The C-value paradox, junk DNA and ENCODE

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.

Evaluating the representational power of pre-trained DNA language models for regulatory genomics

The emergence of genomic language models (gLMs) offers an unsupervised approach to learn a wide diversity of cis-regulatory patterns in the non-coding genome without requiring labels of functional activity generated by wet-lab experiments. Previous evaluations have shown pre-trained gLMs can be leveraged to improve prediction performance across a broad range of regulatory genomics tasks, albeit using relatively simple benchmark datasets and baseline models. Since the gLMs in these studies were tested upon fine-tuning their weights for each downstream task, determining whether gLM representations embody a foundational understanding of cis-regulatory biology remains an open question. Here we evaluate the representational power of pre-trained gLMs to predict and interpret cell-type-specific functional genomics data that span DNA and RNA regulation. Our findings suggest that current gLMs do not offer substantial advantages over conventional machine learning approaches that use one-hot encoded sequences. This work highlights a major limitation with current gLMs, raising potential issues in conventional pre-training strategies for the non-coding genome.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

Evidence for widespread existence of functional novel and non-canonical human transcripts

BACKGROUND

Fraction of functional sequence in the human genome remains a key unresolved question in Biology and the subject of vigorous debate. While a plethora of studies have connected a significant fraction of human DNA to various biochemical processes, the classical definition of function requires evidence of effects on cellular or organismal fitness that such studies do not provide. Although multiple high-throughput reverse genetics screens have been developed to address this issue, they are limited to annotated genomic elements and suffer from non-specific effects, arguing for a strong need to develop additional functional genomics approaches.

RESULTS

In this work, we established a high-throughput lentivirus-based insertional mutagenesis strategy as a forward genetics screen tool in aneuploid cells. Application of this approach to human cell lines in multiple phenotypic screens suggested the presence of many yet uncharacterized functional elements in the human genome, represented at least in part by novel exons of known and novel genes. The novel transcripts containing these exons can be massively, up to thousands-fold, induced by specific stresses, and at least some can represent bi-cistronic protein-coding mRNAs.

CONCLUSIONS

Altogether, these results argue that many unannotated and non-canonical human transcripts, including those that appear as aberrant splice products, have biological relevance under specific biological conditions.

Genome size estimation and its associations with body length, chromosome number and evolution in teleost fishes

Precise estimation of genome size (GS) is vital for various genomic studies, such as deciding genome sequencing depth, genome assembly, biodiversity documentation, evolution, genetic disorders studies, duplication events etc. Animal Genome Size Database provides GS of over 2050 fish species, which ranges from 0.35 pg in pufferfish (Tetraodon nigroviridis) to 132.83 pg in marbled lungfish (Protopterus aethiopicus). The GS of majority of the fishes inhabiting waters of Indian subcontinent are still missing. In present study, we estimated GS of 51 freshwater teleost (31 commercially important, 7 vulnerable and 13 ornamental species) that ranged from 0.58 pg in banded gourami (Trichogaster fasciata) to 1.92 pg in scribbled goby (Awaous grammepomus). Substantial variation in GS was observed within the same fish orders (0.64-1.45 pg in cypriniformes, 0.70-1.41 pg in siluriformes and 0.58-1.92 pg in perciformes). We examined the relationship between the GS, chromosome number and body length across all the fishes. Body length was found to be associated with GS, whereas no relationship was noticed between the GS and the chromosome number. The analysis using ancestral information revealed haploid chromosome number 25, 27 and 24 for the most recent common ancestor of cypriniformes, siluriformes and perciformes, respectively. The study led to generation of new records on GS of 43 fish species and revalidated records for 8 species. The finding is valuable resource for further research in the areas of fish genomics, molecular ecology and evolutionary conservation genetics.

Pervasive translation of small open reading frames in plant long non-coding RNAs

Long non-coding RNAs (lncRNAs) are primarily recognized as non-coding transcripts longer than 200 nucleotides with low coding potential and are present in both eukaryotes and prokaryotes. Recent findings reveal that lncRNAs can code for micropeptides in various species. Micropeptides are generated from small open reading frames (smORFs) and have been discovered frequently in short mRNAs and non-coding RNAs, such as lncRNAs, circular RNAs, and pri-miRNAs. The most accepted definition of a smORF is an ORF containing fewer than 100 codons, and ribosome profiling and mass spectrometry are the most prevalent experimental techniques used to identify them. Although the majority of micropeptides perform critical roles throughout plant developmental processes and stress conditions, only a handful of their functions have been verified to date. Even though more research is being directed toward identifying micropeptides, there is still a dearth of information regarding these peptides in plants. This review outlines the lncRNA-encoded peptides, the evolutionary roles of such peptides in plants, and the techniques used to identify them. It also describes the functions of the pri-miRNA and circRNA-encoded peptides that have been identified in plants.

The Characters of Non-Coding RNAs and Their Biological Roles in Plant Development and Abiotic Stress Response

Plant growth and development are greatly affected by the environment. Many genes have been identified to be involved in regulating plant development and adaption of abiotic stress. Apart from protein-coding genes, more and more evidence indicates that non-coding RNAs (ncRNAs), including small RNAs and long ncRNAs (lncRNAs), can target plant developmental and stress-responsive mRNAs, regulatory genes, DNA regulatory regions, and proteins to regulate the transcription of various genes at the transcriptional, posttranscriptional, and epigenetic level. Currently, the molecular regulatory mechanisms of sRNAs and lncRNAs controlling plant development and abiotic response are being deeply explored. In this review, we summarize the recent research progress of small RNAs and lncRNAs in plants, focusing on the signal factors, expression characters, targets functions, and interplay network of ncRNAs and their targets in plant development and abiotic stress responses. The complex molecular regulatory pathways among small RNAs, lncRNAs, and targets in plants are also discussed. Understanding molecular mechanisms and functional implications of ncRNAs in various abiotic stress responses and development will benefit us in regard to the use of ncRNAs as potential character-determining factors in molecular plant breeding.

