The extent of functionality in the human genome

Pericentromeric satellite RNAs as flexible protein partners in the regulation of nuclear structure

Pericentromeric heterochromatin is mainly composed of satellite DNA sequences. Although being historically associated with transcriptional repression, some pericentromeric satellite DNA sequences are transcribed. The transcription events of pericentromeric satellite sequences occur in highly flexible biological contexts. Hence, the apparent randomness of pericentromeric satellite transcription incites the discussion about the attribution of biological functions. However, pericentromeric satellite RNAs have clear roles in the organization of nuclear structure. Silencing pericentromeric heterochromatin depends on pericentromeric satellite RNAs, that, in a feedback mechanism, contribute to the repression of pericentromeric heterochromatin. Moreover, pericentromeric satellite RNAs can also act as scaffolding molecules in condensate subnuclear structures (e.g., nuclear stress bodies). Since the formation/dissociation of nuclear condensates provides cell adaptability, pericentromeric satellite RNAs can be an epigenetic platform for regulating (sub)nuclear structure. We review current knowledge about pericentromeric satellite RNAs that, irrespective of the meaning of biological function, should be functionally addressed in regular and disease settings. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA in Disease and Development > RNA in Disease.

Are non-protein coding RNAs junk or treasure?: An attempt to explain and reconcile opposing viewpoints of whether the human genome is mostly transcribed into non-functional or functional RNAs

The human genome project's lasting legacies are the emerging insights into human physiology and disease, and the ascendance of biology as the dominant science of the 21st century. Sequencing revealed that >90% of the human genome is not coding for proteins, as originally thought, but rather is overwhelmingly transcribed into non-protein coding, or non-coding, RNAs (ncRNAs). This discovery initially led to the hypothesis that most genomic DNA is "junk", a term still championed by some geneticists and evolutionary biologists. In contrast, molecular biologists and biochemists studying the vast number of transcripts produced from most of this genome "junk" often surmise that these ncRNAs have biological significance. What gives? This essay contrasts the two opposing, extant viewpoints, aiming to explain their bases, which arise from distinct reference frames of the underlying scientific disciplines. Finally, it aims to reconcile these divergent mindsets in hopes of stimulating synergy between scientific fields.

mRNA nuclear export: how mRNA identity features distinguish functional RNAs from junk transcripts

The division of the cellular space into nucleoplasm and cytoplasm promotes quality control mechanisms that prevent misprocessed mRNAs and junk RNAs from gaining access to the translational machinery. Here, we explore how properly processed mRNAs are distinguished from both misprocessed mRNAs and junk RNAs by the presence or absence of various 'identity features'.

RNA out of the mist

RNA has long been regarded primarily as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences interrupted by large tracts of transcribed but untranslated sequences, and that multicellular organisms also express many long 'intergenic' and antisense noncoding RNAs (lncRNAs). The identification of small RNAs that regulate mRNA translation and half-life did not disturb the prevailing view that animals and plant genomes are full of evolutionary debris and that their development is mainly supervised by transcription factors. Gathering evidence to the contrary involved addressing the low conservation, expression, and genetic visibility of lncRNAs, demonstrating their cell-specific roles in cell and developmental biology, and their association with chromatin-modifying complexes and phase-separated domains. The emerging picture is that most lncRNAs are the products of genetic loci termed 'enhancers', which marshal generic effector proteins to their sites of action to control cell fate decisions during development.

Genome-Wide Analysis of Human Long Noncoding RNAs: A Provocative Review

Do long noncoding RNAs (lncRNAs) contribute little or substantively to human biology? To address how lncRNA loci and their transcripts, structures, interactions, and functions contribute to human traits and disease, we adopt a genome-wide perspective. We intend to provoke alternative interpretation of questionable evidence and thorough inquiry into unsubstantiated claims. We discuss pitfalls of lncRNA experimental and computational methods as well as opposing interpretations of their results. The majority of evidence, we argue, indicates that most lncRNA transcript models reflect transcriptional noise or provide minor regulatory roles, leaving relatively few human lncRNAs that contribute centrally to human development, physiology, or behavior. These important few tend to be spliced and better conserved but lack a simple syntax relating sequence to structure and mechanism, and so resist simple categorization. This genome-wide view should help investigators prioritize individual lncRNAs based on their likely contribution to human biology.

