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

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

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

Abstract 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.]

Whole exome sequencing reveals <i>HSPA1L</i> as a genetic risk factor for spontaneous preterm birth

<div><p>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 (<i>HSPA1L</i>), 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 <i>vs</i>. 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 <i>HSPA1L</i> variants. Furthermore, <i>in silico</i> analysis predicted an additional phosphorylation site generated by rs34620296 that could potentially affect chaperone activity or HSPA1L protein stability. Finally, <i>in vitro</i> functional experiment showed a link between HSPA1L activity and decidualization. In conclusion, rare, likely damaging, variants in <i>HSPA1L</i> were observed in multiple families with recurrent SPTB.</p></div

Most significant pathway results for Finnish mothers with recurrent SPTB (n = 10).

<p>Most significant pathway results for Finnish mothers with recurrent SPTB (n = 10).</p