Methods to Analyze the Non-Coding RNA Interactome—Recent Advances and Challenges

Most of the human genome is transcribed to generate a multitude of non-coding RNAs. However, while these transcripts have generated an immense amount of scientific interest, their biological function remains a subject of an intense debate. Understanding mechanisms of action of non-coding RNAs is a key to addressing the issue of biological relevance of these transcripts. Based on some well-understood non-coding RNAs that function inside the cell by interacting with other molecules, it is generally believed many other non-coding transcripts could also function in a similar fashion. Therefore, development of methods that can map RNA interactome is the key to understanding functionality of the extensive cellular non-coding transcriptome. Here, we review the vast progress that has been made in the past decade in technologies that can map RNA interactions with different sites in DNA, proteins or other RNA molecules; the general approaches used to validate the existence of novel interactions; and the challenges posed by interpreting the data obtained using the interactome mapping methods.

Non-Darwinian Molecular Biology

With the discovery of the double helical structure of DNA, a shift occurred in how biologists investigated questions surrounding cellular processes, such as protein synthesis. Instead of viewing biological activity through the lens of chemical reactions, this new field used biological information to gain a new profound view of how biological systems work. Molecular biologists asked new types of questions that would have been inconceivable to the older generation of researchers, such as how cellular machineries convert inherited biological information into functional molecules like proteins. This new focus on biological information also gave molecular biologists a way to link their findings to concepts developed by genetics and the modern synthesis. However, by the late 1960s this all changed. Elevated rates of mutation, unsustainable genetic loads, and high levels of variation in populations, challenged Darwinian evolution, a central tenant of the modern synthesis, where adaptation was the main driver of evolutionary change. Building on these findings, Motoo Kimura advanced the neutral theory of molecular evolution, which advocates that selection in multicellular eukaryotes is weak and that most genomic changes are neutral and due to random drift. This was further elaborated by Jack King and Thomas Jukes, in their paper “Non-Darwinian Evolution”, where they pointed out that the observed changes seen in proteins and the types of polymorphisms observed in populations only become understandable when we take into account biochemistry and Kimura’s new theory. Fifty years later, most molecular biologists remain unaware of these fundamental advances. Their adaptionist viewpoint fails to explain data collected from new powerful technologies which can detect exceedingly rare biochemical events. For example, high throughput sequencing routinely detects RNA transcripts being produced from almost the entire genome yet are present less than one copy per thousand cells and appear to lack any function. Molecular biologists must now reincorporate ideas from classical biochemistry and absorb modern concepts from molecular evolution, to craft a new lens through which they can evaluate the functionality of transcriptional units, and make sense of our messy, intricate, and complicated genome.

OUP accepted manuscript

“Junk DNA” is a popular yet controversial concept that states that organisms carry in their genomes DNA that has no positive impact on their fitness. Nonetheless, biochemical functions have been identified for an increasing fraction of DNA elements traditionally seen as “Junk DNA”. These findings have been interpreted as fundamentally undermining the “Junk DNA” concept. Here, we reinforce previous arguments that this interpretation relies on an inadequate concept of biological function that does not consider the selected effect of a given genomic structure, which is central to the “Junk DNA” concept. Next, we suggest that another (though ignored) confounding factor is that the discussion about biological functions includes two different dimensions: a horizontal, ecological dimension that reflects how a given genomic element affects fitness in a specific time, and a vertical, temporal dimension that reflects how a given genomic element persisted along time. We suggest that “Junk DNA” should be used exclusively relative to the horizontal dimension, while for the vertical dimension, we propose a new term, “Spam DNA”, that reflects the fact that a given genomic element may persist in the genome even if not selected for on their origin. Importantly, these concepts are complementary. An element can be both “Spam DNA” and “Junk DNA”, and “Spam DNA” can also be recruited to perform evolved biological functions, as illustrated in processes of exaptation or constructive neutral evolution.

Alternative splicing level related to intron size and organism complexity

Background

Alternative splicing is the process of selecting different combinations of splice sites to produce variably spliced mRNAs. However, the relationships between alternative splicing prevalence and level (ASP/L) and variations of intron size and organism complexity (OC) remain vague. Here, we developed a robust protocol to analyze the relationships between ASP/L and variations of intron size and OC. Approximately 8 Tb raw RNA-Seq data from 37 eumetazoan species were divided into three sets of species based on variations in intron size and OC.

Results

We found a strong positive correlation between ASP/L and OC, but no correlation between ASP/L and intron size across species. Surprisingly, ASP/L displayed a positive correlation with mean intron size of genes within individual genomes. Moreover, our results revealed that four ASP/L-related pathways contributed to the differences in ASP/L that were associated with OC. In particular, the spliceosome pathway displayed distinct genomic features, such as the highest gene expression level, conservation level, and fraction of disordered regions. Interestingly, lower or no obvious correlations were observed among these genomic features.

Conclusions

The positive correlation between ASP/L and OC ubiquitously exists in eukaryotes, and this correlation is not affected by the mean intron size of these species. ASP/L-related splicing factors may play an important role in the evolution of OC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08172-2.

