Disease heritability enrichment of regulatory elements is concentrated in elements with ancient sequence age and conserved function across species

AbstractRegulatory elements, e.g. enhancers and promoters, have been widely reported to be enriched for disease and complex trait heritability. We investigated how this enrichment varies with the age of the underlying genome sequence, the conservation of regulatory function across species, and the target gene of the regulatory element. We estimated heritability enrichment by applying stratified LD score regression to summary statistics from 41 independent diseases and complex traits (average N =320K) and meta-analyzing results across traits. Enrichment of human enhancers and promoters was larger in elements with older sequence age, assessed via alignment with other species irrespective of conserved functionality: enhancer elements with ancient sequence age (older than the split between marsupial and placental mammals) were 8.8x enriched (vs. 2.5x for all enhancers; p = 3e-14), and promoter elements with ancient sequence age were 13.5x enriched (vs. 5.1x for all promoters; p = 5e-16). Enrichment of human enhancers and promoters was also larger in elements whose regulatory function was conserved across species, e.g. human enhancers that were enhancers in ≥5 of 9 other mammals were 4.6x enriched (p = 5e-12 vs. all enhancers). Enrichment of human promoters was larger in promoters of loss-of-function intolerant genes: 12.0x enrichment (p = 8e-15 vs. all promoters). The mean value of several measures of negative selection within these genomic annotations mirrored all of these findings. Notably, the annotations with these excess heritability enrichments were jointly significant conditional on each other and on our baseline-LD model, which includes a broad set of coding, conserved, regulatory and LD-related annotations.

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The missing link between genetic association and regulatory function

10.1101/2021.06.08.21258515 ◽

2021 ◽

Author(s):

Noah James Connally ◽

Sumaiya Nazeen ◽

Daniel Lee ◽

Huwenbo Shi ◽

John Stamatoyannopoulos ◽

...

Keyword(s):

Gene Expression ◽

Complex Traits ◽

Complex Trait ◽

Regulatory Elements ◽

Regulatory Function ◽

Data Sets ◽

Protein Coding ◽

Regulatory Effects ◽

Complex Forms ◽

Coding Variants

The genetic basis of most complex traits is highly polygenic and dominated by non-coding alleles, and it is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite availability of expansive gene expression and epigenomic data sets, few variant-to-gene links have emerged. We identified 139 genes in which protein-coding variants cause severe or familial forms of nine human traits. We then computed the association between common complex forms of the same traits and non-coding variation, revealing that most such traits are also associated with non-coding variation in the vicinity of the same genes. However, we found colocalization evidence--the same variant influencing both the physiological trait and gene expression--for only 7% of genes, and transcriptome-wide association evidence with correct direction of effect for only 4% of genes, despite an abundance of eQTLs in most loci. Fine mapping variants to regulatory elements and assigning these to genes by linear distance similarly failed to implicate most genes in complex traits. These results contradict the hypothesis that most complex trait-associated variants coincide with currently ascertained expression quantitative trait loci. The field must confront this deficit, and pursue the "missing regulation."

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Integrative analysis of 10,000 epigenomic maps across 800 samples for regulatory genomics and disease dissection

10.1101/810291 ◽

2019 ◽

Cited By ~ 2

Author(s):

Carles B. Adsera ◽

Yongjin P. Park ◽

Wouter Meuleman ◽

Manolis Kellis

Keyword(s):

High Resolution ◽

Genetic Variants ◽

Complex Traits ◽

Target Gene ◽

Activity Patterns ◽

Complex Trait ◽

Contributing Factors ◽

Downstream Target ◽

Downstream Target Gene ◽

Upstream Regulators

AbstractTo help elucidate genetic variants underlying complex traits, we develop EpiMap, a compendium of 833 reference epigenomes across 18 uniformly-processed and computationally-completed assays. We define chromatin states, high-resolution enhancers, activity patterns, enhancer modules, upstream regulators, and downstream target gene functions. We annotate 30,247 genetic variants associated with 534 traits, recognize principal and partner tissues underlying each trait, infer trait-tissue, tissue-tissue and trait-trait relationships, and partition multifactorial traits into their tissue-specific contributing factors. Our results demonstrate the importance of dense, rich, and high-resolution epigenomic annotations for complex trait dissection, and yield numerous new insights for understanding the molecular basis of human disease.

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The SEEL Motif and Members of the MYB-related REVEILLE Transcription Factor Family are Important for the Expression of LORELEI in the Synergid Cells of the Arabidopsis Female Gametophyte

10.1101/2021.08.17.456723 ◽

2021 ◽

Author(s):

Jennifer A. Noble ◽

Alex Seddon ◽

Sahra Uygun ◽

Steven E. Smith ◽

Shin-Han Shiu ◽

...

