1. Microbiology and Infectious Disease
Download icon

Genetically diverse uropathogenic Escherichia coli adopt a common transcriptional program in patients with UTIs

  1. Anna Sintsova
  2. Arwen E Frick-Cheng
  3. Sara Smith
  4. Ali Pirani
  5. Sargurunathan Subashchandrabose
  6. Evan S Snitkin
  7. Harry Mobley  Is a corresponding author
  1. University of Michigan, United States
  2. Texas A&M University, United States
Research Article
Cite this article as: eLife 2019;8:e49748 doi: 10.7554/eLife.49748
6 figures, 11 tables and 2 additional files

Figures

Figure 1 with 5 supplements
Clinical UPEC isolates carry a highly variable set of virulence factors.

Phenotypic and genotypic information about the strains can be found in Figure 1—figure supplement 1, Figure 1—figure supplement 2, Table 1, and Table 2. (A) Clinical UPEC isolates were examined for presence of 40 virulence factors. Virulence factors were identified based on homology using BLAST searches (≥80% identity,≥90% coverage). The heatmap shows presence (black) or absence (white) of virulence factors across 14 UPEC strains. Hierarchical clustering based on presence/absence of virulence factors shows separate clustering of B1 isolates. (B) Log2 TPM for iron acquisition genes (top panel) and adhesins (bottom panel) in urine and patient samples. Gene expression of other virulence factors is shown in Figure 1—figure supplement 3. Correlations of virulence factor expression among in vitro and patient samples is shown in Figure 1—figure supplement 4. (C) Log2 TPM of fim (top panel) and flg (bottom panel) operons across the 14 UPEC strains during in vitro urine culture and human UTI.

https://doi.org/10.7554/eLife.49748.004
Figure 1—figure supplement 1
Growth curves for 14 clinical UPEC strains cultured in LB or filter-sterilized urine.
https://doi.org/10.7554/eLife.49748.005
Figure 1—figure supplement 2
Phylogenetic tree reconstruction of 14 clinical UPEC strains isolated in this study.

Antibiotic resistance profiles are indicated by filled in black circles (as determined by VITEK2 system (BioMerieux).) Patients with recurrent UTIs are indicated by filled in black square. MG1655, EC958, UTI89 and CFT073 are included for reference.

https://doi.org/10.7554/eLife.49748.006
Figure 1—figure supplement 3
Expression of virulence factor genes in urine and patient samples.
https://doi.org/10.7554/eLife.49748.007
Figure 1—figure supplement 4
Correlations among in vitro and patient samples measured by Pearson correlation coefficient of normalized gene expression of 40 virulence factors plotted according to hierarchical clustering of samples.
https://doi.org/10.7554/eLife.49748.008
Figure 1—figure supplement 5
Treatment with MICROBEnrich does not affect measures of gene expression.

Gene expression of a panel of genes was measured for HM86 (n = 3), and HM56 (n = 2) after 5 hr culture in filter-sterilized urine. After isolation RNA samples were either treated with MICROBEnrich or left untreated. Gene expression for each gene was measured by qRT-PCR. ΔCt between the gene of interest and gapA is shown.

https://doi.org/10.7554/eLife.49748.009
Figure 2 with 3 supplements
Core genome expression in patients is highly correlated.

The analysis details are described in Materials and methods, and figure supplements. (A)-(B) Histogram of Pearson correlation coefficients among all samples cultured in vitro (A) or isolated from patients (B) based either on core genome or accessory genome comparisons. Accessory genome includes genes that were found in at least two but fewer than 14 of the clinical isolates. (C) Correlations among in vitro and patient samples measured by Pearson correlation coefficient of normalized gene expression plotted according to hierarchical clustering of samples. (D) Pearson correlation coefficient among all samples cultured in vitro (URINE | URINE, median = 0.92), among all samples isolated from patients (PATIENT | PATIENT, median = 0.91), between samples cultured in urine and samples isolated from patients (URINE | PATIENT, median = 0.73), and between matching urine/patient samples (ex. HM14 | URINE vs HM14 | PATIENT), (URINE | PATIENT:matched, median = 0.74). (E) Principal component analysis of normalized gene expression of 14 clinical isolates in patients and in vitro urine cultures shows distinct clustering of in vitro and patient isolates.

