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A comprehensive joint analysis of the long and short RNA transcriptomes of human erythrocytes.

Doss, Jennifer F., Corcoran, David L., Jima, Dereje D., Telen, Marilyn J., Dave, Sandeep S., Chi, Jen-Tsan·2015·BMC Genomics
DOI 10.1186/s12864-015-2156-2PMC PMC4647483
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Fig. 1 Population characteristics of erythrocyte long RNAs. a Distribution of total number of expressed transcripts across indicated cell types. A transcript was considered expressed if the RPKM value was ≥0.5. b GSEA analysis of the top 500 expressed erythrocyte transcripts in the ranked expressed transcripts of the day 8 erythroid progenitor (D8) vs. PBMC samples. c Distribution of the genomic location for RNA-Seq reads. Locations represent average number of reads for the three RBC, three PBMC, and two erythroid progenitor independent samples. Intronic reads are included if <10 kb upstream of a transcription start site or <10 kb downstream of a transcription end site
Fig. 1 Population characteristics of erythrocyte long RNAs. a Distribution of total number of expressed transcripts across indicated cell types. A transcript was considered expressed if the RPKM value was ≥0.5. b GSEA analysis of the top 500 expressed erythrocyte transcripts in the ranked expressed transcripts of the day 8 erythroid progenitor (D8) vs. PBMC samples. c Distribution of the genomic location for RNA-Seq reads. Locations represent average number of reads for the three RBC, three PBMC, and two erythroid progenitor independent samples. Intronic reads are included if <10 kb upstream of a transcription start site or <10 kb downstream of a transcription end siteCC BY · PubMed Central
Fig. 2 MicroRNA identification pipeline and microRNA population characteristics. a Deep sequencing of short RNAs from mature RBCs was performed using the Illumina HiSeq technology. Raw sequences were mapped to the genome, filtered through miRDeep, and categorized. Identified microRNA loci were cross-referenced with miRBase (v. 21) and UCSC Genome Browser (hg 38) to distinguish between candidate novel and known microRNAs. b Relative percentages (log base 10) of read numbers for top 10 microRNAs among five different samples. Percentages are averages based on total number of known, mature microRNA reads for each sample. c Relative percentage representation of genomic location for both known and putative microRNAs. Listed genomic locations for mature microRNA sequences are relative to RefSeq annotated transcripts in UCSC genome browser (hg38). For mature microRNA sequences spanning both introns and coding region, or UTR and coding regions of alternative transcripts, sequence is listed in coding region. d Relative percentage representation of sequence conservation for both known and putative microRNAs. Conservation of mature microRNA sequence indicates exact sequence alignment in listed number of species (from human, chimp, rhesus monkey, dog, mouse, and zebrafish), allowing for up to one base mismatch outside of the microRNA seed sequence (nucleotides 2–8), and no mismatches within the seed sequence
Fig. 2 MicroRNA identification pipeline and microRNA population characteristics. a Deep sequencing of short RNAs from mature RBCs was performed using the Illumina HiSeq technology. Raw sequences were mapped to the genome, filtered through miRDeep, and categorized. Identified microRNA loci were cross-referenced with miRBase (v. 21) and UCSC Genome Browser (hg 38) to distinguish between candidate novel and known microRNAs. b Relative percentages (log base 10) of read numbers for top 10 microRNAs among five different samples. Percentages are averages based on total number of known, mature microRNA reads for each sample. c Relative percentage representation of genomic location for both known and putative microRNAs. Listed genomic locations for mature microRNA sequences are relative to RefSeq annotated transcripts in UCSC genome browser (hg38). For mature microRNA sequences spanning both introns and coding region, or UTR and coding regions of alternative transcripts, sequence is listed in coding region. d Relative percentage representation of sequence conservation for both known and putative microRNAs. Conservation of mature microRNA sequence indicates exact sequence alignment in listed number of species (from human, chimp, rhesus monkey, dog, mouse, and zebrafish), allowing for up to one base mismatch outside of the microRNA seed sequence (nucleotides 2–8), and no mismatches within the seed sequenceCC BY · PubMed Central
Fig. 3 Genomic locations and expression dynamics of noncoding RNAs in the miR-144/451 locus. a Location, sequence read length, relative read number, and vertebrate conservation of noncoding RNAs within the chromosome 17 miR-144/451 locus according to UCSC genome browser (hg38). Solid lines indicate average read numbers, dotted lines represent highest and lowest standard deviations of read numbers across the samples. The strand orientation of each noncoding RNA is indicated. b Expression of miR-144-5p, miR-4732-3p, and miR-4732-5p, during CD34+ erythroid differentiation using progenitors from three different individuals. Differentiation is listed from day 6 to day 16. U6 snRNA was used as a loading control, with fold difference set relative to day 6. c Predicted folding structure for the miR-4732 pre-microRNA according to miRDeep, and frequency of reads for mature microRNAs from one representative sample. The most prevalent mature read sequences for miR-4732-3p (red) and miR-4732-5p (blue) are shown. d Sequence conservation of miR-4732-3p in listed species. Primates are listed adjacent to white box, non-primates listed adjacent to black box. Seed sequence is boxed, and base mismatches with human miR-4732-3p are highlighted in red
