Biology subjects

Peng, S.

Publications and source records attributed to Peng, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2020

Relatively semi-conservative replication and a folded slippage model for simple repeat sequences

Simple sequence repeats (SSRs) are found ubiquitously in almost all genome, and their formation mechanism is ambiguous yet. Here, the SSRs were analyzed in 55 randomly selected segments of genomes from a fairly wide range of species, with introducing more open standard for extensively mining repeats. A high percentage of repeats were discovered in these segments, which is inconsistent with the current theory suggested that repeats tend to disappear over long-term evolution. Therefore, a mechanism is most probably responsible for continually producing repeats during replication to balance continuous repeat disappearance, which may makes the replicating process relatively semi-conservative. To improve the current straight-line slippage model, we proposed a folded slippage model involving the geometric space of nucleotides and hydrogen bond stability to explain the high-percent SSR occurrence, which can describe SSR expansion and contraction more reasonably. And analysis of external forces in the folding template strands suggested that the microsatellites tend to expand than contract. Our research may provide implements for contributions of microsatellites to genome evolution and complement semi-conservative replication.

molecular biology↗

bioRxiv2020

Duplications drive diversity in Bordetella pertussis on an underestimated scale.

Bacterial genetic diversity is often described using solely base pair changes despite a wide variety of other mutation types likely being major contributors. Tandem duplications of genomic loci are thought to be widespread among bacteria but due to their often intractable size and instability, comprehensive studies of the range and genome dynamics of these mutations are rare. We define a methodology to investigate duplications in bacterial genomes based on read depth of genome sequence data as a proxy for copy number. We demonstrate the approach with Bordetella pertussis, whose insertion sequence element-rich genome provides extensive scope for duplications to occur. Analysis of genome sequence data for 2430 B. pertussis isolates identified 272 putative duplications, of which 94% were located at 11 hotspot loci. We demonstrate limited phylogenetic connection for the occurrence of duplications, suggesting unstable and sporadic characteristics. Genome instability was further described in-vitro using long read sequencing via the Nanopore platform. Clonally derived laboratory cultures produced heterogenous populations containing multiple structural variants. Short read data was used to predict 272 duplications, whilst long reads generated on the Nanopore platform enabled the in-depth study of the genome dynamics of tandem duplications in B. pertussis. Our work reveals the unrecognised and dynamic genetic diversity of B. pertussis and, as the complexity of the B. pertussis genome is not unique, highlights the need for a holistic and fundamental understanding of bacterial genetics.

microbiology↗

bioRxiv2020

AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomics

MotivationThe goal of pharmacogenomics is to predict drug response in patients using their single- or multi-omics data. A major challenge is that clinical data (i.e. patients) with drug response outcome is very limited, creating a need for transfer learning to bridge the gap between large pre-clinical pharmacogenomics datasets (e.g. cancer cell lines), as a source domain, and clinical datasets as a target domain. Two major discrepancies exist between pre-clinical and clinical datasets: 1) in the input space, the gene expression data due to difference in the basic biology, and 2) in the output space, the different measures of the drug response. Therefore, training a computational model on cell lines and testing it on patients violates the i.i.d assumption that train and test data are from the same distribution. ResultsWe propose Adversarial Inductive Transfer Learning (AITL), a deep neural network method for addressing discrepancies in input and output space between the pre-clinical and clinical datasets. AITL takes gene expression of patients and cell lines as the input, employs adversarial domain adaptation and multi-task learning to address these discrepancies, and predicts the drug response as the output. To the best of our knowledge, AITL is the first adversarial inductive transfer learning method to address both input and output discrepancies. Experimental results indicate that AITL outperforms state-of-the-art pharmacogenomics and transfer learning baselines and may guide precision oncology more accurately. Availability of codes and supplementary materialhttps://github.com/hosseinshn/AITL Contactccollins@prostatecentre.com and ester@cs.sfu.ca

