Haley R. Eidem

GEneSTATION 1.0: a synthetic resource of diverse evolutionary and functional genomic data for studying the evolution of pregnancy-associated tissues and phenotypes

Mammalian gestation and pregnancy are fast evolving processes that involve the interaction of the fetal, maternal and paternal genomes. Version 1.0 of the GEneSTATION database (http://genestation.org) integrates diverse types of omics data across mammals to advance understanding of the genetic basis of gestation and pregnancy-associated phenotypes and to accelerate the translation of discoveries from model organisms to humans. GEneSTATION is built using tools from the Generic Model Organism Database project, including the biology-aware database CHADO, new tools for rapid data integration, and algorithms that streamline synthesis and user access. GEneSTATION contains curated life history information on pregnancy and reproduction from 23 high-quality mammalian genomes. For every human gene, GEneSTATION contains diverse evolutionary (e.g. gene age, population genetic and molecular evolutionary statistics), organismal (e.g. tissue-specific gene and protein expression, differential gene expression, disease phenotype), and molecular data types (e.g. Gene Ontology Annotation, protein interactions), as well as links to many general (e.g. Entrez, PubMed) and pregnancy disease-specific (e.g. PTBgene, dbPTB) databases. By facilitating the synthesis of diverse functional and evolutionary data in pregnancy-associated tissues and phenotypes and enabling their quick, intuitive, accurate and customized meta-analysis, GEneSTATION provides a novel platform for comprehensive investigation of the function and evolution of mammalian pregnancy.

Whole exome sequencing reveals HSPA1L as a genetic risk factor for spontaneous preterm birth

Preterm birth is a leading cause of morbidity and mortality in infants. Genetic and environmental factors play a role in the susceptibility to preterm birth, but despite many investigations, the genetic basis for preterm birth remain largely unknown. Our objective was to identify rare, possibly damaging, nucleotide variants in mothers from families with recurrent spontaneous preterm births (SPTB). DNA samples from 17 Finnish mothers who delivered at least one infant preterm were subjected to whole exome sequencing. All mothers were of northern Finnish origin and were from seven multiplex families. Additional replication samples of European origin consisted of 93 Danish sister pairs (and two sister triads), all with a history of a preterm delivery. Rare exonic variants (frequency <1%) were analyzed to identify genes and pathways likely to affect SPTB susceptibility. We identified rare, possibly damaging, variants in genes that were common to multiple affected individuals. The glucocorticoid receptor signaling pathway was the most significant (p<1.7e-8) with genes containing these variants in a subgroup of ten Finnish mothers, each having had 2–4 SPTBs. This pathway was replicated among the Danish sister pairs. A gene in this pathway, heat shock protein family A (Hsp70) member 1 like (HSPA1L), contains two likely damaging missense alleles that were found in four different Finnish families. One of the variants (rs34620296) had a higher frequency in cases compared to controls (0.0025 vs. 0.0010, p = 0.002) in a large preterm birth genome-wide association study (GWAS) consisting of mothers of general European ancestry. Sister pairs in replication samples also shared rare, likely damaging HSPA1L variants. Furthermore, in silico analysis predicted an additional phosphorylation site generated by rs34620296 that could potentially affect chaperone activity or HSPA1L protein stability. Finally, in vitro functional experiment showed a link between HSPA1L activity and decidualization. In conclusion, rare, likely damaging, variants in HSPA1L were observed in multiple families with recurrent SPTB.

Comparing human and macaque placental transcriptomes to disentangle preterm birth pathology from gestational age effects

INTRODUCTION A major issue in the transcriptomic study of spontaneous preterm birth (sPTB) in humans is the inability to collect healthy control tissue at the same gestational age (GA) to compare with pathologic preterm tissue. Thus, gene expression differences identified after the standard comparison of sPTB and term tissues necessarily reflect differences in both sPTB pathology and GA. One potential solution is to use GA-matched controls from a closely related species to tease apart genes that are dysregulated during sPTB from genes that are expressed differently as a result of GA effects. METHODS To disentangle genes whose expression levels are associated with sPTB pathology from those linked to GA, we compared RNA sequencing data from human preterm placentas, human term placentas, and rhesus macaque placentas at 80% completed gestation (serving as healthy non-human primate GA-matched controls). We first compared sPTB and term human placental transcriptomes to identify significantly differentially expressed genes. We then overlaid the results of the comparison between human sPTB and macaque placental transcriptomes to identify sPTB-specific candidates. Finally, we overlaid the results of the comparison between human term and macaque placental transcriptomes to identify GA-specific candidates. RESULTS Examination of relative expression for all human genes with macaque orthologs identified 267 candidate genes that were significantly differentially expressed between preterm and term human placentas. 29 genes were identified as sPTB-specific candidates and 37 as GA-specific candidates. Altogether, the 267 differentially expressed genes were significantly enriched for a variety of developmental, metabolic, reproductive, immune, and inflammatory functions. Although there were no notable differences between the functions of the 29 sPTB-specific and 37 GA-specific candidate genes, many of these candidates have been previously shown to be dysregulated in diverse pregnancy-associated pathologies. DISCUSSION By comparing human sPTB and term transcriptomes with GA-matched control transcriptomes from a closely related species, this study disentangled the confounding effects of sPTB pathology and GA, leading to the identification of 29 promising sPTB-specific candidate genes and 37 genes potentially related to GA effects. The apparent similarity in functions of the sPTB and GA candidates may suggest that the effects of sPTB and GA do not correspond to biologically distinct processes. Alternatively, it may reflect the poor state of knowledge of the transcriptional landscape underlying placental development and disease.

