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Acta Agronomica Sinica ›› 2021, Vol. 47 ›› Issue (6): 1100-1108.doi: 10.3724/SP.J.1006.2021.04138


Genetic analysis of fat content based on nested populations in peanut (Arachis hypogaea L.)

HUANG Bing-Yan1(), SUN Zi-Qi1, LIU Hua1, FANG Yuan-Jin1, SHI Lei1, MIAO Li-Juan1, ZHANG Mao-Ning1, ZHANG Zhong-Xin1, XU Jing1, ZHANG Meng-Yuan2, DONG Wen-Zhao1, ZHANG Xin-You1,*()   

  1. 1Henan Academy of Crops Molecular Breeding, Henan Academy of Agricultural Sciences/Graduate R & T Base of Zhengzhou University/Key Laboratory of Oil Crops in Huang-Huai-Hai Plans, Ministry of Agriculture and Rural Affairs/Henan Provincial Key Laboratory for Oil Crops Improvement, Zhengzhou 450002, Henan, China
    2College of Agriculture, Henan University of Science and Technology, Luoyang 471023, Henan, China
  • Received:2020-06-24 Accepted:2020-12-01 Online:2021-06-12 Published:2020-12-30
  • Contact: ZHANG Xin-You E-mail:huangbingyan@aliyun.com;haasz@126.com
  • Supported by:
    The China Agricultural Research System(CARS-13);The Henan Agricultural Research System(2016-05);The Key Scientific and Technological Project of Henan Province(201300111000)


Nested populations can be used to dissect the heredity of complex traits. The genetic models of fat content of F2:3 families in nested combinations with one common parent and six founder parents were analyzed, aiming to detect the genetic differences among the founders and to provide bases for breeding strategy for fat content improvement in peanut kernels. The common parent was Yuhua 15, an irregular-type variety with high fat content, and the other six founder parents were different botanical varieties with different fat contents. The results showed that the genetic model of fat content traits was different in different combinations. Six crosses were in accordance with three genetic patterns, including none major gene model, one major gene model with additive and dominant effect, and two major genes model with equal additive and dominant effect. The estimated values of various genetic effects were also different. The heritability of the main genes ranged from 32% to 80%, indicating that the gene loci controlling the fat content and their segregation patterns were different in different F2:3 populations. There were more individuals with high fat content in the offspring from combinations with both parents of high fat content. However, the heritability was low and phenotypic selections for fat content were not suggested in the early generations in such combinations. The offspring from combinations with parents of significantly different fat content had a larger variation range in fat content, and phenotypes with variable fat content were available. In this study, the large variances in the nested populations demonstrated the genetic complexity of fat content and the characteristics of multi major gene regulation. These results provide a comprehensive base for understanding the genetics and regulation of fat content, and the nested populations will be helpful in further QTL detection of fat content in peanut.

Key words: peanut (Arachis hypogaea L.), nested populations, fat content, F2:3 family, inheritance model

Table 1

Information of the nested crossing populations"

Population code
Cross combination
Number of F2:3 family
AC 远杂9102×豫花15号 Yuanza 9102×Yuhua 15 472
BC 中花6号×豫花15号 Zhonghua 6×Yuhua 15 392
CE 豫花15号×粤油20 Yuhua 15×Yueyou 20 286
CF 豫花15号×四粒红 Yuhua 15×Silihong 395
CG 豫花15号×伏花生 Yuhua 15×Fuhuasheng 256
CH 豫花15号×NC94022 Yuhua 15×NC94022 269

Fig. 1

Distribution of fat content in F2 population"

Table 2

Analysis of genetic model of fat content"

