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 i...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.展开更多
Background A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle.To prioritize the putative variants and genes,we ra...Background A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle.To prioritize the putative variants and genes,we ran a com-prehensive genome-wide association studies(GWAS)analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle.Then,we applied expression quantitative trait loci(eQTL)mapping between the genotype variants and transcriptome of three tissues(longissimus dorsi muscle,backfat,and liver)in 120 cattle.Results We identified 1,580 association signals for 21 beef agronomic traits using GWAS.We then illuminated 854,498 cis-eQTLs for 6,017 genes and 46,970 trans-eQTLs for 1,903 genes in three tissues and built a synergistic network by integrating transcriptomics with agronomic traits.These cis-eQTLs were preferentially close to the transcription start site and enriched in functional regulatory regions.We observed an average of 43.5%improvement in cis-eQTL discovery using multi-tissue eQTL mapping.Fine-mapping analysis revealed that 111,192,and 194 variants were most likely to be causative to regulate gene expression in backfat,liver,and muscle,respectively.The transcriptome-wide association studies identified 722 genes significantly associated with 11 agronomic traits.Via the colocalization and Mendelian randomization analyses,we found that eQTLs of several genes were associated with the GWAS signals of agronomic traits in three tissues,which included genes,such as NADSYN1,NDUFS3,LTF and KIFC2 in liver,GRAMD1C,TMTC2 and ZNF613 in backfat,as well as TIGAR,NDUFS3 and L3HYPDH in muscle that could serve as the candidate genes for economic traits.Conclusions The extensive atlas of GWAS,eQTL,fine-mapping,and transcriptome-wide association studies aid in the suggestion of potentially functional variants and genes in cattle agronomic traits and will be an invaluable source for genomics and breeding in beef cattle.展开更多
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 th...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.展开更多
Background: Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinn...Background: Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinning these traits and promote the improvement of fatty acid profiles. In this study, we performed a genome-wide association study(GWAS) on fatty acid composition using high-density single nucleotide polymorphism(SNP) arrays in Chinese Wagyu cattle.Results: In total, we detected 15 and 8 significant genome-wide SNPs for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, respectively. Also, we identified nine candidate genes based on 100 kb regions around associated SNPs. Four SNPs significantly associated with C14:1 cis-9 were embedded with stearoyl-CoA desaturase(SCD), while three SNPs in total were identified for C22:6 n-3 within Phospholipid scramblase family member 5(PLSCR5), Cytoplasmic linker associated protein 1(CLASP1), and Chymosin(CYM). Notably, we found the top candidate SNP within SCD can explain ~ 7.37% of phenotypic variance for C14:1 cis-9.Moreover, we detected several blocks with high LD in the 100 kb region around SCD. In addition, we found three significant SNPs within a 100 kb region showing pleiotropic effects related to multiple FA groups(PUFA,n-6, and PUFA/SFA), which contains BAI1 associated protein 2 like 2(BAIAP2 L2), MAF bZIP transcription factor F(MAFF),and transmembrane protein 184 B(TMEM184 B).Conclusions: Our study identified several significant SNPs and candidate genes for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, and these findings will further assist the design of breeding programs for meat quality in cattle.展开更多
Enveloped viruses have been the leading causative agents of viral epidemics in the past decade,including the ongoing coronavirus disease 2019 outbreak.In epidemics caused by enveloped viruses,direct contact is a commo...Enveloped viruses have been the leading causative agents of viral epidemics in the past decade,including the ongoing coronavirus disease 2019 outbreak.In epidemics caused by enveloped viruses,direct contact is a common route of infection,while indirect transmissions through the environment also contribute to the spread of the disease,although their significance remains controversial.Bridging the knowledge gap regarding the influence of interfacial interactions on the persistence of enveloped viruses in the environment reveals the transmission mechanisms when the virus undergoes mutations and prevents excessive disinfection during viral epidemics.Herein,from the perspective of the driving force,partition efficiency,and viral survivability at interfaces,we summarize the viral and environmental characteristics that affect the environmental transmission of viruses.We expect to provide insights for virus detection,environmental surveillance,and disinfection to limit the spread of severe acute respiratory syndrome coronavirus 2.展开更多
