Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing （RNA-Seq） to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in ...Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing （RNA-Seq） to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in analysis of RNA-Seq data involves mapping of short-read sequences to the reference genome. Reference-guided transcriptome assembly is an optional step, which is recommended if the aim is to identify novel transcripts. Following read mapping, the primary interest of biologists in many RNA-Seq studies is the investigation of differential expression between experimental groups. In this review, we discuss recent developments in RNA-Seq data analysis applied to model organisms, including methods and algorithms for direct mapping, reference-guided transcriptome assembly and differential expression analysis, and provide insights for the future direction of RNA-Seq.展开更多
A cDNA subtractive library enriched for dark-induced up-regulated ESTs was constructed by suppression subtractive hybridization(SSH) from leaf tissues of soybean cultivar DongNong L13 treated with short-day(8-h light/...A cDNA subtractive library enriched for dark-induced up-regulated ESTs was constructed by suppression subtractive hybridization(SSH) from leaf tissues of soybean cultivar DongNong L13 treated with short-day(8-h light/16-h dark) and long-day(16-h light/8-h dark) conditions.A total of 148 clones were sequenced,representing 76 unique ESTs which corresponded to about 20% of 738 clones from the cDNA library and showed a significant up-regulation of at least three fold verified by dot blot hybridization.The putative functions of ESTs were predicted by Blastn and Blastx.The 43 differentially expressed genes identified by subtractions were classified according to their putative functions generated by Blast analysis.Genetic functional analysis indicated that putative proteins encoded by these genes were related to diverse functions during organism development,which include biological regulation pathways such as transcription,signal transduction and programmed cell death,protein,nucleic acid and carbohydrate macromolecule degradation,the cell wall modification,primary and secondary metabolism and stress response.Two soybean transcription factors enhanced in SD conditions,GAMYB-binding protein and DNA binding protein RAV cDNAs that may be involved in SD soybean photoperiod response,had been isolated using 5'-and 3'-rapid amplification of cDNA ends(RACE)(Genbank Accession numbers DQ112540 and DQ147914).展开更多
The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically ...The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically characterized the transcript changes in the adherens junction pathway following injury. In this study, a rat model of sciatic nerve crush injury was established by forceps. Deep sequencing data were analyzed using comprehensive transcriptome analysis at 0, 1, 4, 7, and 14 days after injury. Results showed that most individual molecules in the adherens junctions were either upregulated or downregulated after nerve injury. The m RNA expression of ARPC1 B, ARPC3, TUBA8, TUBA1 C, CTNNA2, ACTN3, MET, HGF, NME1 and ARF6, which are involved in the adherens junction pathway and in remodeling of adherens junctions, was analyzed using quantitative real-time polymerase chain reaction. Most of these genes were upregulated in the sciatic nerve stump following peripheral nerve injury, except for CTNNA2, which was downregulated. Our findings reveal the dynamic changes of key molecules in adherens junctions and in remodeling of adherens junctions. These key genes provide a reference for the selection of clinical therapeutic targets for peripheral nerve injury.展开更多
During acute reperfusion,the expression profiles of long noncoding RNAs in adult rats with focal cerebral ischemia undergo broad changes.However,whether long noncoding RNAs are involved in neuroprotective effects foll...During acute reperfusion,the expression profiles of long noncoding RNAs in adult rats with focal cerebral ischemia undergo broad changes.However,whether long noncoding RNAs are involved in neuroprotective effects following focal ischemic stroke in rats remains unclear.In this study,RNA isolation and library preparation was performed for long noncoding RNA sequencing,followed by determining the coding potential of identified long noncoding RNAs and target gene prediction.Differential expression analysis,long noncoding RNA functional enrichment analysis,and co-expression network analysis were performed comparing ischemic rats with and without ischemic postconditioning rats.Rats were subjected to ischemic postconditioning via the brief and repeated occlusion of the middle cerebral artery or femoral artery.Quantitative real-time reverse transcription-polymerase chain reaction was used to detect the expression levels of differentially expressed long noncoding RNAs after ischemic postconditioning in a rat model of ischemic stroke.The results showed that ischemic postconditioning greatly affected the expression profile of long noncoding RNAs and mRNAs in the brains of rats that underwent ischemic stroke.The predicted target genes of some of the identified long noncoding RNAs(cis targets)were related to the cellular response to ischemia and