Genomic context analysis reveals dense interaction network between vertebrate ultraconserved non-coding elements

Overview of methods for characterization and visualization of a protein–protein interaction network in a multi-omics integration context

At the heart of the cellular machinery through the regulation of cellular functions, protein–protein interactions (PPIs) have a significant role. PPIs can be analyzed with network approaches. Construction of a PPI network requires prediction of the interactions. All PPIs form a network. Different biases such as lack of data, recurrence of information, and false interactions make the network unstable. Integrated strategies allow solving these different challenges. These approaches have shown encouraging results for the understanding of molecular mechanisms, drug action mechanisms, and identification of target genes. In order to give more importance to an interaction, it is evaluated by different confidence scores. These scores allow the filtration of the network and thus facilitate the representation of the network, essential steps to the identification and understanding of molecular mechanisms. In this review, we will discuss the main computational methods for predicting PPI, including ones confirming an interaction as well as the integration of PPIs into a network, and we will discuss visualization of these complex data.

The USDA-ARS Ag100Pest Initiative: High-Quality Genome Assemblies for Agricultural Pest Arthropod Research

Simple Summary

High-quality genome assemblies are essential tools for modern biological research. In the past, creating genome assemblies was prohibitively expensive and time-consuming for most non-model insect species due to, in part, the technical challenge of isolating the necessary quantity and quality of DNA from many species. Sequencing methods have now improved such that many insect genomes can be sequenced and assembled at scale. We created the Ag100Pest Initiative to propel agricultural research forward by assembling reference-quality genomes of important arthropod pest species. Here, we describe the Ag100Pest Initiative’s processes and experimental procedures. We show that the Ag100Pest Initiative will greatly expand the diversity of publicly available arthropod genome assemblies. We also demonstrate the high quality of preliminary contig assemblies. We share arthropod-specific technical details and insights that we have gained during the project. The methods and preliminary results presented herein should help other researchers attain similarly high-quality assemblies, effectively changing the landscape of insect genomics.

Abstract

The phylum Arthropoda includes species crucial for ecosystem stability, soil health, crop production, and others that present obstacles to crop and animal agriculture. The United States Department of Agriculture’s Agricultural Research Service initiated the Ag100Pest Initiative to generate reference genome assemblies of arthropods that are (or may become) pests to agricultural production and global food security. We describe the project goals, process, status, and future. The first three years of the project were focused on species selection, specimen collection, and the construction of lab and bioinformatics pipelines for the efficient production of assemblies at scale. Contig-level assemblies of 47 species are presented, all of which were generated from single specimens. Lessons learned and optimizations leading to the current pipeline are discussed. The project name implies a target of 100 species, but the efficiencies gained during the project have supported an expansion of the original goal and a total of 158 species are currently in the pipeline. We anticipate that the processes described in the paper will help other arthropod research groups or other consortia considering genome assembly at scale.

Functional and structural basis of extreme conservation in vertebrate 5' untranslated regions

The lack of knowledge about extreme conservation in genomes remains a major gap in our understanding of the evolution of gene regulation. Here, we reveal an unexpected role of extremely conserved 5' untranslated regions (UTRs) in noncanonical translational regulation that is linked to the emergence of essential developmental features in vertebrate species. Endogenous deletion of conserved elements within these 5' UTRs decreased gene expression, and extremely conserved 5' UTRs possess cis-regulatory elements that promote cell-type-specific regulation of translation. We further developed in-cell mutate-and-map (icM²), a new methodology that maps RNA structure inside cells. Using icM², we determined that an extremely conserved 5' UTR encodes multiple alternative structures and that each single nucleotide within the conserved element maintains the balance of alternative structures important to control the dynamic range of protein expression. These results explain how extreme sequence conservation can lead to RNA-level biological functions encoded in the untranslated regions of vertebrate genomes.

