杂种优势利用.pdf

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Vol.94,pp.9226–9231,August1997

Genetics

Importance of epistasis as the genetic basis of heterosis in an elite rice hybrid

(hybrid vigor?molecular markers?quantitative trait loci?interaction between loci)

S.B.Y U*,J.X.L I*,C.G.X U*,Y.F.T AN*,Y.J.G AO*,X.H.L I*,Q IFA Z HANG*?,AND M.A.S AGHAI M AROOF?

*National Key Laboratory of Crop Genetic Improvement,Huazhong Agricultural University,Wuhan430070,China;and?Department of Crop and Soil Environmental Sciences,Virginia Polytechnic Institute and State University,Blacksburg,VA24061

Communicated by R.W.Allard,University of California,Davis,CA,June3,1997(received for review March6,1997)

ABSTRACT The genetic basis of heterosis was investi-gated in an elite rice hybrid by using a molecular linkage map with150segregating loci covering the entire rice genome.Data for yield and three traits that were components of yield were collected over2years from replicated field trials of250F2:3 families.Genotypic variations explained from about50%to more than80%of the total variation.Interactions between genotypes and years were small compared with the main effects.A total of32quantitative trait loci(QTLs)were detected for the four traits;12were observed in both years and the remaining20were detected in only one year.Overdomi-nance was observed for most of the QTLs for yield and also for a few QTLs for the component traits.Correlations between marker heterozygosity and trait expression were low,indicat-ing that the overall heterozygosity made little contribution to heterosis.Digenic interactions,including additive by additive, additive by dominance,and dominance by dominance,were frequent and widespread in this population.The interactions involved large numbers of marker loci,most of which indi-vidually were not detectable on single-locus basis;many interactions among loci were detected in both years.The results provide strong evidence that epistasis plays a major role as the genetic basis of heterosis.

The two earliest hypotheses regarding heterosis,both pro-posed in1908—i.e.,the dominance hypothesis(1)and the overdominance hypothesis(2,3)—have competed for most of this century(4).However,pertinent data allowing for critical assessments of these hypotheses remained largely unavailable until very recently with the advent of discretely recognizable mendelian markers such as allozymes,restriction fragment length polymorphisms(RFLPs),and more recently high-density molecular linkage maps.Stuber et al.(5),who analyzed the genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines,observed that heterozygotes of almost all the quantitative trait loci(QTLs)for yield had higher phenotypic values than the respective homozygotes.They suggested that both overdominance and QTLs detected by single-locus analysis play a significant role in heterosis.On the other hand,Xiao et al.(6),who conducted an inheritance study of quantitative traits in an intersubspecific cross of rice, suggested that dominance may be the genetic basis of heterosis in rice.Both of the dominance and overdominance hypotheses are based only on single-locus theory.

Wright(7)visualized a‘‘net-like’’structure of population genotypes such that the variations of most characters are affected by many loci and that each gene replacement may have effects on many characters.Based on this perspective, epistasis should be one of the most important genetic com-ponents in the inheritance of quantitative https://www.sodocs.net/doc/c418030271.html,ing morphological markers marking small chromosome segments, Fasoulas and Allard(8)showed that epistasis was responsible for a major part of the total genetic variance for seven of the eight characters studied in crosses between near isogenic lines of cultivated barley.Population genetic analyses have also established that epistasis,functioning to assemble and main-tain favorable multilocus genotypes,is a major mechanism of adaptation in various plant species(9).Surprisingly,however, little evidence for epistasis has been indicated in the recent data from molecular marker-based studies of yield and yield-associated characters,although epistasis has been observed in characters such as plant height in soybean,nitrogen-fixing ability in rice,and seed size in legumes(10–13).Thus,the significance of epistasis in the expression of heterosis in relation to hybrid performance has yet to be established. Rice is the staple food for a large segment of the world population.The success of hybrid rice breeding,together with saturated molecular linkage maps(14,15)and relatively small genome size of this species,has provided a rare opportunity for dissecting the genetic basis of heterosis in elite rice hybrids.In the study reported in this paper,we investigated,at both single-locus and two-locus levels,the genetic components conditioning the inheritance of yield and yield component traits in one of the most heterotic crosses.The main objective was to characterize the genetic basis of heterosis in this hybrid with the long-term goal of manipulating the genome for hybrid rice improvement.

MATERIALS AND METHODS Experimental Population and Field Data Collection.The experimental population consisted of250F3families,each derived from bagged seeds of a single F2plant,from a cross between Zhenshan97and Minghui63.These two lines are the parents of Shanyou63,which is the best hybrid in China,with an annual acreage of6.7million hectares in the last decade and accounting for approximately25%of the rice production of China.The F3families,two parents,and F1were transplanted to a bird-net-equipped field in the experimental farm of Huazhong Agricultural University in the1994and1995rice-growing seasons in Wuhan,China.The field planting followed a randomized complete block design with three replications. For each family within a replication,seedlings approximately 35days old were transplanted to a single-row plot,with distance of17cm between plants within a row,and the rows were27cm apart.The field management followed essentially the normal agricultural practice.Each plant was harvested

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Abbreviations:QTL,quantitative trait locus;LOD,logarithm of odds;

RFLP,restriction fragment length polymorphism;AA,additive by additive interaction;AD,additive by dominance interaction;DA, dominance by additive interaction;DD,dominance by dominance interaction.

?To whom reprint requests should be addressed.e-mail:qifazh@ https://www.sodocs.net/doc/c418030271.html,.

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individually at maturity to prevent loss from over-ripening.Only the 15plants in the middle of each row were used for scoring.Traits examined included yield per plant,which was converted to metric tons ?hectare (t ?ha),tillers per plant scored as the number of seed-setting tillers per plant,grain weight as the weight (g)of 1,000seeds,and grains per panicle.DNA Markers and Laboratory Assay.Leaf tissues were harvested either from single F 2plants or from bulks of at least 20plants from each of the F 3families.Exactly 8g of leaf tissue per sample was ground to fine powder under liquid nitrogen.Total cellular DNA was extracted using the protocol of Murray and Thompson (16).

Two classes of markers were employed to assay DNA polymorphisms in this population:RFLPs and simple se-quence repeats.RFLP analysis followed the method described by Liu et al.(17).For surveying parental polymorphisms,DNA samples from each of the two parents were digested with six restriction enzymes and probed with a total of 537clones from Cornell University and the Japanese Rice Genome Research Project (14,15).Fourteen enzymes were added to the survey for genomic regions in which polymorphisms could not be detected using the six restriction enzymes.

The 54primer pairs used for surveying simple sequence repeat polymorphisms included 29from published data (18,19)and 25prepared by our group mostly from published sequences in GenBank.PCR detection followed essentially the methods by Wu and Tanksley (18).The DNA markers detect-ing polymorphisms between the parents were used to assay the entire population of 250individuals.