stress,cytokine signal transduction,inflammation,and apoptosis signal transduction pathways.In addition,15 significantly differentially expressed long noncoding RNAs were identified in the brains of rats subjected to ischemic postconditioning.Nine candidate long noncoding RNAs that may be related to ischemic postconditioning were identified by a long noncoding RNA expression profile and long noncoding RNA-mRNA co-expression network analysis.Expression levels were verified by quantitative real-time reverse transcription-polymerase chain reaction.These results suggested that the identified long noncoding RNAs may be involved in the neuroprotective effects associated with ischemic postconditioning following ischemic stroke.The experimental animal procedures were approved by the Animal Experiment Ethics Committee of Kunming Medical University(approval No.KMMU2018018)in January 2018.展开更多
Chinese Sapium sebiferum(L.)Roxb has great potential to emerge as a promising biodiesel resource plant due to abundant oil content in seed.However,the unavailability of transcriptomic and genomic data impedes the prog...Chinese Sapium sebiferum(L.)Roxb has great potential to emerge as a promising biodiesel resource plant due to abundant oil content in seed.However,the unavailability of transcriptomic and genomic data impedes the progress of application in biodiesel production.Transcriptome analysis will help to further exploit tallow and kernel oil utilization in industry and facilitate molecular-breeding-based genetic improvement of S.sebiferum.Illumina hiseq 2000 sequencing platform was used to perform de novo transcriptome assembly and gene expression analyses of seeds from three strains in three developmental stages.A total of 188,254 unigenes over 200 bp were assembled with average length of 699 bp.These transcriptic unigenes were functionally assigned by GO and KEGG pathways.RPKM was used to identify differentially expressed unigenes of five cDNA libraries.Transcriptic genes endcoding enzymes related to fatty acid metabolism were evaluated.qRT-PCR was employed to confirm five key enzymes involved in fatty acid and triacylglycerol biosynthesis.This study provided comprehensive gene expression information of Chinese S.sebiferum seed at transcriptional level.These transcriptome data will facilitate high-oil-content genetic cultivation of S.sebiferum,which will further exploit tallow and kernel oil utilization in biodiesel industry.展开更多
Microbial aggregates of different sizes in aerobic granular sludge(AGS)systems have been shown to exhibit distinct microbial community compositions.However,studies comparing the microbial activities of different-sized...Microbial aggregates of different sizes in aerobic granular sludge(AGS)systems have been shown to exhibit distinct microbial community compositions.However,studies comparing the microbial activities of different-sized aggregates in AGS systems remain limited.In this study,genome-resolved metatranscriptomics was used to investigate microbial activity patterns within differently sized aggregates in a full-scale AGS plant.Our analysis revealed a weak correlation between the relative abundance of metagenome-assembled genomes(MAGs)and their transcriptomic activity,indicating that microbial abundance does not directly correspond to metabolic activity within the system.Flocculent sludge(FL;<0.2 mm)predominantly featured active nitrifiers and fermentative polyphosphate-accumulating organisms(PAOs)from Candidatus Phosphoribacter,while small granules(SG;0.2e1.0 mm)and large granules(LG;>1.0 mm)hosted more metabolically active PAOs affiliated with Ca.Accumulibacter.Differential gene expression analysis further supported these findings,demonstrating significantly higher expression levels of key phosphorus uptake genes associated with Ca.Accumulibacter in granular sludge(SG and LG)compared to flocculent sludge.Conversely,Ca.Phosphoribacter showed higher expression of these genes in the FL fraction.This study highlights distinct functional roles and metabolic activities of crucial microbial communities depending on aggregate size within AGS systems,offering new insights into optimizing wastewater treatment processes.展开更多
Background and aims:To identify biomarkers to predict acute liver failure and investigate the mechanisms and immune-related pathways linked to its onset and progression.Methods:We analyzed gene expression differences ...Background and aims:To identify biomarkers to predict acute liver failure and investigate the mechanisms and immune-related pathways linked to its onset and progression.Methods:We analyzed gene expression differences between patients with acute liver failure(ALF)and controls in the GSE14668 dataset.Clinically relevant modules and key ALF-associated genes were identified using weighted gene co-expression network analysis(WGCNA)in conjunction with differential gene expression(DEG)analysis.Enrichment analysis was carried out and protein–protein interaction networks were constructed to understand the functions and pathways.Six potential diagnostic biomarkers were identified using machine learning algorithms.Diagnostic performance was assessed via column charts and area under the curve calculations.Single-sample gene set enrichment analysis evaluated the relationship between known marker gene sets and