Transposon dynamics and the epigenetic switch hypothesis

The recent explosion of interest in epigenetics is often portrayed as the dawning of a scientific revolution that promises to transform biomedical science along with developmental and evolutionary biology. Much of this enthusiasm surrounds what we call the epigenetic switch hypothesis, which regards certain examples of epigenetic inheritance as an adaptive organismal response to environmental change. This interpretation overlooks an alternative explanation in terms of coevolutionary dynamics between parasitic transposons and the host genome. This raises a question about whether epigenetics researchers tend to overlook transposon dynamics more generally. To address this question, we surveyed a large sample of scientific publications on the topics of epigenetics and transposons over the past fifty years. We found that enthusiasm for epigenetics is often inversely related to interest in transposon dynamics across the four disciplines we examined. Most surprising was a declining interest in transposons within biomedical science and cellular and molecular biology over the past two decades. Also notable was a delayed and relatively muted enthusiasm for epigenetics within evolutionary biology. An analysis of scientific abstracts from the past twenty-five years further reveals systematic differences among disciplines in their uses of the term epigenetic, especially with respect to heritability commitments and functional interpretations. Taken together, these results paint a nuanced picture of the rise of epigenetics and the possible neglect of transposon dynamics, especially among biomedical scientists.

Mammals with small populations do not exhibit larger genomes

Genome size in cellular organisms varies by six orders of magnitude, yet the cause of this large variation remains unexplained. The influential Drift-Barrier Hypothesis proposes that large genomes tend to evolve in small populations due to inefficient selection. However, to our knowledge no explicit tests of the Drift-Barrier Hypothesis have been reported. We performed the first explicit test, by comparing estimated census population size and genome size in mammals while incorporating potential covariates and the effect of shared evolutionary history. We found a lack of correlation between census population size and genome size among 199 species of mammals. These results suggest that population size is not the predominant factor influencing genome size and that the Drift-Barrier Hypothesis should be considered provisional.

Which factors contribute most to genome size variation within angiosperms?

Genome size varies greatly across the flowering plants and has played an important role in shaping their evolution. It has been reported that many factors correlate with the variation in genome size, but few studies have systematically explored this at the genomic level. Here, we scan genomic information for 74 species from 74 families in 38 orders covering the major groups of angiosperms (the taxonomic information was acquired from the latest Angiosperm Phylogeny Group (APG IV) system) to evaluate the correlation between genome size variation and different genome characteristics: polyploidization, different types of repeat sequence content, and the dynamics of long terminal repeat retrotransposons (LTRs). Surprisingly, we found that polyploidization shows no significant correlation with genome size, while LTR content demonstrates a significantly positive correlation. This may be due to genome instability after polyploidization, and since LTRs occupy most of the genome content, it may directly result in most of the genome variation. We found that the LTR insertion time is significantly negatively correlated with genome size, which may reflect the competition between insertion and deletion of LTRs in each genome, and that the old insertions are usually easy to recognize and eliminate. We also noticed that most of the LTR burst occurred within the last 3 million years, a timeframe consistent with the violent climate fluctuations in the Pleistocene. Our findings enhance our understanding of genome size evolution within angiosperms, and our methods offer immediate implications for corresponding research in other datasets.

Plant Long Noncoding RNAs: New Players in the Field of Post-Transcriptional Regulations

The first reference to the "C-value paradox" reported an apparent imbalance between organismal genome size and morphological complexity. Since then, next-generation sequencing has revolutionized genomic research and revealed that eukaryotic transcriptomes contain a large fraction of non-protein-coding components. Eukaryotic genomes are pervasively transcribed and noncoding regions give rise to a plethora of noncoding RNAs with undeniable biological functions. Among them, long noncoding RNAs (lncRNAs) seem to represent a new layer of gene expression regulation, participating in a wide range of molecular mechanisms at the transcriptional and post-transcriptional levels. In addition to their role in epigenetic regulation, plant lncRNAs have been associated with the degradation of complementary RNAs, the regulation of alternative splicing, protein sub-cellular localization, the promotion of translation and protein post-translational modifications. In this review, we report and integrate numerous and complex mechanisms through which long noncoding transcripts regulate post-transcriptional gene expression in plants.

Human Ubiquitin-Specific Peptidase 18 Is Regulated by microRNAs via the 3'Untranslated Region, A Sequence Duplicated in Long Intergenic Non-coding RNA Genes Residing in chr22q11.21

Ubiquitin-specific peptidase 18 (USP18) acts as gatekeeper of type I interferon (IFN) responses by binding to the IFN receptor subunit IFNAR2 and preventing activation of the downstream JAK/STAT pathway. In any given cell type, the level of USP18 is a key determinant of the output of IFN-stimulated transcripts. How the baseline level of USP18 is finely tuned in different cell types remains ill defined. Here, we identified microRNAs (miRNAs) that efficiently target USP18 through binding to the 3’untranslated region (3’UTR). Among these, three miRNAs are particularly enriched in circulating monocytes which exhibit low baseline USP18. Intriguingly, the USP18 3’UTR sequence is duplicated in human and chimpanzee genomes. In humans, four USP18 3’UTR copies were previously found to be embedded in long intergenic non-coding (linc) RNA genes residing in chr22q11.21 and known as FAM247A-D. Here, we further characterized their sequence and measured their expression profile in human tissues. Importantly, we describe an additional lincRNA bearing USP18 3’UTR (here linc-UR-B1) that is expressed only in testis. RNA-seq data analyses from testicular cell subsets revealed a positive correlation between linc-UR-B1 and USP18 expression in spermatocytes and spermatids. Overall, our findings uncover a set of miRNAs and lincRNAs, which may be part of a network evolved to fine-tune baseline USP18, particularly in cell types where IFN responsiveness needs to be tightly controlled.

