| Wheat is one of the most important staple food crops in many parts of the world.Nitrogen(N)is often considered to be the most important mineral nutrient element for crop growth and development.It is an important task to develop wheat varieties with high nitrogen efficiency.Using a set of recombinant inbred lines(RILs)derived from the cross of “Tainong 18 × Linmai 6”(TN18×LM6,TL-RIL),we constructed a high-density genetic map for unigenes by RNA-Seq and detected QTLs for nitrogen use efficiency(NUE)related traits at the seedling and maturity stages in wheat.The object of this study is to provide the basis for the marker assisted selection(MAS)and for the further research on the cloning and genetic mechanism of related genes.The major results were as follows:(1)RNA-Seq was performed on 184 lines and their parents of TL-RIL population.Seven stages of 184 TL-RILs and their parents were sampled.For RIL lines,two samples of the early stages and the late stages,respectively,per line were prepared for RNA sequencing.For the parents,the RNA were sequenced for the seven stages,respectively.A total of 2.29 T RNA sequence were obtained: 12 Gb data for each line and 42 Gb data for each parent.After screening and anchoring,1,142,959 markers were obtained by mutation analysis.Then the markers were filtered and the remaining 20,150 unigenes(including 98,431 markers)were used to construct the high-density genetic linkage map.The total length of the map was 16,023.1 cM,including 21 linkage groups,11,710 bins,15,475 unigenes,77,092 markers,and the average density was 1.37 cM/bin.The largest chromosome was 5B(1,348.9 cM),including 1,192 bins and the smallest chromosome is 4D,with a length of 217.8 cM,including 82 bins.Chromosome 1B had the highest density of 1.09 cM/bin and 3D had the lowest density with 3.23 cM/bin.The loci were distributed unevenly on A,B and D genomes.There were 3,945 bins,5,207 unigenes and 27,155 markers on genome A;B genome contained 5,735 bins,7,696 unigenes and 38,483 markers;D genome contained the least number of loci with 2,030 bins,2,572 unigenes and 11,454 markers.The total length of three genomes was 5,377.1 cM(33.56%)for genome A,7,112.7 cM(44.39%)for genome B,and 3,533.3 cM(22.05%)for genome D.Among the seven homologous groups,the fifth homologous group had the longest distance of 2,890.5 cM,contained 2,343 bins and the average distance was 1.23 cM/bin.The next homologous groups with a reduced distance in order were 1,2,6,7,3,and 4.This map was construceted by considering the physical position of markers.The QTL directly corresponds to the physical map and this was helpful to the prediction and verification of candidate genes.(2)The hydroponic culture trials were designed with high N(HN),moderate N(MN)and low N(LN)levels in two time frames using the TL-RILs;18 seedling traits related to NUE traits were investigated.The field trials were designed with CK and LN levels in four growing seasons;22 maturity traits related to NUE traits were investigated.The results of the ANOVA showed that the variance for treatments effects on all the seedling traits were significant at p ? 0.001 levels.The variance for genotype effects on root N concentration(RNC)and total N concentration(TNC)were not significant and not been used in the following QTL analysis;the N concentration(SNC)was significant at p ? 0.01;and the other traits were at p ? 0.001.For the field trial,most of the investigated traits were affected significantly by treatments at p ? 0.01 or p ? 0.001.Top sterile spikelet number per spike(TSSS)were not affected significantly by genotypes and not been used in the following QTL analysis;straw N concentration(StNC),straw N-use efficiency(StNUE)and N-use efficiency above ground(ANUE)were affected by genotypes significantly at p ? 0.01,and rest traits were all significant at p ? 0.001.The correlation coefficients(r)among the seedling traits were almost all significant between biomass traits,between N uptake efficiency(NUpE)traits,and between N utilization efficiency(NUtE)traits.For the maturity traits,there was a significant correlation between yield traits and between NUE traits,and yield traits were correlated with NUE traits to varying degrees.Furthermore,there was a significant correlation between most seedling traits and some maturity traits.The correlation analysis suggested that the biomass traits at seedling stage and some yield traits at maturity stage can be considered as the primary morphological indexes for the evaluation of NUE instead of using element determinations,and the outcomes make it easy to identify NUE on a large-scale.(3)For seedling traits,a total of 53(143 QTLs for trait-treatment combinations)relatively high-frequency QTLs(RHF-QTLs)were identified.Of these,34,12,and 7 QTLs were detected for the biomass traits,NUpE traits and NUtE traits,respectively.These RHF-QTLs were related to all the seedling traits except for RNUE and were located on 10 chromosomes with 16 RHF-QTLS on 5D and 15 on 4B.The additive effects of 17 QTLs were positive,showing that the increasing QTL effects came from TN18;whereas the other 36 QTLs were negative,showing that the increasing QTL effects came from LM6.Each RHF-QTL explained between 7.07%(QSdw-5D)to 31.29%(QRsfw-4B.2)of the phenotypic variations and 25 of them were over 10%.For maturity traits,a total of 105 RHF-QTLs traits(325 QTLs for trait-treatment combinations)were detected on 20 chromosomes except for 3D,with 23 on 4B.Among them,87,6 and 12 QTLs were detected for yield traits,NUpE traits and NUtE traits,respectively.These RHF-QTLs were identified for all the maturity traits except for StNC.Among them,62 QTLs showed positive additive effects with TN18 increasing the effects of QTLs,whereas 43 QTLs had negative effects with LM6 increasing the QTL effects.These RHF-QTLs could explain the phenotypic variation ranging from 4.54%(QSl-3A.3)to 40.26%(QSn-4B)and 42 of them were higher than 10%.(4)A total of 24 QTL clusters(C1-C24)composed of RHF-QTL for 33 traits were located on 10 chromosomes.The QTL clusters could be classified into three types: detected only for the seedling traits(Type I,including C3,C14,C16,C17 and C18),detected only for the maturity traits(Type II,C1,C6,C8,C9,C10,C11,C15,C19,C21,C22,C23 and C24)and detected simultaneously for seedling and maturity traits(Type III,C2,C4,C5,C7,C12,C13 and C20).It is found that there is a most important QTL cluster(C7)on 4B,which belongs to Type III.Cluster C7 included 27 RHF-QTLs.Among which,13 were detected in the seedling stage and 14 in the maturity stage,including biomass and yield traits as well as NUpE and NUtE traits.In addition,the contributions of all 27 RHF-QTLs were more than 10%,indicating that they were all major QTLs.The unigenes of the C7 cluster can be used for MAS in wheat breeding prograsms for high yield or high nitrogen efficiency. |
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