potential biomarker expression.We also examined diagnostic biomarker mRNA levels in ALF models in vivo and in vitro.We estimated the relative infiltration levels of 22 immune cell subpopulations in ALF samples,and explored the link between diagnostic biomarkers and infiltrating immune cells.Result:We found 352 DEGs associated with ALF.WGCNA analysis and intersecting DEGs identified 191 significant ALF-related genes.Machine learning identified HORMAD2,WNT10A,ATP6V1E2,CMBL,ARRDC4,and LPIN2 as potential diagnostic biomarkers.Cell experiments and quantitative real-time polymerase chain reaction supported the therapeutic potential of eriodictyol for ALF.Immune infiltration analysis suggested that plasma cells,CD4 memory resting and activated T cells,macrophages,and neutrophils might play roles in the progression of ALF.Conclusion:We identified HORMAD2,WNT10A,ATP6V1E2,CMBL,ARRDC4,and LPIN2,as diagnostic biomarkers for ALF and demonstrated the effectiveness of eriodictyol for treating ALF.Immune cell infiltration may play a significant role in the pathogenesis and progression of ALF.展开更多
Predatory fungi possess intricate signal transduction systems that regulate their development and support successful infection of the host.Herein,we characterized three components of the cell wall integrity-controllin...Predatory fungi possess intricate signal transduction systems that regulate their development and support successful infection of the host.Herein,we characterized three components of the cell wall integrity-controlling pathway,namely protein kinase C(Ao PKC),SLT2-MAPK(Ao SLT2),and SWI6(Ao SWI6),in a representative nematode-trapping fungus Arthrobotrys oligospora,using gene disruption and multi-omics approaches.The phenotypic traits(such as mycelia development,conidiation,stress response,and trap morphogenesis) and metabolic profiles of ΔAopkc and ΔAoswi6 mutants were similar but differed from those of the ΔAoslt2 mutants.Transcriptomic analysis indicated that the genes differentially expressed in the absence of Aoswi6 were involved in DNA replication,repair,and recombination during trap formation.Moreover,the yeast two-hybrid assay showed that Ao PKC interacted with Ao SWI6,suggesting that in A.oligospora,PKC can directly regulate SWI6,bypassing the SLT2signaling cascade.Conclusively,our findings deepen our understanding of the regulatory mechanism of asexual development and lifestyle switching in nematode-trapping fungi.展开更多
Genome-wide transcriptome profiling identifies genes that are prone to differential expression(DE)across contexts,as well as genes with changes specific to the experimental manipulation.Distinguishing genes that are s...Genome-wide transcriptome profiling identifies genes that are prone to differential expression(DE)across contexts,as well as genes with changes specific to the experimental manipulation.Distinguishing genes that are specifically changed in a context of interest from common differentially expressed genes(DEGs)allows more efficient prediction of which genes are specific to a given biological process under scrutiny.Currently,common DEGs or pathways can only be identified through the laborious manual curation of experiments,an inordinately time-consuming endeavor.Here we pioneer an approach,Specific cOntext Pattern Highlighting In Expression data(SOPHIE),for distinguishing between common and specific transcriptional patterns using a generative neural network to create a background set of experiments from which a null distribution of gene and pathway changes can be generated.We apply SOPHIE to diverse datasets including those from human,human cancer,and bacterial pathogen Pseudomonas aeruginosa.SOPHIE identifies common DEGs in concordance with previously described,manually and systematically determined common DEGs.Further molecular validation indicates that SOPHIE detects highly specific but low-magnitude biologically relevant transcriptional changes.SOPHIE’s measure of specificity can complement log2 fold change values generated from traditional DE analyses.For example,by filtering the set of DEGs,one can identify genes that are specifically relevant to the experimental condition of interest.Consequently,these results can inform future research directions.All scripts used in these analyses are available at https://github.com/greenelab/generic-expression-patterns.Users can access https://github.com/greenelab/sophie to run SOPHIE on their own data.展开更多
文摘Recent advances in next-generation sequencing technology allow high-throughput RNA sequencing （RNA-Seq） to be widely applied in transcriptomic studies. For model organisms with a reference genome, the first step in analysis of RNA-Seq data involves mapping of short-read sequences to the reference genome. Reference-guided transcriptome assembly is an optional step, which is recommended if the aim is to identify novel transcripts. Following read mapping, the primary interest of biologists in many RNA-Seq studies is the investigation of differential expression between experimental groups. In this review, we discuss recent developments in RNA-Seq data analysis applied to model organisms, including methods and algorithms for direct mapping, reference-guided transcriptome assembly and differential expression analysis, and provide insights for the future direction of RNA-Seq.