Retrotransposons and the Evolution of Genome Size in Pisum

Here we investigate the plant population genetics of retrotransposon insertion sites in pea to find out whether genetic drift and the neutral theory of molecular evolution can account for their abundance in the pea genome. (1) We asked whether two contrasting types of pea LTR-containing retrotransposons have the frequency and age distributions consistent with the behavior of neutral alleles and whether these parameters can explain the rate of change of genome size in legumes. (2) We used the recently assembled v1a pea genome sequence to obtain data on LTR-LTR divergence from which their age can be estimated. We coupled these data to prior information on the distribution of insertion site alleles. (3) We found that the age and frequency distribution data are consistent with the neutral theory. (4) We concluded that demographic processes are the underlying cause of genome size variation in legumes.

Increased WD40 motifs in Planctomycete bacteria and their evolutionary relevance

Species of the family Planctomycetes have a complex intracellular structure, which is distinct from that of the majority of non-Planctomycetes bacteria. At present, genomic evidence of the evolution of intracellular complexity is lacking, cognitions of Planctomycetes's intracellular structure mainly rely on electron microscope observation. As the presence of WD40 motifs in eukaryotic proteins probably links to intracellular complexity, bioinformatic studies were conducted to detect and enumerate WD40 motifs, WD40 domains, and WD40 motif-bearing proteins in the genomes of 11 Planctomycetes species, 2775 non-Planctomycetes bacteria, and 63 representative eukaryotes. Compared to non-Planctomycetes bacteria (average 5 WD40 motifs and 1 WD40 motif-bearing protein per genome), a large increase in the number of WD40 motifs in Planctomycetes species (average 116 WD40 motifs and 26 WD40 motif-bearing proteins per genome) was observed. However, the average number of WD40 motifs in Planctomycetes species was significantly lower than that of eukaryotes (average 584 WD40 motifs and 193 WD40 motif-bearing proteins per genome). The number of WD40 motif-bearing proteins was found to correlate with genome size and gene number. Most WD40 motif-bearing proteins of Planctomycetes species belonged to the categories of 'ribosome assembly protein 4' and 'eukaryotic-like serine/threonine protein kinase.' Collinearity analysis of amino acid compositions of Planctomycetes and eukaryotic WD40 motifs revealed that the sequences of the four anti-parallel β-sheets of WD40 motifs were conserved. However, a number of Planctomycetes WD40 motifs had increased size of the interval region of β-sheets D and A. Taken together, results of this study suggest a positive correlation between the number of WD40 motif-bearing proteins and the evolution of Planctomycetes species toward a complex intracellular structure similar to that of eukaryotes.

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.

The IRI-DICE hypothesis: ionizing radiation-induced DSBs may have a functional role for non-deterministic responses at low doses

Low-dose ionizing radiation (IR) responses remain an unresolved issue in radiation biology and risk assessment. Accurate knowledge of low-dose responses is important for estimation of normal tissue risk in cancer radiotherapy or health risks from occupational or hazard exposure. Cellular responses to low-dose IR appear diverse and stochastic in nature and to date no model has been proposed to explain the underlying mechanisms. Here, we propose a hypothesis on IR-induced double-strand break (DSB)-induced cis effects (IRI-DICE) and introduce DNA sequence functionality as a submicron-scale target site with functional outcome on gene expression: DSB induction in a certain genetic target site such as promotor, regulatory element, or gene core would lead to changes in transcript expression, which may range from suppression to overexpression depending on which functional element was damaged. The DNA damage recognition and repair machinery depicts threshold behavior requiring a certain number of DSBs for induction. Stochastically distributed persistent disruption of gene expression may explain-in part-the diverse nature of low-dose responses until the repair machinery is initiated at increased absorbed dose. Radiation quality and complexity of DSB lesions are also discussed. Currently, there are no technologies available to irradiate specific genetic sites to test the IRI-DICE hypothesis directly. However, supportive evidence may be achieved by developing a computational model that combines radiation transport codes with a genomic DNA model that includes sequence functionality and transcription to simulate expression changes in an irradiated cell population. To the best of our knowledge, IRI-DICE is the first hypothesis that includes sequence functionality of different genetic elements in the radiation response and provides a model for the diversity of radiation responses in the (very) low dose regimen.

Long noncoding RNAs shape transcription in plants

The advent of novel high-throughput sequencing techniques has revealed that eukaryotic genomes are massively transcribed although only a small fraction of RNAs exhibits protein-coding capacity. In the last years, long noncoding RNAs (lncRNAs) have emerged as regulators of eukaryotic gene expression in a wide range of molecular mechanisms. Plant lncRNAs can be transcribed by alternative RNA polymerases, acting directly as long transcripts or can be processed into active small RNAs. Several lncRNAs have been recently shown to interact with chromatin, DNA or nuclear proteins to condition the epigenetic environment of target genes or modulate the activity of transcriptional complexes. In this review, we will summarize the recent discoveries about the actions of plant lncRNAs in the regulation of gene expression at the transcriptional level.