Data Processing and Statistical Analyses.A molecular marker linkage map was constructed using Mapmaker 3.0(20).QTLs were determined using Mapmaker ?QTL 1.1.(21).The entire genome was searched for digenic interactions for each trait with two-way analyses of variance using all possible two-locus combinations of marker genotypes.The calculation was based on unweighted cell means (22),and the sums of squares were multiplied by the harmonic means of the cell sizes to form the test criteria.There are eight degrees of freedom among the nine genotypes formed of two codominant loci,two degrees of freedom for each of the additive and dominance effects within each locus,and four degrees of freedom for interaction between loci.The interaction,often referred to as epistasis,can be further partitioned into four terms each specified by a single degree of freedom:additive (first locus)?additive (second locus)(AA),additive ?dominance (AD),dominance ?additive (DA),and dominance ?dominance (DD).Statistical significance for each term was assessed using an orthogonal contrast test provided by the statistical package Statistica (23).

RESULTS

Measurements of the Traits.The performance and heterosis of yield and yield component traits in parents,F 1,and F 3grown in 1994and 1995are given in Table 1.The F 1yield was approximately the same in the two years tested,and is on the same order of magnitude as the average yielding level of this hybrid under normal agricultural conditions (24).The mea-surements of the three yield component traits were also similar in the two years.F 1heterosis,measured as the percentage of

deviation of the F 1from the parental mean,is large for yield in both years.There was still large residual heterosis in the F 3generation.The proportion of genotypic variation in the total phenotypic variation ranged from about 50%in tillers per plant to more than 80%in seed weight in the two years (Table 2).Interactions between genotypes and years were statistically significant for three of the four traits (Table 2).However,the interaction effects were small compared with the main effects of genotypes or years (data not shown).

Linkage Map.The survey of 591molecular markers,includ-ing 537RFLPs and 54simple sequence repeats,identified 150loci polymorphic between the parents.Mapmaker analysis at LOD (logarithm of odds)3.0placed these marker loci into 14linkage groups.A map was constructed (not shown)which spanned a total of 1,842centimorgans in length and well integrated the markers from the two high-density RFLP linkage maps (14,15).

QTLs for Yield and Yield Component Traits.QTLs resolved with LOD 2.4(25)for the four traits are given in Table 3.QTLs with LOD exceeding 2.4in one year but slightly below this threshold in another year are also included in the list.

Five and six QTLs for yield were detected in 1994and 1995,respectively,with one QTL (yd1a )in common between the two years.

For tillers per plant,three QTLs were detected in 1994and two in 1995.Again,there was one QTL (tp4)in common between the two years.

Five and seven QTLs for grains per panicle were detected in 1994and 1995;two (gp1b and gp5)were resolved in both years.In addition,it is almost certain that the effects on chromosome 1revealed by R753-C161in 1994and by RM1-R753in 1995were due to the same QTL (gp1a ),as the 1-LOD support confidence intervals (25)overlapped substantially (map not shown).Similarly,the LOD peaks that appeared in the tightly linked genomic segments (R1966-G144and RZ403-C269)on chromosome 3in the two years were also possibly the result of the same QTL (gp3).

Of the seven and nine QTLs for grain weight resolved in 1994and 1995,four (gw1,gw7,gw9,and gw11)were detected in both years.The LOD peaks in the proximity of RG360on chromosome 5resolved in the two years may also be due to the effect of the same QTL (gw5),as was the case for the LOD peaks in the tightly linked blocks R1952–C226and R565–R902on chromosome 6.

Taken together,a total of 32distinct QTLs were identified using the specified criteria.Twelve were observed in both years,and the remaining 20were detected only in one or the other year.It can also be seen from Table 3that several QTLs

Table 1.

Means and midparent heterosis (%in parentheses)of yield and yield component traits in parents and the progenies

Trait

Minghui 63

Zhenshan 97F 1

F 3

19941995199419951994199519941995Yield,t ?ha 6.50 6.26 4.84 4.488.53(50.4)8.91(66.0)7.40(30.8) 6.62(23.3)Tillers ?plant 10.711.011.49.512.8(15.8)14.3(39.5)11.2(1.4)10.5(2.4)Grains ?panicle

101.2105.781.889.5114.9(25.6)111.9(14.6)112.9(23.4)110.4(13.1)Grain weight,g ?1,000

27.7

25.6

25.1

24.8

27.9(5.7)

26.0(3.2)

26.3(?0.4)

25.4(0.8)

Table 2.Some summary statistics from two-way analysis of variance of the traits measured in 1994and 1995

Trait SSG in SST,*%

G ?Y ?

19941995F P Yield

51.974.1 1.600.000Tillers ?plant 49.053.2 1.140.098Grains ?panicle 74.675.5 2.350.000Grain weight

83.0

89.0

2.06

0.000

*Proportion of genotype sum of squares in total sum of squares.?Interaction between genotypes and years.

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appeared to have pleiotropic effects by simultaneously affect-ing two or more traits.This is particularly the case for the QTL in the vicinity of the genomic block around R753on chromo-some 1,whereby large effects were simultaneously detected for three of the four traits in both years.

Dominance and Overdominance.A locus is regarded as exhibiting overdominance if the ratio of the estimated domi-nance to the absolute value of additive effect is larger than unity.Thus,although the F 3family means usually underesti-mate dominance by a factor of 1?2,partial dominance,full dominance,and overdominance were nonetheless still preva-lent among the QTLs (Table 3).

For yield,three of the five QTLs recovered in 1994and four of the six QTLs in 1995showed overdominance.Another noticeable case is that of grains per panicle,in which over-dominance was detected for one of the five QTLs in 1994and three of the seven QTLs in 1995.A very large overdominance effect was detected in both years for the QTL on chromosome 5(gp5).For grain weight,one QTL on chromosome 1displayed overdominance in both years,while the remaining QTLs showed partial to full dominance.

Various levels of negative dominance were observed in both years at several QTLs,including tp4for tillers per plant,gp1b and gp3for grains per panicle,and gw9for grain weight.There were several QTLs at which negative dominance occurred in one year or the other (Table 3).This indicates that heterozy-gosity was not necessarily always favorable for the expression of the trait even in such a highly heterotic cross.

Relationship Between Marker Heterozygosity and Trait Expression.Correlations between overall heterozygosity of the F 2individuals and the F 3family means were very small for all four traits (data not shown).They were significant at P ?0.05only for grain weight (correlation coefficients 0.17in 1994and 0.16in 1995).Thus,the overall heterozygosity made very little contribution to trait expression.This result differed from analysis of marker distance and hybrid performance in diallel crosses (26,27).A possible explanation for the lack of corre-lation is cancellation between positive and negative dominance among various loci,as suggested by estimated dominance effects in Table 3.

Digenic Interactions Involving QTLs.The two-way analyses of variance detected interactions between QTLs in grains per panicle and grain weight in 1994,and in yield and grains per panicle in 1995(Table 3).The most noteworthy case was that of grain weight in 1994,in which significant interactions were detected in four pairs of QTLs.

Interactions of QTLs with loci in the rest of the genome were also assessed,using markers flanking the QTLs and markers located in the remaining parts of the linkage map.The majority of the QTLs were found to interact with at least one other locus and many of the QTLs interacted with three or more loci (Table 3).