Genomic Characterization and Curation of UCEs Improves Species Tree Reconstruction

Ultraconserved genomic elements (UCEs) are generally treated as independent loci in phylogenetic analyses. The identification pipeline for UCE probes does not require prior knowledge of genetic identity, only selecting loci that are highly conserved, single copy, without repeats, and of a particular length. Here, we characterized UCEs from 11 phylogenomic studies across the animal tree of life, from birds to marine invertebrates. We found that within vertebrate lineages, UCEs are mostly intronic and intergenic, while in invertebrates, the majority are in exons. We then curated four different sets of UCE markers by genomic category from five different studies including: birds, mammals, fish, Hymenoptera (ants, wasps, and bees), and Coleoptera (beetles). Of genes captured by UCEs, we find that many are represented by two or more UCEs, corresponding to nonoverlapping segments of a single gene. We considered these UCEs to be nonindependent, merged all UCEs that belonged to a particular gene, constructed gene and species trees, and then evaluated the subsequent effect of merging cogenic UCEs on gene and species tree reconstruction. Average bootstrap support for merged UCE gene trees was significantly improved across all data sets apparently driven by the increase in loci length. Additionally, we conducted simulations and found that gene trees generated from merged UCEs were more accurate than those generated by unmerged UCEs. As loci length improves gene tree accuracy, this modest degree of UCE characterization and curation impacts downstream analyses and demonstrates the advantages of incorporating basic genomic characterizations into phylogenomic analyses. [Anchored hybrid enrichment; ants; ASTRAL; bait capture; carangimorph; Coleoptera; conserved nonexonic elements; exon capture; gene tree; Hymenoptera; mammal; phylogenomic markers; songbird; species tree; ultraconserved elements; weevils.]

The Developmental Gene Hypothesis for Punctuated Equilibrium: Combined Roles of Developmental Regulatory Genes and Transposable Elements

Theories of the genetics underlying punctuated equilibrium (PE) have been vague to date. Here the developmental gene hypothesis is proposed, which states that: 1) developmental regulatory (DevReg) genes are responsible for the orchestration of metazoan morphogenesis and their extreme conservation and mutation intolerance generates the equilibrium or stasis present throughout much of the fossil record and 2) the accumulation of regulatory elements and recombination within these same genes-often derived from transposable elements-drives punctuated bursts of morphological divergence and speciation across metazoa. This two-part hypothesis helps to explain the features that characterize PE, providing a theoretical genetic basis for the once-controversial theory. Also see the video abstract here https://youtu.be/C-fu-ks5yDs.

Ultraconserved Elements Occupy Specific Arenas of Three-Dimensional Mammalian Genome Organization

This study explores the relationship between three-dimensional genome organization and ultraconserved elements (UCEs), an enigmatic set of DNA elements that are perfectly conserved between the reference genomes of distantly related species. Examining both human and mouse genomes, we interrogate the relationship of UCEs to three features of chromosome organization derived from Hi-C studies. We find that UCEs are enriched within contact domains and, further, that the subset of UCEs within domains shared across diverse cell types are linked to kidney-related and neuronal processes. In boundaries, UCEs are generally depleted, with those that do overlap boundaries being overrepresented in exonic UCEs. Regarding loop anchors, UCEs are neither overrepresented nor underrepresented, but those present in loop anchors are enriched for splice sites. Finally, as the relationships between UCEs and human Hi-C features are conserved in mouse, our findings suggest that UCEs contribute to interspecies conservation of genome organization and, thus, genome stability.

Dark-matter matters: Discriminating subtle blood cancers using the darkest DNA

The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter, the non-coding genomic regions lacking any functional annotation. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can distinguish the fine subtypes of disease that are otherwise genomically indistinguishable. We introduce a novel stochastic regularization, ReVeaL, that empowers ML to discriminate subtle cancer subtypes even from the same ‘cell of origin’. Analogous to heritability, implicitly defined on whole genome, we use predictability (F₁score) definable on portions of the genome. In an effort to distinguish cancer subtypes using dark-matter DNA, we applied ReVeaL to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, and dark. ReVeaL enabled improved discrimination of cancer subtypes for all segments of the genome. The non-genic, non-coding and dark-matter had the highest F₁ scores, with dark-matter having the highest level of predictability. Based on ReVeaL’s predictability of different genomic regions, dark-matter contains enough signal to significantly discriminate fine subtypes of disease. Hence, the agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention.

Many subtypes of cancer are unable to be distinguished based on their genomic profiles. With the ever-increasing use of sequencing, we now have the ability to look deeper into the genome and pick up on hidden signals in areas typically considered irrelevant to disease. To overcome the issue of rare variants and the vast amount of heterogeneity found in these non-coding sectors, we introduce a new algorithm capable of correcting for both challenges, ReVeaL. Using this approach, we are able to demonstrate that the non-coding regions of the genome have more signal for distinguishing subtle subtypes of disease compared to all the coding regions. Specifically, we show that the darkest unexplored genomic regions, the non-coding genome with no functional annotation whatsoever in the literature, have the strongest signal. Thus dark-matter does indeed matter and should not be ignored but rather considered for the continued pressing task of finding biomarkers of disease to adequately treat our patients.