https://doi.org/10.7554/eLife.49748.010
Figure 2—source data 1

Genes differentially expressed between B1 and B2 phylogroup strains during in vitroculture in urine.

https://doi.org/10.7554/eLife.49748.014
Figure 2—source data 2

Genes differentially expressed between B1 and B2 phylogroup strains during human UTI.

https://doi.org/10.7554/eLife.49748.015
Figure 2—figure supplement 1
Saturation curves.

Number of mapped reads was plotted against number of expressed genes detected for each sample (in vitro samples are shown in blue; patient samples are shown in red). Vertical line shows 3 million reads cut off at which samples appear to reach saturation.

https://doi.org/10.7554/eLife.49748.011
Figure 2—figure supplement 2
Expression ranges of core genome genes.

(A) Percentage of genes in the core genome that are expressed at a given level (>1 TPM,>10 TPMs,>100 TPMs,>1000 TPMs, where TPMs are transcripts per million) is shown for patient samples that reached saturation (see Supplementary Figure 2) and corresponding in vitro samples. (B) Percentage of genes in the core genome that are expressed at a given level (>1 TPM,>10 TPMs,>100 TPMs,>1000 TPMs) is shown for patient samples that did not reach saturation and corresponding in vitro samples.

https://doi.org/10.7554/eLife.49748.012
Figure 2—figure supplement 3
Effect of phylogenetic group on core genome expression.

(A) and (C) Clustering of UPEC strains cultured in filter-sterilized urine based on PCA analysis of core genome gene expression. (B) and (D) Clustering of UPEC isolated from patients based on PCA analysis of core genome gene expression. Samples in (A) and (B) are colored based on their phylogroup designation. Samples in (C) and (D) are colored based on whether the strain was isolated from a patient with recurrent UTI (Y) or without recurrent UTI (N).

https://doi.org/10.7554/eLife.49748.013
Figure 3 with 1 supplement
Patient-associated transcriptional signature is consistent with rapid bacterial growth.

(A) The DESeq2 R package was used to compare in vitro urine cultures gene expression to that in patients. Each UPEC strain was considered an independent replicate (n = 14). Genes were considered up-regulated (down-regulated) if log2 fold change in expression was higher (lower) than 2 (vertical lines), and P value < 0.05 (horizontal line). Using these cutoffs, we identified 149 upregulated genes, and 343 downregulated genes. GO/pathway analysis showed that a large proportion of these genes belonged to one of the four functional categories (see legend). For each category, only the genes that have met the significance cut off are shown. The sugar transporters upregulated in UTI patients are shown in figure supplement. (B) Mean normalized expression for genes belonging to differentially expressed functional categories/pathways. The number of up or down-regulated genes belonging to each category is indicated next to the category name.

https://doi.org/10.7554/eLife.49748.019
Figure 3—source data 1

Genes upregulated during human UTI.

https://doi.org/10.7554/eLife.49748.021
Figure 3—source data 2

Genes downregulated during human UTI.

https://doi.org/10.7554/eLife.49748.022
Figure 3—figure supplement 1
Gene expression of four sugar transporters upregulated in UTI patients.

Heatmap shows Log2 of normalized gene expression of ptsG, fruA, fruB and gntU for each in vitro and patient sample.

https://doi.org/10.7554/eLife.49748.020
Figure 4 with 1 supplement
UPEC optimize growth potential via resource reallocation during UTI.

(A) Percentage of reads that aligned to the core genome (2653 genes) out of total mapped reads. (B) Percentage of core genome reads that mapped to r-proteins (ribosomal subunit proteins, 48 genes). (C) Percentage of core genome reads that mapped to catabolic genes (defined as genes regulated by Crp and present in the core genome (277 genes). (D) Percentage of core genome reads that mapped to amino acid biosynthesis genes (54 genes). The equivalent analysis of Subashchandrabose et al. (2014) dataset is shown in the figure supplement.

https://doi.org/10.7554/eLife.49748.023
Figure 4—figure supplement 1
Resource reallocation analysis of Subashchandrabose et al. (2014) dataset.

