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Results for “genomics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Genome-wide analyses supported by RNA-Seq reveal non-canonical splice sites in plant genomes

Most eukaryotic genes comprise exons and introns thus requiring the precise removal of introns from pre-mRNAs to enable protein biosynthesis. U2 and U12 spliceosomes catalyze this step by recognizing motifs on the transcript in order to remove the introns. A process which is dependent on precise definition of exon-intron borders by splice sites, which are consequently highly conserved across species. Only very few combinations of terminal dinucleotides are frequently observed at intron ends, dominated by the canonical GT-AG splice sites on the DNA level.\n\nHere we investigate the occurrence of diverse combinations of dinucleotides at predicted splice sites. Analyzing 121 plant genome sequences based on their annotation revealed strong splice site conservation across species, annotation errors, and true biological divergence from canonical splice sites. The frequency of non-canonical splice sites clearly correlates with their divergence from canonical ones indicating either an accumulation of probably neutral mutations, or evolution towards canonical splice sites. Strong conservation across multiple species and non-random accumulation of substitutions in splice sites indicate a functional relevance of non-canonical splice sites. The average composition of splice sites across all investigated species is 98.7% for GT-AG, 1.2% for GC-AG, 0.06% for AT-AC, and 0.09% for minor non-canonical splice sites. RNA-Seq data sets of 35 species were incorporated to validate non-canonical splice site predictions through gaps in sequencing reads alignments and to demonstrate the expression of affected genes. We conclude that bona fide non-canonical splice sites are present and appear to be functionally relevant in most plant genomes, if at low abundance.

genomics↗

bioRxiv2018

Genomic analysis of dingoes identifies genomic regions under reversible selection during domestication and feralization

Dingoes (Canis dingo) are wild canids living in Australia. They have lived isolated from both the wild and the domestic ancestor and are a unique model for studying feralization, the process in which a domestic species escapes human control, adapts to the wild, and diverges from the domestic ancestor into a genetically distinct population. Here, we sequenced the genomes of 10 dingoes and 2 New Guinea Singing Dogs, to study the origins and feralization process of the dingo. Phylogenetic and demographic analyses show that dingoes originate from domestic dogs in southern East Asia, which migrated via Island Southeast Asia to reach Australia 4300-5000 years ago, and subsequently diverged into a genetically distinct population. Selection analysis identified 99 positively selected genes enriched in starch and fat metabolism pathways, indicating a diet change during feralization of dingoes. Interestingly, we found that 14 genes have shifted allele frequencies compared to dogs but not compared to wolves. This suggests that the selection affecting these genes during domestication of the wolf was reversed in the feralization process. One of these genes, ARHGEF7, may promote the formation of neural spine and synapses in hippocampal neurons. Functional assays showed that an A to G mutation in ARHGEF7, located in a transcription factor-binding site, decreases the endogenous expression. This suggests that ARHGEF7 may have been under selection for behavioral adaptations related to the transitions in environment both from wild to domestic and from domestic back to wild. Our results indicate that adaptation to domestication and feralization primarily affected different genomic regions, but that some genes, related to neurodevelopment, metabolism and reproduction, may have been reversibly affected in the two processes.

genomics↗

bioRxiv2019

GenomegaMap: within-species genome-wide dN/dS estimation from over 10,000 genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters such as dN/dS, but analysing very large datasets poses a major statistical challenge. Here I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: (i) it is fast no matter how large the sample size and (ii) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well-estimated even when genomegaMaps simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in M. tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

genomics↗

bioRxiv2019

The Glossina Genome Cluster: Comparative Genomic Analysis of the Vectors of African Trypanosomes

