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

Baby Genomics: Tracing the Evolutionary Changes That Gave Rise to Placentation

It has long been challenging to uncover the molecular mechanisms behind striking morphological innovations such as mammalian pregnancy. We studied the power of a robust comparative orthology pipeline based on gene synteny to address such problems. We inferred orthology relations between human genes and genes from each of 43 other vertebrate genomes, resulting in ∼18,000 orthologous pairs for each genome comparison. By identifying genes that first appear coincident with origin of the placental mammals, we hypothesized that we would define a subset of the genome enriched for genes that played a role in placental evolution. We thus pinpointed orthologs that appeared before and after the divergence of eutherian mammals from marsupials. Reinforcing previous work, we found instead that much of the genetic toolkit of mammalian pregnancy evolved through the repurposing of preexisting genes to new roles. These genes acquired regulatory controls for their novel roles from a group of regulatory genes, many of which did in fact originate at the appearance of the eutherians. Thus, orthologs appearing at the origin of the eutherians are enriched in functions such as transcriptional regulation by Krüppel-associated box-zinc-finger proteins, innate immune responses, keratinization, and the melanoma-associated antigen protein class. Because the cellular mechanisms of invasive placentae are similar to those of metastatic cancers, we then used our orthology inferences to explore the association between placenta invasion and cancer metastasis. Again echoing previous work, we find that genes that are phylogenetically older are more likely to be implicated in cancer development.

Genome-wide maps of distal gene regulatory enhancers active in the human placenta

Placental dysfunction is implicated in many pregnancy complications, including preeclampsia and preterm birth (PTB). While both these syndromes are influenced by environmental risk factors, they also have a substantial genetic component that is not well understood. Precisely controlled gene expression during development is crucial to proper placental function and often mediated through gene regulatory enhancers. However, we lack accurate maps of placental enhancer activity due to the challenges of assaying the placenta and the difficulty of comprehensively identifying enhancers. To address the gap in our knowledge of gene regulatory elements in the placenta, we used a two-step machine learning pipeline to synthesize existing functional genomics studies, transcription factor (TF) binding patterns, and evolutionary information to predict placental enhancers. The trained classifiers accurately distinguish enhancers from the genomic background and placental enhancers from enhancers active in other tissues. Genomic features collected from tissues and cell lines involved in pregnancy are the most predictive of placental regulatory activity. Applying the classifiers genome-wide enabled us to create a map of 33,010 predicted placental enhancers, including 4,562 high-confidence enhancer predictions. The genome-wide placental enhancers are significantly enriched nearby genes associated with placental development and birth disorders and for SNPs associated with gestational age. These genome-wide predicted placental enhancers provide candidate regions for further testing in vitro, will assist in guiding future studies of genetic associations with pregnancy phenotypes, and aid interpretation of potential mechanisms of action for variants found through genetic studies.

Enabling precision medicine in neonatology, an integrated repository for preterm birth research

Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research.

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.

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.