 作物学报, 2024, 50(6): 1373-1383.
[9] 郑雪晴, 王兴荣, 张彦军, 龚佃明, 邱法展. 玉米果穗相关性状QTL定位及重要候选基因分析[J]. 作物学报, 2024, 50(6): 1435-1450.
[10] 朱明昆, 包俊浩, 庞菁璐, 周诗绮, 方忠艳, 郑文, 张亚洲, 吴丹丹. 纤毛鹅观草-普通小麦高抗条锈病多年生属间杂种F1的创制及鉴定[J]. 作物学报, 2024, 50(6): 1406-1420.
[11] 乔志新, 张杰道, 王雨, 郭启芳, 刘燕静, 陈蕊, 胡文浩, 孙爱清. 干旱胁迫下冬小麦不同品种萌发特性差异的研究[J]. 作物学报, 2024, 50(6): 1568-1583.
[12] 马艳明, 娄鸿耀, 王威, 孙娜, 颜国荣, 张胜军, 刘杰, 倪中福, 徐麟. 新疆冬小麦籽粒品质性状遗传差异与关联分析[J]. 作物学报, 2024, 50(6): 1394-1405.
[13] 陈家婷, 白欣, 谷雨杰, 张潇文, 郭慧娟, 常利芳, 陈芳, 张树伟, 张晓军, 李欣, 冯瑞云, 畅志坚, 乔麟轶. 小麦芽期和苗期耐盐鉴定方法的适用性评价[J]. 作物学报, 2024, 50(5): 1193-1206.
[14] 陆汝华, 王文轩, 曹强, 田永超, 朱艳, 曹卫星, 刘小军. 稻麦复种模式下氮肥与稻秸互作对小麦产量和N2O排放影响及推荐施肥研究[J]. 作物学报, 2024, 50(5): 1300-1311.
[15] 许乃银, 金石桥, 晋芳, 刘丽华, 徐剑文, 刘丰泽, 任雪贞, 孙全, 许栩, 庞斌双. 基于SNP标记的小麦品种遗传相似度及其检测准确度分析[J]. 作物学报, 2024, 50(4): 887-896.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 邢光南, 周斌, 赵团结, 喻德跃, 邢邯, 陈受宜, 盖钧镒. 大豆抗筛豆龟蝽Megacota cribraria (Fabricius)的QTL分析[J]. 作物学报, 2008, 34(03): 361 -368 .
[2] 吕丽华;陶洪斌;夏来坤; 张雅杰; 赵明; 赵久然;王璞. 不同种植密度下的夏玉米冠层结构及光合特性[J]. 作物学报, 2008, 34(03): 447 -455 .
[3] 黄策;王天铎. 水稻群体物质生产过程的计算机模拟[J]. 作物学报, 1986, (01): 1 -8 .
[4] 周录英;李向东;王丽丽;汤笑;林英杰. 钙肥不同用量对花生生理特性及产量和品质的影响[J]. 作物学报, 2008, 34(05): 879 -885 .
[5] 勾玲;黄建军;张宾;李涛;孙锐;赵明. 群体密度对玉米茎秆抗倒力学和农艺性状的影响[J]. 作物学报, 2007, 33(10): 1688 -1695 .
[6] 韩锁义;张恒友;杨玛丽;赵团结;盖钧镒;喻德跃. 大豆“南农86-4”突变体筛选及突变体库的构建[J]. 作物学报, 2007, 33(12): 2059 -2062 .
[7] 郑昀晔;曹栋栋;张胜;关亚静;胡晋. 多胺对玉米种子吸胀期间耐冷性和种子发芽能力的影响[J]. 作物学报, 2008, 34(02): 261 -267 .
[8] 戴忠民;尹燕枰;张敏;李文阳;闫素辉;蔡瑞国;王振林. 旱作和灌溉条件下小麦籽粒淀粉粒粒度的分布特征[J]. 作物学报, 2008, 34(05): 795 -802 .
[9] 李霞;刘友良;焦德茂. 不同高产水稻品种叶片的荧光参数的日变化和光适应特性的关系[J]. 作物学报, 2002, 28(02): 145 -153 .
[10] 靳忠英;彭正松;李育明;王梅. 半夏的光合特性[J]. 作物学报, 2006, 32(10): 1542 -1548 .
京ICP备15008789号-2