Reverse-genetics studies of lncRNAs-what we have learnt and paths forward

Long non-coding RNAs (lncRNAs) represent a major fraction of the transcriptome in multicellular organisms. Although a handful of well-studied lncRNAs are broadly recognized as biologically meaningful, the fraction of such transcripts out of the entire collection of lncRNAs remains a subject of vigorous debate. Here we review the evidence for and against biological functionalities of lncRNAs and attempt to arrive at potential modes of lncRNA functionality that would reconcile the contradictory conclusions. Finally, we discuss different strategies of phenotypic analyses that could be used to investigate such modes of lncRNA functionality.

The Genomic Code: A Pervasive Encoding/Molding of Chromatin Structures and a Solution of the "Non-Coding DNA" Mystery

Recent investigations have revealed 1) that the isochores of the human genome group into two super-families characterized by two different long-range 3D structures, and 2) that these structures, essentially based on the distribution and topology of short sequences, mold primary chromatin domains (and define nucleosome binding). More specifically, GC-poor, gene-poor isochores are low-heterogeneity sequences with oligo-A spikes that mold the lamina-associated domains (LADs), whereas GC-rich, gene-rich isochores are characterized by single or multiple GC peaks that mold the topologically associating domains (TADs). The formation of these "primary TADs" may be followed by extrusion under the action of cohesin and CTCF. Finally, the genomic code, which is responsible for the pervasive encoding and molding of primary chromatin domains (LADs and primary TADs, namely the "gene spaces"/"spatial compartments") resolves the longstanding problems of "non-coding DNA," "junk DNA," and "selfish DNA" leading to a new vision of the genome as shaped by DNA sequences.

The Protein-Coding Human Genome: Annotating High-Hanging Fruits

The major transcript variants of human protein-coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes-they can be protein-coding, noncoding, or pseudogenes-and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro-exons and wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re-assignments. The emerging human pan-genome is necessitating distinctive annotations incorporating differences between individuals and between populations.

Fundamental asymmetry of insertions and deletions in genomes size evolution

The origin of large genomes that underlies the long standing "C-value enigma" is only partially explained by selfish DNA. We investigated insertions and deletions (indels) of nucleotides and discussed their relevance in size evolution of random biological sequences (RBS) and genomes. By developing a probabilistic model of RBS based on size evolution of expandable sites in a thought perfect genome, it was found that insertion bias engenders exponential increase of average RBS sizes. When combined with existing large segments of genome that are not subject to selection pressure (e.g. selfish DNA), such insertion bias results in explosive expansion of genomes, and therefore helps explain the "C value enigma" besides selfish DNA. Such increase of RBS size is caused by the fundamental asymmetry of indels, with insertions result in more available sites and deletions result in less deletable nucleotides. In qualitative agreement with the size distribution of known genomes, tails of RBS size distributions exhibit exponential decay with probabilities of larger RBS segments being smaller. Unsurprisingly, a slight deletion bias (higher deletions probabilities) results in a slow decrease of average RBS size and may lead to their eventual vanishing. Contrary to intuition, strictly balanced insertion and deletion results in linearly increasing instead of completely fixed RBS size. Nonetheless, such slow linear increase of average RBS sizes with time are small in magnitude and are consequently not influential on genome size evolution, and certainly not a major contributor for the "C-value enigma". Our model suggested that insertion bias of nucleotides may provide complementary explanation for large genomes besides selfish DNA. The fundamental indel asymmetry is applicable for all forms of genomic insertions and deletions. Long-lasting exponential increase of genome size present energy and material requirement that is impossible to sustain. We therefore concluded that if there were explosively accelerating expansion caused by significant effective insertion bias for any survival species, it must have occurred sporadically. Our model also provided an explanation for the observed proportional evolution of genome size.

Genome-Wide Identification of Microsatellites and Transposable Elements in the Dromedary Camel Genome Using Whole-Genome Sequencing Data

Transposable elements (TEs) along with simple sequence repeats (SSRs) are prevalent in eukaryotic genome, especially in mammals. Repetitive sequences form approximately one-third of the camelid genomes, so study on this part of genome can be helpful in providing deeper information from the genome and its evolutionary path. Here, in order to improve our understanding regarding the camel genome architecture, the whole genome of the two dromedaries (Yazdi and Trodi camels) was sequenced. Totally, 92- and 84.3-Gb sequence data were obtained and assembled to 137,772 and 149,997 contigs with a N50 length of 54,626 and 54,031 bp in Yazdi and Trodi camels, respectively. Results showed that 30.58% of Yazdi camel genome and 30.50% of Trodi camel genome were covered by TEs. Contrary to the observed results in the genomes of cattle, sheep, horse, and pig, no endogenous retrovirus-K (ERVK) elements were found in the camel genome. Distribution pattern of DNA transposons in the genomes of dromedary, Bactrian, and cattle was similar in contrast with LINE, SINE, and long terminal repeat (LTR) families. Elements like RTE-BovB belonging to LINEs family in cattle and sheep genomes are dramatically higher than genome of dromedary. However, LINE1 (L1) and LINE2 (L2) elements cover higher percentage of LINE family in dromedary genome compared to genome of cattle. Also, 540,133 and 539,409 microsatellites were identified from the assembled contigs of Yazdi and Trodi dromedary camels, respectively. In both samples, di-(393,196) and tri-(65,313) nucleotide repeats contributed to about 42.5% of the microsatellites. The findings of the present study revealed that non-repetitive content of mammalian genomes is approximately similar. Results showed that 9.1 Mb (0.47% of whole assembled genome) of Iranian dromedary's genome length is made up of SSRs. Annotation of repetitive content of Iranian dromedary camel genome revealed that 9,068 and 11,544 genes contain different types of TEs and SSRs, respectively. SSR markers identified in the present study can be used as a valuable resource for genetic diversity investigations and marker-assisted selection (MAS) in camel-breeding programs.