Digenic Interactions Between Loci in the Entire Genome.Table 4presents the numbers of two-locus combinations showing significant (P ?0.01)interactions resulting from testing all possible two-locus combinations and also the num-bers of various types of interactions determined by orthogonal contrast tests.Only data sets formed of two codominant loci with each marker genotypic class containing 5or more indi-viduals were included in the calculation,resulting in 7,585tests for 1994and 7,681for 1995.With ??0.01for individual tests,the 99%confidence intervals for the expected numbers of spurious interactions (false positive)would be 75.85?20.02for 1994and 76.81?20.14for 1995.Thus,the numbers of interactions detected in both years for all the traits much exceeded expectations based on spurious interactions,indicat-ing that real interactions exist in the genome of this population.Significant interactions were detected simultaneously in both years for many of the two-locus combinations (Table 4,column 5).If two loci do not interact with each other,the probability for detecting the same interaction at ??0.01in both years is less than 0.01%.Thus,in essence,none of the two-locus interactions simultaneously observed in both years should be regarded as a chance event.These interactions,referred to as common interactions for ease of description,can

Table 3.Putative QTLs identified for yield and yield component traits in 1994and 1995Trait*QTL ?Flanking markers

LOD

Var,%A D IL 1994

Yield

yd1a R753–C161 3.59.7?0.3 3.20yd1b RG101–C922 2.6 5.8?1.7?0.33yd4R514–C2807 2.47.4?1.8 1.44yd5a G193–RZ649 3.311.7?0.5 3.43yd8C483–R1629 3.2 6.60.8 2.41Ti ?Pl

tp4C820–C56 3.1 6.1?0.4?0.12tp5G1458–G193 2.8 5.5?0.40.22tp10C677–G4003 2.7 5.3?0.2?0.54Gr ?Pa

gp1a R753–C161 3.1 6.1?5.2 4.40gp1b RG173–RG532 4.210.6?7.9?3.54gp3R1966–G1448.316.910.0?3.61gp5?G193–RZ649 2.48.9?1.310.31gp6a ?RG653–G342 2.5 4.9 4.1?5.64Gr wt

gw1?R753–C161 3.512.10.7 1.51gw3a §?R19–RZ40311.423.6?1.8?0.48gw5§RG360–C7348.515.7 1.30.11gw6R1952–C226 2.6 5.20.70.53gw7???RG128–C1023 2.38.6?1.00.23gw9R2638–RG570 4.18.9 1.2?0.30gw11?RM4-RG98 2.2

5.6?0.60.711995

Yield

yd1a R753–C161 2.6 6.2?1.1 2.11yd5b C624–C246a 2.710.2?1.4 2.90yd5c RG360–R1674 2.5 4.8 1.50.24yd6R565–R902 2.8 5.2 1.70.44yd7?RG128–C1023 3.59.4?1.8 2.32yd11?C950–G389b 3.27.0?0.5 2.71Ti ?Pl tp4C820–C56 2.6 5.5?0.3?0.30tp7RZ471–MX2 3.211.30.5?0.56Gr ?Pa

gp1a RM1–R753 6.015.5?8.1 3.410gp1b ?RG173–RG5327.117.8?9.1?2.813gp3?RZ403–C2699.016.08.7?0.54gp5G193–RZ649 2.38.6?0.28.83gp6b R1014–G200 2.5 5.5 5.00.90gp7C1023–R1440 4.79.5?5.2 6.52gp11C950–G389b 3.1 5.9?0.77.30Gr wt

gw1R753–C161 2.69.70.5 1.30gw3b C944–C7469.516.8?1.40.23gw3c R1966–G14411.422.5?1.7?0.79gw5RG360–R167412.924.1 1.6?0.30gw6R565–R902 4.78.6 1.00.35gw7RG128–C1023 5.217.7?1.4?0.49gw8C1121–RG333 2.7 6.70.7?0.75gw9R2638–RG570 4.08.5 1.1?0.41gw11

RM4–RG98 3.5

8.6

?0.9

0.6

Var,variation explained by each QTL;A,additive effect;D,

dominance effect;IL,number of loci with which the QTL interacts.Positive values of the additive effect indicate that alleles from Zhen-shan 97are in the direction of increasing the trait scores,and negative values indicate that alleles from Minghui 63are in the direction of increasing the score.Positive values of the dominance effect indicate that heterozygotes have higher phenotypic values than the respective means of two homozygotes,and negative values indicate that het-erozygotes have lower values than the means of the two homozygotes.*Ti ?Pl,tillers per plant,Gr ?Pa,grains per panicle;Gr wt,grain weight.?Numbers following the two letters represent the chromosomal loca-tions of the QTLs.

?§??Pairs of interacting loci within a trait.

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be taken as the minimum of statistically significant interac-tions.

The proportion of common interactions was the largest for grain weight.They constituted approximately40%and30%of the significant interactions detected in1994and1995,https://www.sodocs.net/doc/c418030271.html,mon interactions ranged from6%to17%of the significant interactions for the remaining three traits in the two years(Table4).

The numbers of three different types of interactions(AA, AD?DA,and DD)determined using the orthogonal contrast test are also given in Table4.By chance alone,these terms should occur in a proportion of1(AA):2(AD?DA):1(DD), which was obviously not the case.In all four traits,AA interactions were much in excess,and DD and also AD?DA were in deficiency,providing additional evidence that the interactions were not the results of chance events.

Patterns of Interactions.We used grains per panicle to illustrate the interactions;two-locus combinations showing interactions at P?0.01in both years are listed in Table5.Two observations can be made from this table.First,the types of interactions(i.e.,AA,AD,and DD)detected for the majority of the two-locus combinations were consistent in the two years. Second,the majority of the interaction terms individually accounted for less than5%of the genotypic variation.It is striking that such small interactions could be repeatedly de-tected under the experimental conditions.

The means of seeds per panicle for the nine genotypic classes for each pair of interacting loci presented in Table5are graphed to discern the patterns of interactions.A few examples are given in Fig.1.

AA.The locus pair RG532and RM4from chromosomes1 and11,respectively,was used to illustrate the AA interaction. As can be seen from Fig.1A and B,performance of the two homozygotes of the first locus(marked by RG532)was favored or disfavored differentially by the homozygotes of the second locus(RM4).The two homozygotes of the RG532locus differed by only1and8seeds per panicle in1994and1995, respectively,when RM4was homozygous for the Minghui63 allele(11).The difference increased to30and31when RM4 was homozygous for the Zhenshan97allele(22),resulting in 11(RG532)?22(RM4)as the favored genotype.Note that a QTL was detected near RG532(gp1b)in both years,and the interaction clearly contributed to the detection of this QTL. AD.The combination of marker loci RG360(chromosome 5)and RG653(chromosome6),showing AD and DA in both years,was chosen as an example to demonstrate AD(Fig.1C and D).The critical characteristic of this AD was that the performance of the homozygotes of the first locus depended on the heterozygote of the second locus,or conversely,the phenotype of the heterozygote of the second locus was largely influenced by the homozygotes of the first locus.Apparently, the heterozygote of the second locus(RG653)not only re-versed the relative grain numbers of the two homozygotes of the first locus(RG360)but also considerably enlarged the

Table4.Summary of the significant(P?0.01)interactions

identified in1994and1995by searching all possible

two-locus combinations

Trait Interaction19941995Common

Yield Positive pairs*10516510

AA60918

AD(DA)51733

DD4180

Tillers?plant Positive pairs*10514117

AA7910517

AD(DA)28421

DD1060

Grains?panicle Positive pairs*9916015

AA52809

AD(DA)567410

DD4160

Grain weight Positive pairs*12516449

AA8410227

AD(DA)477119

DD15169

Number of tests?7,5857,681

*Number of two-locus combinations showing significant interactions

(P?0.01).