Understanding the dynamics of soil respiration,microbial carbon use efficiency(CUE),and temperature sensitivity(Q_(10))in response to exogenous organic matter(EOM)input,soil aggregate size,and incubation temperature i...Understanding the dynamics of soil respiration,microbial carbon use efficiency(CUE),and temperature sensitivity(Q_(10))in response to exogenous organic matter(EOM)input,soil aggregate size,and incubation temperature is crucial for predicting soil carbon cycling responses to environmental changes.In this study,these interactions were investigated by 180-day incubation of soil aggregates supplemented with EOM at various temperatures(5°C,15°C and 25°C).The results reveal an‘L-shaped’trend in soil respiration on the time scale across all treatments,characterized by initial rapid declines followed by stability.EOM input and higher temperatures significantly enhance respiration rates.Notably,the respiratory rates of soil aggregates of different sizes exhibit distinct patterns based on the presence or absence of EOM.Under conditions without the addition of EOM,larger aggregates show relatively lower respiration rates.Conversely,in the presence of EOM,larger aggregates exhibit higher respiratory rates.Furthermore,Q_(10)decreases with increasing aggregate size.The relationship between Q_(10)and the substrate quality index(SQI)supports the carbon quality temperature(CQT)hypothesis,highlighting SQI’s influence on Q_(10)values,particularly during later incubation stages.Microbial CUE decreases with EOM input and rising temperatures.Meanwhile,aggregate size plays a role in microbial CUE,with smaller aggregates exhibiting higher CUE due to enhanced nutrient availability.In conclusion,the intricate interplay of EOM input,aggregate size,and temperature significantly shapes soil respiration,microbial CUE,and Q_(10).These findings underscore the complexity of these interactions and their importance in modeling soil carbon dynamics under changing environmental conditions.展开更多
17 β-Hydroxysteroid dehydrogenase type 8 （HSD17B8） is an important regulator of lipid and steroid metabolism. In the present study, we aimed to assess the effects of HSD17B8 on growth and meat quality traits in cat...17 β-Hydroxysteroid dehydrogenase type 8 （HSD17B8） is an important regulator of lipid and steroid metabolism. In the present study, we aimed to assess the effects of HSD17B8 on growth and meat quality traits in cattle. Transcription profile analysis showed that HSD17B8 was primarily expressed in the salpinx, liver, and testis. Meanwhile, we identified three SNPs （SNPI： intron 1-A91G; SNP2： exon 1-A90G; and SNP3： intron 8-A86G） of the bovine HSD17B8 gene and investigated its haplotype frequencies and linkage disequilibrium. The detected SNPs were found associated with growth traits （body weight, body length, height at withers, heart girth, hip width, and average daily gain） in native cattle populations （Nanyang and Jiaxian） as well as the meat quality traits （Warner- Bratzler shear force, rib area, dressing percentage, carcass weight, and backfat thickness） in commercial breeds （Angus, Hereford, Limousin, Luxi, Simmental, and Jinnan）. Our results provided evidence that polymorphisms in the HSD17B8 gene were associated with growth traits and meat quality traits. Moreover, our findings might be used for marker-assisted selection in beef cattle breeding program展开更多
基金funds from the National Natural Science Foundations of China(32172693)the Program of National Beef Cattle and Yak Industrial Technology System(CARS-37)。
文摘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.
基金supported by grants from the Central Public-interest Scientific Institution Basal Research Fund(2020-YWF-YB-02)the Young Scientists Fund of the National Natural Science Foundation of China(32202652)+1 种基金China Agriculture Research System of MOF and MARA(CARS-37)the Science and Technology Project of Inner Mongolia Autonomous Region(2020GG0210).
