MicroRNA-934 is a novel primate-specific small non-coding RNA with neurogenic function during early development

Integrating differential RNA and miRNA expression during neuronal lineage induction of human embryonic stem cells we identified miR-934, a primate-specific miRNA that displays a stage-specific expression pattern during progenitor expansion and early neuron generation. We demonstrate the biological relevance of this finding by comparison with data from early to mid-gestation human cortical tissue. Further we find that miR-934 directly controls progenitor to neuroblast transition and impacts on neurite growth of newborn neurons. In agreement, miR-934 targets are involved in progenitor proliferation and neuronal differentiation whilst miR-934 inhibition results in profound global transcriptome changes associated with neurogenesis, axonogenesis, neuronal migration and neurotransmission. Interestingly, miR-934 inhibition affects the expression of genes associated with the subplate zone, a transient compartment most prominent in primates that emerges during early corticogenesis. Our data suggest that mir-934 is a novel regulator of early human neurogenesis with potential implications for a species-specific evolutionary role in brain function.


Sample-size estimation
 You should state whether an appropriate sample size was computed when the study was being designed  You should state the statistical method of sample size computation and any required assumptions  If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
 You should report how often each experiment was performed  You should include a definition of biological versus technical replication  The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates  If you encountered any outliers, you should describe how these were handled  Criteria for exclusion/inclusion of data should be clearly stated  High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: This information is included in Material and Methods under the section 'Statistical analysis for low throughput experiments'. Methods of analysis including statistical processing for RNA sequencing data quantification, differential expression analysis, cluster analysis and heatmap construction are described in Materials and Methods under the section 'Quantification and integration of expressed microRNAs and mRNAs'.
Number of biological independent replicates is indicated in figure legends. The use of biological replicates is clearly indicated in Material and Methods under the section 'Statistical analysis for low throughput experiments'. RNA sequencing data accession codes are included in manuscript and cover letter. Statistical reporting  Statistical analysis methods should be described and justified  Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10)  For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d)  Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
 Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied  Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data")  We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table Methods of analysis including statistical processing for RNA sequencing data quantification, differential expression analysis, cluster analysis and heatmap construction are described in Materials and Methods under the section 'Quantification and integration of expressed microRNAs and mRNAs'. Relevant details are also provided in respective figure legends. Information on statistical outcomes of differential expression analysis is provided in supplemental file 1 (p-values of selected genes) and also in the main manuscript in Results under the section 'Identification of miR-934 with species-and stage-specific expression during progenitor expansion and early neuron generation' (for miRNAs), and also under the section 'Inhibition of miR-934 during neural induction affects molecular pathways of neurogenesis and alters the expression of subplate-enriched genes'.
As indicated in the appropriate sections in the manuscript, samples are clearly allocated in experimental groups, according to stage of differentiation and/or treatment for miR934 perturbations.