Prescreening of large-effect markers with multiple strategies improves the accuracy of genomic prediction

Presently,integrating multi-omics information into a prediction model has become a ameliorate strategy for genomic selection to improve genomic prediction accuracy.Here,we set the genomic and transcriptomic data as the training population data,using BSLMM,TWAS,and eQTL mapping to prescreen features according to |β_(b)|>0,top 1%of phenotypic variation explained(PVE),expression-associated single nucleotide polymorphisms(eSNPs),and egenes(false discovery rate(FDR)<0.01),where these loci were set as extra fixed effects(named GBLUP-Fix)and random effects(GFBLUP)to improve the prediction accuracy in the validation population,respectively.The results suggested that both GBLUP-Fix and GFBLUP models could improve the accuracy of longissimus dorsi muscle(LDM),water holding capacity(WHC),shear force(SF),and pH in Huaxi cattle on average from 2.14 to 8.69%,especially the improvement of GFBLUP-TWAS over GBLUP was 13.66%for SF.These methods also captured more genetic variance than GBLUP.Our study confirmed that multi-omics-assisted large-effects loci prescreening could improve the accuracyofgenomic prediction.

Incorporating kernelized multi-omics data improves the accuracy of genomic prediction

Background:Genomic selection(GS)has revolutionized animal and plant breeding after the first implementation via early selection before measuring phenotypes.Besides genome,transcriptome and metabolome information are increasingly considered new sources for GS.Difficulties in building the model with multi-omics data for GS and the limit of specimen availability have both delayed the progress of investigating multi-omics.Results:We utilized the Cosine kernel to map genomic and transcriptomic data as n×n symmetric matrix(G matrix and T matrix),combined with the best linear unbiased prediction(BLUP)for GS.Here,we defined five kernel-based prediction models:genomic BLUP(GBLUP),transcriptome-BLUP(TBLUP),multi-omics BLUP(MBLUP,M=ratio×G+(1-ratio)×T),multi-omics single-step BLUP(mss BLUP),and weighted multi-omics single-step BLUP(wmss BLUP)to integrate transcribed individuals and genotyped resource population.The predictive accuracy evaluations in four traits of the Chinese Simmental beef cattle population showed that(1)MBLUP was far preferred to GBLUP(ratio=1.0),(2)the prediction accuracy of wmss BLUP and mss BLUP had 4.18%and 3.37%average improvement over GBLUP,(3)We also found the accuracy of wmss BLUP increased with the growing proportion of transcribed cattle in the whole resource population.Conclusions:We concluded that the inclusion of transcriptome data in GS had the potential to improve accuracy.Moreover,wmss BLUP is accepted to be a promising alternative for the present situation in which plenty of individuals are genotyped when fewer are transcribed.

A review of anodic catalysts and their application in(non-)Kolbe electrocatalytic decarboxylation of carboxylic acids

Biomass,as the exclusive and abundant organic resources,is considered to be the promising renewable resource.Carboxylic acids are one of the many compounds that can be obtained from raw biomass.Decarboxylation of carboxylic acids into fuels and chemicals via electrochemical method at mild reaction condition has been studied for many years.The(non-)Kolbe reaction,one of the oldest organic electrochemical reactions,is the decarboxylation of carboxylic acids to produce alkanes,alcohols,esters,etc.And electrode materials influence the production of electrocatalytic decarboxylation products from carboxylic acids.Therefore,this work mainly reviews the recent advances in applications of anodic materials for(non-)Kolbe electrocatalytic decarboxylation of carboxylic acids.It discusses the reaction mechanism of(non-)Kolbe electrolytic reaction,and the electrocatalytic oxidation of carboxylic acid using different electrodes and electrolytic systems to synthesize fuels and chemicals.Also,various types of electrode catalysts,such as Pt-based catalysts,C-based catalysts,and other catalysts,are introduced in detail.Finally,the challenges and future trends of the(non-)Kolbe reaction of carboxylic acids are presented.This review found that platinum-based electrocatalysts proved to be the most promising catalysts at present.And in recent years,a variety of synthesis methods have been developed to synthesize small size and high-performance noble metal based amorphous catalysts.Another approach is to study catalysts without platinum electricity,such as Ru,Ir,Ti and carbon materials.The review is helpful in understanding and know the anodic materials and their application in(non-)Kolbe electrocatalytic decarboxylation of carboxylic acids for the readers.