文摘Background A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle.To prioritize the putative variants and genes,we ran a com-prehensive genome-wide association studies(GWAS)analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle.Then,we applied expression quantitative trait loci(eQTL)mapping between the genotype variants and transcriptome of three tissues(longissimus dorsi muscle,backfat,and liver)in 120 cattle.Results We identified 1,580 association signals for 21 beef agronomic traits using GWAS.We then illuminated 854,498 cis-eQTLs for 6,017 genes and 46,970 trans-eQTLs for 1,903 genes in three tissues and built a synergistic network by integrating transcriptomics with agronomic traits.These cis-eQTLs were preferentially close to the transcription start site and enriched in functional regulatory regions.We observed an average of 43.5%improvement in cis-eQTL discovery using multi-tissue eQTL mapping.Fine-mapping analysis revealed that 111,192,and 194 variants were most likely to be causative to regulate gene expression in backfat,liver,and muscle,respectively.The transcriptome-wide association studies identified 722 genes significantly associated with 11 agronomic traits.Via the colocalization and Mendelian randomization analyses,we found that eQTLs of several genes were associated with the GWAS signals of agronomic traits in three tissues,which included genes,such as NADSYN1,NDUFS3,LTF and KIFC2 in liver,GRAMD1C,TMTC2 and ZNF613 in backfat,as well as TIGAR,NDUFS3 and L3HYPDH in muscle that could serve as the candidate genes for economic traits.Conclusions The extensive atlas of GWAS,eQTL,fine-mapping,and transcriptome-wide association studies aid in the suggestion of potentially functional variants and genes in cattle agronomic traits and will be an invaluable source for genomics and breeding in beef cattle.
基金This research was supported by the National Natural Science Foundations of China(31872975)the Science and Technology Project of Inner Mongolia Autonomous Region,China(2020GG0210)the Program of National Beef Cattle and Yak Industrial Technology System,China(CARS-37).
文摘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.
基金supported by the National Natural Science Foundations of China(31372294 and 31702084)Chinese Academy of Agricultural Sciences of Technology Innovation Project(CAAS-XTCX2016010,CAAS-ZDXT2018006,ASTIP-IAS-TS-9,ASTIP-IAS-TS-16 and ASTIP-IAS03)for the design of the study and data collectionpartly supported by Beijing City Board of Education Foundation(PXM2016_014207_000012)for the data analysis and interpretation of the study
文摘Background: Fatty acids are important traits that affect meat quality and nutritive values in beef cattle. Detection of genetic variants for fatty acid composition can help to elucidate the genetic mechanism underpinning these traits and promote the improvement of fatty acid profiles. In this study, we performed a genome-wide association study(GWAS) on fatty acid composition using high-density single nucleotide polymorphism(SNP) arrays in Chinese Wagyu cattle.Results: In total, we detected 15 and 8 significant genome-wide SNPs for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, respectively. Also, we identified nine candidate genes based on 100 kb regions around associated SNPs. Four SNPs significantly associated with C14:1 cis-9 were embedded with stearoyl-CoA desaturase(SCD), while three SNPs in total were identified for C22:6 n-3 within Phospholipid scramblase family member 5(PLSCR5), Cytoplasmic linker associated protein 1(CLASP1), and Chymosin(CYM). Notably, we found the top candidate SNP within SCD can explain ~ 7.37% of phenotypic variance for C14:1 cis-9.Moreover, we detected several blocks with high LD in the 100 kb region around SCD. In addition, we found three significant SNPs within a 100 kb region showing pleiotropic effects related to multiple FA groups(PUFA,n-6, and PUFA/SFA), which contains BAI1 associated protein 2 like 2(BAIAP2 L2), MAF bZIP transcription factor F(MAFF),and transmembrane protein 184 B(TMEM184 B).Conclusions: Our study identified several significant SNPs and candidate genes for individual fatty acids and fatty acid groups in Chinese Wagyu cattle, and these findings will further assist the design of breeding programs for meat quality in cattle.
基金funding from the National Natural Science Foundation of China(Nos.22036002,92043302,21577165,21906176)China Postdoctoral Science Foundation (2018M641495)Strategic Priority Research Program of the Chinese Academy of Sciences(XDPB2002).
