作物学报
作物學報
작물학보
ACTA AGRONOMICA SINICA
2013年
2期
258-268
,共11页
闫宁%谢尚潜%耿青春%徐宇%李广军%刘兵%汪霞%李其刚%章元明*
閆寧%謝尚潛%耿青春%徐宇%李廣軍%劉兵%汪霞%李其剛%章元明*
염저%사상잠%경청춘%서우%리엄군%류병%왕하%리기강%장원명*
大豆%籽粒大小和形状%上位性%主效QTL%QTL×环境互作%QTL×细胞质互作%Bayes分层广义线性模型
大豆%籽粒大小和形狀%上位性%主效QTL%QTL×環境互作%QTL×細胞質互作%Bayes分層廣義線性模型
대두%자립대소화형상%상위성%주효QTL%QTL×배경호작%QTL×세포질호작%Bayes분층엄의선성모형
Soybean%Seed size and shape traits%Main-effect QTL%Epistasis%QTL-by-environment interaction%QTL-by-cyto-plasm interaction%Bayes hierarchical generalized linear model
以溧水中子黄豆(P1)和南农493-1(P2)组合的504个正反交F2:3~F2:7家系群体为材料,调查大豆粒长、粒宽、粒厚、长宽比、长厚比、宽厚比和百粒重性状在2007—2011年的表型观测值,扫描 F2群体 SSR 分子标记信息,用Bayes 分层广义线性模型方法检测了上述性状的主效 QTL、QTL×环境(QE)互作、QTL×细胞质(QC)互作和QTL×QTL(QQ)互作.共检测到89个主效QTL、33对QE、20对QC和35对QQ互作.上述7个性状的主效QTL分别有7、10、10、19、19、17和7个;QQ互作分别有1、10、6、0、6、9和3对,没有检测到显性×显性互作;QE互作分别有5、7、6、3、6、2和4对; QC互作分别有2、1、3、8、4、2和0对.主效、QQ互作、QC互作和QE互作QTL的总贡献率分别为12.42%~61.79%、0~23.21%、0.35%~1.51%和0~14.16%,表明主效QTL贡献最大, QQ互作次之, QE互作最小.各类QTL都有一因多效现象,同一基因座可通过不同方式影响性状表达.这些结果揭示了大豆粒形性状的遗传基础,为标记辅助育种提供了参考信息.
以溧水中子黃豆(P1)和南農493-1(P2)組閤的504箇正反交F2:3~F2:7傢繫群體為材料,調查大豆粒長、粒寬、粒厚、長寬比、長厚比、寬厚比和百粒重性狀在2007—2011年的錶型觀測值,掃描 F2群體 SSR 分子標記信息,用Bayes 分層廣義線性模型方法檢測瞭上述性狀的主效 QTL、QTL×環境(QE)互作、QTL×細胞質(QC)互作和QTL×QTL(QQ)互作.共檢測到89箇主效QTL、33對QE、20對QC和35對QQ互作.上述7箇性狀的主效QTL分彆有7、10、10、19、19、17和7箇;QQ互作分彆有1、10、6、0、6、9和3對,沒有檢測到顯性×顯性互作;QE互作分彆有5、7、6、3、6、2和4對; QC互作分彆有2、1、3、8、4、2和0對.主效、QQ互作、QC互作和QE互作QTL的總貢獻率分彆為12.42%~61.79%、0~23.21%、0.35%~1.51%和0~14.16%,錶明主效QTL貢獻最大, QQ互作次之, QE互作最小.各類QTL都有一因多效現象,同一基因座可通過不同方式影響性狀錶達.這些結果揭示瞭大豆粒形性狀的遺傳基礎,為標記輔助育種提供瞭參攷信息.
이률수중자황두(P1)화남농493-1(P2)조합적504개정반교F2:3~F2:7가계군체위재료,조사대두립장、립관、립후、장관비、장후비、관후비화백립중성상재2007—2011년적표형관측치,소묘 F2군체 SSR 분자표기신식,용Bayes 분층엄의선성모형방법검측료상술성상적주효 QTL、QTL×배경(QE)호작、QTL×세포질(QC)호작화QTL×QTL(QQ)호작.공검측도89개주효QTL、33대QE、20대QC화35대QQ호작.상술7개성상적주효QTL분별유7、10、10、19、19、17화7개;QQ호작분별유1、10、6、0、6、9화3대,몰유검측도현성×현성호작;QE호작분별유5、7、6、3、6、2화4대; QC호작분별유2、1、3、8、4、2화0대.주효、QQ호작、QC호작화QE호작QTL적총공헌솔분별위12.42%~61.79%、0~23.21%、0.35%~1.51%화0~14.16%,표명주효QTL공헌최대, QQ호작차지, QE호작최소.각류QTL도유일인다효현상,동일기인좌가통과불동방식영향성상표체.저사결과게시료대두립형성상적유전기출,위표기보조육충제공료삼고신식.
Seed size and shape traits in soybean play a crucial role in yield and appearance quality. In this study, an experiment was performed to detect main-effect quantitative trait loci (MQTL), QTL-by-environment (QE), QTL-by-cytoplasm (QC), and QTL-by-QTL (QQ) interactions for the soybean seed traits (length, width, thickness, length-to-width, length-to-thickness, width-to-thickness, and 100-seed weight) using Bayes hiearchical generalized linear model approach. Evaluation of these traits for the 504 F2:3–F2:7 families from the direct and reciprocal crosses of Lishuizhongzihuangdou × Nannong 493-1 was carried out in 2007–2011, respectively, and the 504 F2 plants were scanned by 152 SSR markers. As a result, a total of 89 MQTL, 35 QQ inter-actions, 33 QE interactions and 20 QC interactions were detected. As for the above seven traits, there were 7, 10, 10, 19, 19, 17, and 7 MQTL;1, 10, 6, 0, 6, 9, and 3 QQ interactions;5, 7, 6, 3, 6, 2, and 4 QE interactions;and 2, 1, 3, 8, 4, 2, and 0 QC interac-tions respectively. The total proportion of phenotypic variance explained by the above four types of QTL for each trait is 12.42–61.79%, 0–23.21%, 0.35–1.51%, and 0–14.16%, respectively, indicating that the most important genetic component is MQTL, the second one is epistasis, and the last one is QE interaction. Pleiotropic effects were observed in all kinds of QTL, while various types of QTL shared with one same locus were found to be response for a seed trait as well. These results revealed genetic basis of seed size and shape traits in soybean, and provide reference information for marker assisted breeding.