?Number of possible two-locus combinations tested.

Table5.Two-locus interactions for grains per panicle simultaneously detected at P?0.01in1994

and1995by two-way analysis of variance based on marker genotypes

Locus1*Locus2*

19941995

Type P SSG,%?Type P SSG,%?

RG532(1)RM4(11)AA0.002 4.0AA0.010 2.5

RG173(1)RM203(3)AA0.002 4.1AA0.002 3.5

C547x(1)RG634(2)AA0.004 3.6AA0.005 3.4

RG236(1)R1440(7)AD0.009 2.9AD0.012 2.4

DA0.022 2.2DA0.002 3.5

C112(1)G389a(11)AA0.006 3.3AA0.019 2.3

MX7b(2)Waxy(6)DA0.006 3.3DA0.000 5.4

RM168(3)RM18(7)AD0.001 5.0AD0.000 6.9

C1447(5)C677(10)AA0.005 3.3AA0.006 3.2

DA0.015 2.5———

C1447(5)G389a(11)AA0.003 3.9AA0.003 3.7

G1458x(5)?G342(6)AA0.004 3.6AD0.002 4.1

G193x(5)?G342(6)AA0.004 3.7AA0.018 2.3

AD0.036 1.9AD0.005 3.3

RG360(5)RG653(6)§AD0.003 3.7AD0.000 5.3

DA0.011 2.7DA0.021 2.1

RG360(5)G342(6)§AD0.001 5.4AD0.0009.6

R830(5)RZ404(9)AA0.005 3.3AA0.004 3.4

DD0.032 2.0DD0.017 2.3

C1023(7)C794(11)DA0.002 4.1DA0.014 2.2

Interaction types with P?0.01in one year but0.01?P?0.05in the other year are also listed.

*Numbers in parentheses represent chromosomal locations.

?Percentage of genotypic variation explained by the interaction.

?§Marker loci that are closely linked.

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magnitude of the difference between the two homozygotes.The situation was very similar for the DA of the same locus pair.

DD.A significant DD interaction was detected in both 1994and 1995in the R830(chromosome 5)and RZ404(chromo-some 9)combination (Fig.1E and F ),which also showed an AA interaction with the pattern differing from that of the RG534and RM4combination.This is the only DD detected among the various two-locus combinations listed in Table 5.Heterozygotes of the two loci interacted favorably and the double heterozygote produced more grains per panicle than did single heterozygotes.

Influence of Epistasis on Overdominance.A large over-dominance effect was detected in both years at the QTL gp5(Table 3),which was found to interact in both years with a locus on chromosome 6.The line graphs of the 9genotypes (Fig.1G and H ),based on the flanking markers G193x (chromosome 5)and G342(chromosome 6),clearly showed that overdomi-nance marked by the G193x locus was dependent on genotypes at the G342locus.The heterozygote of G193x was superior only when the G342was heterozygous or homozygous for the Zhenshan 97allele,and was intermediate when G342was homozygous for the Minghui 63allele.

DISCUSSION

The most noticeable finding of the present study based on a highly heterotic cross is the prevalence and importance of epistasis in the rice genome with two pronounced features.First,two-locus analyses resolved much larger numbers of loci contributing to trait expression than single-locus analyses.For example,counting only the interactions simultaneously de-tected in both years for grain number per panicle,the signif-icant two-locus interactions involved a total of 25loci located

on 9of the 12rice chromosomes,compared with 5and 7QTLs detected in the two years for this trait.As a second feature,all three types of interactions (AA,AD,and DD)occurred among the various two-locus combinations.It is even more remark-able that multiple interaction terms were found in a consid-erable proportion of the interacting two-locus combinations in all traits examined (Tables 4and 5).

Overdominance at the single-locus level was detected at many of the QTLs.More QTLs showed overdominance for yield than for yield component traits,whereby most of the QTLs for yield and a few QTLs for the component traits showed overdominance.This is largely because of the multi-plicative relation of yield with the component traits (multipli-cative overdominance),as discussed by Zhang et al.(26).However,because QTLs that showed overdominance inter-acted with at least one other locus,it may not be appropriate to interpret the single-locus marginal effects without specify-ing the genotypes of the counterpart.The same argument also applies to QTLs that exhibited dominance and ?or additive effects,most of which are likely to be embedded in the interlocus interactions involving much of the total genome.Additionally,lack of correlation between heterozygosity and trait expression implies that,collectively,the effects of dom-inance and ?or overdominance made only limited contributions to the heterosis observed in this experimental population.While the dominant types of interactions (especially DD)may be most relevant to F 1heterosis,the analysis showed that AA seems to be more common than AD and DD in this data set.The deficiency of dominant types of interactions may be partly ascribed to the one-generation lag resulted from col-lection of marker data from F 2individuals and field data from F 3families;thus both heterozygosity and dominance were reduced by half compared with F 2individuals.Consequently,all the dominant types of effects,including dominance

within

F I

G .1.Patterns of the interactions for grains per panicle displayed by various two-locus combinations in 1994and 1995.P AA ,P AD ,P DA ,and P DD are the probabilities for AA,AD,DA,and DD interactions.The vertical axis represents number of grains per panicle.The numbers 11,12,and 22represent the three genotypes of each locus:11,homozygote for Minghui 63allele;22,homozygote for Zhenshan 97allele;and 12,heterozygote.

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individual loci and AD and DD between loci,were underes-timated in the analysis.Therefore,to determine precisely the extent and significance of dominant types of interactions,it is necessary to have field data collected from F2populations. Experimental designs are called for in future studies to enable the construction of genetically immortalized F2populations. The results also suggest the possibility of higher-order interactions(multilocus epistasis),at least for the most com-plex trait(yield).There are at least two lines of evidence implying the existence of higher-order interactions.First, fewer QTLs were detected and a smaller proportion of geno-typic variation was explained by the QTLs for yield than for two of the yield component traits(Table3),although the reverse should be expected on the basis of multiplicative relations of yield with the component traits.Also,at the two-locus level,the numbers of interactions detected for yield were not much greater than for its component traits.This suggests the involvement of genetic components that could not be resolved with either single-locus or two-locus analyses. Second,inspection of the significant two-locus interactions revealed a‘‘chain-like’’relation among the interacting two-locus combinations such that locus1interacted with locus2, which in turn interacted with locus3,which interacted with locus4...Such chains could grow very long to include a large number of loci and even form circles(data not shown), indicating higher-order interactions as in the case of multilocus structure previously observed in an experimental barley pop-ulation(28)and in natural populations of Avena barbata(9). Unfortunately,the size of the present population did not permit analyses beyond two-locus combinations.