文摘Enveloped viruses have been the leading causative agents of viral epidemics in the past decade,including the ongoing coronavirus disease 2019 outbreak.In epidemics caused by enveloped viruses,direct contact is a common route of infection,while indirect transmissions through the environment also contribute to the spread of the disease,although their significance remains controversial.Bridging the knowledge gap regarding the influence of interfacial interactions on the persistence of enveloped viruses in the environment reveals the transmission mechanisms when the virus undergoes mutations and prevents excessive disinfection during viral epidemics.Herein,from the perspective of the driving force,partition efficiency,and viral survivability at interfaces,we summarize the viral and environmental characteristics that affect the environmental transmission of viruses.We expect to provide insights for virus detection,environmental surveillance,and disinfection to limit the spread of severe acute respiratory syndrome coronavirus 2.
基金supported by the National Natural Science Foundation of China(31971532 and 32171648).
文摘Understanding the dynamics of soil respiration,microbial carbon use efficiency(CUE),and temperature sensitivity(Q_(10))in response to exogenous organic matter(EOM)input,soil aggregate size,and incubation temperature is crucial for predicting soil carbon cycling responses to environmental changes.In this study,these interactions were investigated by 180-day incubation of soil aggregates supplemented with EOM at various temperatures(5°C,15°C and 25°C).The results reveal an‘L-shaped’trend in soil respiration on the time scale across all treatments,characterized by initial rapid declines followed by stability.EOM input and higher temperatures significantly enhance respiration rates.Notably,the respiratory rates of soil aggregates of different sizes exhibit distinct patterns based on the presence or absence of EOM.Under conditions without the addition of EOM,larger aggregates show relatively lower respiration rates.Conversely,in the presence of EOM,larger aggregates exhibit higher respiratory rates.Furthermore,Q_(10)decreases with increasing aggregate size.The relationship between Q_(10)and the substrate quality index(SQI)supports the carbon quality temperature(CQT)hypothesis,highlighting SQI’s influence on Q_(10)values,particularly during later incubation stages.Microbial CUE decreases with EOM input and rising temperatures.Meanwhile,aggregate size plays a role in microbial CUE,with smaller aggregates exhibiting higher CUE due to enhanced nutrient availability.In conclusion,the intricate interplay of EOM input,aggregate size,and temperature significantly shapes soil respiration,microbial CUE,and Q_(10).These findings underscore the complexity of these interactions and their importance in modeling soil carbon dynamics under changing environmental conditions.
基金supported by the National Natural Science Foundation of China(No.31172193)the Program of the National Beef Cattle Industrial Technology System(CARS-38)+4 种基金the Chinese National High Technology Research and DevelopmentPrograms(No.2013AA102505-4)the Plan for Scientific Innovation Talent of Henan Province(No.134100510012)the Science&Technology Innovation Talents in Universities of Henan Province(No.2012 HASTIT027)the National 12th‘‘Five-Year’’Key Project(No.2011BAD28B04)the Technology Innovation Teams in Universities of Henan Province(No.14IRTSTHN012)
文摘17 β-Hydroxysteroid dehydrogenase type 8 （HSD17B8） is an important regulator of lipid and steroid metabolism. In the present study, we aimed to assess the effects of HSD17B8 on growth and meat quality traits in cattle. Transcription profile analysis showed that HSD17B8 was primarily expressed in the salpinx, liver, and testis. Meanwhile, we identified three SNPs （SNPI： intron 1-A91G; SNP2： exon 1-A90G; and SNP3： intron 8-A86G） of the bovine HSD17B8 gene and investigated its haplotype frequencies and linkage disequilibrium. The detected SNPs were found associated with growth traits （body weight, body length, height at withers, heart girth, hip width, and average daily gain） in native cattle populations （Nanyang and Jiaxian） as well as the meat quality traits （Warner- Bratzler shear force, rib area, dressing percentage, carcass weight, and backfat thickness） in commercial breeds （Angus, Hereford, Limousin, Luxi, Simmental, and Jinnan）. Our results provided evidence that polymorphisms in the HSD17B8 gene were associated with growth traits and meat quality traits. Moreover, our findings might be used for marker-assisted selection in beef cattle breeding program