Keyword(s):

Transcription Factors ◽

Pollen Tube ◽

Female Gametophyte ◽

Regulatory Networks ◽

Clock Genes ◽

Regulatory Element ◽

Regulatory Elements ◽

Loss Of Function ◽

Seed Formation ◽

Synergid Cell

Synergid cells in the micropylar end of the female gametophyte are required for critical cell-cell signaling interactions between the pollen tube and the ovule that precede double fertilization and seed formation in flowering plants. LORELEI (LRE) encodes a GPI-anchored protein that is expressed primarily in the synergid cells, and together with FERONIA, a receptor-like kinase, it controls pollen tube reception by the receptive synergid cell. Still, how LRE expression is controlled in synergid cells remains poorly characterized. We identified candidate cis-regulatory elements enriched in LRE and other synergid cell-expressed genes. One of the candidate motifs (TAATATCT) in the LRE promoter was an uncharacterized variant of the Evening Element motif that we named as the Short Evening Element-like (SEEL) motif. Deletion or point mutations in the SEEL motif of the LRE promoter resulted in decreased reporter expression in synergid cells, demonstrating that the SEEL motif is important for expression of LRE in synergid cells. Additionally, we found that LRE expression is decreased in the loss of function mutants of REVEILLE (RVE) transcription factors, which are clock genes known to bind the SEEL and other closely related motifs. We propose that RVE transcription factors regulate LRE expression in synergid cells by binding to the SEEL motif in the LRE promoter. Identification of a cis-regulatory element and transcription factors involved in the expression of LRE will serve as a foundation to characterize the gene regulatory networks in synergid cells and investigate the potential connection between circadian rhythm and fertilization.

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Biobank-scale inference of ancestral recombination graphs enables genealogy-based mixed model association of complex traits

10.1101/2021.11.03.466843 ◽

2021 ◽

Author(s):

Brian C Zhang ◽

Arjun Biddanda ◽

Pier Francesco Palamara

Keyword(s):

Complex Traits ◽

Large Scale ◽

Mixed Model ◽

Large Population ◽

Complex Trait ◽

Genotype Imputation ◽

Loss Of Function ◽

Genome Wide ◽

Wide Range ◽

Ancestral Recombination Graphs

Accurate inference of gene genealogies from genetic data has the potential to facilitate a wide range of analyses. We introduce a method for accurately inferring biobank-scale genome-wide genealogies from sequencing or genotyping array data, as well as strategies to utilize genealogies within linear mixed models to perform association and other complex trait analyses. We use these new methods to build genome-wide genealogies using genotyping data for 337,464 UK Biobank individuals and to detect associations in 7 complex traits. Genealogy-based association detects more rare and ultra-rare signals (N = 133, frequency range 0.0004% - 0.1%) than genotype imputation from ~65,000 sequenced haplotypes (N = 65). In a subset of 138,039 exome sequencing samples, these associations strongly tag (average r = 0.72) underlying sequencing variants, which are enriched for missense (2.3×) and loss-of-function (4.5×) variation. Inferred genealogies also capture additional association signals in higher frequency variants. These results demonstrate that large-scale inference of gene genealogies may be leveraged in the analysis of complex traits, complementing approaches that require the availability of large, population-specific sequencing panels.

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Loss of Function of OsARG Resulted in Pepper-Shaped Husk in Indica Rice

Life ◽

10.3390/life11060523 ◽

2021 ◽

Vol 11 (6) ◽

pp. 523

Author(s):

Yan Zheng ◽

Mjomba Fredrick Mwamburi ◽

Huaqing Liu ◽

Feng Wang

Keyword(s):

Complex Traits ◽

Target Gene ◽

Indica Rice ◽

Recessive Gene ◽

Sequencing Analysis ◽

Loss Of Function ◽

Regenerated Plants ◽

Grain Width ◽

Different Genetic Background ◽

Mutant Phenotypes

Grain shape is one of the most important and complex traits determining the grain yield in rice. In this study, we discovered two rice mutants with defective shape spikelets, designated as psh1-1/2 (pepper-shaped husk 1-1/2), which were both isolated from the tissue-culture-regenerated plants of indica cultivar Minghui 86. The two mutants showed the same mutant phenotypes, containing pepper-shaped spikelets; shorter, smaller and compact panicles; very low seed-setting rate; high percentage of split grains; and lower grain width. Genetic analysis indicated that the mutant phenotypes were controlled by a recessive gene. Gene mapping indicated that the target gene PSH1 was located on the short arm of chromosome 4. Sequencing analysis revealed that the two mutants each had a different nonsense mutation in OsARG, confirming that the target gene is OsARG. Compared with the previously reported OsARG mutant nglf-1, psh1-1/2 possessed some distinct mutant phenotypes, probably because of the influence of different genetic background, suggesting that OsARG may function differently under different genetic backgrounds.