bioinformatics↗

bioRxiv2019

The Ocular Glymphatic Clearance System

Despite high metabolic activity, the retina and optic nerve head lack traditional lymphatic drainage. We here identified a novel ocular glymphatic clearance route for fluid and wastes via the proximal optic nerve. Amyloid-{beta} (A{beta}) was cleared from the vitreous via a pathway driven by the ocular-cranial pressure difference. After traversing the lamina barrier, intra-axonal A{beta} was cleared via the perivenous space and subsequently drained to lymphatic vessels. Light-induced pupil constriction enhanced, while atropine or raising intracranial pressure blocked efflux. In two distinct murine models of glaucoma, A{beta} leaked from the eye via defects in the lamina barrier instead of directional axonal efflux. The discovery of a novel pathway for removal of fluid and metabolites from the intraocular space prompts a reevaluation of the core principles governing eye physiology and provides a framework for new therapeutic approaches to treat common eye diseases, including glaucoma. One Sentence SummaryGlymphatic pathway clears ocular amyloid-{beta} via optic nerve and fails in glaucoma.

physiology↗

bioRxiv2019

Probing glioblastoma and its microenvironment using single-nucleus and single-cell sequencing

Single-cell (scSeq) and single-nucleus sequencing (snSeq) are powerful tools to investigate cancer genomics at single cell resolution. Multiple studies have recently illuminated intratumoral heterogeneity in glioblastoma, however, the majority focused on molecular complexity of tumor cells, without considering unexplored host cell types that contribute to the microenvironment around tumor. To address the glioblastoma microenvironment composition and potential tumor-host interactions, we performed deep coverage sequencing of freshly resected primary GBM patient tissue without implementing any tumor enrichment strategies. The sequencing resulted in 902 cells and 1186 nuclei, respectively, passing quality control and with low mitochondrial gene percentage. We customized reference transcriptome by listing gene transcript loci as exons to take into account immature RNA, which greatly improved the alignment rate for single-nucleus data. We applied Cell Ranger pipelines (Version 3.0.2) and Seurat package (Version 2.3.1) and discovered 10 clusters in both scSeq and snSeq. Pathway analysis of each cluster signature in scSeq data along with known GBM microenvironment cell signatures revealed glioma tumor population along with surrounding microglia/macrophages, astrocytes, pericytes, oligodendrocytes, T cells and endothelial cells. The analysis of snSeq was able to capture the majority of cell types from patient tissues (tumor and microenvironment cells), but interestingly presented different cell type composition in microenvironment cell types such as microglia/macrophages. Integrating single-cell and single-nucleus transcriptomic data using canonical correlation analysis facilitated a comparison of snSeq and scSeq, contrasting depiction for certain cell types (e.g. NKX6-2 gene in Oligodendrocytes). Differential analysis of pathways between tumor and microenvironment cells unveiled potentially rewired pathways such as double strand break repair pathway. Our results demonstrate the cellular diversity of brain tumor microenvironment and lay a foundation to further investigate the individual tumor and host cell transcriptomes that are influenced not only by their cell identity but also by their interaction with surrounding microenvironment.

genomics↗

bioRxiv2019

JAM-A functions as a female microglial tumor suppressor in glioblastoma

Glioblastoma (GBM) remains refractory to treatment. In addition to its cellular and molecular heterogeneity, epidemiological studies indicate the presence of additional complexity associated with biological sex. GBM is more prevalent and aggressive in male compared to female patients, suggesting the existence of sex-specific growth, invasion, and therapeutic resistance mechanisms. While sex-specific molecular mechanisms have been reported at a tumor cell-intrinsic level, sex-specific differences in the tumor microenvironment have not been investigated. Using transgenic mouse models, we demonstrate that deficiency of junctional adhesion molecule-A (JAM-A) in female mice enhances microglia activation, GBM cell proliferation, and tumor growth. Mechanistically, JAM-A suppresses anti-inflammatory/pro-tumorigenic gene activation via interferon-activated gene 202b (Ifi202b) and found in inflammatory zone (Fizz1) in female microglia. Our findings suggest that cell adhesion mechanisms function to suppress pathogenic microglial activation in the female tumor microenvironment, which highlights an emerging role for sex differences in the GBM microenvironment and suggests that sex differences extend beyond previously reported tumor cell intrinsic differences.\n\nSummaryTuraga et al. demonstrate that female microglia drive a more aggressive glioblastoma phenotype in the context of JAM-A deficiency. These findings highlight a sex-specific role for JAM-A and represent the first evidence of sexual dimorphism in the glioblastoma microenvironment.

