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.].

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.

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.

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.

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.

Comprehensive RNA profiling of villous trophoblast and decidua basalis in pregnancies complicated by preterm birth following intra-amniotic infection.

INTRODUCTION: We performed RNA sequencing with the primary goal of discovering key placental villous trophoblast (VT) and decidua basalis (DB) transcripts differentially expressed in intra-amniotic infection (IAI)-induced preterm birth (PTB). METHODS: RNA was extracted from 15 paired VT and DB specimens delivered of women with: 1) spontaneous PTB in the setting of amniocentesis-proven IAI and histological chorioamnionitis (n = 5); 2) spontaneous idiopathic PTB (iPTB, n = 5); and 3) physiologic term pregnancy (n = 5). RNA sequencing was performed using the Illumina HiSeq 2500 platform, and a spectrum of computational tools was used for gene prioritization and pathway analyses. RESULTS: In the VT specimens, 128 unique long transcripts and 7 mature microRNAs differed significantly between pregnancies complicated by IAI relative to iPTB (FDR<0.1). The up-regulated transcripts included many characteristic of myeloblast-derived cells, and bioinformatic analyses revealed enrichment for multiple pathways associated with acute inflammation. In an expanded cohort including additional IAI and iPTB specimens, the expression of three proteins (cathepsin S, lysozyme, and hexokinase 3) and two microRNAs (miR-133a and miR-223) was validated using immunohistochemistry and quantitative PCR, respectively. In the DB specimens, only 11 long transcripts and no microRNAs differed significantly between IAI cases and iPTB controls (FDR<0.1). Comparison of the VT and DB specimens in each clinical scenario revealed signatures distinguishing these placental regions. DISCUSSION: IAI is associated with a transcriptional signature consistent with acute inflammation in the villous trophoblast. The present findings illuminate novel signaling pathways involved in IAI, and suggest putative therapeutic targets and potential biomarkers associated with this condition.

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.

Gestational tissue transcriptomics in term and preterm human pregnancies: a systematic review and meta-analysis.

BACKGROUND: Preterm birth (PTB), or birth before 37 weeks of gestation, is the leading cause of newborn death worldwide. PTB is a critical area of scientific study not only due to its worldwide toll on human lives and economies, but also due to our limited understanding of its pathogenesis and, therefore, its prevention. This systematic review and meta-analysis synthesizes the landscape of PTB transcriptomics research to further our understanding of the genes and pathways involved in PTB subtypes. METHODS: We evaluated published genome-wide pregnancy studies across gestational tissues and pathologies, including those that focus on PTB, by performing a targeted PubMed MeSH search and systematically reviewing all relevant studies. RESULTS: Our search yielded 2,361 studies on gestational tissues including placenta, decidua, myometrium, maternal blood, cervix, fetal membranes (chorion and amnion), umbilical cord, fetal blood, and basal plate. Selecting only those original research studies that measured transcription on a genome-wide scale and reported lists of expressed genetic elements identified 93 gene expression, 21 microRNA, and 20 methylation studies. Although 30 % of all PTB cases are due to medical indications, 76 % of the preterm studies focused on them. In contrast, only 18 % of the preterm studies focused on spontaneous onset of labor, which is responsible for 45 % of all PTB cases. Furthermore, only 23 of the 10,993 unique genetic elements reported to be transcriptionally active were recovered 10 or more times in these 134 studies. Meta-analysis of the 93 gene expression studies across 9 distinct gestational tissues and 29 clinical phenotypes showed limited overlap of genes identified as differentially expressed across studies. CONCLUSIONS: Overall, profiles of differentially expressed genes were highly heterogeneous both between as well as within clinical subtypes and tissues as well as between studies of the same clinical subtype and tissue. These results suggest that large gaps still exist in the transcriptomic study of specific clinical subtypes as well in the generation of the transcriptional profile of well-studied clinical subtypes; understanding the complex landscape of prematurity will require large-scale, systematic genome-wide analyses of human gestational tissues on both understudied and well-studied subtypes alike.