遗传学报
遺傳學報
유전학보
ACTA GENETICA SINICA
2006年
7期
607-616
,共10页
数量性状位点%生物学产量%干草产量%谷粒产量%上位性%水稻
數量性狀位點%生物學產量%榦草產量%穀粒產量%上位性%水稻
수량성상위점%생물학산량%간초산량%곡립산량%상위성%수도
quantitative trait locus (QTL)%biomass yield%straw yield%grain yield%epistasis%rice (Oryza sativa L.)
QTL的加性效应、加性×加性上位性效应及它们与环境的互作效应是数量性状的重要遗传分量.利用IR64/Azucena的125个DH品系为群体,分析了水稻生物学产量及其两个构成性状干草产量和谷粒产量的遗传组成.用基于混合模型的复合区间作图(MCIM)方法进行QTL定位.检测到12个位点有加性主效应,27个位点涉及双位点互作,18个位点存在环境互作.结果表明水稻生物学产量和它的两个构成性状普遍存在上位性效应和QE互作效应.此外,还探讨了性状间相关的遗传基础.发现4个QTLs和一对上位性QTLs可能与生物学产量与干草产量之间的正相关有关.3个QTL可能与干草产量与谷粒产量之间的负相关有关.这些结果可能部分地解释了这3个性状相关的遗传原因.通过对水稻生物学产量及其两个构成性状所定位QTL的分析,加深了对数量性状QTL的认识.首先,QTL的上位性效应和QE互作效应是普遍存在的;其次,QTL的多效性或紧密连锁可能是遗传相关的原因,当QTL对两个性状作用的方向相同时可导致正向遗传相关,反之则为负向遗传相关,当有些QTL表现为同向作用而另一些QTL表现为反向作用时,则可削弱性状间的遗传相关性;第三,复合性状的QTL效应可分解为其组成性状的QTL效应,如果QTL对各组成性状的效应方向相反而相互抵消,可使复合性状的QTL效应不易被检测;第四,加性效应的QTL常参预构成上位性效应,而具有上位性效应的QTL并非都有加性主效应,表明忽略上位性的QTL定位方法会降低检测QTL的功效;最后,鉴别不同类型的QTL效应有利于指导育种实践,选择主效QTL适用于多环境,QE互作QTL适用于特定环境,对上位性QTL应强调选择基因组合而并非单个基因.
QTL的加性效應、加性×加性上位性效應及它們與環境的互作效應是數量性狀的重要遺傳分量.利用IR64/Azucena的125箇DH品繫為群體,分析瞭水稻生物學產量及其兩箇構成性狀榦草產量和穀粒產量的遺傳組成.用基于混閤模型的複閤區間作圖(MCIM)方法進行QTL定位.檢測到12箇位點有加性主效應,27箇位點涉及雙位點互作,18箇位點存在環境互作.結果錶明水稻生物學產量和它的兩箇構成性狀普遍存在上位性效應和QE互作效應.此外,還探討瞭性狀間相關的遺傳基礎.髮現4箇QTLs和一對上位性QTLs可能與生物學產量與榦草產量之間的正相關有關.3箇QTL可能與榦草產量與穀粒產量之間的負相關有關.這些結果可能部分地解釋瞭這3箇性狀相關的遺傳原因.通過對水稻生物學產量及其兩箇構成性狀所定位QTL的分析,加深瞭對數量性狀QTL的認識.首先,QTL的上位性效應和QE互作效應是普遍存在的;其次,QTL的多效性或緊密連鎖可能是遺傳相關的原因,噹QTL對兩箇性狀作用的方嚮相同時可導緻正嚮遺傳相關,反之則為負嚮遺傳相關,噹有些QTL錶現為同嚮作用而另一些QTL錶現為反嚮作用時,則可削弱性狀間的遺傳相關性;第三,複閤性狀的QTL效應可分解為其組成性狀的QTL效應,如果QTL對各組成性狀的效應方嚮相反而相互牴消,可使複閤性狀的QTL效應不易被檢測;第四,加性效應的QTL常參預構成上位性效應,而具有上位性效應的QTL併非都有加性主效應,錶明忽略上位性的QTL定位方法會降低檢測QTL的功效;最後,鑒彆不同類型的QTL效應有利于指導育種實踐,選擇主效QTL適用于多環境,QE互作QTL適用于特定環境,對上位性QTL應彊調選擇基因組閤而併非單箇基因.
QTL적가성효응、가성×가성상위성효응급타문여배경적호작효응시수량성상적중요유전분량.이용IR64/Azucena적125개DH품계위군체,분석료수도생물학산량급기량개구성성상간초산량화곡립산량적유전조성.용기우혼합모형적복합구간작도(MCIM)방법진행QTL정위.검측도12개위점유가성주효응,27개위점섭급쌍위점호작,18개위점존재배경호작.결과표명수도생물학산량화타적량개구성성상보편존재상위성효응화QE호작효응.차외,환탐토료성상간상관적유전기출.발현4개QTLs화일대상위성QTLs가능여생물학산량여간초산량지간적정상관유관.3개QTL가능여간초산량여곡립산량지간적부상관유관.저사결과가능부분지해석료저3개성상상관적유전원인.통과대수도생물학산량급기량개구성성상소정위QTL적분석,가심료대수량성상QTL적인식.수선,QTL적상위성효응화QE호작효응시보편존재적;기차,QTL적다효성혹긴밀련쇄가능시유전상관적원인,당QTL대량개성상작용적방향상동시가도치정향유전상관,반지칙위부향유전상관,당유사QTL표현위동향작용이령일사QTL표현위반향작용시,칙가삭약성상간적유전상관성;제삼,복합성상적QTL효응가분해위기조성성상적QTL효응,여과QTL대각조성성상적효응방향상반이상호저소,가사복합성상적QTL효응불역피검측;제사,가성효응적QTL상삼예구성상위성효응,이구유상위성효응적QTL병비도유가성주효응,표명홀략상위성적QTL정위방법회강저검측QTL적공효;최후,감별불동류형적QTL효응유리우지도육충실천,선택주효QTL괄용우다배경,QE호작QTL괄용우특정배경,대상위성QTL응강조선택기인조합이병비단개기인.
Additive effects, additive by additive epistatic effects, and their environmental interactions of QTLs are important genetic components of quantitative traits. Genetic architecture underlying rice biomass yield and its two component traits (straw yield and grain yield) were analyzed for a population of 125 DH lines from an inter-subspecific cross of IR64/Azucena. The mixed-model based composite interval mapping approach (MCIM) was used to detect QTLs, There were 12 QTLs detected with additive main effects, 27 QTLs involved in digenic interaction with aa and/or aae effects, and 18 QTLs affected by environments with ae and/or aae effects. It was revealed that epistatic effects and QE interaction effects existed on biomass yield and its component traits in rice. In addition, the genetic basis of relationships among these traits were investigated. Four QTLs and one pair of epistatic QTLs were detected to be responsible for the positive correlation between biomass yield and straw yield. Three QTLs might be responsible for the negative correlation between straw yield and grain yield. This result could partially explain the genetic basis of correlation among the three traits, and provide useful information for genetic improvement of these traits by marker-assisted selection.
