| Soybean(Glycine max L.Merr.)is an essential worldwide oil-seed crop and is a good source of plant edible oil with high nutrition values.Therefore,it is of theoretical and practical significance to investigate the oil-related traits in soybean.Although to date there have been many studies on the genetic relationships between traits(or metabolites/lipids)and their genes in the past decades,there have been limited studies on the genetic relationships among traits,metabolites/lipids,and their genes,especially for non coding RNA.Therefore,it necessitates the studies on the genetic foundations for seed oil-related traits and lipid related metabolites via their multidimension genetic networks.To address this issue,in this study one multi-dimension genetic network among oil related traits,metabolites/lipids,genes,miRNAs and lincRNAs was constructed using genomics,metabolomics,lipomics,transcriptomics and other omics datasets.To obtain the candidate genes,miRNAs and lincRNAs for oil-related traits,firstly,six oil-related traits,measured at Wuhan in 2014,Ezhou in 2015,and Nanjing in 2015,249 metabolites,measured by GC-TOF MS at Nanjing in 2016,and 214 lipids,measured by Q Exactive orbitrap at Nanjing in 2016,in 398 soybean RILs were used to detect main-effect QTL,and QTL × environment and QTL × QTL interactions.Meanwhile,GGM model,MCP and SCAD analysis,along with t-test,were used to identify the significances of the metabolite-metabolite,lipid-lipid,metabolite-lipid,metabolite-trait and lipid-trait associations.Then,the above-mentioned candidate genes,miRNAs,and lincRNAs were used to constructed co-expression,ce RNA,and protein-protein interaction networks.Finally,the trait-gene and metabolite/lipid-gene associations obtained in the first step were integrated into the above-mentioned three types of networks so as to construct multi-dimension genetic networks.In the multi-dimension genetic network,the hub genes,vital metabolites and housekeeping lipids were mined to obtain key multi-dimension sub-networks.To validate these key sub-networks,the differences for the nodes(traits and metabolites)in these key sub-networks were tested using five high-oil RILs and five low-oil RILs.The main results were as follows.1)A total of 67 trait-lipid,93 lipid-metabolite,551 metabolite-metabolite and 885 lipid-lipid associations were found by GGM model,MCP and SCAD analysis,along with t-test,to be significant.Among them,24 trait-metabolite and 43 trait-lipid associations were found commonly between the trait average and BLUP.2)Among 1,222 significant main-effect QTLs detected in three environments and BLUP values for oil-related traits,175 QTLs were identified by at least two approaches and/or in at least two environments,including 32 for palmitic acid,21 for stearic acid,23 for oleic acid,40 for linoleic acid,38 for linolenic acid,and 21 for oil content,and 32 were pleiotropic.Among 36 QTL × environment interactions,7,6,7,5,9,2,and 2 were found to be associated with palmitic acid,stearic acid,oleic acid,linoleic acid,linolenic,and oil content,respectively.Among 19 QTL × QTL interactions,2,6,2,2,6,and 1 were found to be associated with above-mentioned corresponding traits,respectively.395,667,and 764 mQTLs were found by GCIM,ICIM and multi-locus GWAS methods,respectively,to be associated with 249 metabolites,while 674,1092,and 1332 m QTLs were found by the above-mentioned approaches,respectively,to be associated with 214 lipids.All the mQTLs for metabolites and lipids were merged into 339 m QTL clusters,including 31 for FAs,57 for phospholipids,and 251 for glycerolipids.Among these m QTL clusters,75 were identified in the above-mentioned stable QTLs for oil-related traits;30 were identified in the QTL × environment interaction detection;112 were consistent with the meta QTLs in Qi et al(2018),including 39 for fatty acids,59 for oil content,46 for protein content,and 28 meta QTLs for multiple traits.3)Around 175 trait QTLs and 339 m QTL clusters,142 candidate oil synthesis genes,109 miRNA,and 494 lincRNAs were found to be associated with oil-related traits;326 candidate acyl-lipid genes,228 miRNAs,and 1,226 lincRNAs were found to be associated with metabolites and lipids.75 candidate genes,i.e.,Gm DGAT1 a,Gm OLEO1,Gm PLDα1,and Gm PDCT/ROD1,were found to be associated commonly with oil related traits and lipids/metabolites,indicating the genetic correlation between oil-related traits and metabolites/lipids.4)The above-mentioned candidate genes,miRNAs and lincRNAs were used to construct co-expression,ce RNA,and PPI networks.In the co-expression network,six modules with distinct expression patterns were found to be related to acyl-lipid pathways at seed developmental stages,and included 175 hub genes,which were found to be associated with oil-related traits and metabolite/lipids.The dark green module was found to be related to seed nutrient accumulation and included 16 hub genes,i.e.,Gm FBPase,Gm WRI1,Gm LEC1 b,and Gm FUS3.The ce RNA network included post-transcriptional regulations,97 acyl lipid metabolism genes,57 miRNAs,and 49 lincRNAs.At the same time,10 hub genes were identified in this network.The protein-protein interaction network included 97 candidate genes,which participated five acyl-lipid pathways,in above-mentioned six co-expression modules.Here 20 were identified as hub genes with ‘date’ characteristics.5)The trait-gene and metabolite-gene associations were integrated into the co-expression,ce RNA,and PPI networks to obtain multi-dimension genetic networks for metabolites/lipids,oil-related traits,genes,miRNAs,and lincRNAs.Using the topological characteristics of each node in multi-dimension networks,10 vital metabolites related to six oil traits,23 housekeeping lipids,88 3D and 13 4D genetic sub-networks were identified.Among these selected sub-networks,53 are known in biological experiments,i.e.,Gm KAS-Oleic acid-TG(18:0/18:1/18:1).Meanwhile,all the trait nodes and 61 metabolite/lipid nodes in these selected subnetworks were found to have significant differences between five high-oil RILs and five low-oil RILs.In addition,11 oil-related metabolites,18 candidate genes,and 5 trait-gene associations in our previous study were also observed as well in this study.Sub-networks with hub genes Gm FAD2,Gm DGAT1 a,Gm LEC1 a,and Gm DGAT1 c revealed the genetic relationship between TAG/DAG and oil related traits.Sub-networks with hub genes Gm LPD1(E3)and Gm KAR revealed genetic relationships between the hub genes Gm NADP-MDH and fatty acid related traits.miR167,miR1513 and miR172 along with their target genes Gm LEC1 a,Gm LEC1 b,Gm PLDγ,Gm SPT and Gm KAS revealed the regulations in lipid metabolism and the genetic relationship between lipid metabolism and oil content traits.This study will provide abundant information for genetic regulations in lipid metabolism and genetic improvement in soybean breeding. |
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