| Phosphorus is by far the least mobile and available to maize in most soil conditions compared with the other major nutrients.It is therefore frequently a major or even the prime constraint factor for maize growth.P fertilizers are costly,nonrenewably,potentially effective because of immobilization by the soil.Efficient nutrient acquisition is important for the productivity of low-input system and intensive system.Efficient phosphorus uptake and utilization are useful for reducing environmental impact from fertilizer runoff and leaching.Phosphorus is an essential nutrient for plant production,the phosphorus deficiency is one of the most common and serious environmental constraints in tropic regions,reducing maize mean yields.As a result,improving the adaptation and/or tolerance of maize to phosphorus deficiency is an important objective in most regions.Plants can actively improve their acquisition of P in several ways.Access to total soil P resources might be improved by increasing the absorbing area of the root system,through increased root length and root fiber number.QTL mapping provides a means to detect complex genetic characters such as QTL of plant in response to phosphorus deficiency,and allows the identification of molecular markers linked to desirable QTLs,so that these can be directly used to improve phosphorus absorption efficiency and root-related traits in marker-assisted selection.In maize,The QTLs for root number in Polj17×F-2 and QTL for root volume in B73×Mo17 were described.Tuberosa et al.(2002b)reported QTL regions influencing root diameter and root legth in hydroponics,while Guingo et al(1998) identified QTL for root weight.More recently,Giuliani et al.(2000)and Tuberosa et al.(2002b) described QTL fo root pulling force in hydroponics.The QTLs of root hair length,lateral branch length in hydroponics were studied,and a QTL flanked by npi409-nc007 for root hair length was mapped on chromosome 5.The previous studies in QTLs for root traits were in hydroponics,which was unnatural environment for plant growth.And the number of QTLs was a few.The linkage map for QTLs was short and distance between markers was comparatively large.Furthermore,the QTL for same root trait in different environments was not studied as so far.The genotypic responses to phosphorus deficiency was different,genotype×environment interaction are well known in many quantitative trait locus(QTL),which severely limits practice in plant breeding by using marker-assisted selection(MAS).Only identification of stable QTL responsible for phosphorus absorption efficiency and root-related traits across P levels,different environments,and different growth stages might be used in MAS.Construction of genetic linkage mapThe mapping population included 241 F2:3families derived from a corresponding number of randomly chosen F2 plants of the cross between inbreds 082(P deficiency tolerant)and Ye107(P deficiency susceptible),which were known to differ for phosphorus efficiency and root traits.The F2 families were reproduced in October,2006-February,2007 in Hainan,China.The F2:3families were reproduced in March,2007-July,2007 in Xiema,Beibei,China.For the F2:3population,436 SSRs primers presented polymorphism.From the polymorphic primers,only 297 of 436 polymorphic SSRs primers were used to develop the genetic map, whereas the other 139 SSRs primers were not used to map because of various reasons.The polymorphic bands ranged from 50bp to ll50bp were produced by each AFLP primer combination.The combination of P4M7 exhibited the highest polymorphism.1170 AFLP loci were used to map.The 421 loci from 275 SSR and 146 AFLP loci were placed on 13 linkage groups representing the 10 maize chromosomes,whereas the remaining 46 loci were not linked to map. Chromosome 2,3,and 5 were initially represented by two unlinked segments.These segments were assembled into single linkage group based on maize reference maps(maize GDB).The genetic map spanned 1,681.3 cM in length with an average interval of 3.84 cM between adjacent markers.The linkage groups in our study ranged from 241.3 lcM in chromosome 3 to 90.54cM in chromosome 8,and the distances between markers ranged from 3.02 cM in chromosome 5 to 7.54 cM.in chromosome 10.Some regions in all chromosomes presented larger distances between markers,but the distances larger than 50cM were