Left panel. Percentage of core genome reads that mapped to r-proteins (ribosomal subunit proteins, 48 genes) in five clinical strains from Subashchandrabose et al. study. The outlier patient sample that has only 2% of core genome mapped to r-proteins could potentially be attributed to very low depth of sequencing for that sample (HM26, see Table 6). Right panel. Percentage of core genome reads that mapped to catabolic genes. URINE: in vitro culture in filter-sterilized urine, LB: in vitro culture in LB, PATIENT: human UTI.

https://doi.org/10.7554/eLife.49748.024
Increased expression of ribosomal subunit transcripts is a host specific response.

(A) Growth curve for HM43 strain cultured in LB and filter-sterilized urine. (B) Percentage of HM43 core genome reads that mapped to ribosomal subunit proteins under different conditions (URINE: in vitro culture in filter-sterilized urine, LB: in vitro culture in LB, MOUSE: mice with UTI, PATIENT: human UTI. (C) Percentage of HM43 core genome reads that mapped to catabolic genes under different conditions.

https://doi.org/10.7554/eLife.49748.027
Differential regulon expression suggests role for multiple regulators in resource reallocation.

Regulon expression for 8 out of 22 regulons enriched for genes downregulated in the patients. Expression of each gene in the regulon during in vitro culture (blue) or during UTI (red) is shown along the x-axis. Histograms show proportion of genes in the regulon expressed at any given level.

