Study On Waterlogging Tolerance During Seedling Stage And Haploid Breeding In Maize

Maize haploid breeding method has a lot of advance than traditional breeding methodand many maize breeders focus on it. In this study, Stock6 was used to evaluate the effectof genotype and environment on the haploid induction frequency, the doubling efficiencyof colchicine, the success ratio of doubled haploid lines, the induction frequency of Stock6, and the accuracy rate of haploids identification.In tropical and subtropical regions, severe crop losses are always caused byprolonged seasonal rainfall. Waterlogging is also a serious environmental stress on maizegrown at maize seedling stage in southeastern China. As an other part of this study was toexplore screening methods or index and the best susceptible stage to waterlogging atmaize seedling stage. Two maize inbred lines, HZ32 is a highly tolerant inbred line andK12 is a highly susceptible inbred line to waterlogging which was identified using theWTC as the selection criteria, were used to construct the F₂ population and QTLassociated with waterlogging tolerance during the seedling stage in maize was mapped.The main results were as following:1. The haploid induction frequency was identified in 2003 and 2004 respectively.The results indicated that the haploid induction frequency was significantly affected bymaternal genotypes, while the environment hadn't this effect. The accuracy rate ofhaploid identification was low with the average value was 21.2ï¼…. Inhibit gene(s) for R-njcoloration was found in TZi9.2. The numbers of haploid plants with shedding pollen and plants with silking earwere tested in two combinations, (K12×HZ32) F₁ and (HuangZao4×HZ32) F₁, in theseason 2003. 13.7ï¼…of the haploids had fertile pollen. The average of haploid plants withsilk, which was 39.6ï¼…, was higher than the average of the haploid plants with sheddingpollen. All the results indicated that the main problem in doubling was from tassel not ear.3. All the genotypes separated into five grades to waterlogging tolerance accordingto the typical symptom of leaves and obtained highly tolerant genotypes such as HZ32,Jiao51 and highly susceptible genotypes such as TZi9, K12 and Mo17. The materials withdifferent genotype had significantly difference tolerance to waterlogging. The scorchdegree of leaf could be an important index for primary screen.4. Waterlogging tolerance coefficient (WTC) had significantly changed as treatmenttime elongation in three replication experiments. There was significantly negativelinearity correlation between treatment time and WTC of total dry weight, the linearityequation was: y=-0.03323x+0.96197(P＜0.0001). Comparing with the results of typicalsymptom of leaves and waterlogging tolerance coefficient, because WTC is a relative value without inherent variance of characteristics among varieties, it can be used as anindex for measuring tolerant or susceptible genotypes at waterlogging sensitive stage. Inaddition, we identified the best continued treatment time was 6 days after waterlogging.WTC of plant total dry weight and plant height were used to identify the relativesusceptible stage to waterlogging at maize seedling stage, the less is the WTC, the moresignificant difference is between control and waterlogging, so the V2 is the best treatmentstage.5. Six inbred lines were used to test the POD activities and MDA content.Comparing with the material screened results of WTC and the typical symptom of leaves,we deduced that POD activities and MDA contents can be used as the indexes to screentolerant or susceptible genotype associated with WTC.6. Leaves and roots of HZ32 and K12 were harvested 1 day before and 2, 4, 6, 8and 10 days after the start of waterlogging treatment. SOD, APX, GR, CAT and PODactivities and MDA content were measured. We deduced that CAT was the mostimportant H₂O₂ scavenging enzyme in leaves, while APX seems to play a key role in roots.POD, APX, GR and CAT activities in conjunction with SOD seem to play an essentialprotective role in the O₂·- and H₂O₂ scavenging process. These results indicated thatoxidative stress may play an important role in waterlogging-stressed maize plants and thatthe greater protection of HZ32 leaves and roots from waterlogging-induced oxidativedamage results, at least in part, through the maintenance of increased antioxidant enzymeactivity.7. Using composite interval mapping method, 59 QTL were detected for fivewaterlogging tolerance traits, which located on chromosomes 1, 2, 3, 4, 6, 7, 9 and 10,respectively. Fourteen QTL were detected under control and twenty-five were detectedunder waterlogging condition. The other twenty QTL were detected by WTC. The QTLindividually explained 3.9%-37.3% of the phenotypic variation.8. QTL cluster. 59 QTL were detected in EXP.1 and EXP.2. Eleven QTL cluster wasformed. The most important cluster was located on chromosome 9 between umc1519 andumc1231 interval. The other important QTL clusters were located on chromosome 3, 4and 7, respectively. All dusters could be detected by more than two traits, which indicatedthat they may have the same genetic mechanism to waterlogging.9. Epistatic interaction QTL was detected by the mean values of EXP.1 and EXP.2.Eight epistatic interaction QTL was detected under control. Three of eight was for majorQTLxmajor QTL. The other interaction QTL only had one major QTL. The epistaticinteraction QTL individually explained 4.62%-11.81% of the total phenotypic variation.Ten interaction QTL was detected under waterlogging condition. The digenic interaction QTL individually explained 7.6%-33.4% of the total phenotypic variation. Two of teninteracted QTL had two major QTLs, the other eight only had one major QTL. Therewere also ten epistatic QTL which were detected by WTC. Four of ten had two majorQTL, the other only had one major QTL. They could explain 5.98-25.49% of the totalphenotypic variation.10. Additive effects, partial dominance effects, dominance effects andoverdominance effects affected waterlogging tolerance QTL. Out of 59 QTL, six hadadditive effects, occupied 10%; 15 had partial dominance effects, occupied 25.4%; 12 haddominance effects, occupied 20.3%; 26 had overdominance effects, occupied 44%.