文摘A cDNA subtractive library enriched for dark-induced up-regulated ESTs was constructed by suppression subtractive hybridization(SSH) from leaf tissues of soybean cultivar DongNong L13 treated with short-day(8-h light/16-h dark) and long-day(16-h light/8-h dark) conditions.A total of 148 clones were sequenced,representing 76 unique ESTs which corresponded to about 20% of 738 clones from the cDNA library and showed a significant up-regulation of at least three fold verified by dot blot hybridization.The putative functions of ESTs were predicted by Blastn and Blastx.The 43 differentially expressed genes identified by subtractions were classified according to their putative functions generated by Blast analysis.Genetic functional analysis indicated that putative proteins encoded by these genes were related to diverse functions during organism development,which include biological regulation pathways such as transcription,signal transduction and programmed cell death,protein,nucleic acid and carbohydrate macromolecule degradation,the cell wall modification,primary and secondary metabolism and stress response.Two soybean transcription factors enhanced in SD conditions,GAMYB-binding protein and DNA binding protein RAV cDNAs that may be involved in SD soybean photoperiod response,had been isolated using 5'-and 3'-rapid amplification of cDNA ends(RACE)(Genbank Accession numbers DQ112540 and DQ147914).
基金supported by the National Natural Science Foundation of China,No.31700926the Priority Academic Program Development of Jiangsu Higher Education Institutions of China
文摘The neural regeneration process is driven by a wide range of molecules and pathways. Adherens junctions are critical cellular junctions for the integrity of peripheral nerves. However, few studies have systematically characterized the transcript changes in the adherens junction pathway following injury. In this study, a rat model of sciatic nerve crush injury was established by forceps. Deep sequencing data were analyzed using comprehensive transcriptome analysis at 0, 1, 4, 7, and 14 days after injury. Results showed that most individual molecules in the adherens junctions were either upregulated or downregulated after nerve injury. The m RNA expression of ARPC1 B, ARPC3, TUBA8, TUBA1 C, CTNNA2, ACTN3, MET, HGF, NME1 and ARF6, which are involved in the adherens junction pathway and in remodeling of adherens junctions, was analyzed using quantitative real-time polymerase chain reaction. Most of these genes were upregulated in the sciatic nerve stump following peripheral nerve injury, except for CTNNA2, which was downregulated. Our findings reveal the dynamic changes of key molecules in adherens junctions and in remodeling of adherens junctions. These key genes provide a reference for the selection of clinical therapeutic targets for peripheral nerve injury.
基金the National Natural Science Foundation of China,No.31560295(to LYL)the Yunnan Applied Basic Research Projects of China,Nos.2018FE001(-016)(to WM),2018FE001(-163)(to LYL)the Research Innovation Team of Yunnan Province of China,No.2019HC022(to LYL).
文摘During acute reperfusion,the expression profiles of long noncoding RNAs in adult rats with focal cerebral ischemia undergo broad changes.However,whether long noncoding RNAs are involved in neuroprotective effects following focal ischemic stroke in rats remains unclear.In this study,RNA isolation and library preparation was performed for long noncoding RNA sequencing,followed by determining the coding potential of identified long noncoding RNAs and target gene prediction.Differential expression analysis,long noncoding RNA functional enrichment analysis,and co-expression network analysis were performed comparing ischemic rats with and without ischemic postconditioning rats.Rats were subjected to ischemic postconditioning via the brief and repeated occlusion of the middle cerebral artery or femoral artery.Quantitative real-time reverse transcription-polymerase chain reaction was used to detect the expression levels of differentially expressed long noncoding RNAs after ischemic postconditioning in a rat model of ischemic stroke.The results showed that ischemic postconditioning greatly affected the expression profile of long noncoding RNAs and mRNAs in the brains of rats that underwent ischemic stroke.The predicted target genes of some of the identified long noncoding RNAs(cis targets)were related to the cellular response to ischemia and stress,cytokine signal transduction,inflammation,and apoptosis signal transduction pathways.In addition,15 significantly differentially expressed long noncoding RNAs were identified in the brains of rats subjected to ischemic postconditioning.Nine candidate long noncoding RNAs that may be related to ischemic postconditioning were identified by a long noncoding RNA expression profile and long noncoding RNA-mRNA co-expression network analysis.Expression levels were verified by quantitative real-time reverse transcription-polymerase chain reaction.These results suggested that the identified long noncoding RNAs may be involved in the neuroprotective effects associated with ischemic postconditioning following ischemic stroke.The experimental animal procedures were approved by the Animal Experiment Ethics Committee of Kunming Medical University(approval No.KMMU2018018)in January 2018.
