DYNAMIC VARIATIONS OF WATER QUALITY IN TAIHU LAKE AND MULTIVARIATE ANALYSIS OF ITS INFLUENTIAL FACTORS

ＤＹＮＡＭＩＣ ＶＡＲＩＡＴＩＯＮＳ ＯＦ ＷＡＴＥＲ ＱＵＡＬＩＴＹ ＩＮ ＴＡＩＨＵ ＬＡＫＥ ＡＮＤ ＭＵＬＴＩＶＡＲＩＡＴＥ ＡＮＡＬＹＳＩＳ ＯＦ ＩＴＳ ＩＮＦＬＵＥＮＴＩＡＬ ＦＡＣＴＯＲＳＤＹＮＡＭＩＣＶＡＲＩＡＴＩＯＮＳＯＦＷＡＴＥ...

Allopolyploidization increases genetic recombination in the ancestral diploid D genome during wheat evolution

Genetic recombination produces new allelic combinations,thereby introducing variation for domestication.Allopolyploidization has increased the evolutionary potential of hexaploid common wheat by conferring the advantages of heterosis and gene redundancy,but whether a relationship exists between allopolyploidization and genetic recombination is currently unknown.To study the impact of allopolyploid ization on genetic recombination in the ancestral D genome of wheat,we generated new synthetic hexaploid wheats by crossing tetraploid Triticum turgidum with multiple diploid Aegilops tauschii accessions,with subsequent chromosome doubling,to simulate the evolutionary hexaploidization process.Using the DArT-Seq approach,we determined the genotypes of two new synthetic hexaploid wheats with their parents,F;plants in a diploid population(2 x,D_(1)D_(1)×D_(2)D_(2))and its new synthetic hexaploid wheatderived population(6 x,AABBD_(1)D_(1)×AABBD_(2)D_(2)).About 11%of detected SNP loci spanning the D genome of Ae.tauschii were eliminated after allohexaploidization,and the degree of segregation distortion was increased in their hexaploid offspring from the F_(1) generation.Based on codominant genotypes,the mean genetic interval length and recombination frequency between pairs of adjacent and linked SNPs on D genome of the hexaploid F;population were 2.3 fold greater than those in the diploid F_(2) population,and the recombination frequency of Ae.tauschii was increased by their hexaploidization with T.turgidum.In conclusion,allopolyploidization increases genetic recombination of the ancestral diploid D genome of wheat,and DNA elimination and increased segregation distortion also occur after allopolyploidization.Increased genetic recombination could have produced more new allelic combinations subject to natural or artificial selection,helping wheat to spread rapidly to become a major global crop and thereby accelerating the evolution of wheat via hexaploidization.

WheatOmics:A platform combining multiple omics data to accelerate functional genomics studies in wheat

Dear Editor,Mold-breaking progress in whole-genome sequencing and rapid accumulation of multi-omics data have revolutionized the research strategies of functional genomics in wheat(Wang et al.,2018).However,how to access these vast multi-omics data and to extract key information on genes of in-terest,is still challenging for most wet-lab or field wheat re-searchers who have little bioinformatic experiences and cannot access the expensive computational resources.Here,we pre-sent WheatOmics(http://wheatomics.sdau.edu.cn/,previously designated as Triticeae Multi-omics Center,http://202.194.139.32/),a free,web-accessible,and user-friendly platform.WheatOmics not only empowers the effective access to the visualized multi-omics data of user-interested genes but also offers several distinctive and practical toolkits that can ease almost every aspect of wheat functional genomics studies(Figure 1A).

A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement

Gene regulation is central to all aspects of organism growth,and understanding it using large-scale functional datasets can provide a whole view of biological processes controlling complex phenotypic traits in crops.However,the connection between massive functional datasets and trait-associated gene discovery for crop improvement is still lacking.In this study,we constructed a wheat integrative gene regulatory network(wGRN)by combining an updated genome annotation and diverse complementary functional datasets,including gene expression,sequence motif,transcription factor(TF)binding,chromatin accessibility,and evolutionarily conserved regulation.wGRN contains 7.2 million genome-wide interactions covering 5947 TFs and 127439 target genes,which were further verified using known regulatory relationships,condition-specific expression,gene functional information,and experiments.We used wGRN to assign genome-wide genes to 3891 specific biological pathways and accurately prioritize candidate genes associated with complex phenotypic traits in genome-wide association studies.In addition,wGRN was used to enhance the interpretation of a spike temporal transcriptome dataset to construct high-resolution networks.We further unveiled novel regulators that enhance the power of spike phenotypic trait prediction using machine learning and contribute to the spike phenotypic differences among modern wheat accessions.Finally,we developed an interactive webserver,wGRN(http://wheat.cau.edu.cn/wGRN),for the community to explore gene regulation and discover trait-associated genes.Collectively,this community resource establishes the foundation for using large-scale functional datasets to guide trait-associated gene discovery for crop improvement.