The N-space Episenome unifies cellular information space-time within cognition-based evolution

Self-referential cellular homeostasis is maintained by the measured assessment of both internal status and external conditions based within an integrated cellular information field. This cellular field attachment to biologic information space-time coordinates environmental inputs by connecting the cellular senome, as the sum of the sensory experiences of the cell, with its genome and epigenome. In multicellular organisms, individual cellular information fields aggregate into a collective information architectural matrix, termed a N-space Episenome, that enables mutualized organism-wide information management. It is hypothesized that biological organization represents a dual heritable system constituted by both its biological materiality and a conjoining N-space Episenome. It is further proposed that morphogenesis derives from reciprocations between these inter-related facets to yield coordinated multicellular growth and development. The N-space Episenome is conceived as a whole cell informational projection that is heritable, transferable via cell division and essential for the synchronous integration of the diverse self-referential cells that constitute holobionts.

A rigorous measure of genome-wide genetic shuffling that takes into account crossover positions and Mendel's second law

Comparative studies in evolutionary genetics rely critically on evaluation of the total amount of genetic shuffling that occurs during gamete production. Such studies have been hampered by the absence of a direct measure of this quantity. Existing measures consider crossing-over by simply counting the average number of crossovers per meiosis. This is qualitatively inadequate, because the positions of crossovers along a chromosome are also critical: a crossover toward the middle of a chromosome causes more shuffling than a crossover toward the tip. Moreover, traditional measures fail to consider shuffling from independent assortment of homologous chromosomes (Mendel's second law). Here, we present a rigorous measure of genome-wide shuffling that does not suffer from these limitations. We define the parameter [Formula: see text] as the probability that the alleles at two randomly chosen loci are shuffled during gamete production. This measure can be decomposed into separate contributions from crossover number and position and from independent assortment. Intrinsic implications of this metric include the fact that [Formula: see text] is larger when crossovers are more evenly spaced, which suggests a selective advantage of crossover interference. Utilization of [Formula: see text] is enabled by powerful emergent methods for determining crossover positions either cytologically or by DNA sequencing. Application of our analysis to such data from human male and female reveals that (i) [Formula: see text] in humans is close to its maximum possible value of 1/2 and that (ii) this high level of shuffling is due almost entirely to independent assortment, the contribution of which is ∼30 times greater than that of crossovers.

Sc-ncDNAPred: A Sequence-Based Predictor for Identifying Non-coding DNA in Saccharomyces cerevisiae

With the rapid development of high-speed sequencing technologies and the implementation of many whole genome sequencing project, research in the genomics is advancing from genome sequencing to genome synthesis. Synthetic biology technologies such as DNA-based molecular assemblies, genome editing technology, directional evolution technology and DNA storage technology, and other cutting-edge technologies emerge in succession. Especially the rapid growth and development of DNA assembly technology may greatly push forward the success of artificial life. Meanwhile, DNA assembly technology needs a large number of target sequences of known information as data support. Non-coding DNA (ncDNA) sequences occupy most of the organism genomes, thus accurate recognizing of them is necessary. Although experimental methods have been proposed to detect ncDNA sequences, they are expensive for performing genome wide detections. Thus, it is necessary to develop machine-learning methods for predicting non-coding DNA sequences. In this study, we collected the ncDNA benchmark dataset of Saccharomyces cerevisiae and reported a support vector machine-based predictor, called Sc-ncDNAPred, for predicting ncDNA sequences. The optimal feature extraction strategy was selected from a group included mononucleotide, dimer, trimer, tetramer, pentamer, and hexamer, using support vector machine learning method. Sc-ncDNAPred achieved an overall accuracy of 0.98. For the convenience of users, an online web-server has been built at: http://server.malab.cn/Sc_ncDNAPred/index.jsp.

Defining microbiome function

Why does a microorganism associate with a host? What function does it perform? Such questions are difficult to unequivocally address and remain hotly debated. This is partially because scientists often use different philosophical definitions of 'function' ambiguously and interchangeably, as exemplified by the controversy surrounding the Encyclopedia of DNA Elements (ENCODE) project. Here, I argue that research studying host-associated microbial communities and their genomes (that is, microbiomes) faces similar pitfalls and that unclear or misapplied conceptions of function underpin many controversies in this field. In particular, experiments that support phenomenological models of function can inappropriately be used to support functional models that instead require specific measurements of evolutionary selection. Microbiome research also requires uniquely clear definitions of 'who the function is for', in contrast to most single-organism systems where this is implicit. I illustrate how obscuring either of these issues can lead to substantial confusion and misinterpretation of microbiome function, using the varied conceptions of the holobiont as a current and cogent example. Using clear functional definitions and appropriate types of evidence are essential to effectively communicate microbiome research and foster host health.

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.