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Parallel Genomic Changes Drive Repeated Evolution of Placentas in Live-Bearing Fish

Molecular Biology and Evolution ◽

10.1093/molbev/msab057 ◽

2021 ◽

Author(s):

Henri van Kruistum ◽

Reindert Nijland ◽

David N Reznick ◽

Martien A M Groenen ◽

Hendrik-Jan Megens ◽

...

Keyword(s):

Complex Traits ◽

Evolutionary Rate ◽

Complex Trait ◽

Regulatory Elements ◽

Evolutionary Origin ◽

Regulatory Change ◽

Protein Coding ◽

Genomic Changes ◽

Rate Analysis ◽

Repeated Evolution

Abstract The evolutionary origin of complex organs challenges empirical study because most organs evolved hundreds of millions of years ago. The placenta of live-bearing fish in the family Poeciliidae represents a unique opportunity to study the evolutionary origin of complex organs, because in this family a placenta evolved at least nine times independently. It is currently unknown whether this repeated evolution is accompanied by similar, repeated, genomic changes in placental species. Here, we compare whole genomes of 26 poeciliid species representing six out of nine independent origins of placentation. Evolutionary rate analysis revealed that the evolution of the placenta coincides with convergent shifts in the evolutionary rate of 78 protein-coding genes, mainly observed in transporter- and vesicle-located genes. Furthermore, differences in sequence conservation showed that placental evolution coincided with similar changes in 76 noncoding regulatory elements, occurring primarily around genes that regulate development. The unexpected high occurrence of GATA simple repeats in the regulatory elements suggests an important function for GATA repeats in developmental gene regulation. The distinction in molecular evolution observed, with protein-coding parallel changes more often found in metabolic and structural pathways, compared with regulatory change more frequently found in developmental pathways, offers a compelling model for complex trait evolution in general: changing the regulation of otherwise highly conserved developmental genes may allow for the evolution of complex traits.

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Return of a lost structure in the evolution of felid dentition revisited: A DevoEvo perspective on the irreversibility of evolution

10.1101/2021.02.04.429820 ◽

2021 ◽

Author(s):

Vincent J. Lynch

Keyword(s):

Protein Interactions ◽

Complex Traits ◽

Ad Hoc ◽

Complex Trait ◽

Regulatory Elements ◽

Developmental Model ◽

Lynx Lynx ◽

Eurasian Lynx ◽

Protein Coding ◽

Dollo’S Law

AbstractThere is a longstanding interest in whether the loss of complex characters is reversible (so-called “Dollo’s law”). Reevolution has been suggested for numerous traits but among the first was Kurtén (1963), who proposed that the presence of the second lower molar (M2) of the Eurasian lynx (Lynx lynx) was a violation of Dollo’s law because all other Felids lack M2. While an early and often cited example for the reevolution of a complex trait, Kurtén (1963) and Werdelin (1987) used an ad hoc parsimony argument to support their proposition that M2 reevolved in Eurasian lynx. Here I revisit the evidence that M2 reevolved in Eurasian lynx using explicit parsimony and maximum likelihood models of character evolution and find strong evidence that Kurtén (1963) and Werdelin (1987) were correct – M2 reevolved in Eurasian lynx. Next, I explore the developmental mechanisms which may explain this violation of Dollo’s law and suggest that the reevolution of lost complex traits may arise from the reevolution of cis-regulatory elements and protein-protein interactions, which have a longer half-life after silencing that protein coding genes. Finally, I present a model developmental model to explain the reevolution M2 in Eurasian lynx.

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Widespread signatures of negative selection in the genetic architecture of human complex traits

10.1101/145755 ◽

2017 ◽

Cited By ~ 9

Author(s):

Jian Zeng ◽

Ronald de Vlaming ◽

Yang Wu ◽

Matthew R Robinson ◽

Luke Lloyd-Jones ◽

...

Keyword(s):

Gene Expression ◽

Natural Selection ◽

Effect Size ◽

Complex Traits ◽

Negative Selection ◽

Complex Trait ◽

Mixed Linear Model ◽

Phenotypic Variance ◽

The Relationship ◽

Human Complex

AbstractEstimation of the joint distribution of effect size and minor allele frequency (MAF) for genetic variants is important for understanding the genetic basis of complex trait variation and can be used to detect signature of natural selection. We develop a Bayesian mixed linear model that simultaneously estimates SNP-based heritability, polygenicity (i.e. the proportion of SNPs with nonzero effects) and the relationship between effect size and MAF for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752), and show that on average across 28 traits, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (p < 0.05/28 =1.8×10−3) signatures of natural selection for 23 out of 28 traits including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. We further apply the method to 27,869 gene expression traits (N = 1,748), and identify 30 genes that show significant (p < 2.3×10−6) evidence of natural selection. All the significant estimates of the relationship between effect size and MAF in either complex traits or gene expression traits are consistent with a model of negative selection, as confirmed by forward simulation. We conclude that natural selection acts pervasively on human complex traits shaping genetic variation in the form of negative selection.

