Fast-evolving noncoding sequences in the human genome

Background

Gene regulation is considered one of the driving forces of evolution. Although protein-coding DNA sequences and RNA genes have been subject to recent evolutionary events in the human lineage, it has been hypothesized that the large phenotypic divergence between humans and chimpanzees has been driven mainly by changes in gene regulation rather than altered protein-coding gene sequences. Comparative analysis of vertebrate genomes has revealed an abundance of evolutionarily conserved but noncoding sequences. These conserved noncoding (CNC) sequences may well harbor critical regulatory variants that have driven recent human evolution.

Results

Here we identify 1,356 CNC sequences that appear to have undergone dramatic human-specific changes in selective pressures, at least 15% of which have substitution rates significantly above that expected under neutrality. The 1,356 'accelerated CNC' (ANC) sequences are enriched in recent segmental duplications, suggesting a recent change in selective constraint following duplication. In addition, single nucleotide polymorphisms within ANC sequences have a significant excess of high frequency derived alleles and high F _ST values relative to controls, indicating that acceleration and positive selection are recent in human populations. Finally, a significant number of single nucleotide polymorphisms within ANC sequences are associated with changes in gene expression. The probability of variation in an ANC sequence being associated with a gene expression phenotype is fivefold higher than variation in a control CNC sequence.

Conclusion

Our analysis suggests that ANC sequences have until very recently played a role in human evolution, potentially through lineage-specific changes in gene regulation.     

Identifying sequence features that drive ribosomal association for lncRNA

Background

With the increasing number of annotated long noncoding RNAs (lncRNAs) from the genome, researchers are continually updating their understanding of lncRNAs. Recently, thousands of lncRNAs have been reported to be associated with ribosomes in mammals. However, their biological functions or mechanisms are still unclear.

Results

In this study, we tried to investigate the sequence features involved in the ribosomal association of lncRNA. We have extracted ninety-nine sequence features corresponding to different biological mechanisms (i.e., RNA splicing, putative ORF, k-mer frequency, RNA modification, RNA secondary structure, and repeat element). An \(\mathcal {L}1\)-regularized logistic regression model was applied to screen these features. Finally, we obtained fifteen and nine important features for the ribosomal association of human and mouse lncRNAs, respectively.

Conclusion

To our knowledge, this is the first study to characterize ribosome-associated lncRNAs and ribosome-free lncRNAs from the perspective of sequence features. These sequence features that were identified in this study may shed light on the biological mechanism of the ribosomal association and provide important clues for functional analysis of lncRNAs.

     

Autophagy regulated by lncRNA HOTAIR contributes to the cisplatin-induced resistance in endometrial cancer cells

Objectives

To identify whether lncRNAs (long non-coding RNA) participate in the regulation of cisplatin-resistant induced autophagy in endometrial cancer cells.

Results

Autophagy activity was significantly boosted in cisplatin-resistant Ishikawa cells, a human endometrial cancer cell line, compared with that in parental Ishikawa cells. After analyzing the overall long noncoding RNA (lncRNA) profiling, a meaningful lncRNA, HOTAIR, was identified. It was down-regulated simultaneously in cisplatin-resistant Ishikawa cells and parental Ishikawa cells treated with cisplatin. RNA interference of HOTAIR reduced the proliferation of cisplatin-resistant Ishikawa cells and enhanced the autophagy activity of cisplatin-resistant Ishikawa cells with or without cisplatin treatment, in addition, beclin-1, multidrug resistance (MDR), and P-glycoprotein (P-gp) were mediated by lncRNA HOTAIR.

Conclusions

It is clear that lncRNAs, specifically HOTAIR, can regulate the cisplatin-resistance ability of human endometrial cancer cells through the regulation of autophagy by influencing Beclin-1, MDR, and P-gp expression.

     

Molecular evolution of genes in avian genomes

Background

Obtaining a draft genome sequence of the zebra finch (Taeniopygia guttata), the second bird genome to be sequenced, provides the necessary resource for whole-genome comparative analysis of gene sequence evolution in a non-mammalian vertebrate lineage. To analyze basic molecular evolutionary processes during avian evolution, and to contrast these with the situation in mammals, we aligned the protein-coding sequences of 8,384 1:1 orthologs of chicken, zebra finch, a lizard and three mammalian species.

Results

We found clear differences in the substitution rate at fourfold degenerate sites, being lowest in the ancestral bird lineage, intermediate in the chicken lineage and highest in the zebra finch lineage, possibly reflecting differences in generation time. We identified positively selected and/or rapidly evolving genes in avian lineages and found an over-representation of several functional classes, including anion transporter activity, calcium ion binding, cell adhesion and microtubule cytoskeleton.

Conclusions

Focusing specifically on genes of neurological interest and genes differentially expressed in the unique vocal control nuclei of the songbird brain, we find a number of positively selected genes, including synaptic receptors. We found no evidence that selection for beneficial alleles is more efficient in regions of high recombination; in fact, there was a weak yet significant negative correlation between ω and recombination rate, which is in the direction predicted by the Hill-Robertson effect if slightly deleterious mutations contribute to protein evolution. These findings set the stage for studies of functional genetics of avian genes.     