https://doi.org/10.7554/eLife.49748.030

Tables

Table 1
Sequence type for 14 clinical UPEC isolates
https://doi.org/10.7554/eLife.49748.002
StrainSequence typeAdkfumCgyrBIcdMdhpurArecA
HM01692135276554
HM03101434115181176
HM0613153404713362829
HM07641*9633*1312487
HM14Novel64416241314
HM17733624913171125
HM43Novel*40*1419361710203
HM54404*14*14101417774
HM5653813401913362830
HM57733624913171125
HM60648924879670582
HM66801324191423110
HM68998135215614172517
HM8612713141936231110
Table 2
In silico determined serotypes for 14 clinical UPEC strains
https://doi.org/10.7554/eLife.49748.003
StrainH_typeO_type
HM01H4O25
HM03H21NA
HM06H4O25
HM07H45O45
HM14H10O8
HM17H1O6
HM43H23NA
HM54H5O75
HM56H4O13/O135
HM57H1O2/O50
HM60H10O102
HM66H7O7
HM68H6O2/O50
HM86H31O6
Table 3
Summary of alignment statistics (% mapped).
https://doi.org/10.7554/eLife.49748.016
Sample:Total
reads
Mapped
reads
% Mapped% Mapped
to CDS
% Mapped
to misc_RNA
% Mapped
to rRNA
% Mapped
to tRNA
% Mapped
to sRNA
% Mapped
to tmRNA
HM01 | UR172884191648032695.374.915.510.010.2610.25.49
HM01 | UTI18496607371704020.180.443.3600.513.422.45
HM03 | UR21354719209275419877.774.7800.369.495.21
HM03 | UTI16544044805907648.780.182.4500.862.231.35
HM06 | UR233598472284737497.878.723.9600.336.33.23
HM06 | UTI5799351947090928.176.942.6200.361.550.87
HM07 | UR213122242098047398.475.26.0200.1910.324.79
HM07 | UTI708046882097350373.714.1400.62.080.77
HM14 | UR219273022153381798.276.135.3300.159.975.16
HM14 | UTI159447621296821881.380.512.2100.462.251.5
HM17 | UR197902151936029497.877.414.2900.137.023.32
HM17 | UTI2387458518425837.774.354.1400.732.731.6
HM43 | UR185414841823982698.476.545.0300.219.074.76
HM43 | UTI5830685981385591480.382.7600.373.952.38
HM54 | UR216125812116254497.974.964.130.010.127.174.06
HM54 | UTI1800084363019983577.333.050.010.521.540.98
HM56 | UR174941351713084797.977.934.0900.097.143.56
HM56 | UTI254087551493594858.879.412.5900.581.981.17
HM57 | UR192530781896674898.577.074.8500.088.263.86
HM57 | UTI1056298169267950.971.484.200.652.631.5
HM60 | UR158980451565191698.576.354.1400.097.474.05
HM60 | UTI76149837764255170.693.7600.71.841.04
HM66 | UR171840181673606697.474.154.9300.129.535.28
HM66 | UTI25954183798590.365.412.7100.461.420.67
HM68 | UR158416391556271198.278.312.8400.146.033.67
HM68 | UTI6541393124010893.773.114.800.834.582.73
HM86 | UR150196691460634697.276.064.0900.166.993.54
HM86 | UTI10667404641379460.178.332.800.773.081.62
Table 4
Summary of alignment statistics (raw counts).
https://doi.org/10.7554/eLife.49748.017
Sample:CDSmisc_RNArRNAtRNAsRNAtmRNA
HM01 | UR123459339079001504434351680592905367
HM01 | UTI29898891247441431913312698591056
HM03 | UR16274560999727447618119858851090263
HM03 | UTI64617811974332469006179905109081
HM06 | UR1798517490428743761601439268738927
HM06 | UTI362318112342823170157287340864
HM07 | UR1577698612622361773936321655371005391
HM07 | UTI15460608676130126814370816065
HM14 | UR163934711148443863262521461801110769
HM14 | UTI104410622864905059823291189194198
HM17 | UR1498623783064748248651358261642452
HM17 | UTI13700477622715134945027329443
HM43 | UR1396027691683621374501653607867656
HM43 | UTI65418102250032930200321597194030
HM54 | UR158639338734141662253261517844858505
HM54 | UTI4873058192289353329329732161939
HM56 | UR1334957670131378156971222601609922
HM56 | UTI118608353868455286723295607175048
HM57 | UR14617905919256157150691567276732845
HM57 | UTI662515389101360572434013929
HM60 | UR1194973164730662136011169464633959
HM60 | UTI54021528718115361140627958
HM66 | UR1240969382558351193231595303884439
HM66 | UTI52232216103661137534
HM68 | UR121870244423122222226938831571220
HM68 | UTI1755457115276161997011005265627
HM86 | UR11110009597368551234241021292517105
HM86 | UTI50238031798234649276197828103919
Table 5
GO modules differentially expressed in UTI patients.
https://doi.org/10.7554/eLife.49748.018
Go idAnnotatedSignificantExpectedP valueTerm
GO:0006518892416.630.03134peptide metabolic process
GO:0016052763614.20.00403carbohydrate catabolic process
GO:0044262752914.010.0022cellular carbohydrate metabolic process
GO:0015980702013.080.02632energy derivation by oxidation of organic compounds
GO:0043043691912.890.04306peptide biosynthetic process
GO:0046395652512.140.00556carboxylic acid catabolic process
GO:0006412631811.770.03421translation
GO:0008643553010.280.02488carbohydrate transport
