Technical CommentsINFERTILITY

Response to Comment on “Absence of sperm RNA elements correlates with idiopathic male infertility”

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Science Translational Medicine  24 Aug 2016:
Vol. 8, Issue 353, pp. 353tr1
DOI: 10.1126/scitranslmed.aaf4550
  • Fig. 1. Distribution of all possible RNA elements’ percentile rankings.

    The 278,604 possible RNA-coding, noncoding, and sperm-specific RNA elements were measured in 72 sperm samples, and their abundance was ranked by percentile. Elements were sorted by average rank as measured in all samples, and the relative percentage of individual samples with specific rank at each average percentile tier was calculated. (A) On the basis of the sort by average rank, the surface plot shows the distribution of individual sample ranks as compared to the average. (B) Higher-resolution heat map with nonlinear scaling and a lower-threshold color scale bar* with higher-ranked sample fractions >0.20 combined. This resolves the relatively wide distribution among individual samples for lower-ranked elements (indicated in green). Both panels show minimal intersample variation for the top-tier rank elements (indicated in yellow) compared to the broad dispersion of lower-ranked elements.

  • Fig. 2. Germ cell–differentiated and prostate RNA markers.

    (A) GTEx expression of PRAC1, a prostate cancer antigen, is higher in the prostate than in the testis, suggesting that PRAC1 may be used as a prostate marker (upper panel). RNA-seq (lower panel) shows the presence of PRAC1 exclusively in the exosomal fraction. (B) GTEx expression of LELP1 is higher in the testis than in the prostate, suggesting that LELP1 could be used as a testis marker (upper panel). LELP1 that is present in sperm is exclusively from the testes. The absence of LELP1 in GTEx and the small amount of this transcript in the exosome fraction (lower panel) are consistent with an RNA transport pathway.

  • Table 1. SRE criteria for natural conception applied to differential germ cell markers.

    Differentiated germ cell markers provided in the technical comment of Cappallo-Obermann and Spiess (3) were examined. The first SRE criterion for natural conception required that a sperm element exceed the 99th percentile rank on average across seven fertile control samples. From the 28 sperm elements examined, only 13 met the first criterion (marked with an asterisk, percentile rank average). Some elements, such as ODF1 and OAZ3, that did not satisfy the first criterion are moderately abundant (95th to 98th percentile rank). Other elements, such as PFN4 and ACRV1, are absent in the majority of control samples (zeroth percentile rank). These spermatid-specific RNAs are not present in mature spermatozoa and accordingly were not considered. If the first criterion was satisfied, the second outlier criterion was applied. This discarded those elements that did not satisfy the IQR rule. Of the 13 elements exceeding the 99th percentile range on average across the control samples, only 6 satisfied the IQR rule (marked with a dagger sign) and were retained as SREs from four genes: TNP1, LELP1, SMCP, and OAZ3.

    Transcript
    name
    S1S2S3S4S5S6S7Percentile rank
    average
    Outlier
    (<Q1–1.5 × IQR)
    Outliers in
    control
    samples
    PRM1*0.9999960.9999640.9999800.9999780.9999430.9998670.9999930.9999520.9998911
    PRM1*0.9999890.9999280.999960.9999640.9999250.9997490.9999820.9999170.9998671
    PRM2*0.9999780.9999860.9999710.9999960.9999280.9999640.9999750.9999670.9999481
    PRM2*0.9999390.9999030.999940.9999680.9997670.9999210.9999570.9999100.9998671
    ODF10.9898710.9734250.9708510.9743970.8873960.9615440.9867450.9561866
    ODF10.9925160.9880080.9890490.9938190.9801010.9862490.9899140.9878264
    TNP1*0.9999640.9992640.9999350.9999350.9991600.9994440.9999530.9996850.9987080
    TNP1*0.9999930.9998960.9999820.9999860.9997700.9998960.9999780.9999220.9997670
    LELP1*0.9996160.9988940.9993000.9996880.9973370.9987260.9991740.9988450.9978651
    LELP1*0.9995190.9987720.9992430.9996980.9983670.9991420.9988660.9990630.9983010
    SMCP*0.9996770.9998640.9998640.9999390.9996980.9998100.9999500.9998520.9996170
    SMCP*0.9994360.9995190.9995940.9998890.9994900.9996910.9998380.9997000.9992280
    OAZ30.9793720.9771540.9825920.9921140.8350350.9664260.9820790.951649
    OAZ3*0.9974730.9971970.9986900.9992100.9947420.9972580.9988510.9977500.9948691
    OAZ3*0.9973010.9942000.9982700.9986860.9941890.9974700.9976560.9972540.9962700
    OAZ3*0.9935430.9835720.9926890.9973470.9747920.9929830.9932340.9902090.9918722
    OAZ30.8331900.9672330.9710130.9875090.9152530.9862960.9823760.968489
    OAZ30.9848500.9790530.9787910.9966550.9457220.9899320.9918380.980588
    PFN40.0000000.0000000.0000000.7489350.0000000.0000000.0000000.149787
    PFN40.0000000.0000000.0000000.7836110.0000000.0000000.0000000.156722
    PFN40.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
    PFN40.0000000.0000000.0000000.0000000.0000000.0000000.0000000.000000
    PFN40.0000000.0000000.0000000.8493310.0000000.0000000.0000000.169866
    ACRV10.0000000.8058970.0000000.7351380.0000000.0000000.0000000.147028
    ACRV10.0000000.8899410.9424380.9173670.5778610.0000000.0000000.487533
    ACRV10.7705570.7512570.8807420.8821490.6094180.0000000.0000000.474462
    ACRV10.0000000.0000000.0000000.8699020.0000000.7754740.0000000.329075
    ACRV10.0000000.0000000.0000000.8188910.0000000.7027050.0000000.304319
  • Table 2. SRE criteria for natural conception applied to seminal vesicle and prostate markers.