An RNA-Based Theory of Natural Universal Computation

Life is confronted with computation problems in a variety of domains including animal behavior, single-cell behavior, and embryonic development. Yet we currently do not know of a naturally existing biological system that is capable of universal computation, i.e., Turing-equivalent in scope. Generic finite-dimensional dynamical systems (which encompass most models of neural networks, intracellular signaling cascades, and gene regulatory networks) fall short of universal computation, but are assumed to be capable of explaining cognition and development. I present a class of models that bridge two concepts from distant fields: combinatory logic (or, equivalently, lambda calculus) and RNA molecular biology. A set of basic RNA editing rules can make it possible to compute any computable function with identical algorithmic complexity to that of Turing machines. The models do not assume extraordinarily complex molecular machinery or any processes that radically differ from what we already know to occur in cells. Distinct independent enzymes can mediate each of the rules and RNA molecules solve the problem of parenthesis matching through their secondary structure. In the most plausible of these models all of the editing rules can be implemented with merely cleavage and ligation operations at fixed positions relative to predefined motifs. This demonstrates that universal computation is well within the reach of molecular biology. It is therefore reasonable to assume that life has evolved - or possibly began with - a universal computer that yet remains to be discovered. The variety of seemingly unrelated computational problems across many scales can potentially be solved using the same RNA-based computation system. Experimental validation of this theory may immensely impact our understanding of memory, cognition, development, disease, evolution, and the early stages of life.

A bird-like genome from a frog: Mechanisms of genome size reduction in the ornate burrowing frog, Platyplectrum ornatum

The diversity of genome sizes across the tree of life is of key interest in evolutionary biology. Various correlates of variation in genome size, such as accumulation of transposable elements (TEs) or rate of DNA gain and loss, are well known, but the underlying molecular mechanisms driving or constraining genome size are poorly understood. Here, we study one of the smallest genomes among frogs characterized thus far, that of the ornate burrowing frog (Platyplectrum ornatum) from Australia, and compare it to other published frog and vertebrate genomes to examine the forces driving reduction in genome size. At ∼1.06 gigabases (Gb), the P. ornatum genome is like that of birds, revealing four major mechanisms underlying TE dynamics: reduced abundance of all major classes of TEs; increased net deletion bias in TEs; drastic reduction in intron lengths; and expansion via gene duplication of the repertoire of TE-suppressing Piwi genes, accompanied by increased expression of Piwi-interacting RNA (piRNA)-based TE-silencing pathway genes in germline cells. Transcriptomes from multiple tissues in both sexes corroborate these results and provide insight into sex-differentiation pathways in Platyplectrum Genome skimming of two closely related frog species (Lechriodus fletcheri and Limnodynastes fletcheri) confirms a reduction in TEs as a major driver of genome reduction in Platyplectrum and supports a macroevolutionary scenario of small genome size in frogs driven by convergence in life history, especially rapid tadpole development and tadpole diet. The P. ornatum genome offers a model for future comparative studies on mechanisms of genome size reduction in amphibians and vertebrates generally.

GC-content biases in protein-coding genes act as an "mRNA identity" feature for nuclear export

It has long been observed that human protein-coding genes have a particular distribution of GC-content: the 5' end of these genes has high GC-content while the 3' end has low GC-content. In 2012, it was proposed that this pattern of GC-content could act as an mRNA identity feature that would lead to it being better recognized by the cellular machinery to promote its nuclear export. In contrast, junk RNA, which largely lacks this feature, would be retained in the nucleus and targeted for decay. Now two recent papers have provided evidence that GC-content does promote the nuclear export of many mRNAs in human cells.

Functional Long Non-coding RNAs Evolve from Junk Transcripts

Transcriptome studies reveal pervasive transcription of complex genomes, such as those of mammals. Despite popular arguments for functionality of most, if not all, of these transcripts, genome-wide analysis of selective constraints indicates that most of the produced RNA are junk. However, junk is not garbage. On the contrary, junk transcripts provide the raw material for the evolution of diverse long non-coding (lnc) RNAs by non-adaptive mechanisms, such as constructive neutral evolution. The generation of many novel functional entities, such as lncRNAs, that fuels organismal complexity does not seem to be driven by strong positive selection. Rather, the weak selection regime that dominates the evolution of most multicellular eukaryotes provides ample material for functional innovation with relatively little adaptation involved.

FuncPEP: A Database of Functional Peptides Encoded by Non-Coding RNAs

Non-coding RNAs (ncRNAs) are essential players in many cellular processes, from normal development to oncogenic transformation. Initially, ncRNAs were defined as transcripts that lacked an open reading frame (ORF). However, multiple lines of evidence suggest that certain ncRNAs encode small peptides of less than 100 amino acids. The sequences encoding these peptides are known as small open reading frames (smORFs), many initiating with the traditional AUG start codon but terminating with atypical stop codons, suggesting a different biogenesis. The ncRNA-encoded peptides (ncPEPs) are gradually becoming appreciated as a new class of functional molecules that contribute to diverse cellular processes, and are deregulated in different diseases contributing to pathogenesis. As multiple publications have identified unique ncPEPs, we appreciated the need for assembling a new web resource that could gather information about these functional ncPEPs. We developed FuncPEP, a new database of functional ncRNA encoded peptides, containing all experimentally validated and functionally characterized ncPEPs. Currently, FuncPEP includes a comprehensive annotation of 112 functional ncPEPs and specific details regarding the ncRNA transcripts that encode these peptides. We believe that FuncPEP will serve as a platform for further deciphering the biologic significance and medical use of ncPEPs.