RNAstrand: reading direction of structured RNAs in multiple sequence alignments

Motivation

Genome-wide screens for structured ncRNA genes in mammals, urochordates, and nematodes have predicted thousands of putative ncRNA genes and other structured RNA motifs. A prerequisite for their functional annotation is to determine the reading direction with high precision.

Results

While folding energies of an RNA and its reverse complement are similar, the differences are sufficient at least in conjunction with substitution patterns to discriminate between structured RNAs and their complements. We present here a support vector machine that reliably classifies the reading direction of a structured RNA from a multiple sequence alignment and provides a considerable improvement in classification accuracy over previous approaches.

Software

RNAstrand is freely available as a stand-alone tool from http://www.bioinf.uni-leipzig.de/Software/RNAstrand and is also included in the latest release of RNAz, a part of the Vienna RNA Package.     

Integrated multi-level quality control for proteomic profiling studies using mass spectrometry

Background

Evolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential.

Results

We systematically assessed the ability of various measures to detect conserved RNA structures in multiple sequence alignments. We tested three existing and eight novel strategies that are based on metrics of folding energies, metrics of single optimal structure predictions, and metrics of structure ensembles. We find that the folding energy based SCI score used in the RNAz program and a simple base-pair distance metric are by far the most accurate. The use of more complex metrics like for example tree editing does not improve performance. A variant of the SCI performed particularly well on highly conserved alignments and is thus a viable alternative when only little evolutionary information is available. Surprisingly, ensemble based methods that, in principle, could benefit from the additional information contained in sub-optimal structures, perform particularly poorly. As a general trend, we observed that methods that include a consensus structure prediction outperformed equivalent methods that only consider pairwise comparisons.

Conclusion

Structural conservation can be measured accurately with relatively simple and intuitive metrics. They have the potential to form the basis of future RNA gene finders, that face new challenges like finding lineage specific structures or detecting mis-aligned sequences.     

A comprehensive analysis of piRNAs from adult human testis and their relationship with genes and mobile elements

Background

Piwi-interacting RNAs (piRNAs) are a recently discovered class of small non-coding RNAs whose best-understood function is to repress mobile element (ME) activity in animal germline. To date, nearly all piRNA studies have been conducted in model organisms and little is known about piRNA diversity, target specificity and biological function in human.

Results

Here we performed high-throughput sequencing of piRNAs from three human adult testis samples. We found that more than 81% of the ~17 million putative piRNAs mapped to ~6,000 piRNA-producing genomic clusters using a relaxed definition of clusters. A set of human protein-coding genes produces a relatively large amount of putative piRNAs from their 3’UTRs, and are significantly enriched for certain biological processes, suggestive of non-random sampling by the piRNA biogenesis machinery. Up to 16% of putative piRNAs mapped to a few hundred annotated long non-coding RNA (lncRNA) genes, suggesting that some lncRNA genes can act as piRNA precursors. Among major ME families, young families of LTR and endogenous retroviruses have a greater association with putative piRNAs than other MEs. In addition, piRNAs preferentially mapped to specific regions in the consensus sequences of several ME (sub)families and some piRNA mapping peaks showed patterns consistent with the “ping-pong” cycle of piRNA targeting and amplification.

Conclusions

Overall our data provide a comprehensive analysis and improved annotation of human piRNAs in adult human testes and shed new light into the relationship of piRNAs with protein-coding genes, lncRNAs, and mobile genetic elements in human.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-545) contains supplementary material, which is available to authorized users.     

A short guide to long non-coding RNA gene nomenclature

The HUGO Gene Nomenclature Committee (HGNC) is the only organisation authorised to assign standardised nomenclature to human genes. Of the 38,000 approved gene symbols in our database (http://www.genenames.org), the majority represent protein-coding (pc) genes; however, we also name pseudogenes, phenotypic loci, some genomic features, and to date have named more than 8,500 human non-protein coding RNA (ncRNA) genes and ncRNA pseudogenes. We have already established unique names for most of the small ncRNA genes by working with experts for each class. Small ncRNAs can be defined into their respective classes by their shared homology and common function. In contrast, long non-coding RNA (lncRNA) genes represent a disparate set of loci related only by their size, more than 200 bases in length, share no conserved sequence homology, and have variable functions. As with pc genes, wherever possible, lncRNAs are named based on the known function of their product; a short guide is presented herein to help authors when developing novel gene symbols for lncRNAs with characterised function. Researchers must contact the HGNC with their suggestions prior to publication, to check whether the proposed gene symbol can be approved. Although thousands of lncRNAs have been predicted in the human genome, for the vast majority their function remains unresolved. lncRNA genes with no known function are named based on their genomic context. Working with lncRNA researchers, the HGNC aims to provide unique and, wherever possible, meaningful gene symbols to all lncRNA genes.