基金funded by the National Science&Technology Pillar Program during the Twelfth Five-year Plan Period of China(2011BAD22B08).
文摘Chinese Sapium sebiferum(L.)Roxb has great potential to emerge as a promising biodiesel resource plant due to abundant oil content in seed.However,the unavailability of transcriptomic and genomic data impedes the progress of application in biodiesel production.Transcriptome analysis will help to further exploit tallow and kernel oil utilization in industry and facilitate molecular-breeding-based genetic improvement of S.sebiferum.Illumina hiseq 2000 sequencing platform was used to perform de novo transcriptome assembly and gene expression analyses of seeds from three strains in three developmental stages.A total of 188,254 unigenes over 200 bp were assembled with average length of 699 bp.These transcriptic unigenes were functionally assigned by GO and KEGG pathways.RPKM was used to identify differentially expressed unigenes of five cDNA libraries.Transcriptic genes endcoding enzymes related to fatty acid metabolism were evaluated.qRT-PCR was employed to confirm five key enzymes involved in fatty acid and triacylglycerol biosynthesis.This study provided comprehensive gene expression information of Chinese S.sebiferum seed at transcriptional level.These transcriptome data will facilitate high-oil-content genetic cultivation of S.sebiferum,which will further exploit tallow and kernel oil utilization in biodiesel industry.
基金sponsored by the Irish Research Council(IRC)as a Starting Laureate Award(Grant No.IRCLA/2017/246)IRC Postdoctoral Fellowship(Grant No.GOIPD/2023/1290).
文摘Microbial aggregates of different sizes in aerobic granular sludge(AGS)systems have been shown to exhibit distinct microbial community compositions.However,studies comparing the microbial activities of different-sized aggregates in AGS systems remain limited.In this study,genome-resolved metatranscriptomics was used to investigate microbial activity patterns within differently sized aggregates in a full-scale AGS plant.Our analysis revealed a weak correlation between the relative abundance of metagenome-assembled genomes(MAGs)and their transcriptomic activity,indicating that microbial abundance does not directly correspond to metabolic activity within the system.Flocculent sludge(FL;<0.2 mm)predominantly featured active nitrifiers and fermentative polyphosphate-accumulating organisms(PAOs)from Candidatus Phosphoribacter,while small granules(SG;0.2e1.0 mm)and large granules(LG;>1.0 mm)hosted more metabolically active PAOs affiliated with Ca.Accumulibacter.Differential gene expression analysis further supported these findings,demonstrating significantly higher expression levels of key phosphorus uptake genes associated with Ca.Accumulibacter in granular sludge(SG and LG)compared to flocculent sludge.Conversely,Ca.Phosphoribacter showed higher expression of these genes in the FL fraction.This study highlights distinct functional roles and metabolic activities of crucial microbial communities depending on aggregate size within AGS systems,offering new insights into optimizing wastewater treatment processes.
