Derivation of an endogenous small RNA from double-stranded Sox4 sense and natural antisense transcripts in the mouse brain

Natural antisense transcripts (NATs) are involved in cellular development and regulatory processes. Multiple NATs at the Sox4 gene locus are spatiotemporally regulated throughout murine cerebral corticogenesis. In the study, we evaluated the potential functional role of Sox4 NATs at Sox4 gene locus. We demonstrated Sox4 sense and NATs formed dsRNA aggregates in the cytoplasm of brain cells. Over expression of Sox4 NATs in NIH/3T3 cells generally did not alter the level of Sox4 mRNA expression or protein translation. Upregulation of a Sox4 NAT known as Sox4ot1 led to the production of a novel small RNA, Sox4_sir3. Its biogenesis is Dicer1-dependent and has characteristics resemble piRNA. Expression of Sox4_sir3 was observed in the marginal and germinative zones of the developing and postnatal brains suggesting a potential role in regulating neurogenesis. We proposed that Sox4 sense-NATs serve as Dicer1-dependent templates to produce a novel endo-siRNA- or piRNA-like Sox4_sir3

In depth analysis of the Sox4 gene locus that consists of sense and natural antisense transcripts

SRY (Sex Determining Region Y)-Box 4 or Sox4 is an important regulator of the pan-neuronal gene expression during post-mitotic cell differentiation within the mammalian brain. Sox4 gene locus has been previously characterized with multiple sense and overlapping natural antisense transcripts [1] and [2]. Here we provide accompanying data on various analyses performed and described in Ling et al. [2]. The data include a detail description of various features found at Sox4 gene locus, additional experimental data derived from RNA-Fluorescence in situ Hybridization (RNA-FISH), Western blotting, strand-specific reverse-transcription quantitative polymerase chain reaction (RT-qPCR), gain-of-function and in situ hybridization (ISH) experiments. All the additional data provided here support the existence of an endogenous small interfering- or PIWI interacting-like small RNA known as Sox4_sir3, which origin was found within the overlapping region consisting of a sense and a natural antisense transcript known as Sox4ot1

Deep sequencing analysis of the developing mouse brain reveals a novel microRNA

Extent: 15p.Background: MicroRNAs (miRNAs) are small non-coding RNAs that can exert multilevel inhibition/repression at a post-transcriptional or protein synthesis level during disease or development. Characterisation of miRNAs in adult mammalian brains by deep sequencing has been reported previously. However, to date, no small RNA profiling of the developing brain has been undertaken using this method. We have performed deep sequencing and small RNA analysis of a developing (E15.5) mouse brain. Results: We identified the expression of 294 known miRNAs in the E15.5 developing mouse brain, which were mostly represented by let-7 family and other brain-specific miRNAs such as miR-9 and miR-124. We also discovered 4 putative 22-23 nt miRNAs: mm_br_e15_1181, mm_br_e15_279920, mm_br_e15_96719 and mm_br_e15_294354 each with a 70-76 nt predicted pre-miRNA. We validated the 4 putative miRNAs and further characterised one of them, mm_br_e15_1181, throughout embryogenesis. Mm_br_e15_1181 biogenesis was Dicer1-dependent and was expressed in E3.5 blastocysts and E7 whole embryos. Embryo-wide expression patterns were observed at E9.5 and E11.5 followed by a near complete loss of expression by E13.5, with expression restricted to a specialised layer of cells within the developing and early postnatal brain. Mm_br_e15_1181 was upregulated during neurodifferentiation of P19 teratocarcinoma cells. This novel miRNA has been identified as miR-3099. Conclusions: We have generated and analysed the first deep sequencing dataset of small RNA sequences of the developing mouse brain. The analysis revealed a novel miRNA, miR-3099, with potential regulatory effects on early embryogenesis, and involvement in neuronal cell differentiation/function in the brain during late embryonic and early neonatal development.King-Hwa Ling, Peter J Brautigan, Christopher N Hahn, Tasman Daish, John R Rayner, Pike-See Cheah, Joy M Raison, Sandra Piltz Jeffrey R Mann, Deidre M Mattiske, Paul Q Thomas, David L Adelson and Hamish S Scot