not present,and the distances larger than 20cM were present in chromosome 3,9 and 10.The mean number of markers per chromosome was 42. And the number of markers ranged from 15 markers in chromosome 9 to 72 markers in chromosome 5.Some alterations in marker positions were observed for chromosome 6 and 7 compared with the positions presented in the Maize Data Bank site.The umc1006 and bnlg1161 markers were located in bin 6.02 and 7.04 in previous study,whereas they were located in bin 6.06 and 7.02 respectively in our study.In F2:3populations,the majority of markers fit the expected 1:2:1 to co-dominance markers and 1:3 to dominance markers(P＜0.01).But significant deviation from expected segregation was observed for 69 loci.Distorted loci were widely distributed in all chromosomes.Compared with the IBM map(Michael Leel et al.,2002;Natalya Sharopoval et al.,2002),the integration of AFLPs into the linkage map did not cause appreciable increment in the distance between adjacent SSR markers,which indicated AFLP was a reliable marker.Limited clustering of AFLP markers occurred on chromosomes 1,2,8 and 9.Other than these cases,AFLPs were distributed quite evenly.AFLPs allowed us to extend the map coverage of chromosome arms(on chromosome 1 and 6)and also to quickly increase marker density in a number of regions poorly covered with SSR.Compared the length of our map with that of the IBM map,sizeable fluctuation were evidenced among chromosomes.The Tx303×CO159 IF2 linkage map has a total map length of 1829.8 with an average SSR marker distance of 4.1 cM(347.7-714.5 cM per chromosome) (Gardiner et al.,1993;Davis et al.,1999).The T218×GT119 IF2 linkage map has a total map length of 1716.4 cM with an average SSR marker density of 6.3 cM(143.8-280.1 cM per chromosome)(McMullen et al.,2000).Compared with previous linkage map,the genetic map in our study spanned 1,681.3 cM in length with an average interval of 3.84 cM between adjacent markers has higher density markers.Compared with the linkage map used for QTL of P and root traits by ZHU J et al,the linkage map in our study also has higher density markers.The main results of analysis of QTLs for traitsThe genetic linkage map of chromosome 6 covered 117.6 cM with an average interval of 3.68 cM between adjacent markers,and then detected the QTLs affecting phosphorus absorption efficiency and root -related traits in the four environments,i.e.,KXDP,KXNP,SUDP1,and SUDP2.Since the QTLs of RW mapped in four environments are within approximate 0.2 cM of dupssr15 locus(bin 6.06)on chromosome 6,dupssr15 locus might be considered as the candidate gene for the QTL of root weight.In previous study,the region for QTL on bin 6.06 was for the QTL of root pulling force in hydroponics in Lo964×Lo1016(Tuberosa et al.,2002b).Among QTLs mapped for phosphorus absorption efficiency and root-related traits,one QTL was detected in two environments,one QTL were detected in three environments and one (dupssr15 locus(bin 6.06))was detected in all four environments.Most of QTL were detected in one environment,indicating that individual QTLs seem to be sensitive to the environmental factors.The stable locus of the same QTL was a few.The genotype×environment is important to the phenotypic expression level of important quantitative traits in different environments.In situations with strong genotype×environment,the same locus of QTLs for root weight also showed different levels of expression in the four environments examined.Interaction between the genotype×environments severely limits progress in selection for better adaptation/tolerance to the different sites,the different P levels,and the different growth stages.Although the genotype×environment interactions were obtained in this study,the genomic regions in dupssr15 locus(bin 6.06)for QTL of RW were free of the genotype×environment interactions while others were more affected by these.Identification of the non-environment specific QTLs or QTLs with minor QTLs×environment interaction should be particularly useful in MAS manipulation of breeding maize.The QTLs conferring RW of chromosome 6 were stable in four environments,suggesting the QTL in the dupssr15 locus is non-environment specific QTLs or QTLs with minor QTLs×environment interactions.The QTL detected at the same marker intervals in four environments indicate that QTL are stable