BackgroundTsetse flies (Glossina sp.) are the sole vectors of human and animal trypanosomiasis throughout sub-Saharan Africa. Tsetse are distinguished from other Diptera by unique adaptations, including lactation and the birthing of live young (obligate viviparity), a vertebrate blood specific diet by both sexes and obligate bacterial symbiosis. This work describes comparative analysis of six Glossina genomes representing three sub-genera: Morsitans (G. morsitans morsitans (G.m. morsitans), G. pallidipes, G. austeni), Palpalis (G. palpalis, G. fuscipes) and Fusca (G. brevipalpis) which represent different habitats, host preferences and vectorial capacity. ResultsGenomic analyses validate established evolutionary relationships and sub-genera. Syntenic analysis of Glossina relative to Drosophila melanogaster shows reduced structural conservation across the sex-linked X chromosome. Sex linked scaffolds show increased rates of female specific gene expression and lower evolutionary rates relative to autosome associated genes. Tsetse specific genes are enriched in protease, odorant binding and helicase activities. Lactation associated genes are conserved across all Glossina species while male seminal proteins are rapidly evolving. Olfactory and gustatory genes are reduced across the genus relative to other characterized insects. Vision associated Rhodopsin genes show conservation of motion detection/tracking functions and significant variance in the Rhodopsin detecting colors in the blue wavelength ranges. ConclusionsExpanded genomic discoveries reveal the genetics underlying Glossina biology and provide a rich body of knowledge for basic science and disease control. They also provide insight into the evolutionary biology underlying novel adaptations and are relevant to applied aspects of vector control such as trap design and discovery of novel pest and disease control strategies.

genomics↗

bioRxiv2019

Leveraging genome-wide data to investigate differences between opioid use vs. opioid dependence in 41,176 individuals from the Psychiatric Genomics Consortium

To provide novel insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing up to 4,503 OD cases, 4,173 opioid-exposed controls, and 32,500 opioid-unexposed controls. Among the variants identified, rs9291211 was associated with OE (a comparison of exposed vs. unexposed controls; z=-5.39, p=7.2x10-8). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N>360,000) found association of this variant with propensity to use dietary supplements (p=1.68x10-8). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (z=4.69, p=10-6), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (z=5.55, p=2.9x10-8) and a significant association with musculoskeletal disorders in the UK Biobank (p=4.88x10-7). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (N=466,571) was positively associated with OD (OD cases vs. unexposed controls, p=8.1x10-5; OD cases vs. exposed controls, p=0.054) and OE (exposed controls vs. unexposed controls, p=3.6x10-5). A PRS based on a GWAS of neuroticism (N=390,278) was positively associated with OD (OD cases vs. unexposed controls, p=3.2x10-5; OD cases vs. exposed controls, p=0.002) but not with OE (p=0.671). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls (exposed vs. unexposed) in studies of addiction.

genetics↗

bioRxiv2019

Whole genome analysis identifies the association of TP53 genomic deletions with lower survival in Stage III colorectal cancer

DNA copy number aberrations (CNA) were frequently observed in colorectal cancers (CRC). There is an urgent call for CNA-based biomarkers in clinics, in particular for Stage III CRC, if combined with imaging or pathologic evidence, promise more precise care at the timing. We conducted this Stage III specific biomarker discovery with a cohort of 134 CRCs, and with a newly developed high-efficiency CNA profiling protocol. Specifically, we developed the profiling protocol for tumor-normal matched tissue samples based on low-coverage clinical whole-genome sequencing (WGS). We demonstrated the protocols accuracy and robustness by a systematic benchmark with microarray, high-coverage whole-exome and -genome approaches, where the low-coverage WGS-derived CNA segments were highly accordant (PCC>0.95) with those derived from microarray, and they were substantially less variable if compared to exome-derived segments. A lasso-based model and multivariate cox regression analysis identified a chromosome 17p loss, containing the TP53 tumor suppressor gene, that was significantly associated with reduced survival (P=0.0139, HR=1.688, 95% CI = [1.112-2.562]), which was validated by an independent cohort of 187 Stage III CRCs. In summary, the new low-coverage WGS protocol has high sensitivity, high resolution and low cost and the identified 17p-loss is an effective poor prognosis marker for Stage III patients.

genomics↗

bioRxiv2019

Choosing the optimal population for a genome-wide association study: a simulation using whole-genome sequences from rice