The CXCL12 SNPs and their haplotypes are associated with serum lipid traits

The relationship among the single nucleotide polymorphisms (SNPs) of the C-X-C motif chemokine ligand 12 gene (CXCL12) and the serum lipid profiles in the Chinese population has rarely been described, especially in somewhat old-fashioned and isolated Maonan minority. The goal of the current study was to elucidate the connection among the CXCL12 rs501120 and rs1746048 SNPs, haplotypes, several environmental factors and serum lipid traits in the Maonan as well as Han populations. Genotyping of the two SNPs, gel electrophoresis and direct sequencing were accomplished in 1,494 distinct subjects (Maonan, 750 and Han, 744) using polymerase chain reaction and restriction fragment length polymorphism. The frequencies of genotypes as well as alleles of the two SNPs were not similar between the two ethnic groups. The rs501120 SNP was related with serum total cholesterol levels, while the rs1746048 SNP was related with serum apolipoprotein (Apo) B levels. Four haplotypes were identified, of which the rs501120A-rs1746048C haplotype was the most common. The haplotypes of rs501120A-rs1746048T increased and rs501120G-rs1746048C decreased the risk of hyperlipidemia (P < 0.001 for each), showing consistent association with the levels of serum triglyceride, ApoA1 and ApoB. These outcomes specify that the CXCL12 SNPs as well as their haplotypes are related to serum lipid levels. Different serum lipid levels between both populations may partially be related to the CXCL12 SNPs, their haplotypes along with several environmental factors.

Identifying co-opted transposable elements using comparative epigenomics

The human genome gives rise to different epigenomic landscapes that define each cell type and can be deregulated in disease. Recent efforts by ENCODE, the NIH Roadmap and the International Human Epigenome Consortium (IHEC) have made significant advances towards assembling reference epigenomic maps of various tissues. Notably, these projects have found that approximately 80% of human DNA was biochemically active in at least one epigenomic assay while only approximately 10% of the sequence displayed signs of purifying selection. Given that transposable elements (TEs) make up at least 50% of the human genome and can be actively transcribed or act as regulatory elements either for their own purposes or be co-opted for the benefit of their host; we are interested in exploring their overall contribution to the "functional" genome. Traditional methods used to identify functional DNA have relied on comparative genomics, conservation analysis and low throughput validation assays. To discover co-opted TEs, and distinguish them from noisy genomic elements, we argue that comparative epigenomic methods will also be important.

Estimating the prevalence of functional exonic splice regulatory information

In addition to coding information, human exons contain sequences necessary for correct splicing. These elements are known to be under purifying selection and their disruption can cause disease. However, the density of functional exonic splicing information remains profoundly uncertain. Several groups have experimentally investigated how mutations at different exonic positions affect splicing. They have found splice information to be distributed widely in exons, with one estimate putting the proportion of splicing-relevant nucleotides at >90%. These results suggest that splicing could place a major pressure on exon evolution. However, analyses of sequence conservation have concluded that the need to preserve splice regulatory signals only slightly constrains exon evolution, with a resulting decrease in the average human rate of synonymous evolution of only 1–4%. Why do these two lines of research come to such different conclusions? Among other reasons, we suggest that the methods are measuring different things: one assays the density of sites that affect splicing, the other the density of sites whose effects on splicing are visible to selection. In addition, the experimental methods typically consider short exons, thereby enriching for nucleotides close to the splice junction, such sites being enriched for splice-control elements. By contrast, in part owing to correction for nucleotide composition biases and to the assumption that constraint only operates on exon ends, the conservation-based methods can be overly conservative.

What is an RNA? A top layer for RNA classification

Every ribonucleic acid begins its cellular life as a transcript. If the transcript or its processing product has a function it should be regarded an RNA. Nonfunctional transcripts, by-products from processing, degradation intermediates, even those originating from (functional) RNAs, and non-functional products of transcriptional gene regulation accomplished via the act of transcription, as well as stochastic (co)transcripts could simply be addressed as transcripts (class 0). The copious functional RNAs (class I), often maturing after one or more processing steps, already are systematized into ever expanding sub-classifications ranging from micro RNAs to rRNAs. Established sub-classifications addressing a wide functional diversity remain unaffected. mRNAs (class II) are distinct from any other RNA by virtue of their potential to be translated into (poly)peptide(s) on ribosomes. We are not proposing a novel RNA classification, but wish to add a basic concept with existing terminology (transcript, RNA, and mRNA) that should serve as an additional framework for carefully delineating RNA function from an avalanche of RNA sequencing data. At the same time, this top level hierarchical model should illuminate important principles of RNA evolution and biology thus heightening our awareness that in biology boundaries and categorizations are typically fuzzy.