and not easily affected by environmental factors.The favorable allele originating from 082 might be useful to improve phosphorus absorption efficiency and root weight in maize by means of marker-assisted selection.Aside from the gene action,the genotype×environments,the genotype×P levels,and the genotype×stages interaction is exists in acid phosphatase activities.Identification of the non-environment,non-P levels,and non-stages specific QTLs or QTLs with minor QTLs×environment,minor QTLs×P levels,and minor QTLs×stages interaction effects should be particularly useful in MAS manipulation of breeding maize.The QTLs conferring AP of chromosome 1 and 9 were detected in four treatments,and the phenotypic variation of which was explained 15-20%and 8-11%,suggesting the QTLs in the Bnlg1268a and P1M3/g loci are non-environment,non-P levels,and non-stages specific QTLs or QTLs with minor QTLs×environment,minor QTLs×P levels,and minor QTLs×stages interaction effects.The favorable allele originating from 082 and the favorable allele originating from Ye107 can be used to improve acid phosphatase activities in maize by means of marker-assisted selection.The QTLs for root exudations(RAP and RH)were detected in one site and the heritability varied highly.These results showed that root exudations repetition for QTLs was poor.The heritability of traits(PE,RBW,RRW,RTW and TPS)was high,but the number and loci of QTL for these traits still were not identical at two sites.Several authors have pointed out that only QTLs stable across different sites are useful for MAS.In contrast,other authors think that QTLs showing interaction between genotype and environment could allow the development of varieties adapting to different environments.Pleiotropy or linkage among QTLs for traitsPE was correlated with RPH,RBW,RRW,RLA,RTW and RFN suggested that phosphorus efficiency are not only affected by root traits,but also affected by above-ground plant parts(RPH,RBW,and RLA).TPS was correlated with RPH,RBW,RRW and RLA suggests that tolerance index to low P stress are affected collaboratively by root and above-ground plant parts. The distribution of the QTLs for the phenotypic traits showed a high concentration of QTLs in few chromosome regions.Many traits(for instance PE,RRW and TPS),which were correlated each other,were linked.This showed that these QTLs seem to be closely linked or pleiotropy.But RAP had no same position at two sites.Some QTLs(PE,RBW,RRW,RLA,TPS and RTW)were consistently detected at two sites.Two traits(RRW and RTW)are closely linked to PE in the interval mmc0282-phi333597(bins 5.05)on chromosome 5,and RRW and TPS are also closely linked to PE in the interval bnlg1346-bnlg1695(bins5.07)on chromosome 5.According to Aastveit(1993),there are three primary causes of correlation among traits:pleiotropy,linkage,and environmental effects.It also can be used to explain traits invested in our study.Location of QTLs for phosphorus efficiencyThe most important QTLs effects were detected on chromosome bins 1.06,4.08,5.05,5.07 and 5.08 for phosphorus efficiency.To our knowledge,the work described here was in the first comprehensive analysis of the location of QTL for traits by using relative quantity between normal and deficient phosphorus in field condition at two different sites.It is interesting to find that five common regions at two sites are in bnlg1556-bnlg1564(bins 1.06),in mmc0341-umc1101(bins4.08),in mmc0282-phi333597(bins 5.05)(for QTLs of PE,RRW and RTW),in bnlg1346-bnlg1695(bins 5.07)(for QTLs of PE,RRW and TPS)and in bnlg118a-umc2136(bins 5.08).The QTLs are normally located in clusters which contain genes controlling several traits and these QTLs mapped here can represent regions which are extremely important to improve genetically phosphorus efficiency.The heritability of the PE,PSW,RRW, RTW and TPS was generally high(＞60%)although the allele effects varied.It is important to stress here that in this case these QTLs are extremely stable,justifying even more importance in assisted selection programs.If true,the interval bnlg1556-bnlg1564(bins1.06), mmc0341-umc1101(bins4.08),mmc0282-phi333597(bins 5.05),bnlg1346-bnlg1695(bins 5.07)and bnlg118a-umc2136(bins 5.08)may be useful for improving phosphorus efficiency by means of marker-assisted selection.
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