A genome-wide association study (GWAS) needs to have a suitable population. The factors that affect a GWAS, e.g. population structure, sample size, and sequence analysis and field testing costs, need to be considered. Mixture populations containing subpopulations of different genetic backgrounds may be suitable populations. We conducted simulation experiments to see if a population with high genetic diversity, e.g., a diversity panel, should be added to a target population, especially when the target population harbors small genetic diversity. The target population was 112 accessions of Oryza sativa subsp. japonica, mainly developed in Japan. We combined the target population with three populations that had higher genetic diversities. These were 100 indica accessions, 100 japonica accessions, and 100 accessions with various genetic backgrounds. The results showed that the GWAS power with a mixture population was generally higher than with a separate population. Also, the GWAS optimal population varied depending on the fixation index FST of the quantitative trait nucleotide (QTN) and its polymorphism of QTN in each population. When a QTN is polymorphic in a target population, a target population combined with a higher diversity population improves the QTN detection power. Investigating FST and the expected heterozygosity He as factors influencing the detection power, we showed that SNPs with high FST or low He are less likely to be detected by GWAS with mixture populations. Sequenced/genotyped germplasm collections can improve the GWAS detection power by using a subset of them with a target population.\n\nCore ideas (3-5 impact statements, 85 char max for each)\n\n- Genome-wide association studies with mixture populations are expected to improve the detection power of novel genes due to the increase of the sample size although the influence of population structure is a concern.\n- When a quantitative trait nucleotide (QTN) is polymorphic in a target population, a combination of the target population and a population with higher diversity than the target population improves the detection power of the QTN.\n- We found that the fixation index (FST) and the expected heterozygosity (He) were strongly related to the detection power of QTNs.\n- Germplasm collections which have been already sequenced/genotyped are useful for improving the detection power of GWAS without any addition of sequence costs by using a subset of them with a target population.

genomics↗

bioRxiv2019

The complete mitochondrial genome of endangered Assam Roofed Turtle, Pangshura sylhetensis (Testudines: Geoemydidae): Genomic features and Phylogeny

Assam Roofed Turtle, Pangshura sylhetensis is an endangered and least studied species endemic to India and Bangladesh. The genomic feature of P. sylhetensis mitogenome is still anonymous to the scientific community. The present study decodes the first complete mitochondrial genome of P. sylhetensis (16,568 bp) by using next-generation sequencing. This de novo assembly encodes 13 Protein-coding genes (PCGs), 22 transfer RNAs (tRNAs), two ribosomal RNAs (rRNAs), and one control region (CR). Most of the genes were encoded on the majority strand, except NADH dehydrogenase subunit 6 (nad6) and eight tRNAs. Most of the PCGs were started with an ATG initiation codon, except for Cytochrome oxidase subunit 1 (cox1) and NADH dehydrogenase subunit 5 (nad5) with GTG. The study also found the typical cloverleaf secondary structure in most of the tRNA genes, except for serine (trnS1) with lack of conventional DHU arm and loop. Both, Bayesian and Maximum-likelihood topologies showed distinct clustering of all the Testudines species with their respective taxonomic ranks and congruent with the previous phylogenetic hypotheses (Pangshura and Batagur sister taxa). Nevertheless, the mitogenomic phylogeny with other amniotes corroborated the sister relationship of Testudines with Archosaurians (Birds and Crocodilians). Additionally, the mitochondrial Gene Order (GO) analysis indicated that, most of the Testudines species showed plesiomorphy with typical vertebrate GO.

genomics↗

bioRxiv2025

Zooming into rearranged genome: applying pipeline of cytological, genomic, and transcriptomic methods for structural variant interpretation

Recent advances in genomic technologies have greatly enhanced our understanding of genotype-phenotype relationships and improved diagnostic of genetic diseases. However, the dissection of complex structural variants remains challenging due to the limitations of current methods in resolving their breakpoint and interpreting phenotypes involving multiple disrupted genes. In this study, we demonstrate how an integrative approach--combining cytological, genomic, and transcriptomic methods--enables the detection, structural and functional characterization of a complex structural variants affecting the MBD5, USP34, and XPO1 genes. Our findings underscore the utility of the Exo-C, a modified chromosome conformation capture technique, in resolving complex rearrangements. We also report, for the first time, a composite neurodevelopmental phenotype resulting from the combined effects of MBD5-associated intellectual disability and 2p15p16.1 microdeletion syndromes.