Long non-coding RNAs in corticogenesis: deciphering the non-coding code of the brain

Evidence on the role of long non-coding (lnc) RNAs has been accumulating over decades, but it has been only recently that advances in sequencing technologies have allowed the field to fully appreciate their abundance and diversity. Despite this, only a handful of lncRNAs have been phenotypically or mechanistically studied. Moreover, novel lncRNAs and new classes of RNAs are being discovered at growing pace, suggesting that this class of molecules may have functions as diverse as protein-coding genes. Interestingly, the brain is the organ where lncRNAs have the most peculiar features including the highest number of lncRNAs that are expressed, proportion of tissue-specific lncRNAs and highest signals of evolutionary conservation. In this work, we critically review the current knowledge about the steps that have led to the identification of the non-coding transcriptome including the general features of lncRNAs in different contexts in terms of both their genomic organisation, evolutionary origin, patterns of expression, and function in the developing and adult mammalian brain.

Non-coding RNA: what is functional and what is junk?

The genomes of large multicellular eukaryotes are mostly comprised of non-protein coding DNA. Although there has been much agreement that a small fraction of these genomes has important biological functions, there has been much debate as to whether the rest contributes to development and/or homeostasis. Much of the speculation has centered on the genomic regions that are transcribed into RNA at some low level. Unfortunately these RNAs have been arbitrarily assigned various names, such as “intergenic RNA,” “long non-coding RNAs” etc., which have led to some confusion in the field. Many researchers believe that these transcripts represent a vast, unchartered world of functional non-coding RNAs (ncRNAs), simply because they exist. However, there are reasons to question this Panglossian view because it ignores our current understanding of how evolution shapes eukaryotic genomes and how the gene expression machinery works in eukaryotic cells. Although there are undoubtedly many more functional ncRNAs yet to be discovered and characterized, it is also likely that many of these transcripts are simply junk. Here, we discuss how to determine whether any given ncRNA has a function. Importantly, we advocate that in the absence of any such data, the appropriate null hypothesis is that the RNA in question is junk.

Using genomics to characterize evolutionary potential for conservation of wild populations

Genomics promises exciting advances towards the important conservation goal of maximizing evolutionary potential, notwithstanding associated challenges. Here, we explore some of the complexity of adaptation genetics and discuss the strengths and limitations of genomics as a tool for characterizing evolutionary potential in the context of conservation management. Many traits are polygenic and can be strongly influenced by minor differences in regulatory networks and by epigenetic variation not visible in DNA sequence. Much of this critical complexity is difficult to detect using methods commonly used to identify adaptive variation, and this needs appropriate consideration when planning genomic screens, and when basing management decisions on genomic data. When the genomic basis of adaptation and future threats are well understood, it may be appropriate to focus management on particular adaptive traits. For more typical conservations scenarios, we argue that screening genome-wide variation should be a sensible approach that may provide a generalized measure of evolutionary potential that accounts for the contributions of small-effect loci and cryptic variation and is robust to uncertainty about future change and required adaptive response(s). The best conservation outcomes should be achieved when genomic estimates of evolutionary potential are used within an adaptive management framework.

Functional repeat-derived RNAs often originate from retrotransposon-propagated ncRNAs

The human genome is scattered with repetitive sequences, and the ENCODE project revealed that 60–70% of the genomic DNA is transcribed into RNA. As a consequence, the human transcriptome contains a large portion of repeat-derived RNAs (repRNAs). Here, we present a hypothesis for the evolution of novel functional repeat-derived RNAs from non-coding RNAs (ncRNAs) by retrotransposition. Upon amplification, the ncRNAs can diversify in sequence and subsequently evolve new activities, which can result in novel functions. Non-coding transcripts derived from highly repetitive regions can therefore serve as a reservoir for the evolution of novel functional RNAs. We base our hypothetical model on observations reported for short interspersed nuclear elements derived from 7SL RNA and tRNAs, α satellites derived from snoRNAs and SL RNAs derived from U1 small nuclear RNA. Furthermore, we present novel putative human repeat-derived ncRNAs obtained by the comparison of the Dfam and Rfam databases, as well as several examples in other species. We hypothesize that novel functional ncRNAs can derive also from other repetitive regions and propose Genomic SELEX as a tool for their identification.

Defining functional DNA elements in the human genome

With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.