Introduction of 'Generalized Genomic Signatures' for the quantification of neighbour preferences leads to taxonomy- and functionality-based distinction among sequences

Analysis of DNA composition at several length scales constitutes the bulk of many early studies aimed at unravelling the complexity of the organization and functionality of genomes. Dinucleotide relative abundances are considered an idiosyncratic feature of genomes, regarded as a ‘genomic signature’. Motivated by this finding, we introduce the ‘Generalized Genomic Signatures’ (GGSs), composed of over- and under-abundances of all oligonucleotides of a given length, thus filtering out compositional trends and neighbour preferences at any shorter range. Previous works on alignment-free genomic comparisons mostly rely on k-mer frequencies and not on distance-dependent neighbour preferences. Therein, nucleotide composition and proximity preferences are combined, while in the present work they are strictly separated, focusing uniquely on neighbour relationships. GGSs retain the potential or even outperform genomic signatures defined at the dinucleotide level in distinguishing between taxonomic subdivisions of bacteria, and can be more effectively implemented in microbial phylogenetic reconstruction. Moreover, we compare DNA sequences from the human genome corresponding to protein coding segments, conserved non-coding elements and non-functional DNA stretches. These classes of sequences have distinctive GGSs according to their genomic role and degree of conservation. Overall, GGSs constitute a trait characteristic of the evolutionary origin and functionality of different genomic segments.

Evolutionary stability of topologically associating domains is associated with conserved gene regulation

Background

The human genome is highly organized in the three-dimensional nucleus. Chromosomes fold locally into topologically associating domains (TADs) defined by increased intra-domain chromatin contacts. TADs contribute to gene regulation by restricting chromatin interactions of regulatory sequences, such as enhancers, with their target genes. Disruption of TADs can result in altered gene expression and is associated to genetic diseases and cancers. However, it is not clear to which extent TAD regions are conserved in evolution and whether disruption of TADs by evolutionary rearrangements can alter gene expression.

Results

Here, we hypothesize that TADs represent essential functional units of genomes, which are stable against rearrangements during evolution. We investigate this using whole-genome alignments to identify evolutionary rearrangement breakpoints of different vertebrate species. Rearrangement breakpoints are strongly enriched at TAD boundaries and depleted within TADs across species. Furthermore, using gene expression data across many tissues in mouse and human, we show that genes within TADs have more conserved expression patterns. Disruption of TADs by evolutionary rearrangements is associated with changes in gene expression profiles, consistent with a functional role of TADs in gene expression regulation.

Conclusions

Together, these results indicate that TADs are conserved building blocks of genomes with regulatory functions that are often reshuffled as a whole instead of being disrupted by rearrangements.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0556-x) contains supplementary material, which is available to authorized users.

Differential Gene Expression in the Human Brain Is Associated with Conserved, but Not Accelerated, Noncoding Sequences

Previous studies have found that genes which are differentially expressed within the developing human brain disproportionately neighbor conserved noncoding sequences (CNSs) that have an elevated substitution rate in humans and in other species. One explanation for this general association of differential expression with accelerated CNSs is that genes with pre-existing patterns of differential expression have been preferentially targeted by species-specific regulatory changes. Here we provide support for an alternative explanation: genes that neighbor a greater number of CNSs have a higher probability of differential expression and a higher probability of neighboring a CNS with lineage-specific acceleration. Thus, neighboring an accelerated element from any species signals that a gene likely neighbors many CNSs. We extend the analyses beyond the prenatal time points considered in previous studies to demonstrate that this association persists across developmental and adult periods. Examining differential expression between non-neural tissues suggests that the relationship between the number of CNSs a gene neighbors and its differential expression status may be particularly strong for expression differences among brain regions. In addition, by considering this relationship, we highlight a recently defined set of putative human-specific gain-of-function sequences that, even after adjusting for the number of CNSs neighbored by genes, shows a positive relationship with upregulation in the brain compared with other tissues examined.

