数量性状主基因+多基因混合遗传分析R软件包SEA v2.0

doi:10.3724/SP.J.1006.2022.14088

Abstract

Abstract:

The phenotypic values for quantitative trait from bi-parental segregation populations can be used to identify its mixed major genes plus polygenes inheritance model, which provides important information for the genetic basis of quantitative traits and crop breeding. To comprehensively summarize the research results of methodological advances, add the new functions of the software and correct its shortcomings in previous versions, an R software package SEA v2.0 with interactive graphical user interface is developed under R studio-1.4.1103 platform and R environment. In this software, there were 14 types of bi-parental segregation populations, and each type included four modules: data input, data analysis, posterior probability calculation, and distribution curve drawing. To save running time, doParallel was used to conduct parallel computing, data.table was used to quickly read and write datasets, and MASS was used to estimate the parameters in component distributions. KScorrect, kolmim, and shiny packages were used to simplify the programs. As long as users uploaded the data file with *.csv format and set the related parameters, the results could be quickly displayed. The software was validated by real data analysis of soybean podding habit and Monte Carlo simulation studies, and can be downloaded from https://cran.r-project.org/web/packages/SEA/index.html.

Key words: bi-parental segregation population, quantitative trait, mixed major genes plus polygenes inheritance model, R software, SEA

WANG Jing-Tian, ZHANG Ya-Wen, DU Ying-Wen, REN Wen-Long, LI Hong-Fu, SUN Wen-Xian, GE Chao, ZHANG Yuan-Ming. SEA v2.0: an R software package for mixed major genes plus polygenes inheritance analysis of quantitative traits[J].Acta Agronomica Sinica, 2022, 48(6): 1416-1424.

Figures/Tables 5

Table 1

Table 2

Genetic models and their codes in software SEA v2.0"

类别 Type	主基因 Major genes	多基因 Polygenes	模型代号 Model code
类别 Type	主基因 Major genes	多基因 Polygenes	主基因 Only major genes	主基因+多基因 Major gene & polygenes
多基因		加性-显性-上位性ADE		PG-ADI
Polygenes		加性-显性 AD		PG-AD
1对主基因	加性-显性 AD	加性-显性-上位性ADE	1MG-AD	MX1-AD-ADI
One MG	加性-显性 AD	加性-显性 AD	1MG-AD	MX1-AD-AD
	加性 A	加性-显性 AD	1MG-A	MX1-A-AD
	加性 A	加性-上位性 AE	1MG-A	MX1-A-AI
	加性 A	加性 A	1MG-A	MX1-A-A
	完全显性 CD	加性-显性 AD	1MG-EAD	MX1-EAD-AD
	负向完全显性 NCD	加性-显性 AD	1MG-NCD	MX1-NCD-AD
2对主基因	加性-显性-上位性 ADE	加性-显性-上位性 ADE	2MG-ADI	MX2-ADI-ADI
Two MGs	加性-显性-上位性 ADE	加性-显性 AD	2MG-ADI	MX2-ADI-AD
	加性-显性 AD	加性-显性 AD	2MG-AD	MX2-AD-AD
	加性 A	加性-显性 AD	2MG-A	MX2-A-AD
	加性 A	加性 A	2MG-A	MX2-A-A
	加性-上位性 AE	加性-上位性 AE	2MG-AI	MX2-AI-AI
	加性-上位性 AE	加性 A	2MG-AI	MX2-AI-A
	等加性 EA	加性-显性 AD	2MG-EA	MX2-EA-AD
	等加性 EA	加性 A	2MG-EA	MX2-EA-A
2对主基因	显性上位 DE1	加性 A	2MG-ED	MX2-ED-A
Two MGs	隐性上位 RE	加性 A	2MG-ER	MX2-ER-A
	累加作用 CE1	加性 A	2MG-AE	MX2-AE-A
	互补作用 CE2	加性 A	2MG-CE	MX2-CE-A
	重叠作用 DE2	加性 A	2MG-DE	MX2-DE-A
	抑制作用 IE	加性 A	2MG-IE	MX2-IE-A
	完全显性 CD	加性-显性 AD	2MG-CD	MX2-CD-AD
	等显性 ED	加性-显性 AD	2MG-EAD	MX2-EAD-AD
3对主基因	加性-上位性 AE	加性-上位性 AE	3MG-AI	MX3-AI-AI
Three MGs	加性-上位性 AE	加性 A	3MG-AI	MX3-AI-A
	加性 A	加性 A	3MG-A	MX3-A-A
	等加性 EA	加性 A	3MG-CEA	MX3-CEA-A
	部分等加性 PEA	加性 A	3MG-PEA	MX3-PEA-A
4对主基因	加性-上位性 AE		4MG-AI
Four MGs	等加性 EA		4MG-CEA
	部分等加性1 PEA1		4MG-EEA
	部分等加性2 PEA2		4MG-EEEA