genomics↗

bioRxiv2026

Genome Report: Long read, high-coverage reference genomes of the Nymphalid butterflies Catonephele acontius and C. numilia (Nymphalidae: Biblidinae)

Withdrawal StatementThe authors have withdrawn this manuscript because in February 2026, the authors found that the Catonephele numilia specimen was misidentified and was in fact also Catonephele acontius. Thus, the data in the article describing the Catonephele numilia genome is invalid, as it in fact describes a second Catonephele acontius genome. This data invalidation has resulted in a loss of confidence in the results and conclusions reported in the article as far as they apply to Catonephele numilia. The data describing Catonephele acontius is not affected and remains valid. The authors are, therefore, retracting this article. All authors agree with the retraction. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

genomics↗

bioRxiv2026

Transposable element-host genome evolutionary arms race revealed by multi-modal epigenomic profiling in a telomere-to-telomere human genome reference

For a quarter of a century transposable elements have been recognized as a major component of the human genome, comprising 46.1% according to recent estimates, and as key drivers of regulatory innovation as well as participants in an ongoing evolutionary arms race with host defense systems. Using the newly released T2T ENCODE dataset, we quantified the epigenetic impact of 3.7 million transposable elements across evolutionary time by analyzing seven epigenomic modalities in twelve human cell lines, spanning six transposon classes, 44 families, and 1,122 subfamilies. We show that SVA elements exhibit the strongest signatures of the arms race, characterized by progressive escape from H3K9me3-mediated heterochromatinization accompanied by increased acquisition of CTCF binding and enhancer-associated chromatin marks. Among Alu elements, the AluYb8 and AluYb9 subfamilies display age-dependent accumulation of CTCF binding, while seven LTR subfamilies (HERV16-int, MER11C, LTR43-int, HERVE-int, LTR22C, LTR5_Hs, HERVIP10FH-int) demonstrate dynamic evolutionary behavior within active chromatin, H3K9me3 chromatin and CTCF contexts. We further evaluated the relative contribution of distinct epigenomic modalities to the host-transposable element conflict and found that transposon-driven evolution is dominated by evasion of host-imposed heterochromatinization primarily at H3K9me3 and secondarily at H3K27me3, together with progressive invasion into CTCF-rich regions. In contrast, enhancer, promoter, and H3K36me3 marks appear to play more limited roles. Collectively, these findings deepen our insight into the coevolutionary epigenomic dynamics between human genome and transposable elements and the associated processes driving regulatory innovation.

genomics↗

bioRxiv2014

Using Bayesian multilevel whole-genome regression models for partial pooling of estimation sets in genomic prediction

Estimation set size is an important determinant of genomic prediction accuracy. Plant breeding programs are characterized by a high degree of structuring, particularly into populations. This hampers establishment of large estimation sets for each population. Pooling populations increases estimation set size but ignores unique genetic characteristics of each. A possible solution is partial pooling with multilevel models, which allows estimating population specific marker effects while still leveraging information across populations. We developed a Bayesian multilevel whole-genome regression model and compared its performance to that of the popular BayesA model applied to each population separately (no pooling) and to the joined data set (complete pooling). As example we analyzed a wide array of traits from the nested association mapping maize population. There we show that for small population sizes (e.g., < 50), partial pooling increased prediction accuracy over no or complete pooling for populations represented in the estimation set. No pooling was superior however when populations were large. In another example data set of interconnected biparental maize populations either partial or complete pooling were superior, depending on the trait. A simulation showed that no pooling is superior when differences in genetic effects among populations are large and partial pooling when they are intermediate. With small differences, partial and complete pooling achieved equally high accuracy. For prediction of new populations, partial and complete pooling had very similar accuracy in all cases. We conclude that partial pooling with multilevel models can maximize the potential of pooling by making optimal use of information in pooled estimation sets.

