Primate deep conserved noncoding sequences and non-coding RNA: their possible relatedness to brain and Central Nervous System

Conserved non coding Sequences (CNSs) are extensively studied for their regulatory properties and functional importance to organisms. Many features such as location, proximity to the likely target gene, lineage specificity, functionality of likely target genes, and nucleotide composition of these sequences have been investigated, thus have provided very meaningful insight to signify underlying evolutionary importance of these elements. Also thorough investigation around how to assign function to non-coding regions of eukaryote genomes is another area that is studied. On one hand evolutionary analyses, including signatures of selection or conservation which can indicate the presence of constraint, suggesting that sequences that are evolving non-neutrally are candidates for functionality. On the other hand evidence that is based on experimental profiling of transcription, methylation, histone modifications and chromatin state. While these types of data are very important and are associated with function in most cases, this is not always the case. Evolutionary conservation though highly conservative which mostly considers elements identifiable in more than one species, is still being used as the initial guideline in investigating function via experiments. If we had an understanding of the experimental profiles of conserved non-coding regions as there may be patterns that are often associated these potentially functional elements it may help to construed functionality of conserved non coding regions easily. In an effort to try integrate experimental profile data, we investigated evidence of expression of conserved noncoding sequences (CNSs). For CNSs from ten primates, we assessed transcription, histone modifications, level of evolutionary constraint or accelerated evolution, and assessed possible target genes, tissue expression profiles of likely target genes (as some CNSs may be enhancers, and may be ncRNAs that interact directly with mRNA) and clustering patterns of CNSs. In total we found 153475 CNSs conserved across all ten primates. Of these 59,870 were overlapping non coding regions of ncRNA genes. H3K4Me1 marks (often associated with active enhancers) were highly correlated with CNSs whereas H4K20Me1 (linked to, e.g. DNA damage repair) had high correlation with conserved ncRNA regions (ncRNA-gene-CEs). Both CNSs and conserved ncRNA showed evidence of being under purifying selection. The CNSs in our dataset overall exhibited lower allele frequencies, consistent with higher levels of evolutionary constraint. We also found that CNSs and ncRNA-gene-CEs produce mutually exclusive groups. The analyses also suggest that both types of conserved elements have undergone waves of accelerated evolution, which we speculate may indicate changes in regulatory requirements following divergence events. Finally, we find that likely target genes for hominoidae, primate and mammalian-specific CNSs and ncRNA-gene-CEs are predominantly associated with brain-related function in humans. The deep conserved primate CNSs and ncRNA gene-CEs signify functional importance suggesting ongoing recruitment of these elements into brain-related functions, consistent with King and Wilsons hypothesis that regulatory changes may account for rapid changes in phenotype among primates.

Systematic prediction of genes functionally associated with bacterial retrons and classification of the encoded tripartite systems

Bacterial retrons consist of a reverse transcriptase (RT) and a contiguous non-coding RNA (ncRNA) gene. One third of annotated retrons carry additional open reading frames (ORFs), the contribution and significance of which in retron biology remains to be determined. In this study we developed a computational pipeline for the systematic prediction of genes specifically associated with retron RTs based on a previously reported large dataset representative of the diversity of prokaryotic RTs. We found that retrons generally comprise a tripartite system composed of the ncRNA, the RT and an additional protein or RT-fused domain with diverse enzymatic functions. These retron systems are highly modular, and their components have coevolved to different extents. Based on the additional module, we classified retrons into 13 types, some of which include additional variants. Our findings provide a basis for future studies on the biological function of retrons and for expanding their biotechnological applications.

Complete Genome Sequence of Xanthomonas campestris pv. campestris Strain 17 from Taiwan

Xanthomonas campestris pv. campestris 17 is a Gram-negative bacterium that is phytopathogenic to cruciferous plants in Taiwan. The 4,994,426-bp-long genome consists of 24 contigs with 4,050 protein-coding genes, 1 noncoding RNA (ncRNA) gene, 6 rRNA genes, and 55 tRNA genes.

ANALYZING MODULAR RNA STRUCTURE REVEALS LOW GLOBAL STRUCTURAL ENTROPY IN MICRORNA SEQUENCE

Secondary structure remains the most exploitable feature for noncoding RNA (ncRNA) gene finding in genomes. However, methods based on secondary structure prediction may generate superfluous amount of candidates for validation and have yet to deliver the desired performance that can complement experimental efforts in ncRNA gene finding. This paper investigates a novel method, unpaired structural entropy (USE) as a measurement for the structure fold stability of ncRNAs. USE proves to be effective in identifying from the genome background a class of ncRNAs, such as precursor microRNAs (pre-miRNAs) that contains a long stem hairpin loop. USE correlates well and performs better than other measures on pre-miRNAs, including the previously formulated structural entropy. As an SVM classifier, USE outperforms existing pre-miRNA classifiers. A long stem hairpin loop is common for a number of other functional RNAs including introns splicing hairpins loops and intrinsic termination hairpin loops. We believe USE can be further applied in developing ab initio prediction programs for a larger class of ncRNAs.

FPQRNA: HARDWARE-ACCELERATED QRNA PACKAGE FOR NONCODING RNA GENE DETECTING ON FPGA

Noncoding RNAs (ncRNAs) have important functional roles in biological processes and have become a central research interest in modern molecular biology. However, how to find ncRNA attracts much more attention since ncRNA gene sequences do not have strong statistical signals, unlike protein coding genes. QRNA is a powerful program and has been widely used as an efficient analysis tool to detect ncRNA gene at present. Unfortunately, the O(L3) computing requirements and complicated data dependency greatly limit the usefulness of QRNA package with the explosion in gene database. In this paper, we present a fine-grained parallel QRNA prototype system, FPQRNA, for accelerating ncRNA gene detection application on FPGA chip. We propose a systolic-like array architecture with multiple PEs (Processing Elements). We partition the tasks by columns and assign tasks to PEs for load balance. We exploit data reuse schemes to reduce the need to load matrices from external memory. The experimental results show a speedup factor of more than 18× over the QRNA - 2.0.3c software running on a PC platform with AMD Phenom 9650 Quad CPU for pairwise sequence alignment with 996 residues, however the power consumption of our FPGA accelerator is only about 30% of that of the general-purpose microprocessors.