Cross combination
Maximum likelihood value
AIC value
AC 1对主基因加性显性 1MG-AD -944.2088 1896.418
无主基因 0MG -946.4774 1896.955
1对主基因负向完全显性 1MG-NCD -944.7637 1897.527
2对主基因等加性 2MG-EA -946.4752 1898.950
BC 2对主基因等显性 2MG-EAD -729.4342 1464.868
1对主基因加性显性 1MG-AD -728.9680 1465.936
无主基因 0MG -731.3869 1466.774
1对主基因完全显性 1MG-EAD -729.4457 1466.891
CE 2对主基因等显性 2MG-EAD -521.0105 1048.021
1对主基因加性显性 1MG-AD -520.7663 1049.533
2对主基因完全显性 2MG-CD -521.1385 1050.277
1对主基因完全显性 1MG-EAD -521.1419 1050.284
CF 无主基因 0MG -719.3989 1442.798
2对主基因等显性 2MG-EAD -718.5605 1443.121
2对主基因等加性 2MG-EA -719.3983 1444.797
1对主基因加性 1MG-A -719.4056 1444.811
CG 2对主基因等显性 2MG-EAD -547.5336 1101.067
1对主基因加性显性 MG-AD -548.7668 1105.534
2对主基因完全显性 2MG-CD -548.9751 1105.950
1对主基因完全显性 1MG-EAD -548.9754 1105.951
CH 无主基因 0MG -565.0724 1134.145
2对主基因等显性 2MG-EAD -564.9840 1135.968
2对主基因等加性 2MG-EA -565.0737 1136.147
1对主基因加性 1MG-A -565.0762 1136.152

Table 3

Fitness test for genetic models"

U12 PU12 U22 PU22 U32 PU32 nW2 PnW2 Dn PDn
AC 1对主基因加性显性 1MG-AD 0.0539 0.8164 0.4283 0.5128 2.9528 0.0857 0.1785 0.3143 0.0467 0.2480
无主基因 0MG 0.4265 0.5137 1.0459 0.3064 2.4383 0.1184 0.2416 0.2045 0.0506 0.1718
1对主基因负向完全显性 1MG-NCD 0.1073 0.7432 0.5637 0.4528 3.0078 0.0829 0.1927 0.2835 0.0483 0.2129
2对主基因等加性 2MG-EA 0.4274 0.5132 1.0343 0.3091 2.3592 0.1245 0.2394 0.2074 0.0504 0.1755
BC 2对主基因等显性 2MG-EAD 0.0536 0.8169 0.0023 0.9615 1.1869 0.2760 0.0736 0.738 0.0334 0.7598
1对主基因加性显性 1MG-AD 0.0248 0.8749 0.0097 0.9216 1.0076 0.3155 0.0586 0.8246 0.0326 0.7864
无主基因 0MG 0.3584 0.5494 0.1334 0.7150 0.7358 0.3910 0.1308 0.4576 0.0391 0.5727
1对主基因完全显性 1MG-EAD 0.0516 0.8202 0.0021 0.9637 1.1286 0.2881 0.0688 0.7650 0.0334 0.7615
U12 PU12 U22 PU22 U32 PU32 nW2 PnW2 Dn PDn
CE 2对主基因等显性 2MG-EAD 0.0580 0.8097 0.0003 0.9863 0.7465 0.3876 0.0662 0.7798 0.0336 0.8915
1对主基因加性显性 1MG-AD 0.0241 0.8766 0.0019 0.9655 0.6001 0.4385 0.0419 0.9229 0.0271 0.9812
2对主基因完全显性 2MG-CD 0.0462 0.8298 0 0.9999 0.6924 0.4053 0.0521 0.8641 0.0303 0.9479
1对主基因完全显性 1MG-EAD 0.0465 0.8293 0 0.9994 0.6927 0.4052 0.0521 0.8638 0.0304 0.9474
CF 无主基因 0MG 0.2154 0.6426 0.0247 0.8752 1.3671 0.2423 0.0934 0.6303 0.0341 0.7341
2对主基因等显性 2MG-EAD 0.0791 0.7785 0.0018 0.9660 1.5871 0.2077 0.0770 0.7192 0.0354 0.6928
2对主基因等加性 2MG-EA 0.2156 0.6424 0.0271 0.8692 1.2986 0.2545 0.0918 0.6386 0.0338 0.7446
1对主基因加性 1MG-A 0.2160 0.6421 0.0272 0.8691 1.3008 0.2541 0.0919 0.6379 0.0338 0.7440
CG 2对主基因等显性 2MG-EAD 0 0.9982 0.0006 0.9809 0.0109 0.9168 0.0299 0.9766 0.0329 0.9352
1对主基因加性显性 1MG-AD 0.0051 0.9428 0.0186 0.8914 0.0720 0.7885 0.0430 0.9170 0.0284 0.9821
2对主基因完全显性 2MG-CD 0.0024 0.9609 0.0212 0.8841 0.1546 0.6942 0.0444 0.9094 0.0291 0.9772
1对主基因完全显性 1MG-EAD 0.0024 0.9608 0.0213 0.8841 0.1543 0.6945 0.0444 0.9094 0.0291 0.9778
CH 无主基因 0MG 0.0062 0.9374 0.0148 0.9033 0.6243 0.4295 0.1133 0.5313 0.0546 0.3845
2对主基因等显性 2MG-EAD 0.0009 0.9765 0.0263 0.8712 0.5813 0.4458 0.1173 0.5131 0.0549 0.3795
2对主基因等加性 2MG-EA 0.0061 0.9379 0.0128 0.9100 0.5685 0.4509 0.1122 0.5362 0.0542 0.3951
1对主基因加性 1MG-A 0.0061 0.9377 0.0128 0.9101 0.5694 0.4505 0.1122 0.5362 0.0542 0.3949