In summary,the results clearly indicate that epistasis plays a significant role in the inheritance of quantitative traits as well as in the genetic basis of heterosis.The relationship between traits and genes in the manifestation of heterosis is much more complex than has commonly been expected on the basis of dominance and overdominance hypotheses.

We thank the Cornell Group and the Japanese Rice Genome Project for kindly providing the RFLP probes.This work was supported by a grant from Chinese National Natural Science Foundation and a grant from the Rockefeller Foundation.

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第八章杂种优势利用

第八章杂种优势利用 教学内容：杂种优势利用 教学目标：杂种优势的概念；杂种优势的度量方法；了解杂种优势的理论基础； 掌握一般配合力和特殊配合力的概念及其测定方法；熟悉利用杂种优 势的途径；三系制种原理及方法。 教学重点：杂种优势表现的普遍性、复杂多样性和遗传基础；杂种优势利用的基本条件；杂种亲本选配的基本原则；利用作物杂种优势的途径；质核 互作雄性不育和核雄性不育的遗传；质核互作雄性不育系、保持系、 恢复系的选育方法；杂种品种的选育和利用。 教学难点：配合力的测定。 一杂种优势利用的简史与现状 杂种优势 (heterosis) :指两个性状不同的亲本杂交产生的杂种F1 , 在生长势、生活力、繁殖力、适应性以及产量、品质等性状方面超过其双亲的现象。 1 利用简史： 简述杂种优势现象的发现，列举古今中外在杂种优势利用方面的研究，主要农作物杂种优势利用的简史。 2 利用现状 作物杂种优势利用主要集中在以下五个方面：核质互作雄性不育系的选育、化学杀雄、光温敏雄性不育系的选育、核雄性不育的利用与核质互作杂种优势利用。 二杂种优势表现特征 1 杂种优势的普遍性 （1）生长势和营养体 （2）产量和产量因素方面 （3）品质方面 （4）生理功能方面 （5）生化表现方面 （6）抗逆性和适应性 2 杂种优势表现的复杂多样性 (1) 从基因型看：自交系强于自由授粉品种 (2) 作物种类：二倍体大于多倍体 (3) 亲本亲缘关系：亲缘关系远的强于近的 (4) 杂交组合：亲本之间性状互补，杂种优势强 3 F2及以后世代杂种优势的衰退 原因：发生遗传分离，出现个体差异，后代不整齐一致。 杂种优势衰退速度的影响因素： (1) F1基因型的杂合位点数：杂合位点越多，衰退越慢 (2) 作物授粉方式：异花授粉比自花授粉作物下降慢

玉米杂种优势利用 论文

玉米杂种优势利用 摘要：玉米是异花授粉植物,育种主要是利用其杂种优势.本文首先介绍了杂种优势的概念,表现及原则,随后着重讲述了玉米杂种优势的利用,并以玉米与其近缘种和远缘种杂交的利用为例,阐述了玉米杂种优势利用模式及其在生产上的重要性,以及利用的现状和前景,使读者更多的了解玉米杂种优势的有关知识. 关键词：玉米;杂种优势;利用 1. 杂种优势的概念.表现及原则 杂种优势是指两个以上亲本杂交后,所产生的杂种在生长势,生活力,抗逆性,适应性,产量和品质等方面比其亲本优越的现象.它是生物界的普遍现象.其表现是多方面的:(1)营养体优势.多数杂种F代长势旺盛,分蘖力强,根系发达,茎杆粗壮,块根,块茎增大增重.(2)生殖优势.一些主要农作物如玉米,高粱,水稻等杂交种F1的产品多数较高,一般此推广的普通良种增产20%`～40%.(3)抗逆性和适应性方面的优势.杂种F1代生长势强,抵御外界不良环境的能力和适应环境条件的能力往往优于亲本.(4)品质优势.杂种优势在生产上可以大大地提高产量,也应遵循以下原则:1.选配遗传基础差异大的亲本.2.尽量提高亲本的纯合度.3.便于杂交,并能获得大量杂交种子.。 玉米在我国及至全世界被大面积种植,其育种目标在不同地区有所侧重,但大部分是共同性的.现概括地将饲用玉米育种的目标性状分述如下:(1)高产性状.通常认为,产量性状优势的.子粒玉米杂交同样应用较多的饲用产量.(2)稳产性状.该性状主要包括生态适应性和各种抗逆性两方面(3)营养价值(4)早熟性(5)适应机械化收获的性状,如适宜的植株高度和穗位高度.玉米是最重要的饲用作物之一,适合于许多地方种植,但因为各地区地理位置,气候条件等的不同,又需要育种家们培育出许多适合当地种植的优良品种,杂种优势就是一个重要的研究方向,下面我们将分别论述玉米与其近缘种,远缘种的杂交。 2. 玉米与其近缘种的杂交 2.1杂交试验 目前,栽培种与其近缘物种直接杂交仍是将近缘物种基因转移到栽培种的主要手段。而杂交成功的关键取决于栽培种与近缘物种间的杂交亲和性。如果不亲和或亲和力低,即杂交不结实或结实率低,杂交不易成功[7～10]。远缘杂交不亲和性是物种间长期进化中形成的生殖隔离。不亲和性表现为受精前(杂交受精不能完成)、受精过程中(胚败育)和受精后(杂种衰败和杂种不育)3种情况。为了提高可杂交性,克服远缘杂交不育障碍和在育种中有效导入、利用近缘种的有利基因,开展杂交亲和性研究是必要的。我们知道，在玉蜀黍族中,与玉米亲缘关系最近的是玉蜀黍属中的各个种,该属中除栽培玉米亚种以外其余各分类单位均可称为大刍草(teosinte)。大刍草具有许多优良特征特性,如抗逆性、抗病虫害和优质等,因此把大刍草资源的有益基因导入玉米创建新的基因库,将对玉米遗传改良具有重要的意义。 通过玉米与其近缘种墨西哥玉米、小颖玉米、二倍体多年生玉米和四倍体多年生玉米杂交结实的试验发现：结实率和杂种种子形态有较大差别。其中,玉米