Current Research on Non-Coding Ribonucleic Acid (RNA)

Non-coding ribonucleic acid (RNA) has without a doubt captured the interest of biomedical researchers. The ability to screen the entire human genome with high-throughput sequencing technology has greatly enhanced the identification, annotation and prediction of the functionality of non-coding RNAs. In this review, we discuss the current landscape of non-coding RNA research and quantitative analysis. Non-coding RNA will be categorized into two major groups by size: long non-coding RNAs and small RNAs. In long non-coding RNA, we discuss regular long non-coding RNA, pseudogenes and circular RNA. In small RNA, we discuss miRNA, transfer RNA, piwi-interacting RNA, small nucleolar RNA, small nuclear RNA, Y RNA, single recognition particle RNA, and 7SK RNA. We elaborate on the origin, detection method, and potential association with disease, putative functional mechanisms, and public resources for these non-coding RNAs. We aim to provide readers with a complete overview of non-coding RNAs and incite additional interest in non-coding RNA research.

Biological information systems: Evolution as cognition-based information management

An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental stresses.

Defining Functional Genic Regions in the Human Genome through Integration of Biochemical, Evolutionary, and Genetic Evidence

The human genome is dominated by large tracts of DNA with extensive biochemical activity but no known function. In particular, it is well established that transcriptional activities are not restricted to known genes. However, whether this intergenic transcription represents activity with functional significance or noise is under debate, highlighting the need for an effective method of defining functional genomic regions. Moreover, these discoveries raise the question whether genomic regions can be defined as functional based solely on the presence of biochemical activities, without considering evolutionary (conservation) and genetic (effects of mutations) evidence. Here, computational models integrating genetic, evolutionary, and biochemical evidence are established that provide reliable predictions of human protein-coding and RNA genes. Importantly, in addition to sequence conservation, biochemical features allow accurate predictions of genic sequences with phenotypic evidence under strong purifying selection, suggesting that they can be used as an alternative measure of selection. Moreover, 18.5% of annotated noncoding RNAs exhibit higher degrees of similarity to phenotype genes and, thus, are likely functional. However, 64.5% of noncoding RNAs appear to belong to a sequence class of their own, and the remaining 17% are more similar to pseudogenes and random intergenic sequences that may represent noisy transcription.

Retrotransposons Are the Major Contributors to the Expansion of the Drosophila ananassae Muller F Element

The discordance between genome size and the complexity of eukaryotes can partly be attributed to differences in repeat density. The Muller F element (∼5.2 Mb) is the smallest chromosome in Drosophila melanogaster, but it is substantially larger (>18.7 Mb) in D. ananassae To identify the major contributors to the expansion of the F element and to assess their impact, we improved the genome sequence and annotated the genes in a 1.4-Mb region of the D. ananassae F element, and a 1.7-Mb region from the D element for comparison. We find that transposons (particularly LTR and LINE retrotransposons) are major contributors to this expansion (78.6%), while Wolbachia sequences integrated into the D. ananassae genome are minor contributors (0.02%). Both D. melanogaster and D. ananassae F-element genes exhibit distinct characteristics compared to D-element genes (e.g., larger coding spans, larger introns, more coding exons, and lower codon bias), but these differences are exaggerated in D. ananassae Compared to D. melanogaster, the codon bias observed in D. ananassae F-element genes can primarily be attributed to mutational biases instead of selection. The 5' ends of F-element genes in both species are enriched in dimethylation of lysine 4 on histone 3 (H3K4me2), while the coding spans are enriched in H3K9me2. Despite differences in repeat density and gene characteristics, D. ananassae F-element genes show a similar range of expression levels compared to genes in euchromatic domains. This study improves our understanding of how transposons can affect genome size and how genes can function within highly repetitive domains.

The lncRNA VELUCT strongly regulates viability of lung cancer cells despite its extremely low abundance

Little is known about the function of most non-coding RNAs (ncRNAs). The majority of long ncRNAs (lncRNAs) is expressed at very low levels and it is a matter of intense debate whether these can be of functional relevance. Here, we identified lncRNAs regulating the viability of lung cancer cells in a high-throughput RNA interference screen. Based on our previous expression profiling, we designed an siRNA library targeting 638 lncRNAs upregulated in human cancer. In a functional siRNA screen analyzing the viability of lung cancer cells, the most prominent hit was a novel lncRNA which we called Viability Enhancing LUng Cancer Transcript (VELUCT). In silico analyses confirmed the non-coding properties of the transcript. Surprisingly, VELUCT was below the detection limit in total RNA from NCI-H460 cells by RT-qPCR as well as RNA-Seq, but was robustly detected in the chromatin-associated RNA fraction. It is an extremely low abundant lncRNA with an RNA copy number of less than one copy per cell. Blocking transcription with actinomycin D revealed that VELUCT RNA was highly unstable which may partially explain its low steady-state concentration. Despite its extremely low abundance, loss-of-function of VELUCT with three independent experimental approaches in three different lung cancer cell lines led to a significant reduction of cell viability: Next to four individual siRNAs, also two complex siPOOLs as well as two antisense oligonucleotides confirmed the strong and specific phenotype. In summary, the extremely low abundant lncRNA VELUCT is essential for regulation of cell viability in several lung cancer cell lines. Hence, VELUCT is the first example for a lncRNA that is expressed at a very low level, but has a strong loss-of-function phenotype. Thus, our study proves that at least individual low-abundant lncRNAs can play an important functional role.

