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SI Appendix Materials and Methods Bioinformatics. Using SI Appendix S upporting Information Corrected November 7, 2011 Materials and Methods Bioinformatics. Using the 454 next generation sequencing platforms, we previously sequenced a small RNA library prepared using pooled adult mouse testes (testes from 3 individual adult mice). A total of ~half million reads were obtained. We developed an in-house computer program to identify endo-siRNAs. A flow chart illustrating the identification process is shown in SI Appendix, Fig. S1. Briefly, three criteria were used in the initial screening: 1) the length of small RNAs ranged from 19-23-nt; 2) sequences of small RNAs were matched to the mouse genome; 3) sequences of small RNAs were completely complementary to known transcripts. Transcript libraries used in this study included cDNA from Ensembl, refMrna from UCSC Genome Browser (1), LTR retrotransposon, Endogenous Retrovirus and Non-LTR retrotransposon from Genetic Information Research Institute (2), piRNA from RNAdb (3), miRNA from miRBase (4), tRNA from Genomic tRNA Database (5), snoRNA from RNAdb (3), and rRNA from Ensembl. Small RNAs that fulfilled all the three criteria were defined as candidate endo-siRNAs. All candidate endo-siRNAs then went through further analyses of the inherent stem-loop structure using Mfold (6). Candidate endo-siRNAs that cannot form the short stem-loop structure were included in the final list as endo-siRNAs (SI Appendix, Table S1). Sequences of endo-siRNAs were then subject to forward and reverse complementary (RC) matching against the sequences of all known transcripts collected in the libraries described above. If the forward- and RC-matched sequences were complementary to each other, then these two sequences were defined as two strands of a potential dsRNA precursor for the endo-siRNA(s). If two sequences were from two different transcripts, than the dsRNA precursor was defined as an intermolecular dsRNA. If two sequences came from one single transcript, than the dsRNA precursor was defined as intramolecular dsRNA. The length and percentage of complementarity of the two strands of the dsRNA precursor were calculated (SI Appendix, Dataset 1). For intermolecular dsRNA precursors, the top two potential dsRNA precursors with the greatest length and percentage of complementarity were chosen as the most likely precursors. Since some dsRNA precursors contained multiple endo-siRNAs, a total of 60 intermolecular dsRNA precursors were analyzed in this study that could generate 42 endo-siRNAs (SI Appendix, Dataset 1). Quantitative analyses of endo-siRNAs, miRNAs and other transcripts. Small RNA isolation, small RNA cDNA synthesis, and small RNA semi-quantitative PCR were performed following our published protocols (7). For TaqMan-based small RNA quantitative real-time PCR (qPCR), a TaqMan probe (5’FAM-CTCGGATCCACTAGTC-MGB3’) was used (Applied Biosystems) and U6 snoRNA was used as endogenous control. Total RNA of human testis was purchased from Zyagen. Small RNAs were further isolated using the method described previously (7). For sequencing, the products from small RNA semi-quantitative PCR were cloned into pCR4-TOPO vector (Invitrogen) and sequenced by M13 forward or reverse primer. Semi-quantitative PCR for other transcripts including mRNAs, transcripts of pseudogenes, retrotransposons, and large non- coding RNAs was performed as described previously (8). Primer sequences for quantitative analyses of endo-siRNAs, miRNAs and other transcripts can be found in SI Appendix, Table S3. Image J (NIH) was used to determine the band density in the semi-qPCR gels, and an in-house computer program was created to convert densitometric values into a heat map. Luciferase Assay. The 3’UTR sequences containing the predicted targeting sites for endo- siRNAs were inserted into the XbaI-FesI site immediately downstream of the stop codon in the pGL4.13 firefly luciferase vector (Promega). The endo-siRNAs were chemically synthesized double-stranded RNAs, which can mimic endo-siRNAs after transfection into cells (QIAGEN). Details of construction are available upon request. The NIH/3T3 cells were cultured in 10% fetal calf serum (Hyclone) in DMEM (Invitrogen). On the day before transfection, growing cells were trypsinized and plated into 12- well plates at a density of 1 × 105 cells/well in an antibiotic-free medium. The next day, cells were co-transfected using the Attractene Transfection Reagent (QIAGEN) with 20ng of pGL4.13 constructs, 480ng of pRL-TK control vector (Renilla luciferase vector, Promega), and 1pmol of endo-siRNA mimics in a final volume of 1.0 ml. 24 hours after transfection, firefly and Renilla luciferase activities were measured using the Dual-Luciferase Reporter Assay System (Promega). The luciferase activity was expressed as the ratio of firefly/Renilla luciferase activities. For quantitative analyses of firefly and Renilla mRNAs, total RNA was isolated from each sample and cDNAs were then