Genetics↗

bioRxiv2015

Integrative tissue-specific functional annotations in the human genome provide novel insights on many complex traits and improve signal prioritization in genome wide association studies

Extensive efforts have been made to understand genomic function through both experimental and computational approaches, yet proper annotation still remains challenging, especially in non-coding regions. In this manuscript, we introduce GenoSkyline, an unsupervised learning framework to predict tissue-specific functional regions through integrating high-throughput epigenetic annotations. GenoSkyline successfully identified a variety of non-coding regulatory machinery including enhancers, regulatory miRNA, and hypomethylated transposable elements in extensive case studies. Integrative analysis of GenoSkyline annotations and results from genome-wide association studies (GWAS) led to novel biological insights on the etiologies of a number of human complex traits. We also explored using tissue-specific functional annotations to prioritize GWAS signals and predict relevant tissue types for each risk locus. Brain and blood-specific annotations led to better prioritization performance for schizophrenia than standard GWAS p-values and non-tissue-specific annotations. As for coronary artery disease, heart-specific functional regions was highly enriched of GWAS signals, but previously identified risk loci were found to be most functional in other tissues, suggesting a substantial proportion of still undetected heart-related loci. In summary, GenoSkyline annotations can guide genetic studies at multiple resolutions and provide valuable insights in understanding complex diseases. GenoSkyline is available at http://genocanyon.med.yale.edu/GenoSkyline.

Bioinformatics↗

bioRxiv2016

Annotation Regression for Genome-Wide Association Studies with an Application to Psychiatric Genomic Consortium Data

Although genome-wide association studies (GWAS) have been successful at finding thousands of disease-associated genetic variants (GVs), identifying causal variants and elucidating the mechanisms by which genotypes influence phenotypes are critical open questions. A key challenge is that a large percentage of disease-associated GVs are potential regulatory variants located in noncoding regions, making them difficult to interpret. Recent research efforts focus on going beyond annotating GVs by integrating functional annotation data with GWAS to prioritize GVs. However, applicability of these approaches is challenged by high dimensionality and heterogeneity of functional annotation data. Furthermore, existing methods often assume global associations of GVs with annotation data. This strong assumption is susceptible to violations for GVs involved in many complex diseases. To address these issues, we develop a general regression framework, named Annotation Regression for GWAS (ARoG). ARoG is based on finite mixture of linear regression models where GWAS association measures are viewed as responses and functional annotations as predictors. This mixture framework addresses heterogeneity of effects of GVs by grouping them into clusters and high dimensionality of the functional annotations by enabling annotation selection within each cluster. ARoG further employs permutation testing to evaluate the significance of selected annotations. Computational experiments indicate that ARoG can discover distinct associations between disease risk and functional annotations. Application of ARoG to autism and schizophrenia data from Psychiatric Genomics Consortium led to identification of GVs that significantly affect interactions of several transcription factors with DNA as potential mechanisms contributing to these disorders.

Bioinformatics↗

bioRxiv2016

290 Metagenome-assembled Genomes from the Mediterranean Sea: Ongoing Effort to Generate Genomes from the Tara Oceans Dataset

The Tara Oceans Expedition has provided large, publicly-accessible microbial metagenomic datasets from a circumnavigation of the globe. Utilizing several size fractions from the samples originating in the Mediterranean Sea, we have used current assembly and binning techniques to reconstruct 290 putative high-quality metagenome-assembled bacterial and archaeal genomes, with an estimated completion of [≥]50%, and an additional 2,786 bins, with estimated completion of 0-50%. We have submitted our results, including initial taxonomic and phylogenetic assignments, for the putative high-quality genomes to open-access repositories for the scientific community to use in ongoing research.