In Silico Approach for Characterization and Comparison of Repeats in the Genomes of Oil and Date Palms

Transposable elements (TEs) are mobile genetic elements present in almost all eukaryotic genomes. Due to their typical patterns of repetition, discovery, and characterization, they demand analysis by various bioinformatics software. Probably, as a result of the need for a complex analysis, many genomes publicly available do not have these elements annotated yet. In this study, a de novo and homology-based identification of TEs and microsatellites was performed using genomic data from 3 palm species: Elaeis oleifera (American oil palm, v.1, Embrapa, unpublished; v.8, Malaysian Palm Oil Board [MPOB], public), Elaeis guineensis (African oil palm, v.5, MPOB, public), and Phoenix dactylifera (date palm). The estimated total coverage of TEs was 50.96% (523 572 kb) and 42.31% (593 463 kb), 39.41% (605 015 kb), and 33.67% (187 361 kb), respectively. A total of 155 726 microsatellite loci were identified in the genomes of oil and date palms. This is the first detailed description of repeats in the genomes of oil and date palms. A relatively high diversity and abundance of TEs were found in the genomes, opening a range of further opportunities for applied research in these genera. The development of molecular markers (mainly simple sequence repeat), which may be immediately applied in breeding programs of those species to support the selection of superior genotypes and to enhance knowledge of the genetic structure of the breeding and natural populations, is the most notable opportunity.

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.

Useful parasites: the evolutionary biology and biotechnology applications of transposable elements

Transposable elements usually comprise the most abundant nongenic fraction of eukaryotic genomes. Because of their capacity to selfreplicate and to induce a wide range of mutations, transposable elements have long been considered as 'parasitic' or 'selfish'. Today, we recognize that the findings about genomic changes affected by transposable elements have considerably altered our view of the ways in which genomes evolve and work. Numerous studies have provided evidences that mobile elements have the potential to act as agents of evolution by increasing, rearranging and diversifying the genetic repertoire of their hosts. With large-scale sequencing becoming increasingly available, more and more scientists come across transposable element sequences in their data. I will provide examples that transposable elements, although having signatures of 'selfish' DNA, play a significant biological role in the maintainance of genome integrity and providing novel regulatoty networks. These features, along with the transpositional and mutagenic capacity to produce a raw genetic diversity, make the genome mobile fraction, a key player in species adaptation and microevolution. The last but not least, transposable elements stand as informative DNA markers that may complement other conventional DNA markers. Altogether, transposable elements represent a promising, but still largely unexplored research niche and deserve to be included into the agenda of molecular ecologists, evolutionary geneticists, conservation biologists and plant breeders.

Time, space, and disorder in the expanding proteome universe

Proteins are highly dynamic entities. Their myriad functions require specific structures, but proteins' dynamic nature ranges all the way from the local mobility of their amino acid constituents to mobility within and well beyond single cells. A truly comprehensive view of the dynamic structural proteome includes: (i) alternative sequences, (ii) alternative conformations, (iii) alternative interactions with a range of biomolecules, (iv) cellular localizations, (v) alternative behaviors in different cell types. While these aspects have traditionally been explored one protein at a time, we highlight recently emerging global approaches that accelerate comprehensive insights into these facets of the dynamic nature of protein structure. Computational tools that integrate and expand on multiple orthogonal data types promise to enable the transition from a disjointed list of static snapshots to a structurally explicit understanding of the dynamics of cellular mechanisms.

Genes, behavior, and behavior genetics

According to the 'first law' of behavior genetics, 'All human behavioral traits are heritable.' Accepting the validity of this first law and employing statistical methods, researchers within psychology, sociology, political science, economics, and business claim to have demonstrated that all the behaviors studied by their disciplines are heritable-no matter how culturally specific these behaviors appear to be. Further, in many cases they claim to have identified specific genes that play a role in those behaviors. The validity of behavior genetics as a discipline depends upon the validity of the research methods used to justify such claims. It also depends, foundationally, upon certain key assumptions concerning the relationship between genotype (one's specific DNA sequences) and phenotype (any and all observable traits or characteristics). In this article, I examine-and find serious flaws with-both the methodologies of behavior genetics and the underlying assumptions concerning the genotype-phenotype relationship. WIREs Cogn Sci 2017, 8:e1405. doi: 10.1002/wcs.1405 For further resources related to this article, please visit the WIREs website.

Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms

A major aim of evolutionary biology is to explain the respective roles of adaptive versus non-adaptive changes in the evolution of complexity. While selection is certainly responsible for the spread and maintenance of complex phenotypes, this does not automatically imply that strong selection enhances the chance for the emergence of novel traits, that is, the origination of complexity. Population size is one parameter that alters the relative importance of adaptive and non-adaptive processes: as population size decreases, selection weakens and genetic drift grows in importance. Because of this relationship, many theories invoke a role for population size in the evolution of complexity. Such theories are difficult to test empirically because of the time required for the evolution of complexity in biological populations. Here, we used digital experimental evolution to test whether large or small asexual populations tend to evolve greater complexity. We find that both small and large-but not intermediate-sized-populations are favored to evolve larger genomes, which provides the opportunity for subsequent increases in phenotypic complexity. However, small and large populations followed different evolutionary paths towards these novel traits. Small populations evolved larger genomes by fixing slightly deleterious insertions, while large populations fixed rare beneficial insertions that increased genome size. These results demonstrate that genetic drift can lead to the evolution of complexity in small populations and that purifying selection is not powerful enough to prevent the evolution of complexity in large populations.

Capturing Darwin's dream

Evolutionary biologists from Darwin forward have dreamed of having data that would elucidate our understanding of evolutionary history and the diversity of life. Sequence capture is a relatively old DNA technology, but its use is growing rapidly due to advances in (i) massively parallel DNA sequencing approaches and instruments, (ii) massively parallel bait construction, (iii) methods to identify target regions and (iv) sample preparation. We give a little historical context to these developments, summarize some of the important advances reported in this special issue and point to further advances that can be made to help fulfill Darwin's dream.