Superior <i>ab initio</i> identification, annotation and characterisation of TEs and segmental duplications from genome assemblies

<div><p>Transposable Elements (TEs) are mobile DNA sequences that make up significant fractions of amniote genomes. However, they are difficult to detect and annotate <i>ab initio</i> because of their variable features, lengths and clade-specific variants. We have addressed this problem by refining and developing a Comprehensive <i>ab initio</i> Repeat Pipeline (CARP) to identify and cluster TEs and other repetitive sequences in genome assemblies. The pipeline begins with a pairwise alignment using krishna, a custom aligner. Single linkage clustering is then carried out to produce families of repetitive elements. Consensus sequences are then filtered for protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. This process yields three types of family: fully annotated, partially annotated and unannotated. Fully annotated families reflect recently diverged/young known TEs present in Repbase. The remaining two types of families contain a mixture of novel TEs and segmental duplications. These can be resolved by aligning these consensus sequences back to the genome to assess copy number vs. length distribution. Our pipeline has three significant advantages compared to other methods for <i>ab initio</i> repeat identification: 1) we generate not only consensus sequences, but keep the genomic intervals for the original aligned sequences, allowing straightforward analysis of evolutionary dynamics, 2) consensus sequences represent low-divergence, recently/currently active TE families, 3) segmental duplications are annotated as a useful by-product. We have compared our <i>ab initio</i> repeat annotations for 7 genome assemblies to other methods and demonstrate that CARP compares favourably with RepeatModeler, the most widely used repeat annotation package.</p></div

Phylogenetic analysis of L2 elements in the platypus genome.

<p>Figure shows the dendrograms of full-length L2 elements in the platypus genome. Panel A) long L2 sequences from the platypus genome. Panel B) Long L2 CARP consensus sequences from platypus. Panel C) Long L2 RMD consensus sequences from platypus. Sequences were aligned with MUSCLE, trees inferred with FastTree and visualized with Archaeopteryx. ORF2-instact L2s are shown with a red dot at the tip of the branch.</p

Comparison of the total number of specific TE types in each method.

<p>Comparison of the total number of specific TE types in each method.</p

Scatter plot of unclassified sequence copy number <i>versus</i> length.

<p>Plots show the copy number of hits of unclassified sequences annotated using CENSOR and combined libraries, with respect to their length. Both copy number and length were <i>log</i>₁₀-transformed. Red regions on the plot indicate high density, while blue regions indicate low density. Linear regression lines are plotted in red, with STANDARD ERROR represented by the gray shadow around the lines.</p

Summary of consensus sequence libraries generated by CARP and RMD.

<p>Summary of consensus sequence libraries generated by CARP and RMD.</p

Comprehensive <i>ab initio</i> Repeat Pipeline (CARP).

<p>Figure shows the detailed steps for CARP. Repetitive DNA is identified by all vs all pairwise alignment using krishna. Single linkage clustering is then carried out to produce families of repetitive sequences that are globally aligned to generate a consensus sequence for each family. Consensus sequences are filtered for non-TE protein coding genes and then annotated using Repbase and a custom library of retrovirus and reverse transcriptase sequences. The annotated consensus sequences are then used to annotate the genome. This is required to identify repeats with less than the threshold identity used for alignment that are overlooked during the initial pairwise alignment step.</p

Coverage plot of the top 5 high hit copy number CARP unclassified consensus sequences from the bearded dragon.

<p>A) CENSOR and BLASTN annotation of the peak coverage region in unclassified family 015220; B) CENSOR and BLASTN annotation of the peak coverage region in unclassified family 0309690; C) CENSOR and BLASTN annotation of the peak coverage region in unclassified family 127805; D) CENSOR and BLASTN annotation of the peak coverage region in unclassified family 137078; E) CENSOR and BLASTN annotation of the peak coverage region in unclassified family 187168. The number of family members identified by krishna/igor used for consensus sequence generation is shown in the upper left corner of each panel.</p