    Although some samples presented seminal vesicle and prostate markers as candidate sperm elements above the 99th percentile rank as indicated in bold text, none of the elements met the first criterion, above the 99th percentile rank on average across seven control samples (average percentile rank), so they were marked as variable and excluded from analysis.

    Transcript
    name
    S1S2S3S4S5S6S7Percentile
    rank
    average
    SEMG20.8468940.9050120.9012620.8927050.7215810.9036880.9498570.856337
    SEMG20.0000000.6801530.8781320.8690440.9266240.9241220.9192760.909706
    SEMG20.0000000.8991190.0000000.9459200.7121700.9609160.9771790.752753
    SEMG20.8750670.9392760.9146320.9145960.7694940.9279660.9640350.884026
    SEMG20.0000000.6984260.0000000.7696090.5926560.7237060.8354550.605398
    SEMG10.9670610.9926200.8935340.9911270.7394270.9927890.9954490.906363
    SEMG10.9330880.9804350.7745090.9688730.8097410.9799930.9906930.901935
    SEMG10.9513360.9516120.0000000.9682130.7811780.9847810.9916300.784537
    SEMG10.9382710.9870140.7971000.9827350.8394030.9883560.9945620.918559
    SEMG10.9134980.9460280.0000000.8605160.7317850.9456900.9740960.741366
    MSMB0.0000000.9976630.0000000.0000000.9989560.9987690.9946590.712873
    MSMB0.8433160.9976810.9283650.8516860.9992610.9994720.9944330.967421
    MSMB0.8433190.9971390.9544520.8516900.9990380.9993720.9883380.970186
    MSMB0.9365190.9958940.9372190.7475390.9987440.9994830.9921790.953342
    TGM40.0000000.9983170.9249190.9654670.9993900.9982910.9603700.978017
    TGM40.0000000.9982700.9171120.9657440.9991490.9983810.9410170.974133
    TGM40.7559740.8567580.7529730.0000000.8671420.8277630.6951170.691129
    TGM40.0000000.9816440.8323250.0000000.9872510.9766730.8752030.805054
    TGM40.0000000.8148200.0000000.0000000.9010360.8539800.8346120.620663
    TGM40.0000000.7288200.0000000.0000000.7458620.7832130.0000000.436879
    TGM40.0000000.9380200.9245060.8772670.9851150.9830010.9317850.952827
    TGM40.7922040.9928820.8440300.0000000.9932700.9906750.9062360.816879
    TGM40.0000000.9845480.9219580.9348790.9911340.9928720.9342690.965588
    TGM40.8237580.9622230.9554460.9781450.9701260.9606900.9257340.960137
    TGM40.9209780.9687950.8972380.9333720.9851800.9653880.8753320.943868
    TGM40.8677340.9354030.8068810.0000000.9529330.9601870.7740170.772448
    TGM40.8732260.9784170.0000000.8739580.9797170.9734070.6595320.777105
    TGM40.8451000.9893970.8917720.8539400.9902190.9903090.7238600.918661
    TGM40.8318370.9702090.7895480.7618820.9836540.9782130.8735450.906958

Supplementary Materials

  • www.sciencetranslationalmedicine.org/cgi/content/full/8/353/353tr1/DC1

    Materials and Methods

    Fig. S1. Determining the abundance of PTPRC by qRT-PCR and by RNA-seq.

    Table S1. Summary of optical microscopy and qRT-PCR of PTPRC (provided as an Excel file).

    Table S2. Percentile ranks of IL8, CD45/PTPRC, CDH1, and KIT (provided as an Excel file).

    Table S3. Comparison of testes and prostate transcript markers (provided as an Excel file).

    Table S4. Tissue-specific markers (provided as an Excel file).

    Table S5. Comparative expression of tissue markers in seven control sperm samples (provided as an Excel file).

  • Supplementary Material for:

    Response to Comment on "Absence of sperm RNA elements correlates with idiopathic male infertility"

    Meritxell Jodar, Edward Sendler, Sergey I. Moskovtsev, Clifford L. Librach, Robert Goodrich, Sonja Swanson, Russ Hauser, Michael P. Diamond, Stephen A. Krawetz*

    *Corresponding author. Email: steve{at}compbio.med.wayne.edu

    Published 24 August 2016, Sci. Transl. Med. 8, 353tr1 (2016)
    DOI: 10.1126/scitranslmed.aaf4550

    This PDF file includes:

    • Materials and Methods
    • Fig. S1. Determining the abundance of PTPRC by qRT-PCR and by RNA-seq.
    • Legends for tables S1 to S5

    [Download PDF]

    Other Supplementary Material for this manuscript includes the following:

    • Table S1. Summary of optical microscopy and qRT-PCR of PTPRC (provided as an Excel file).
    • Table S2. Percentile ranks of IL8, CD45/PTPRC, CDH1, and KIT (provided as an Excel file).
    • Table S3. Comparison of testes and prostate transcript markers (provided as an Excel file).
    • Table S4. Tissue-specific markers (provided as an Excel file).
    • Table S5. Comparative expression of tissue markers in seven control sperm samples (provided as an Excel file).

    [Download Tables]

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