GO:190382539127.290.04583organic acid transmembrane transport
GO:000803338137.10.0159tRNA processing
GO:190503938127.10.03786carboxylic acid transmembrane transport
GO:004636538217.10.04177monosaccharide catabolic process
GO:003421937206.910.0005carbohydrate transmembrane transport
GO:004271035116.540.04746biofilm formation
GO:004401034116.350.03879single-species biofilm formation
GO:000640034116.350.03879tRNA modification
GO:007232932155.980.02795monocarboxylic acid catabolic process
GO:000940130115.60.01501phosphoenolpyruvate-dependent sugar phosphotransferase system
GO:001060829105.420.03121posttranscriptional regulation of gene expression
GO:00342482694.860.03925regulation of cellular amide metabolic process
GO:00064172694.860.03925regulation of translation
GO:001574924134.480.03338monosaccharide transmembrane transport
GO:00512482394.30.01728negative regulation of protein metabolic process
GO:004427522114.110.04263cellular carbohydrate catabolic process
GO:00322692284.110.03829negative regulation of cellular protein metabolic process
GO:00158071973.550.04819L-amino acid transport
GO:00171481883.360.01044negative regulation of translation
GO:00342491883.360.01044negative regulation of cellular amide metabolic process
GO:19024751773.180.02607L-alpha-amino acid transmembrane transport
GO:00094091482.620.00144response to cold
GO:00422551492.620.00021ribosome assembly
GO:00193211482.620.03705pentose metabolic process
GO:00468351362.430.02143carbohydrate phosphorylation
GO:00065261282.240.00034arginine biosynthetic process
GO:00425421051.870.02449response to hydrogen peroxide
GO:00193231071.870.02539pentose catabolic process
Table 6
Summary of alignment statistics (% mapped) for Subashchandrabose et al. (2014).
https://doi.org/10.7554/eLife.49748.025
Sample:TotalMapped
reads
% MappedMapped
to CDS
Mapped to
misc_RNA
Mapped
to rRNA
Mapped
to tRNA
Mapped
to tmRNA
HM46 | UR841954388144752596.742.410.0560.550.010.01
HM26 | UTI2025325210009684.9416.750.2421.240.090.16
HM46 | UTI633384181078379817.036.930.1240.30.10.1
HM27 | LB674224986506561596.52.250.0455.60.020.01
HM27 | UTI672587481830817127.229.250.1345.490.080.2
HM26 | UR622429785999453896.392.310.0860.580.010.01
HM65 | LB734513467122133896.962.53051.410.010
HM69 | LB13769075813364972797.073.490.0567.260.010.01
HM69 | UTI725092143850655953.116.520.1342.090.040.21
HM46 | LB780180267559029796.892.780.0656.90.010.01
HM27 | UR981851809468353496.432.820.03610.010.01
HM26 | LB709198966867179896.832.020.0655.740.020.01
HM65 | UR760240087355593996.752.49055.040.010
HM65 | UTI734465765969671881.286.19040.30.040
HM69 | UR671127506483431196.612.450.0452.920.010.01
Table 7
Summary of alignment statistics (% mapped) for Subashchandrabose et al. (2014).
https://doi.org/10.7554/eLife.49748.026
SampleCDSmisc_RNArRNAtRNAtmRNA
HM46 | UR1960841369014931260473025604
HM26 | UTI16766323662126419491605
HM46 | UTI7477021294843458811028911281
HM27 | LB14636272608136173268117175088
HM27 | UTI16934482424583290041442736287
HM26 | UR1387110488473634562065325837
HM65 | LB180185803661219072631
HM69 | LB46645797188189896218138287949
HM69 | UTI251173351962162066801707081355
HM46 | LB20994934235643011663111358549
HM27 | UR26732833118557757240101528399
HM26 | LB13857663897138278745110815724
HM65 | UR182803904048661156751
HM65 | UTI3697360024059705240552
HM69 | UR1587484263223430817047377686
Table 8
Summary of alignment statistics (% mapped) for mouse UTI study.
https://doi.org/10.7554/eLife.49748.028
SampleTotal
reads
Mapped
reads
% MappedMapped
to CDS
Mapped to
misc_RNA
Mapped
to rRNA
Mapped
to tRNA
Mapped
to sRNA
Mapped
to tmRNA
HM43 | LB | rep1639666466281394698.273.015.4900.211.036.41
HM43 | LB | rep2378339573709086398.0471.595.9100.211.636.69
HM43 | UR | rep1431799464229300697.95638.900.0619.9611.94
HM43 | UR | rep2441769524309384097.5553.6410.940.010.0327.817.9
HM43 | mouse4431453736901748.3376.722.7500.246.114
Table 9
Summary of alignment statistics (% mapped) for mouse UTI study.
https://doi.org/10.7554/eLife.49748.029
SampleCDSmisc_RNArRNAtRNAsRNAtmRNA
HM43 | LB | rep145862961344923232712395069292614028787
HM43 | LB | rep22655454621925392047439643120752482416
HM43 | UR | rep12664407137652812182648884396685049595
HM43 | UR | rep2231154564714597296214049119799137714978
HM43 | mouse2831120101419558994225533147467
Table 10
GSEA results.