Table 2

Fig. 1

Fig. 2

Table 3

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群体类型 Population type	缩写 Abbreviation	文件列名 Column name	参考文献 Reference	群体类型 Population type	缩写 Abbreviation	文件列名 Column name	参考文献 Reference
F₂	SEA-F2	F2	[12, 13]	P₁, F₁, P₂, F_2:3	SEA-G4F3	P1, F1, P2, F23	[16]
F_2:3	SEA-F3	F23	[14]	P₁, P₂, DH	SEA-G3DH	P1, P2, DH	[15]
DH/RIL	SEA-DH	DH	[15]	P₁, F₁, P₂ B₁, B₂	SEA-G5BC	P1, F1, P2, B1, B2	[17]
BIL	SEA-BIL	BIL	[11]	P₁, F₁, P₂, B_1:2, B_2:2	SEA-G5BCF	P1, F1, P2, B12, B22	[17]
B₁, B₂	SEA-BC	B1, B2	[13]	P₁, F₁, P₂, F₂, F_2:3	SEA-G5	P1, F1, P2, F2, F23	[18, 19]
B_1:2, B_2:2	SEA-BCF	B12, B22	[11]	P₁, F₁, P₂, F₂, B₁, B₂	SEA-G6	P1, F1, P2, F2, B1, B2	[20, 21]
P₁, F₁, P₂, F₂	SEA-G4F2	P1, F1, P2, F2	[16]	P₁, F_1, P₂, F_2:3, B_1:2, B_2:2	SEA-G6F	P1, F1, P2, F23, B12, B22	[22]

模型 Model	统计量 Statistic	平均数 Mean (m)	加性效应1 Additive (d_a)	加性效应2 Additive (d_b)	显性效应1 Dominant (h_a)	显性效应2 Dominant (h_b)	误差方差 Residual variance	主基因遗传方差 MG variance	B₁主基因遗传率 MG heritability in B₁ (%)	功效 Power (%)
1MG-AD	参数真值 TVP	100.00	10.00		3.68		10.00	10.00	50.00	92.00
	估计值±标准差 Estimates ± SD	99.97±0.17	9.97±0.09		3.69±0.20		9.96±0.58	10.02±1.31	49.99±3.77
	平均差 AD	0.14	0.07		0.15		0.48	1.04	3.02
2MG-ADI	参数真值 TVP	10.00	7.07	3.16	14.14	6.32	10.00	15.00	60.00	90.00
	估计值±标准差 Estimates ± SD	101.59±1.77	7.90±1.23	2.25±1.24	11.05±1.83	6.45±1.82	9.64±0.80	12.34±1.29	56.07±3.41
	平均差 AD	1.76	1.08	1.11	3.09	1.63	0.71	2.71	4.36
PG-ADI	参数真值 TVP	100.00					10.00			100.00
	估计值±标准差 Estimates ± SD	100.32±0.28					9.59±1.34
	平均差 AD	0.35					1.18
MX1-AD-ADI	参数真值 TVP	100.00	10.00		17.07		10.00	12.50	50.00	99.00
	估计值±标准差 Estimates ± SD	115.24±0.36	10.05±0.15		17.06±0.26		9.47±0.76	12.31±1.41	54.40±4.20
	平均差 AD	15.24	0.13		0.21		0.73	1.13	5.25
MX2-ADI-ADI	参数真值 TVP	100.00	7.07	3.16	14.14	6.32	10.00	15.00	60.00	79.00
	估计值±标准差 Estimates ± SD	102.06±2.41	7.06±1.10	7.06±1.10	8.79±2.88	4.06±2.99	9.82±1.14	13.04±3.78	47.27±13.16
	平均差 AD	2.51	0.87	3.90	5.41	2.93	0.91	3.29	14.01

SEA v2.0: an R software package for mixed major genes plus polygenes inheritance analysis of quantitative traits

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