Microbiology↗

bioRxiv2016

Genome-wide prediction of microRNAs in Zika virus genomes reveals possible interactions with human genes involved in the nervous system development

Zika virus (ZIKV) is a member of the family Flaviviridae. In 2015, ZIKV triggered a large epidemic in Brazil and spread across Latin America. In November of that year, the Brazilian Ministry of Health reported a 20-fold increase in cases of neonatal microcephaly, which corresponds geographically and temporally to the ZIKV outbreak. ZIKV was isolated from the brain tissue of a fetus diagnosed with microcephaly, and recent studies in mice models revealed that ZIKV infection may cause brain defects by influencing brain cell developments. Unfortunately, the mechanisms by which ZIKV alters neurophysiological development remain unknown. MicroRNAs (miRNAs) are small noncoding RNAs that regulate post-transcriptional gene expression by translational repression. In order to gain insight into the possible role of ZIKV-mediated miRNA signaling dysfunction in brain-tissue development, we computationally predicted new miRNAs encoded by the ZIKV genome and their effective hybridization with transcripts from human genes previously shown to be involved in microcephalia. The results of these studies suggest a possible role of these miRNAs on the expression of human genes associated with this disease. Besides, a new ZIKV miRNA was predicted in the 3stem loop (3 SL) of the 3untranslated region (3UTR) of the ZIKV genome, suggesting the role of the 3UTR of flaviviruses as a source of miRNAs.

Microbiology↗

bioRxiv2017

Mitochondrial genome variation affects the mutation rate of the nuclear genome in Drosophila melanogaster

Mutations are the raw material for evolutionary change. While the mutation rate has been thought constant between individuals, recent research has shown that poor genetic condition can elevate the mutation rate. Mitonuclear genetic conflict is a potential source of poor genetic condition, and considering the high mutation rate of mitochondrial genomes, there should be ample scope for mitochondrial mutations to interfere with genetic condition, with concomitant effects on the nuclear mutation rate. Moreover, because theory suggests mitochondrial genetic effects will often be male-biased, such effects could be more strongly felt in males than females. Here, by mating irradiated male Drosophila melanogaster to isogenic females bearing six distinct mitochondrial haplotypes, we tested whether mitochondrial genetic variation affects DNA repair capacity, and whether effects of mutation load on reproductive function are shaped by interactions between sex and mitochondrial haplotype. We found mitochondrial genetic effects on DNA repair, and that the mutational variance of reproductive fitness was higher in males bearing haplotypes characterized by high female fitness. These results suggest that mitochondrial genome variation may affect the mutation rate, and that induced mutations interact more strongly with male than female reproductive function. The potential for haplotype-specific effects on the nuclear mutation rate has broad implications for evolutionary dynamics, such as the accumulation of genetic load, adaptive potential, and the evolution of sexual dimorphism.

evolutionary biology↗

bioRxiv2017

Genome-wide Enhancer Maps Differ Significantly in Genomic Distribution, Evolution, and Function

Non-coding gene regulatory enhancers are essential to transcription in mammalian cells. As a result, a large variety of experimental and computational strategies have been developed to identify cis-regulatory enhancer sequences. In practice, most studies consider enhancers identified by only a single method, and the concordance of enhancers identified by different methods has not been comprehensively evaluated. Here, we assess the similarities of enhancer sets identified by ten representative strategies in four biological contexts and evaluate the robustness of downstream conclusions to the choice of identification strategy. All pairs of enhancer sets we evaluated overlap significantly more than expected by chance; however, we also found significant dissimilarity between enhancer sets in their genomic characteristics, evolutionary conservation, and association with functional loci within each context. We find most regions identified as enhancers are supported by only one method. The disagreement is sufficient to influence interpretation of GWAS SNPs and eQTL, and to lead to disparate conclusions about enhancer biology and disease mechanisms. We also find only limited evidence that regions identified by multiple enhancer identification methods are better candidates than those identified by a single method. Our results highlight the inherent complexity of enhancer biology and argue that current approaches have yet to adequately account for enhancer diversity. As a result, we cannot recommend the use of any single enhancer identification strategy in isolation. To facilitate assessment of enhancer diversity on studies conclusions, we developed creDB, a database of enhancer annotations designed to integrate into bioinformatics workflows. While our findings highlight a major challenge to mapping the genetic architecture of complex disease and interpreting regulatory variants found in patient genomes, a systematic understanding of similarities and differences in enhancer identification methodology will ultimately enable robust inferences about gene regulatory sequences.

genetics↗