Table 4

Estimation of genetic parameters of fat content"

m da db ha hb Var.mg hmg
AC 1对主基因加性显性 1MG-AD 57.5201 1.1342 -2.3266 1.0357 31.9936
无主基因 0MG
1对主基因负向完全显性 1MG-NCD 57.2576 1.2970 0.9789 30.2396
2对主基因等加性 2MG-EA 56.9106 0.2372 0.0660 2.0382
BC 2对主基因等显性 2MG-EAD 55.5452 0.9807 1.1551 47.1385
1对主基因加性显性 1MG-AD 55.4744 1.0402 2.1944 0.8997 36.7188
无主基因 0MG
1对主基因完全显性 1MG-EAD 55.7181 1.2259 0.8773 35.8046
CE 2对主基因等显性 2MG-EAD 54.0134 1.0075 1.2100 52.9489
1对主基因加性显性 1MG-AD 53.9686 1.0950 2.1686 0.9448 41.3432
2对主基因完全显性 2MG-CD 54.1576 1.2797 0.1270 0.9596 41.9920
1对主基因完全显性 1MG-EAD 54.1894 1.2796 0.9498 41.5652
CF 无主基因 0MG
2对主基因等显性 2MG-EAD 53.6370 0.7674 0.7028 31.3534
2对主基因等加性 2MG-EA 54.0267 0.2282 0.0604 2.6958
1对主基因加性 1MG-A 54.0290 0.2888 0.0494 2.2052
m da db ha hb Var.mg hmg
CG 2对主基因等显性 2MG-EAD 51.6018 1.6437 3.6377 79.7548
1对主基因加性显性 1MG-AD 51.8983 2.3225 1.5772 2.9822 65.3833
2对主基因完全显性 2MG-CD 51.7690 2.1335 0.1047 2.7537 60.3730
1对主基因完全显性 1MG-EAD 51.7952 2.1334 2.7468 60.2228
CH 无主基因 0MG
2对主基因等显性 2MG-EAD 53.8575 0.7166 0.6290 16.0300
2对主基因等加性 2MG-EA 54.2152 0.3550 0.1469 3.7446
1对主基因加性 1MG-A 54.2168 0.4650 0.1280 3.2625
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