• Research on the interactions between natural and social systems, and with how those interactions affect the challenge of sustainability.
  • Science Sessions: The PNAS Podcast Program

An RNA structure-mediated, posttranscriptional model of human α-1-antitrypsin expression

  1. Alain Laederacha,b,1
  1. aDepartment of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  2. bCurriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  3. cDepartment of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  4. dLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  5. eDepartment of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599;
  6. fDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
  1. Edited by Rachel Green, Johns Hopkins University, Baltimore, MD, and approved October 19, 2017 (received for review April 20, 2017)

  1. Fig. 2.

    Translation efficiency (TE) differs between SERPINA1 transcripts and is affected by uORFs. (A) The TEs of six SERPINA1 5′-UTRs and their SDs, as measured by luciferase reporter assays. Replicate TE values are shown as open squares. Transcripts are labeled by NCBI name. Measurements are relative to the luciferase assay control. The number of uORFs in each transcript is indicated (Bottom). The Kozak sequence of each uORF is listed. (B) Schematic of the SERPINA1 luciferase constructs and empty vector control. Luciferase CDS not to scale. uORFs in each transcript are indicated with Greek letters and shaded by Kozak sequence score (see color scale). Red arrows indicate uORFs selected for mutation. (C) TEs of the six SERPINA1 constructs with disrupted (mutated) uORFs and their SDs, relative to the wild type (above). (D) TEs of wild type and uORF mutant SERPINA1 constructs predicted with a leaky-scanning model of translation (Eq. 1) fit to experimental TEs, as measured by luciferase assays (r2 = 0.400, n = 12).

  2. Fig. 3.

    SHAPE-MaP structure probing data for SERPINA1 transcripts. (A) SHAPE reactivity of each nucleotide in a region of low median SHAPE values around the start codon of transcript NM_001002236.2. Each value is shown with its SE and colored by SHAPE reactivity according to the color scale. Nucleotides are numbered by their relative position within the transcript; the start codon is labeled +1. (B) SHAPE reactivity of each position in a region of high median SHAPE values in the coding sequence of transcript NM_001002236.2. (C) The windowed, median-centered SHAPE profiles of six SERPINA1 transcripts ordered by length. Higher SHAPE values indicate unstructured (unpaired) regions, while lower SHAPE values indicate structured (base-paired) regions. uORFs are indicated with gray shaded regions and named with Greek letters. Vertical bars separate exons. (D) The minimum free-energy (MFE) secondary structure of transcript NM_001002236.2, modeled by computational folding with SHAPE reactivity information.

  3. Fig. 4.

    Structural data greatly improve the leaky-scanning model of translation efficiency (TE). (A) SHAPE-based predicted structures around the uORFs and coding sequence start in transcript NM_001002236.2. uORFs are labeled by name. Bases are colored according to their SHAPE reactivity, as measured by SHAPE-MaP. Bases with unknown SHAPE data are colored gray. Kozak sequences are outlined in green. (B) SHAPE-based predicted structures around the uORF and coding sequence start in transcript NM_000295.4. (C) TEs of wild type and uORF mutant SERPINA1 constructs predicted with the structure leaky-scanning model of translation (Eq. 3) fit to experimental TEs, as measured by luciferase assays (r2 = 0.936, n = 12).

  4. Fig. 5.

    Structure mutants show translation efficiency (TE) is a function of ΔG of unfolding around the uORF Kozak sequence. (A) TE relative to wild type (WT) for three uORFα structure mutants in transcript NM_001002235.2. Replicate TE values are shown as open squares. The predicted ΔG of unfolding is shown for each structure mutant. (B) Structure mutant and WT TEs plotted with the structure leaky-scanning (solid line) and leaky-scanning (dotted line) models as functions of uORFα ΔG of unfolding. The predicted structure for each mutant and the WT uORFα is shown. Kozak sequences are outlined in green. CAA repeats are abbreviated in the mutants. (C) The structure leaky-scanning and leaky-scanning models as functions of uORFα ΔG of unfolding (lilac), or uORF δ/δ′ ΔG of unfolding (peach). Experimental TEs are plotted for SERPINA1 structure mutants (stars), uORF mutants (triangles), and WT constructs (circles) that contained only uORFα or uORFα, β, and δ/δ′. (D) The structure leaky-scanning and leaky-scanning models as functions of ORF (CDS) ΔG of unfolding. Experimental TEs are plotted for SERPINA1 constructs that contained no uORFs.

  5. Fig. 6.

    Predictions of SERPINA1 translation efficiency (TE) in 10 human tissues are improved with the structure leaky-scanning model. (A) Total SERPINA1 transcript versus α-1-antitrypsin protein measurements show no correlation (r2 = 0.0, n = 10). Protein measurements are in normalized spectral counts (68); transcript measurements are in transcripts per million (TPM). (B) Leaky-scanning model predictions of TE versus measured TE in each tissue (r2 = 0.591, n = 10). Each tissue is labeled and colored in the plot and in the human figure according to its prediction percent error (Eq. 5). (C) Structure leaky-scanning model predictions of TE versus measured TE in each tissue (r2 = 0.655, n = 10).

Online Impact

                                      1. 99132880 2018-01-23
                                      2. 802899879 2018-01-23
                                      3. 295573878 2018-01-23
                                      4. 352668877 2018-01-23
                                      5. 984633876 2018-01-23
                                      6. 545928875 2018-01-23
                                      7. 976569874 2018-01-23
                                      8. 871324873 2018-01-23
                                      9. 263462872 2018-01-23
                                      10. 577161871 2018-01-23
                                      11. 255603870 2018-01-23
                                      12. 117346869 2018-01-23
                                      13. 90982868 2018-01-23
                                      14. 663415867 2018-01-23
                                      15. 793874866 2018-01-23
                                      16. 843582865 2018-01-23
                                      17. 864971864 2018-01-22
                                      18. 258841863 2018-01-22
                                      19. 957295862 2018-01-22
                                      20. 553518861 2018-01-22