第二章__杂种优势利用

第二章杂种优势利用(Utilization of heterosis) 杂种优势（heterosis）：是生物界一种普遍现象，是指两个性状不同的亲本杂交产生的杂种，在生长势、生活力、繁殖力、适应性以及产量、品质等性状方面超过其双亲的现象。 The increase in size, vigor or productivity of a hybrid plant over the average or mean of its parents 第一节杂种优势利用的概况及表现 一、杂种优势利用的简史与现状 早在1400多年前，我们的祖先就利用了马和驴杂交生骡，为人类历史开辟了利用杂种优势的先例（后魏贾思勰的《齐民要术》记载）。 园艺植物的杂优利用 园艺作物的杂优利用也十分广泛，据农业部1998年的统计，西瓜、甜瓜、番茄、大白菜、甘蓝、黄瓜、辣椒等杂交利用率达90%以上菠菜、萝卜、洋葱、芦笋等也在80%以上。西方发达国家及日本、韩国等超过这个水平。林木果树和观赏园艺植物中，如速生毛白杨、椰子、四季海棠等在世界范围开展杂优利用研究。 二、杂种优势的分类与度量 1. 分类： ①体质型：杂种的营养器官发育良好，如茎、叶生长发育旺盛，产量高； ②生殖型：杂种的生殖器官发育较强，如结实器官增大，结实性增强，种子和果实产量高； ③适应型：杂种具有较高的生活力、适应性和生长竞争能力。 2、杂种优势的度量方法 （1）中亲优势（mid-parent heterosis) 指杂交种（F1）的产量或某一数量性状的平均值与双亲（P1或P2）同一性状之和平均值差数的比率。计算公式为： F1-（P1+ P2）/2 中亲优势= ×100% （P1 + P2）/2 Hybrid performance is measured relative to mean of the parents (MP) （2）超亲优势（over-parent heterosis) 指杂交种（F1）的产量或某一数量性状的平均值与高值亲本（HP）同一性状平均值差数的比率。计算公式为： F1-HP 超亲优势= X100% HP （3）超标优势（over-standard heterosis) 指杂交种（F1）的产量或某一数量性状的平均值与当地推广品种（CK）同一性状的平均值差数的比率。 计算公式为: F1- CK 超标优势= X100% CK （4）杂种优势指数(index of heterosis) 是杂交种某一数量性状的平均值与双亲同一性状的平均值的比值，也用百分率表示。计算公式如下： F1 杂种优势指数= X100%

第十章习题答案

第十章数量性状遗传 一、名词解释 1、数量性状（计量性状）：凡容易受环境条件的影响、在一个群体内表现为连续性变异的性状。 2、标准误：即平均数方差的平方根,表示平均数变异范围。 3、遗传率：又称遗传力，是指一群体内由遗传原因引起的变异在表型变异中所占的比率。 4、表现型值(P):对个体某性状度量或观测到的数值，是个体基因型在一定条件下的实际表 现，是基因型与环境共同作用的结果。 5、基因型值：表现型中由基因型所决定的部分，称为基因型值(G)。 6、环境离差：如果不存在基因型与环境互作效应，则表现型值与基因型值之差就是环境条 件引起的变异，称为环境离差(E)。 7、广义遗传率：指遗传方差占表型总方差的比值。 8、狭义遗传率：真实遗传的加性方差占表型方差的百分比。 9、加性方差：指同一座位上等位基因间和不同座位上的非等位基因间的累加作用引起的变 异量，是能够在上下代间真实遗传的方差。 10、显性方差：指同一座位上等位基因间相互作用引起的变异量。 11、上位性方差：指非等位基因间的相互作用引起的变异量。 12、近交系数(F):一个个体从某一祖先得到一对纯合的、且遗传上等同的基因的概率。 13、杂种优势：两个遗传组成不同的亲本杂交，产生的杂种在生长势、生活力、繁殖力、抗 逆性、产量和品质等方面优于双亲的现象。 二、是非题 1、数量性状中每对微效基因的遗传仍符合孟德尔遗传规律。 ( √ ) 2、方差和标准差都是表示一组数据偏离平均数的变异程度。 ( √ ) 3、性状的遗传率越大，在后代出现的机会就越大，人工选择效果也就越好。（×） 4、杂种后代性状的形成决定于两方面的因素,一是亲本的基因型,二是环境条件的影响。( √ ) 5、遗传率是指一个性状的遗传方差或加性方差占表型总方差的比率，它是性状传递能力的衡量指标。（×） 6、根据遗传率的定义：一个纯系的遗传率最大等于1。 ( √ ) 7、AAbb和aaBB杂交，F1代基因型为杂合体，因此F1代中存在遗传方差，V ≠0。（×） G 8、基因的加性方差是可以在上下代之间固定遗传的，而显性和上位性方差是不可以固定的。( √ ) 9、如果某地块中水稻株高的广义遗传率为58%，表示该地块中水稻株高的差异大约有58%是由于遗传差异造成的，42%是环境影响造成的。 ( √ ) 10、杂种优势主要表现在质量性状上。（×） 11、近亲繁殖导致了隐性基因纯合表现，而显性基因却一直处于杂合状态。（×） 12、利用杂种优势育种时，双交种的制备是用两个不同的自交系杂交获得的。（×）

作物育种学总论习题

《作物育种学总论》习题 第一章育种目标 1.名词术语：育种目标、生物产量、经济产量、收获指数、株型育种、高光效育种 2.现代农业对作物品种有哪些基本要求？ 3.制订育种目标的原则是什么？ 4.作物育种的主要目标性状有哪些？ 5.怎样才能正确制订出切实可行的育种目标？ 6.为什么通过矮秆育种能提高作物的单产？ 7.针对你所熟悉的某一地区制订某一个作物的育种目标，并说明其理由。 第二章作物的繁殖方式及品种类型 1.简述小麦、玉米、棉花、大豆等作物的花器构造及开花习性。哪些花器构造和开花 习性有利于异花授粉？哪些花器构造和开花习性有利于自花授粉？ 2.结合具体作物简述自交和异交的遗传效应。 3.农作物品种有哪些类型、各有哪些基本特性？ 4.不同类型的品种群体的育种特点是什么 第三章种质资源 1.概念解释：种质资源、起源中心、初生中心、次生中心、原生作物、次生作物、遗传多样性中心、基因银行、初级基因库、次级基因库、三级基因库 2.简述种质资源在作物育种中的作用。 3.简述本地种质资源的特点与利用价值。 4. 简述外地种质资源的特点与利用价值。 5.Vavilov起源中心学说在作物育种中有何作用？ 6.如何划分初生中心与次生中心？

7.试述作物种质资源研究的主要工作内容与鉴定方法。 8.建拓作物基因库有何意义？如何建拓作物基因库？ 9.建立作物种质资源数据库有何意义？如何建立作物种质资源数据库？ 10.发掘、收集、保存种质资源的必要性与意义何在？ 第四章引种与驯化 1.引种驯化的概念及基本原理是什么？ 2.影响引种的因素和引种规律是什么？ 第五章选择育种 1.试述选择育种的基本原理及程序。 第六章杂交育种 1.杂交育种按其指导思想可分为哪两种类型？各自的遗传机理是什么？ 2.为什么说正确选配亲本是杂交育种的关键？有何重要意义？ 3.如何理解杂交育种亲本选配的四条原则？ 4.选用遗传差异大的材料作亲本有何利弊？如何理解双亲来源地远近与双亲亲缘关系远近的关系？ 5.为什么要求双亲应具有较高的配合力？ 6.为什么说杂交方式是影响杂交育种成败的重要因素之一？杂交方式有哪些？试说明在单交、三交、四交、双交等杂交方式中，每一亲本遗传比重如何？为什么在三交和四交中要把农艺性状好的亲本放在最后一次杂交？ 7.解释系谱法、混合法、衍生系统法、单粒传法，简述它们各自的工作要点。试比较它们各自的优缺点及应用。 第七章回交育种 1.什么是回交育种？回交育种有哪些用途及有何局限性？什么情况下回交育种最有