synthesized followed by SYBR Green-based quantitative real-time PCR. Primer sequences used can be found in SI Appendix, Table S3. This protocol was modified from Luciferase Assay method in the previous report (9). Generation of male germ cell-specific Dicer or Drosha knockout mice with EGFP expression in Cre-expressing cells. Four lines of mice (Stra8-iCre, Dicerlox/lox, Droshalox/lox and Rosa26mTmGtg/tg) were used to generate the compound male postnatal germ cell-specific Dicer or Drosha knockout mice (Stra8-iCre-Dicerlox/lox-Rosa26mTmG+/tg and Stra8-iCre-Droshalox/lox- Rosa26mTmG+/tg). Stra8-iCre, Dicer-loxp and Rosa26mTmG mice were previously characterized (10-12) and were purchased from the Jackson Laboratory. Drosha-loxp mice were generated as described (13). Purification of spermatogenic cells using the STA-PUT method. We purified pachytene spermatocytes from control (Stra8-iCre-Rosa26mTmG+/tg) and knockout (Stra8-iCre-Dicerlox/lox- Rosa26mTmG+/tg and Stra8-iCre-Droshalox/lox-Rosa26mTmG+/tg) testes (SI Appendix, Fig. S4A) at the age of postnatal day 25 (P25) using the STA-PUT system (Proscience) as described (14). Briefly, the gradient of 2%-4% BSA was formed under the suspension of germ cells in the sedimentation chamber. After 3 hours, the 2%-4% BSA gradient was unloaded from bottom of the sedimentation chamber. According to unit gravity, the initial fractions from bottom gradients were cells with larger radius like pachytene spermatocytes, and the later fractions from top gradients were cells with smaller radius like round spermatids. Since all Cre-expressing cells were green (EGFP-positive) and non-Cre-expressing cells were red, the cell types and purity collected from each fraction were monitored directly using phase and fluorescent microscopy (Carl Zeiss, Axioplan2). A representative result of purified Dicer-null or Drosha-null spermatocytes is shown in SI Appendix, Fig. S4B. In addition to morphological evaluation of the cell types and purity in each of the fractions collected, we also performed quantitative real-time PCR (qPCR) analyses to more accurately determine the purity of the cells in each fraction by examining levels of marker mRNAs for all major types of testicular cells (SI Appendix, Fig. S5). Small RNAs and mRNAs were isolated from first four fractions (No.2-No.5), and we generated small RNA cDNAs and mRNAs cDNAs, respectively. SYBR Green-based qPCR was used to quantify levels of marker genes among four fractions of purified cells and P25 whole testis. These marker genes included Cyp17a1 for Leydig cells (15), Gata4 for Sertoli cells (16), Sohlh1 for spermatogonia (17), Sycp2 for spermatocytes (18), and Catsper3 for spermatids (8). The fractions with the highest levels of Sycp2 and the lowest levels of other marker genes were chosen for quantitative analyses of Drosha and Dicer mRNAs, endo-siRNAs and miRNAs. Primer sequences for all qPCR analyses can be found in SI Appendix, Table S3. References 1. Fujita PA, et al. (2011) The UCSC Genome Browser database: update 2011. Nucleic Acids Res 39(Database issue):D876-882. 2. Jurka J, et al. (2005) Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res 110(1-4):462-467. 3. Pang KC, et al. (2005) RNAdb--a comprehensive mammalian noncoding RNA database. Nucleic Acids Res 33(Database issue):D125-130. 4. Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, & Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34(Database issue):D140-144. 5. Chan PP & Lowe TM (2009) GtRNAdb: a database of transfer RNA genes detected in genomic sequence. Nucleic Acids Res 37(Database issue):D93-97. 6. Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31(13):3406-3415. 7. Ro S, Park C, Jin J, Sanders KM, & Yan W (2006) A PCR-based method for detection and quantification of small RNAs. Biochem Biophys Res Commun 351(3):756-763. 8. Jin JL, et al. (2005) Catsper3 and catsper4 encode two cation channel-like proteins exclusively expressed in the testis. Biol Reprod 73(6):1235-1242. 9. Yu Z, Raabe T, & Hecht NB (2005) MicroRNA Mirn122a reduces expression of the posttranscriptionally regulated germ cell transition protein 2 (Tnp2) messenger RNA (mRNA) by mRNA cleavage. Biol Reprod 73(3):427-433. 10. Sadate-Ngatchou PI, Payne CJ, Dearth AT, & Braun RE (2008) Cre recombinase activity specific to postnatal, premeiotic male germ cells in transgenic mice. Genesis 46(12):738- 742. 11. Harfe BD, McManus MT, Mansfield JH, Hornstein E, & Tabin CJ (2005) The RNaseIII enzyme Dicer is required for morphogenesis but not patterning of the vertebrate limb. Proc Natl Acad Sci U S A 102(31):10898-10903. 12. Muzumdar MD, Tasic B, Miyamichi K, Li L, & Luo L (2007) A global double-fluorescent Cre reporter mouse. Genesis 45(9):593-605. 13. Chong MM, Rasmussen JP, Rudensky AY, & Littman DR (2008) The RNAseIII enzyme Drosha is critical in T cells for preventing lethal inflammatory disease. J Exp Med 205(9):2005-2017. 14. Bellve AR (1993) Purification, culture, and fractionation of spermatogenic cells.
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