Fig. 3 Genomic locations and expression dynamics of noncoding RNAs in the miR-144/451 locus. a Location, sequence read length, relative read number, and vertebrate conservation of noncoding RNAs within the chromosome 17 miR-144/451 locus according to UCSC genome browser (hg38). Solid lines indicate average read numbers, dotted lines represent highest and lowest standard deviations of read numbers across the samples. The strand orientation of each noncoding RNA is indicated. b Expression of miR-144-5p, miR-4732-3p, and miR-4732-5p, during CD34+ erythroid differentiation using progenitors from three different individuals. Differentiation is listed from day 6 to day 16. U6 snRNA was used as a loading control, with fold difference set relative to day 6. c Predicted folding structure for the miR-4732 pre-microRNA according to miRDeep, and frequency of reads for mature microRNAs from one representative sample. The most prevalent mature read sequences for miR-4732-3p (red) and miR-4732-5p (blue) are shown. d Sequence conservation of miR-4732-3p in listed species. Primates are listed adjacent to white box, non-primates listed adjacent to black box. Seed sequence is boxed, and base mismatches with human miR-4732-3p are highlighted in redCC BY · PubMed Central
Fig. 4 MiR-4732-3p directly regulates SMAD2 and SMAD4. a Alignment of miR-4732-3p and predicted target sites in the 3’ UTR of SMAD2 and SMAD4, with mutated binding sites underlined. b Relative changes of reporter activities in K562s co-transfected with luciferase constructs and indicated microRNA mimics. A portion the SMAD2 and the SMAD4 3’UTRs were cloned downstream of Renilla in separate psiCheck-2 vectors (n = 4) (*p < 0.05, **p < 0.01). c Relative changes of reporter activities in K562s co-transfected with luciferase constructs and microRNA-blocking antisense oligonucleotides (ASOs) (n = 4) (***p < 0.001). d Relative changes of reporter activities in K562s transfected with wild-type (WT) or mutated (MUT) SMAD2 or SMAD4 3’UTR constructs (n = 4) (*p < 0.05). e Western blots of SMAD2 and SMAD4 protein expression 24 h after transfection of K562s with indicated microRNA mimics or f microRNA ASOs. α-tubulin was used as a loading control for normalization. Protein desitometric values are listed. The fold change of expression for each treatment group was first normalized to alpha tubulin input for that treatment, then ratio set relative to the control treatment
Fig. 4 MiR-4732-3p directly regulates SMAD2 and SMAD4. a Alignment of miR-4732-3p and predicted target sites in the 3’ UTR of SMAD2 and SMAD4, with mutated binding sites underlined. b Relative changes of reporter activities in K562s co-transfected with luciferase constructs and indicated microRNA mimics. A portion the SMAD2 and the SMAD4 3’UTRs were cloned downstream of Renilla in separate psiCheck-2 vectors (n = 4) (*p < 0.05, **p < 0.01). c Relative changes of reporter activities in K562s co-transfected with luciferase constructs and microRNA-blocking antisense oligonucleotides (ASOs) (n = 4) (***p < 0.001). d Relative changes of reporter activities in K562s transfected with wild-type (WT) or mutated (MUT) SMAD2 or SMAD4 3’UTR constructs (n = 4) (*p < 0.05). e Western blots of SMAD2 and SMAD4 protein expression 24 h after transfection of K562s with indicated microRNA mimics or f microRNA ASOs. α-tubulin was used as a loading control for normalization. Protein desitometric values are listed. The fold change of expression for each treatment group was first normalized to alpha tubulin input for that treatment, then ratio set relative to the control treatmentCC BY · PubMed Central
Fig. 5 MiR-4732-3p regulates TGF-β signaling and promotes erythroid cell proliferation. a Relative changes of TGF-β reporter activities in K562 cells co-transfected with luciferase constructs and microRNA mimics (n = 4) (**p < 0.01). Cells were transfected with microRNA mimic, SMAD4-responsive Firefly construct, and a separate Renilla construct as a transfection control. b Relative mRNA levels of p21, PAI-1, Bax, and Bim 24 h after transfection of K562s with microRNA mimics. Levels were determined using qPCR and normalized by GAPDH (n = 3) (*p < 0.05). c Total cell number of primary CD34 erythroid progenitors 48 and 72 h after equal numbers of cells were transfected with indicated microRNA mimics on day 8 of differentiation (n = 3) (*p < 0.05). d Total cell number of primary CD34 erythroid progenitors 24 h after equal numbers of cells were transfected with indicated combinations of microRNA mimics and overexpression constructs on day 8 of differentiation (n = 3) (*p < 0.05, **p < 0.01)
Fig. 5 MiR-4732-3p regulates TGF-β signaling and promotes erythroid cell proliferation. a Relative changes of TGF-β reporter activities in K562 cells co-transfected with luciferase constructs and microRNA mimics (n = 4) (**p < 0.01). Cells were transfected with microRNA mimic, SMAD4-responsive Firefly construct, and a separate Renilla construct as a transfection control. b Relative mRNA levels of p21, PAI-1, Bax, and Bim 24 h after transfection of K562s with microRNA mimics. Levels were determined using qPCR and normalized by GAPDH (n = 3) (*p < 0.05). c Total cell number of primary CD34 erythroid progenitors 48 and 72 h after equal numbers of cells were transfected with indicated microRNA mimics on day 8 of differentiation (n = 3) (*p < 0.05). d Total cell number of primary CD34 erythroid progenitors 24 h after equal numbers of cells were transfected with indicated combinations of microRNA mimics and overexpression constructs on day 8 of differentiation (n = 3) (*p < 0.05, **p < 0.01)CC BY · PubMed Central

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Metadata

Authors
Doss, J. F., Corcoran, D. L., Jima, D. D., Telen, M. J., Dave, S. S., & Chi, J.-T.
Venue
BMC Genomics
Publisher
Springer Science and Business Media LLC
Published
2015-11-16
Volume
16
Issue
1
ISSN
1471-2164
DOI
10.1186/s12864-015-2156-2
PMC
PMC4647483
Cited by
113
References
3
Language
en
Funders
  • Doris Duke Charitable Foundation (US) (2011098)
  • World Anti-Doping Agency (CA) (13C31JC)

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