植物杂种优势复习题

植物杂种优势复习题 名词解释 1.雄性不育:花药或花粉不能正常发育的现象。一旦形成，是可遗传。雄性不育的植株，雌蕊能正常发育。 2.自交系:通过多代自花授粉或多代近交后所得到的纯系。 3.杂种优势指数:杂交种某一数量性状的平均值与双亲同一性状平均值的比值。 4. 配合力:指一个亲本(纯系、自交系或品种)材料在由它所产生的杂种一代或后代的产量或其他性状表现中所起作用相对大小的度量。 5.自交不亲和性:指某一植物的雌雄两性机能正常,但不能进行自花受精或同一品系内异株花粉受精的现象。 6.综合种: 7.两用系: 8.雌株系 9.顶交种:顶交法选用遗传基础广泛的品种群体作为测验种测定自交系的配合力。顶交法产生的杂交种成为顶交种。 10.单交种:两个亲本杂交所得到的后代,为单交种... 1.临保系:将可育ＤＨ系单株与不育单株测交，测交种出现的全不育所对应的测验种即为临保系。 2.高不育系：是指有少量自交结实的不育系，这种自交结实的种子能够使高不育特性得以遗传。 3.双交种:双杂交种的简称。由四个品种或自交系先两两配成单交种,再由两种单交种杂交而得的杂交组合。 4. 雌性系:以黄瓜为例)在黄瓜中,有些植株所开的花全部或绝大多数都是雌花,而无雄花或只有少数雄花,通过选育可获得具有这种稳定遗传能力的系统,称为雌性系 5. 自交不亲和性:指某一植物的雌雄两性机能正常,但不能进行自花受精或同一品系内异株花粉受精的现象。 6.一环系:从品种群体和品种间杂交种中选育出的自交系。 7.细胞核雄性不育两用系;： 8测验种:测交所用的亲本 9.杂种优势指数:杂交种某一数量性状的平均值与双亲同一性状平均值的比值。 10.特殊配合力：指一个亲本在与另一亲本所产生杂交组合的性状表现中偏离两亲本平均效应的特殊效应。

第十章 杂种优势利用

第十章杂种优势利用 第一节杂种优势利用的简史与现状 第二节杂种优势表现特性 第三节杂种优势表现的遗传基础 第四节杂种品种的选育程序 第五节利用作物杂种优势的方法 杂种优势： 两个性状不同的亲本杂交产生的杂种在生长势、生活力、繁殖力、适应性以及产量、品质等方面超过其双亲的现象。 第一节 杂种优势利用的简史与现状 第一节 杂种优势利用的简史与现状 ?孟德尔8 年豌豆杂交试验（1856－1864 ）中观察到杂种优势现象，并首先提出杂种活力（hyhrid vigor）这个术语，但未作解释。 ?达尔文最早发现玉米杂种优势现象，指出玉米异花授粉与自花授粉后代株高之比，盆栽是100:87，田间是100:80。 ?Shull等研究了玉米自交和杂交的作用，于1907 年首次提出“杂种优势”（heterosis）这一科学术语。 第一节 杂种优势利用的简史与现状 ?Shull认为?°杂种优势?±是指遗传上不同的雄雌配子在结合中，由于种种机制而产生对发育的刺激作用。具体表现在杂种个体器官组织增大、产量和长势的增加。Shull 把?°杂种优势?±与?°杂种活力?±区别开来，认为杂种活力是杂种优势的表现，而杂种优势是遗传实质，二者之间是表现型与基因型的关系。 ?Reiger等人（1976）则认为?°杂种优势?±和?°杂种活力?±两词的意义相同，都是指杂合体与其相应纯合体比较，在一个或多性状上表现优越性，杂种优势是杂合体中基因互作的结果。 第一节 杂种优势利用的简史与现状 ?目前，国内外大多数学者大体上支持Reiger的意见，把杂种优势与杂种活力视为同义词。 第一节

杂种优势利用的简史与现状 ?法国学者 Kolereuter ，在 1761 ?a 1766 年育成了早熟优良的烟草种间杂种，并提出种植烟草杂交种的建议。 ?20世纪20－30年代，美国首先在玉米上利用了杂种优势。 ?1954年，美国选育出高粱?°三系?±配制高粱杂交种在生产上应用。 ?我国在20世纪50年代首先在烟草和玉米上利用杂种优势,此后在高梁上。?1973年，我国先后完成了水稻的?°三系?±配套工作,水稻杂种优势的利用处于世界领先水平。而后在小麦、油菜、棉花上研究利用。 第一节 杂种优势利用的简史与现状 ?在蔬菜上利用杂种优势最为普遍。据统计，日本的220种蔬菜中，利用杂种一代的占71.3%；番茄、甘蓝、白菜有90%以上应用杂种，黄瓜生产已全部应用杂种。美国在蔬菜生产上也有相同的趋势。有人认为，在不久的将来，作物生产上的杂种是今后的发展趋势。 第一节 杂种优势利用的简史与现状 目前世界上已经利用和即将利用杂种优势的植物有： ?大田作物?a玉米、水稻、高粱、黑麦、向日葵、棉花、烟草、小麦、大麦、燕麦、谷子、珍珠粟、大豆、油菜、甜菜、苜蓿草等。 ?蔬菜作物?a甜玉米、番茄、洋葱、茄子、黄瓜、西葫芦、西瓜、笋瓜、南瓜、甘蓝、花椰菜、白菜、萝卜、胡萝卜、菠菜、石刁柏、莴苣、辣椒、葱、芹菜、食荚菜豆、菜豆、豌豆、马铃薯。 ?还有一些果树植物（椰子）、林木植物（桉树）、观赏植物（秋海棠）。 第二节 杂种优势表现特性 一、杂种优势的表现 １、生长势和营养体 表现在： ①长势旺盛； ②分蘖力强； ③根系发达； ④茎杆粗壮； ⑤块根、块茎体积增大。 在株高上，F1具有明显优势是不同作物的共同特征，株高大多受多基因控制，但也有受单基因控制的，高杆表现为显性或部分显性，所以F1为高杆或倾向于高杆

