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.

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

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

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).

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.

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.

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.

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.

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.

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.

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.

Preliminary validation of a consumer-oriented colorectal cancer risk assessment tool compatible with the US Surgeon General's My Family Health Portrait.

Purpose: This study examines the analytic validity of a software tool designed to provide individuals with risk assessments for colorectal cancer based on personal health and family history information. The software is compatible with the US Surgeon General's My Family Health Portrait (MFHP).

Methods: An algorithm for risk assessment was created using accepted colorectal risk assessment guidelines and programmed into a software tool (MFHP).

Genomic inheritances: disclosing individual research results from whole-exome sequencing to deceased participants' relatives.

Whole-genome analysis and whole-exome analysis generate many more clinically actionable findings than traditional targeted genetic analysis. These findings may be relevant to research participants themselves as well as for members of their families. Though researchers performing genomic analyses are likely to find medically significant genetic variations for nearly every research participant, what they will find for any given participant is unpredictable.

Intentions to receive individual results from whole-genome sequencing among participants in the ClinSeq study.

Genome sequencing has been rapidly integrated into clinical research and is currently marketed to health-care practitioners and consumers alike. The volume of sequencing data generated for a single individual and the wide range of findings from whole-genome sequencing raise critical questions about the return of results and their potential value for end-users. We conducted a mixed-methods study of 311 sequential participants in the NIH ClinSeq study to assess general preferences and specific attitudes toward learning results.