Integrating Diverse Types of Genomic Data to Identify Genes that Underlie Adverse Pregnancy Phenotypes

Progress in understanding complex genetic diseases has been bolstered by synthetic approaches that overlay diverse data types and analyses to identify functionally important genes. Pre-term birth (PTB), a major complication of pregnancy, is a leading cause of infant mortality worldwide. A major obstacle in addressing PTB is that the mechanisms controlling parturition and birth timing remain poorly understood. Integrative approaches that overlay datasets derived from comparative genomics with function-derived ones have potential to advance our understanding of the genetics of birth timing, and thus provide insights into the genes that may contribute to PTB. We intersected data from fast evolving coding and non-coding gene regions in the human and primate lineage with data from genes expressed in the placenta, from genes that show enriched expression only in the placenta, as well as from genes that are differentially expressed in four distinct PTB clinical subtypes. A large fraction of genes that are expressed in placenta, and differentially expressed in PTB clinical subtypes (23–34%) are fast evolving, and are associated with functions that include adhesion neurodevelopmental and immune processes. Functional categories of genes that express fast evolution in coding regions differ from those linked to fast evolution in non-coding regions. Finally, there is a surprising lack of overlap between fast evolving genes that are differentially expressed in four PTB clinical subtypes. Integrative approaches, especially those that incorporate evolutionary perspectives, can be successful in identifying potential genetic contributions to complex genetic diseases, such as PTB.

Shared Selective Pressures on Fungal and Human Metabolic Pathways Lead to Divergent yet Analogous Genetic Responses

Reduced metabolic efficiency, toxic intermediate accumulation, and deficits of molecular building blocks, which all stem from disruptions of flux through metabolic pathways, reduce organismal fitness. Although these represent shared selection pressures across organisms, the genetic signatures of the responses to them may differ. In fungi, a frequently observed signature is the physical linkage of genes from the same metabolic pathway. In contrast, human metabolic genes are rarely tightly linked; rather, they tend to show tissue-specific coexpression. We hypothesized that the physical linkage of fungal metabolic genes and the tissue-specific coexpression of human metabolic genes are divergent yet analogous responses to the range of selective pressures imposed by disruptions of flux. To test this, we examined the degree to which the human homologs of physically linked metabolic genes in fungi (fungal linked homologs or FLOs) are coexpressed across six human tissues. We found that FLOs are significantly more correlated in their expression profiles across human tissues than other metabolic genes. We obtained similar results in analyses of the same six tissues from chimps, gorillas, orangutans, and macaques. We suggest that when selective pressures remain stable across large evolutionary distances, evidence of selection in a given evolutionary lineage can become a highly reliable predictor of the signature of selection in another, even though the specific adaptive response in each lineage is markedly different.

integRATE: a desirability-based data integration framework for the prioritization of candidate genes across heterogeneous omics and its application to preterm birth

Background The integration of high-quality, genome-wide analyses offers a robust approach to elucidating genetic factors involved in complex human diseases. Even though several methods exist to integrate heterogeneous omics data, most biologists still manually select candidate genes by examining the intersection of lists of candidates stemming from analyses of different types of omics data that have been generated by imposing hard (strict) thresholds on quantitative variables, such as P-values and fold changes, increasing the chance of missing potentially important candidates. Methods To better facilitate the unbiased integration of heterogeneous omics data collected from diverse platforms and samples, we propose a desirability function framework for identifying candidate genes with strong evidence across data types as targets for follow-up functional analysis. Our approach is targeted towards disease systems with sparse, heterogeneous omics data, so we tested it on one such pathology: spontaneous preterm birth (sPTB). Results We developed the software integRATE, which uses desirability functions to rank genes both within and across studies, identifying well-supported candidate genes according to the cumulative weight of biological evidence rather than based on imposition of hard thresholds of key variables. Integrating 10 sPTB omics studies identified both genes in pathways previously suspected to be involved in sPTB as well as novel genes never before linked to this syndrome. integRATE is available as an R package on GitHub (https://github.com/haleyeidem/integRATE). Conclusions Desirability-based data integration is a solution most applicable in biological research areas where omics data is especially heterogeneous and sparse, allowing for the prioritization of candidate genes that can be used to inform more targeted downstream functional analyses.

Correction: Whole exome sequencing reveals HSPA1L as a genetic risk factor for spontaneous preterm birth

[This corrects the article DOI: 10.1371/journal.pgen.1007394.].

The transformative potential of an integrative approach to pregnancy

BACKGROUND Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors. Pregnancy-associated traits and pathologies are further complicated by extensive communication across multiple tissues in two individuals, interactions between two genomes-maternal and fetal-that obscure causal variants and lead to genetic conflict, and rapid evolution of pregnancy-associated traits across mammals and in the human lineage. Given the multi-faceted complexity of human pregnancy, integrative approaches that synthesize diverse data types and analyses harbor tremendous promise to identify the genetic architecture and environmental influences underlying pregnancy-associated traits and pathologies. METHODS We review current research that addresses the extreme complexities of traits and pathologies associated with human pregnancy. RESULTS We find that successful efforts to address the many complexities of pregnancy-associated traits and pathologies often harness the power of many and diverse types of data, including genome-wide association studies, evolutionary analyses, multi-tissue transcriptomic profiles, and environmental conditions. CONCLUSION We propose that understanding of pregnancy and its pathologies will be accelerated by computational platforms that provide easy access to integrated data and analyses. By simplifying the integration of diverse data, such platforms will provide a comprehensive synthesis that transcends many of the inherent challenges present in studies of pregnancy.