SVD-phy: improved prediction of protein functional associations through singular value decomposition of phylogenetic profiles

Summary: A successful approach for predicting functional associations between non-homologous genes is to compare their phylogenetic distributions. We have devised a phylogenetic profiling algorithm, SVD-Phy, which uses truncated singular value decomposition to address the problem of uninformative profiles giving rise to false positive predictions. Benchmarking the algorithm against the KEGG pathway database, we found that it has substantially improved performance over existing phylogenetic profiling methods.

Availability and implementation: The software is available under the open-source BSD license at https://bitbucket.org/andrea/svd-phy

Contact:lars.juhl.jensen@cpr.ku.dk

Supplementary information:Supplementary data are available at Bioinformatics online.

Allele frequencies of variants in ultra conserved elements identify selective pressure on transcription factor binding

Ultra-conserved genes or elements (UCGs/UCEs) in the human genome are extreme examples of conservation. We characterized natural variations in 2884 UCEs and UCGs in two distinct populations; Singaporean Chinese (n = 280) and Italian (n = 501) by using a pooled sample, targeted capture, sequencing approach. We identify, with high confidence, in these regions the abundance of rare SNVs (MAF<0.5%) of which 75% is not present in dbSNP137. UCEs association studies for complex human traits can use this information to model expected background variation and thus necessary power for association studies. By combining our data with 1000 Genome Project data, we show in three independent datasets that prevalent UCE variants (MAF>5%) are more often found in relatively less-conserved nucleotides within UCEs, compared to rare variants. Moreover, prevalent variants are less likely to overlap transcription factor binding site. Using SNPfold we found no significant influence of RNA secondary structure on UCE conservation. All together, these results suggest UCEs are not under selective pressure as a stretch of DNA but are under differential evolutionary pressure on the single nucleotide level.

Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers

Scarce work has been done in the analysis of the composition of conserved non-coding elements (CNEs) that are identified by comparisons of two or more genomes and are found to exist in all metazoan genomes. Here we present the analysis of CNEs with a methodology that takes into account word occurrence at various lengths scales in the form of feature vector representation and rule based classifiers. We implement our approach on both protein-coding exons and CNEs, originating from human, insect (Drosophila melanogaster) and worm (Caenorhabditis elegans) genomes, that are either identified in the present study or obtained from the literature. Alignment free feature vector representation of sequences combined with rule-based classification methods leads to successful classification of the different CNEs classes. Biologically meaningful results are derived by comparison with the genomic signatures approach, and classification rates for a variety of functional elements of the genomes along with surrogates are presented.

Conserved noncoding elements follow power-law-like distributions in several genomes as a result of genome dynamics

Conserved, ultraconserved and other classes of constrained elements (collectively referred as CNEs here), identified by comparative genomics in a wide variety of genomes, are non-randomly distributed across chromosomes. These elements are defined using various degrees of conservation between organisms and several thresholds of minimal length. We here investigate the chromosomal distribution of CNEs by studying the statistical properties of distances between consecutive CNEs. We find widespread power-law-like distributions, i.e. linearity in double logarithmic scale, in the inter-CNE distances, a feature which is connected with fractality and self-similarity. Given that CNEs are often found to be spatially associated with genes, especially with those that regulate developmental processes, we verify by appropriate gene masking that a power-law-like pattern emerges irrespectively of whether elements found close or inside genes are excluded or not. An evolutionary model is put forward for the understanding of these findings that includes segmental or whole genome duplication events and eliminations (loss) of most of the duplicated CNEs. Simulations reproduce the main features of the observed size distributions. Power-law-like patterns in the genomic distributions of CNEs are in accordance with current knowledge about their evolutionary history in several genomes.

The mystery of extreme non-coding conservation

Regions of several dozen to several hundred base pairs of extreme conservation have been found in non-coding regions in all metazoan genomes. The distribution of these elements within and across genomes has suggested that many have roles as transcriptional regulatory elements in multi-cellular organization, differentiation and development. Currently, there is no known mechanism or function that would account for this level of conservation at the observed evolutionary distances. Previous studies have found that, while these regions are under strong purifying selection, and not mutational coldspots, deletion of entire regions in mice does not necessarily lead to identifiable changes in phenotype during development. These opposing findings lead to several questions regarding their functional importance and why they are under strong selection in the first place. In this perspective, we discuss the methods and techniques used in identifying and dissecting these regions, their observed patterns of conservation, and review the current hypotheses on their functional significance.