Gene sets found to be enriched in differentially expressed genes. For example, Lrp, Repressor indicates gene set repressed by Lrp (data obtained from RegulonDB 9.4). Expression indicates whether regulon expression was higher in patients of during in vitro culture in urine. Regulon size: number of genes in the gene set; Matched size: number of genes found in data set; NES: normalized enrichment score; FDR: false discovery rate.

https://doi.org/10.7554/eLife.49748.031
FunctionExpression
(higher in)
Regulon sizeMatched sizeNESFDR
LrpRepressorUrine85272.290799780
NarLRepressorUrine87652.244358010
LrpActivatorUrine38192.212695650
MetJRepressorUrine15142.128852230.00083422
CrpActivatorUrine4252772.121504020.00066738
CsgDActivatorUrine13122.011976930.00250267
GadXActivatorUrine23151.893503040.00929563
ModEActivatorUrine31281.872896060.0108449
YdeOActivatorUrine18141.819751460.02002136
FurRepressorUrine110661.766586930.02752936
PhoPActivatorUrine45331.76073790.0256334
RcsBActivatorUrine58281.706675580.03781812
HnsRepressorUrine144621.698806650.03657748
GadEActivatorUrine70381.694004780.03515655
RcsAActivatorUrine42241.686156330.03448122
NarPActivatorUrine32291.656758980.04045982
NarPRepressorUrine33261.64063590.04279074
FhlAActivatorUrine30151.625360480.04514074
FliZRepressorUrine20151.609489530.04750681
LexARepressorPatients5943−1.6960720.03586007
CraRepressorPatients5950−1.71218550.04267527
PurRRepressorPatients3131−1.7522990.04410253
FadRActivatorPatients1211−1.98715240.00342544
Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional information
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM01This studyStrain isolation described in Study Design section below
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM03This studyStrain isolation described in Study Design section below
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM06This studyStrain isolation described in Study Design section below
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM07This studyStrain isolation described in Study Design section below
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM14This studyStrain isolation described in Study Design section below
Strain, strain background
(Escherichia coli)
Uropathogenic Escherichia coli HM17This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM43This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM54This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM56This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM57This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM60This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM66This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM68This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM86This studyStrain isolation described in Study Design section below
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM26(Subashchandrabose et al., 2014)
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM27(Subashchandrabose et al., 2014)
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM46(Subashchandrabose et al., 2014)
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM65(Subashchandrabose et al., 2014)
Strain, strain background (Escherichia coli)Uropathogenic Escherichia coli HM69(Subashchandrabose et al., 2014)
Strain, strain background (Mus musculus)CBA/J
commercial assay or kitMICROBEnrich KitThermo FisherAM1901
commercial assay or kitRNeasy kitQiagen74104
commercial assay or kitTurbo DNase kitThermo FisherAM2238
commercial assay or kitiScript cDNA synthesis kitBio Rad1708890
commercial assay or kitScriptSeq Complete Gold Kit (Epidemiology)IlluminaDiscontinued
commercial assay or kitScriptSeq Complete Kit (Bacteria)IlluminaDiscontinued
commercial assay or kitPowerUP SYBR Green Master MixBio RadA25779
commercial assay or kitDynabeads mRNA DIRECT Purification kitThermo Fisher61011
chemical compound, drugRNAprotectQiagen76526
software, algorithmTrimmomatic(Bolger et al., 2014)0.36
software, algorithmBowtie2(Langmead and Salzberg, 2012)2.3.4
software, algorithmsamtools(Li, 2011)1.5
software, algorithmHTseq(Anders et al., 2015)0.9.1
software, algorithmGet_homologues(Contreras-Moreira and Vinuesa, 2013)20170807
software, algorithmDESeq2(Love et al., 2014)1.22.2

Additional files

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)