论述作物利用杂种优势的途径有哪些方面

与杂种衰弱相反，有些种间杂交组合中还可见到F1植株的某些器官或整个植株体表现出强大的营养生长优势。即使是在一些局部器官畸形的植株上，往往亦可见到其他部分的旺盛生长势。在植物的种间杂交中，F1代的杂种优势比杂种衰弱更为常见，尤其是在成株阶段。 禾谷类的种间或属间杂交中，F1植株的杂种优势常表现为分蘖增加，株高、穗轴、护颖及外颖增大。例如曾报道斯卑尔脱小麦×黑麦F1代植株的干重为双亲均值的8倍。芸苔属的种间杂种，以及芸苔属与萝卜属(Raphanus)杂交产生的F1代植株常表现出植株高大，生长势旺盛的特点。用果重为2kg的笋瓜(Cucurbita maxima)作母本与果重4．8kg的南瓜(C.moschata)杂交，F1代的单果重达10.35kg。在观赏植物醉鱼草(Buddleia)中，以驳骨丹×日本醉鱼草(B．aslatlca × B.japonica)产生的杂种一代，其花大而美丽，且花朵数目剧增(香川冬夫，1957)。澳大利亚悉尼大学作物科学院从俗名为袋鼠爪花(Kangaroopaw，Anigozanthos)的野生种间的杂种一代中培育的品种，花期长、生长势旺，且耐逆性强，远销欧美(Goodwin，1989，私人通讯)。东方白松和西方白松的杂种植株生长速率显著大于双亲，F1达到的高度为三年前种植的西方白松的232％(Allard，1960)。 种间杂种一代的超常优势来源于高度的异质结合。由于种之间的遗传分化程度比种内的遗传差异大得多，因而种间F1杂种在集中双亲显性基因的数目上，在等位及非等位基因间互作的强度和广度上，以及在核质互作的程度上，都可能比品种间杂种大得多。如何利用种间F1代强大的杂种优势，是植物育种家非常感兴趣的课题。 直接利用种间F1代繁茂的营养体，是最经济有效的杂种优势利用途径。多年生植物常进行无性繁殖，一旦产生了在生活力上明显超过亲本种的F1杂种，这些植物就能利用各种无性繁殖方式大量繁衍后代。这种情形广泛地出现在野生的乔木、灌木和一些草本植物中，在松(Pinus)、刺柏(Juniperus)和栎(Quercus)各属中更为普遍。如美国的波缘栎(Q．undulata)就是冈孛栎(Q．gambeli)同其他6个种的杂交复合体(徐炳声和顾德兴，1986)。前苏联在开展人工利用松、杨树等林木和果树的种间F1代杂种优势上曾取得了很大的成绩。在多年生的饲料作物、蔬菜作物中也可以利用种间F1杂种优势进行品种改良，如从菊芋(Helianthus tuberosus) × H．strumosus产生的F1中曾培育出多年生草本植物，抗寒性强，绿色体产量高，块茎含碳水化合物达20％，成为在欧洲广为栽培的一种新饲料作物(齐津，1974)。

杂种优势利用

杂种优势利用 第一节杂种优势利用的现状与度量 （一）杂种优势利用简史： 中国早在1400 多年前后，魏贾思勰著的《齐民要术》中就记载了马和驴杂交产生骡的事实，为人类历史上开辟了观察和利用杂种优势的先例。 1637 年出版的《天工开物》中也记载了蚕的杂交事例。1761～1766年Ko1reuter，烟草杂交发现杂种优势，并提出利用杂交种。 1865年Mendel，豌豆杂交，提出杂种活力概念。 1866～1876年Darwin，提出异花授粉有利、自花授粉有害。1908年Shull,玉米自交系间杂交，杂种优势一词，方法体系建立。 杂种优势利用现状： 1934年美国玉米杂交种只占玉米种植面积的0.4%，到1944年玉米杂交种面积已占56%，而在美国玉米带各州杂交种面积已占90%，到1956年，全美国已普及了玉米杂交种。 中国对玉米杂种优势的研究，始于20世纪30年代，直到50年代才推广品种间杂交种，60年代推广双交种，70年代推广单交种。中国杂交高粱的研究始于20世纪50年代后期，到60年代后期，育成并推广了一批高粱杂交种。

杂种优势的概念： 是指两个遗传性状不同的品种、品系或自交系进行杂交，所产生的杂交种，在生活力、生长势、抗逆性、适应性以及产量、品质等方面优于其亲本的现象。 杂种优势理论： 显性学说（显性基因互补学说）：处于杂合状态的生物个体，由于显性基因的存在，不同程度地消除了隐性基因的有害或不利的效应，从而提高了杂种个体的生活力以及数量性状的效应值等，因此表现出杂种优势。根据这一理论，杂种优势可以固定，因为在子代群体中，显性纯合体和杂合体等效。杂种F1集中了控制双亲有利性状的显性基因，每个基因都能产生完全显性或部分显性效应，由于双亲显性基因的互补作用，从而产生杂种优势。 如两个具有不同基因型的亲本自交系杂交 AABBccdd X aabbCCDD F1 AaBbCcDd 因为每个基因都能产生完全显性或部分显性效应 AA、BB、CC、DD＞aa、bb、cc、dd Aa、Bb、Cc、Dd ＞aa、bb、cc、dd AaBbCcDd ＞AABBccdd（aabbCCDD） 超显性学说：杂合等位基因的互作胜过纯合等位基因的作用，杂种优势是由双亲杂交的F1的异质性引起的，即由杂合性的等位基因间互作引起的。 Aa>AA（aa） Bb>BB（bb） Cc>CC（cc）

作物杂种优势及其利用

作物杂种优势及其利用 摘要作物杂种优势是重要的生物学现象，有很大的应用价值。介绍了杂种优势利用简史、利用途径及其固定方法。 关键词杂种优势；遗传机理；预测方法 杂种优势是指2个遗传组成不同的亲本杂交产生的F1在生活力、生长势、抗逆性、适应性以及产量、品质等方面超过双亲的现象。杂种优势在许多农作物和园艺作物上得到广泛的应用，并获得巨大成功，对推动农业生产做出了重大贡献。但长期以来，由于研究方法的限制，杂种优势的遗传机理及预测方法至今尚未完全探明；且未能对F1及其双亲的基因结构和表达差异进行深入研究。近年来，众多植物分子生物学技术的不断建立和日臻完善，为人们认识和利用杂种优势现象提供了保障。 1杂种优势利用简史 我国早在1 400多年前，后魏贾思勰著的《齐民要术》中就记载了马和驴杂交产生骡的事实，为人类历史上开辟了观察和利用杂种优势的先例。法国Koireutier在1761～1766年育成了早熟优良的烟草品种间杂种，并提出了种植烟草杂交种的建议。以后，MerdeI、Darwin、Beal、Pichey等分别做了大量研究，最后Shull在1905～1909年进行玉米自交系选育与杂种优势的研究中，首次提出了“杂种优势”这一术语和选育单交种的基本程序，从理论上和育种模式上为玉米自交系间的杂种优势利用奠定了基础。到20世纪30年代，人们已经利用杂交玉米在生产上取得高产，自此杂种优势在农作物生产上的大规模应用便开始了，到1956年，全美已经普及了玉米杂交种。 玉米杂交种广泛成功应用，推动了作物杂种优势利用的探索和研究。随着雄性不育系的选育成功，创造了自花授粉作物和常异花授粉作物杂种优势利用的条件，扩大了杂种优势利用的领域，到20世纪50年代后期，美国已基本普及高粱杂交种。 我国对玉米杂种优势的研究利用较晚，20世纪50年代才推广品种间杂交种，60年代推广双交种，70年代推广单交种。杂交高粱始于20世纪50年代后期，育成并推广了一批高粱杂交种，现在高粱杂交种全世界已普及。我国有杂交水稻方面的研究并于20世纪70年代前期完成籼型和粳型三系配套，开创了自花授粉作物杂种优势利用的先例，处于国际领先地位。