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Functional Predictors of Causative Cis-Regulatory Mutations in Mendelian Disease

10.1101/2020.08.03.232926 ◽

2020 ◽

Author(s):

Hemant Bengani ◽

Detelina Grozeva ◽

Lambert Moyon ◽

Shipra Bhatia ◽

Susana R Louros ◽

...

Keyword(s):

Target Gene ◽

Rare Variants ◽

Regulatory Elements ◽

Human Populations ◽

Mendelian Disease ◽

Loss Of Function ◽

Coding Region ◽

Endogenous Gene ◽

Neurodevelopmental Disease

AbstractUndiagnosed neurodevelopmental disease is significantly associated with rare variants in cis-regulatory elements (CRE) but demonstrating causality is challenging as target gene consequences may differ from a causative variant affecting the coding region. Here, we address this challenge by applying a procedure to discriminate likely diagnostic regulatory variants from those of neutral/low-penetrant effect. We identified six rare CRE variants using targeted and whole genome sequencing in 48 unrelated males with apparent X-linked intellectual disability (XLID) but without detectable coding region variants. These variants segregated appropriately in families and altered conserved bases in predicted CRE targeting known XLID genes. Three were unique and three were rare but too common to be plausibly causative for XLID. We compared the cis-regulatory activity of wild-type and mutant alleles in zebrafish embryos using dual-color fluorescent reporters. Two variants showed striking changes: one plausibly causative (FMR1CRE) and the other likely neutral/low-penetrant (TENM1CRE). These variants were “knocked-in” to mice and both altered embryonic neural expression of their target gene. Only Fmr1CRE mice showed disease-relevant behavioral defects. FMR1CRE is plausibly disease-associated resulting in complex misregulation of Fmr1/FMRP rather than loss-of-function. This is consistent both with absence of Fragile X syndrome in the probands and the observed electrophysiological anomalies in the FMR1CRE mouse brain. Although disruption of in vivo patterns of endogenous gene expression in disease-relevant tissues by CRE variants cannot be used as strong evidence for Mendelian disease association, in conjunction with extreme rarity in human populations and with relevant knock-in mouse phenotypes, such variants can become likely pathogenic.

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Leveraging molecular QTL to understand the genetic architecture of diseases and complex traits

10.1101/203380 ◽

2017 ◽

Cited By ~ 5

Author(s):

Farhad Hormozdiari ◽

Steven Gazal ◽

Bryce van de Geijn ◽

Hilary Finucane ◽

Chelsea J.-T. Ju ◽

...

Keyword(s):

Complex Traits ◽

Genetic Architecture ◽

Genetic Correlations ◽

Complex Trait ◽

Effect Sizes ◽

Joint Analysis ◽

Loss Of Function ◽

Tissue Specific ◽

Functional Annotations ◽

Using Data

AbstractThere is increasing evidence that many GWAS risk loci are molecular QTL for gene ex-pression (eQTL), histone modification (hQTL), splicing (sQTL), and/or DNA methylation (meQTL). Here, we introduce a new set of functional annotations based on causal posterior prob-abilities (CPP) of fine-mapped molecular cis-QTL, using data from the GTEx and BLUEPRINT consortia. We show that these annotations are very strongly enriched for disease heritability across 41 independent diseases and complex traits (average N = 320K): 5.84x for GTEx eQTL, and 5.44x for eQTL, 4.27-4.28x for hQTL (H3K27ac and H3K4me1), 3.61x for sQTL and 2.81x for meQTL in BLUEPRINT (all P ≤ 1.39e-10), far higher than enrichments obtained using stan-dard functional annotations that include all significant molecular cis-QTL (1.17-1.80x). eQTL annotations that were obtained by meta-analyzing all 44 GTEx tissues generally performed best, but tissue-specific blood eQTL annotations produced stronger enrichments for autoimmune dis-eases and blood cell traits and tissue-specific brain eQTL annotations produced stronger enrich-ments for brain-related diseases and traits, despite high cis-genetic correlations of eQTL effect sizes across tissues. Notably, eQTL annotations restricted to loss-of-function intolerant genes from ExAC were even more strongly enriched for disease heritability (17.09x; vs. 5.84x for all genes; P = 4.90e-17 for difference). All molecular QTL except sQTL remained significantly enriched for disease heritability in a joint analysis conditioned on each other and on a broad set of functional annotations from previous studies, implying that each of these annotations is uniquely informative for disease and complex trait architectures.

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