Ribosome Footprint Density in Human Lymphoblast Cell Lines (WT vs RPL17 Heterozygous c.217-3C>G)

Supplementary Information from:

Fellmann, F., Saunders, C., O’Donohue, M.-F., Reid, D. W., McFadden, K. A., Montel-Lehry, N., Yu, C., Fang, M., Zhang, J., Royer-Bertrand, B., Farinelli, P., Karboul, N., Willer, J. R., Fievet, L., Bhuiyan, Z. A., Kleinhenz, A. L. W., Jadeau, J., Fulbright, J., Rivolta, C., Renella, R., Katsanis, N., Beckmann, J. S., Nicchitta, C. V., Da Costa, L., Davis, E. E., Gleizes, P.-E.

An atypical form of 60S ribosomal subunit in Diamond-Blackfan anemia linked to RPL17 variants

Data Type:

Processed RNAseq to Measure Ribosome Footprint Density

Sample information:

Species: Human

Cell type: EBV-transformed lymphoblast cell line (LCL)

N=3 healthy control individuals; WT

N=3 individuals with heterozygous RPL17 c.217-3C>G (1-IV-2, 1-III-3, and 1-III-5); mutant

Table S6 – Ribosome Footprint Density – Gene Level Data

Abbreviations:

Muttrln:            mutant translation (ribosome-associated mRNA)

WTtrln:            WT translation (ribosome-associated mRNA)

Mutmrna:         mutant mRNA (bulk mRNA)

WTmrna:         WT mRNA (bulk mRNA)

Mut eff:            mutant effect (ribosome-associated mRNA / bulk mRNA)

Wt eff:             WT effect (ribosome-associated mRNA / bulk mRNA)

Table S7 – Ribosome Footprint Density – Gene Ontology Analysis

Abbreviations:

Mut / WT ribo-seq:      mutant effect / WT effect

Methods:

Ribosome profiling was performed essentially as described (1-3). For LCLs, 5.106 cells were collected by centrifugation, then lysed in 250 µl 200 mM KOAc, 15 mM MgCl2, 25 mM K-HEPES pH 7.2, 4 mM CaCl2, 2% dodecylmaltoside. For samples where RNA-seq was performed, 50 µl of the lysate was set aside and RNA was extracted using GT/phenol (4). With the remaining lysate, the sample was diluted 1:1 with water, then micrococcal nuclease (Sigma-Aldrich) was added to a final concentration of 20 µg/ml. The sample was incubated for 30 min at 37 °C. Ribosomes were then pelleted through a 500 mM sucrose cushion at 90,000 rpm for 40 min in a TLA-100.2 (Beckman-Coulter). the resulting ribosome pellet was resuspended in 200 µl 50 mM NaCl, 50 mM K-HEPES pH 7.2, 5 mM EDTA, 0.5% SDS, 200 ug/ml proteinase K. RNA was extracted by phenol/chloroform, then treated with polynucleotide kinase (New England Biolabs). Ribosome footprints were isolated by polyacrylamide gel electrophoresis, and deep sequencing libraries prepared using the NEBNext Small RNA Library Prep Set (New England Biolabs). RNA-seq libraries were generated using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (New England Biolabs). All sequencing was performed using either Illumina HiSeq 2500 (for ribosome profiling) or Illumina Genome Analyzer (for RNA-seq). Reads were mapped to the RefSeq transcriptome (RefSeq release 60), mapping to the longest transcript derived from each gene. Reads with more than five valid mapped positions were discarded and as many as two valid mappings were allowed. A 20 nt seed region was used. Following mapping, the position of each ribosome was defined by adding 14 nt to the start of each read. The abundance of ribosomes or of mRNA was determined by the number of coding sequence-mapped reads normalized by the length of the coding sequence and the size of each deep sequencing library. Ribosome density was defined as the number of ribosome footprinting read density divided by RNA-seq read density. Statistical significance of differences in ribosome density was determined by Student’s t-test. Gene ontology analysis was performed by bootstrapping, where the mean log2 difference in ribosome density was calculated, then compared to random permutations to determine p-value.

References

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