文摘Background and aims:To identify biomarkers to predict acute liver failure and investigate the mechanisms and immune-related pathways linked to its onset and progression.Methods:We analyzed gene expression differences between patients with acute liver failure(ALF)and controls in the GSE14668 dataset.Clinically relevant modules and key ALF-associated genes were identified using weighted gene co-expression network analysis(WGCNA)in conjunction with differential gene expression(DEG)analysis.Enrichment analysis was carried out and protein–protein interaction networks were constructed to understand the functions and pathways.Six potential diagnostic biomarkers were identified using machine learning algorithms.Diagnostic performance was assessed via column charts and area under the curve calculations.Single-sample gene set enrichment analysis evaluated the relationship between known marker gene sets and potential biomarker expression.We also examined diagnostic biomarker mRNA levels in ALF models in vivo and in vitro.We estimated the relative infiltration levels of 22 immune cell subpopulations in ALF samples,and explored the link between diagnostic biomarkers and infiltrating immune cells.Result:We found 352 DEGs associated with ALF.WGCNA analysis and intersecting DEGs identified 191 significant ALF-related genes.Machine learning identified HORMAD2,WNT10A,ATP6V1E2,CMBL,ARRDC4,and LPIN2 as potential diagnostic biomarkers.Cell experiments and quantitative real-time polymerase chain reaction supported the therapeutic potential of eriodictyol for ALF.Immune infiltration analysis suggested that plasma cells,CD4 memory resting and activated T cells,macrophages,and neutrophils might play roles in the progression of ALF.Conclusion:We identified HORMAD2,WNT10A,ATP6V1E2,CMBL,ARRDC4,and LPIN2,as diagnostic biomarkers for ALF and demonstrated the effectiveness of eriodictyol for treating ALF.Immune cell infiltration may play a significant role in the pathogenesis and progression of ALF.
基金supported by the National Natural Science Foundation of China(31960556,U1402265,32160665)the Applied Basic Research Foundation of Yunnan Province(202001BB050004)Postdoctoral Science Foundation of Yunnan Province。
文摘Predatory fungi possess intricate signal transduction systems that regulate their development and support successful infection of the host.Herein,we characterized three components of the cell wall integrity-controlling pathway,namely protein kinase C(Ao PKC),SLT2-MAPK(Ao SLT2),and SWI6(Ao SWI6),in a representative nematode-trapping fungus Arthrobotrys oligospora,using gene disruption and multi-omics approaches.The phenotypic traits(such as mycelia development,conidiation,stress response,and trap morphogenesis) and metabolic profiles of ΔAopkc and ΔAoswi6 mutants were similar but differed from those of the ΔAoslt2 mutants.Transcriptomic analysis indicated that the genes differentially expressed in the absence of Aoswi6 were involved in DNA replication,repair,and recombination during trap formation.Moreover,the yeast two-hybrid assay showed that Ao PKC interacted with Ao SWI6,suggesting that in A.oligospora,PKC can directly regulate SWI6,bypassing the SLT2signaling cascade.Conclusively,our findings deepen our understanding of the regulatory mechanism of asexual development and lifestyle switching in nematode-trapping fungi.
基金supported by grants from the Gordon and Betty Moore Foundation of USA(Grant No.GBMF4552 to CSG)the National Institutes of Health of USA(Grant Nos.R01 HG010067 to CSG,R01 CA237170 to CSG,U01 CA231978 to JCC)+3 种基金the Cystic Fibrosis Foundation of USA(Grant No.HOGAN19G0 to DAH)Support for the project was also provided by Dart CF at the Geisel School of Medicine at Dartmouth to DAH,which is supported by NIH NIDDK(Grant No.P30 DK117469)the Cystic Fibrosis Foundation’s Research Development Program of USA(Grant No.STANTO19R0)the bio MT through NIH NIGMS(Grant No.P20 GM113132)。
文摘Genome-wide transcriptome profiling identifies genes that are prone to differential expression(DE)across contexts,as well as genes with changes specific to the experimental manipulation.Distinguishing genes that are specifically changed in a context of interest from common differentially expressed genes(DEGs)allows more efficient prediction of which genes are specific to a given biological process under scrutiny.Currently,common DEGs or pathways can only be identified through the laborious manual curation of experiments,an inordinately time-consuming endeavor.Here we pioneer an approach,Specific cOntext Pattern Highlighting In Expression data(SOPHIE),for distinguishing between common and specific transcriptional patterns using a generative neural network to create a background set of experiments from which a null distribution of gene and pathway changes can be generated.We apply SOPHIE to diverse datasets including those from human,human cancer,and bacterial pathogen Pseudomonas aeruginosa.SOPHIE identifies common DEGs in concordance with previously described,manually and systematically determined common DEGs.Further molecular validation indicates that SOPHIE detects highly specific but low-magnitude biologically relevant transcriptional changes.SOPHIE’s measure of specificity can complement log2 fold change values generated from traditional DE analyses.For example,by filtering the set of DEGs,one can identify genes that are specifically relevant to the experimental condition of interest.Consequently,these results can inform future research directions.All scripts used in these analyses are available at https://github.com/greenelab/generic-expression-patterns.Users can access https://github.com/greenelab/sophie to run SOPHIE on their own data.
