A Study On Relationaships Of Yield With Dynamic Characteristics Of Biomass Accumulation And Stem-Leaf Traits And QTL Analyses Of Yield-Related Traits In A Recombinant Inbred Line Population Of Soybean

Yield is the most important trait for soybean breeding.It is a valuable strategy to study yield related traits or yield components for revealing genetic basis of yield since yield is believed a composite trait by many researchers.There are many traits relating yield including morphological,photosynthesis,physiological traits and yield components et al, all which can be summed uo to three kinds of trats,i.e.,biomass accumulation and partition, leaf-related traits and lodging in terms of the reports published.The two former determine size of yield and the latter can restrict a high yield.It is clear only for relation of yield with maturity time and growth habit in QTL locations.There is no report for QTL mapping for biomass,harest index and leaf area index.Although study on QTL mapping for lodging of soybean has been conducted for many years,there is absent of an affective method for precisely evaluating lodging due to demand to corresponging field environment.Crop breeders need a method for detecting lodging pential of plant.This paper employed a RIL population from a cross of Kefeng 1 and Nannong 1138-2 and tested phenotypic values of traits across two years to study dynamic characteristics of biomass accumulation and partition and relationships and QTL mapping for yield,biomass accumulation,harvest index,leaf area index canopy related traits and yield components.We work together with departent of statistics,university of Florida,to develop two genetic models for detecting genotype environment interactions for growth curves of plant height and QTL regulating ontogenetic allometry of stem with whole biomass.The aim of this paper is to supply molecular marker information and to study genetic basis of yield for yield enhancement of soybean.Through testing data of biomass accumulation and partition from 25 d after emergence to seed filling time,dynamic characteristics showed that(1) yield was positively and significantly correlated with under and above ground biomass accumulation and their correlation increased in the process of growth with the peak correlation coefficients during R5(start of seed filling) to R6(medium of seed filling).(2)The lines with yield at above 2500～2800 kg ha^-1 and stand plants at 190 000 ha^-1,had a significant higher biomass accumulation than medium yield and low yield lines.Biomass accumulation of the high yield lines was 300～330 kg ha^-1(R1),500 kg ha^-1(R3),650 kg ha^-1(R5) and 700 kg ha^-1 (the peak) for under ground part,and 1500～1600 kg ha^-1(R1),3100-3400 kg ha^-1(R3), 5500～6500 kg ha^-1(R5) and 7200～7800 kg ha^-1(the peak) for above ground part.Both of under and above ground biomass accumulation reached to peak at R5～R6.(3)Comprising with the medium and low yield lines,the high yield ones had significantly higher mean proportions of petiole and stem biomass to the whole biomass across the two years with 10.5%(at R1),11.7%(at R3),10.6%(at R5) and 8.2%(at R6) for petiole and 29.4%(R1), 32.0%(R3),30.8%(R5)å’Œ27.1%(R6)for stem,and significant lower proportions of leaf and root with 46.0%(R1),41.2%(R3),34.1%(R5) and 25.4%(R6) for leaf and 17.1%(R1),12.6%(R3),9.7%(R5)and 7.9%(R6) for root.Biomass in harvest time had the biggest correlation coefficient with yield followed by leaf area index,root,canopy width and canopy height and the lowest ones were yield components including pod number,seed weight,seed number per pod.The regression for traits obtained was as following.There appeared some negative exponential correlation between yield and biomass at R5,with the biomass of 5 500～6500 kg ha^-1 as the highest turning point.A linear correlation of yield with biomass at harvest stage was detected,but without upper limit of the biomass found in the present experiment.Leaf area index had a linear relation with yield and there did not occur the upper limit for size of biomass.There was an exponential correlation between yield and apparent harvest index,with 0.42 as the turning point,positive relationship as less than 0.42 and negative relationship as larger than 0.42.Biomass in harvest negatively related with harvet index which shows that harvest index will become a restricting factor as biomass accumulation to some high size.Analizing results using method of Pearson simple correlation showed that yield was closely and significantly related with root weight,canopy width,canopy height,seed weight,pod number,seed number per pod,pod number per node,pod number in branch and node number in main stem excluding effective branch and pod number in branch.Result of QTL mapping in the NJRIKY population showed that,(1)Nine yield QTLs were detected in NJRIKY population distributing with explaining ratios from 6%to 17%. Of those yield QTLs there are two major ones,qYDB1-1 and qYDD1a-2,which could been detected across the two years and other two QTL,qYDD2-1 and qYDD2-2 were also major yield QTLs for their biger axplaning retios(13%and 16%).The other five yield QTL appeared effects less than 10%.All the information showed the genetic basis of yield were composited of major genes and less efects' genes.(2) 6,9 and 6 QTLs for biomass at R1, R3 and R5 were identified in the population,respectively,with 2 of them being detected across R1 through R5 in both years.9 QTLs for root weight were found in five lingage groups with R² from 5.1%to 21.1%.The major QTL for root weight was qRTB1-1.Ten biomass QTLs were found with three QTLs,qBMB1-2,qBMC2-1 and qBMO-1,as major QTLs for biomass.(3)Ten apparent harcest indexes QTL have been detected with explain ration from 2%to 22%.qHIB1-2,qHIO-1 and qHIO-2 were major QTLs for this trait.(4) 9 QTLs for root weight were dected and the major QTL was qRTB1-1 with a explaining effect more than 10%.(5) 5 and 6 QTLs for LAI at R1 and R5 were detected in the population with R² from 6.4 to 26.2%.qLAIR3B1-1 was the major QTL for LM.4 and 12 QTLs for canopy width and canopy height.The marker interval,satt262-satt173,was the same for the two traits.QTLs for seed weight,seed number per pod and pod number were 6, 2 and 1 respectively with R² from 6.9%to 15.7%and corresponding major QTL was qSWB1-1,qSNPPO-2 and qPPB1.5,3,8 and 3 QTL were found for pod number at branch, pod number at main stem,node number of main stem and effective branch.Most of QTLs for yield and yield related traits were distributed in B1,C2 and O linkage groups.Among the marker intervals of yield QTLs,were found to have QTLs conferring biomass and apparent harvest index,leaf area index which implied a partial same genetic basis among the three traits.We can integrate linkage groups of QTLs of yield with yield closely related traits as gentic component of yield,which will benefit for revealing genetic basis of yield.Results of studying on lodging resistance indices and related QTLs showed that fresh matter moment(PF) had the best representation among the four indices studied which denoted lodging potential.QTL analysis was performed also for lodging score and lodging potential.Seven QTLs for lodging score were found but no common one between the two years.There were seven QTLs for lodging potential with explaining 5%～12%phenotypic variation,with the same QTL qPFC2-2 in two years as major QTL.We have mapped dynamic traits with university of Florida together.Two genetic models were developed by extending composite functional mapping for estimating the effects of QTL-environment interactions on growth curves of plant height and allometry of stem with whole biomass respectively.Three QTL for plant height wer detected locating B1, C2 and O linkage groups,we have characterized the dynamic patterns of the genetic effects of the QTLs governing growth curves of plant height and estimated the global effects of the underlying QTLs during the course of growth and development,and test the differentiation in the shapes of QTL genotype-specific growth curves between different environments.Employed allometry gentic model,four QTLs controlling allometry of stem with whole biomass were found.The two models have successfully detected several QTLs that cause significant genotype-environment interactions for plant height growth processes. The model provides a basis for deciphering the genetic architecture of trait expression adjusted to different biotic and abiotic environments for any organism and will help to study the genetic architecture of complex phenotypes and,therefore,gain better insights into the mechanistic regulation for developmental pattems and processes in organisms.