cancer biology↗

bioRxiv2019

Transcriptome analysis reveals the difference between \"healthy\" and \"common\" aging and their connection with age-related diseases

A key goal of aging research is to understand mechanisms underlying healthy aging and use them to develop methods to promote the human healthspan. One approach is to identify gene regulations differentiating healthy aging from aging in the general population (i.e., \"common\" aging). In this study, we leveraged GTEx (Genotype-Tissue Expression) project data to investigate \"healthy\" and \"common\" aging in humans and their interconnection with diseases.\n\nWe selected GTEx donors who were not annotated with diseases to approximate a \"healthy\" aging cohort. We then compared the age-associated genes derived from this cohort with age-associated genes from our \"common\" aging cohort which included all GTEx donors; we also compared the \"healthy\" and \"common\" aging gene expressions with various disease-associated gene expression to elucidate the relationships among \"healthy\", \"common\" aging and disease. Our analyses showed that 1. \"healthy\" and \"common\" aging shared a large number of gene regulations; 2. Despite the substantial commonality, \"healthy\" and \"common\" aging genes also showed distinct function enrichment, and \"common\" aging genes had a higher enrichment for disease genes; 3. Disease-associated gene regulations were overall different from aging gene regulations. However, for genes regulated by both, their regulation directions were largely consistent, implying some aging processes could increase the susceptibility to disease development; and 4. Possible protective mechanisms were associated with the \"healthy\" aging gene regulations.\n\nIn summary, our work highlights several unique features of human \"healthy\" aging program. This new knowledge can be used for the development of therapeutics to promote human healthspan.

genetics↗

bioRxiv2019

Kinetic Inference Resolves Epigenetic Mechanism of Drug Resistance in Melanoma

Drug-induced dedifferentiation towards a drug-tolerant persister state is a common mechanism cancer cells exploit to escape therapies, posing a significant obstacle to sustained therapeutic efficacy. The dynamic coordination of epigenomic and transcriptomic programs at the early-stage of drug exposure, which initiates and orchestrates these reversible dedifferentiation events, remains largely unexplored. Here we employ high-temporal-resolution multi-omics profiling, information-theoretic approaches, and dynamic system modeling to probe these processes in BRAF-mutant melanoma models and patient specimens. We uncover a hysteretic transition trajectory of melanoma cells in response to oncogene inhibition and subsequent release, driven by the sequential operation of two tightly coupled transcriptional waves, which orchestrate genome-scale chromatin state reconfiguration. Modeling of the transcriptional wave interactions predicts NF-{kappa}B/RelA-driven chromatin remodeling as the underlying mechanism of cell-state dedifferentiation, a finding we validate experimentally. Our results identify critical RelA-target genes that are epigenetically modulated to drive this process, establishing a quantitative epigenome gauge to measure cell-state plasticity in melanomas, which supports the potential use of drugs targeting epigenetic machineries to potentiate oncogene inhibition. Extending our investigation to other cancer models, we identify oxidative stress-mediated NF-{kappa}B/RelA activation as a common mechanism driving cellular transitions towards drug-tolerant persister states, revealing a novel and pivotal role for the NF-{kappa}B signaling axis in linking cellular oxidative stress to cancer progression.

cancer biology↗

bioRxiv2019

Characterizing the Emergence of Liver and Gallbladder from the Embryonic Endoderm through Single-Cell RNA-Seq

The liver and gallbladder are among the most important internal organs derived from the endoderm. Several inductive signals regulate liver development, yet the pure nascent hepatic and gallbladder cells are unable to be isolated due to limited cell markers and cell numbers. The transcriptome networks of the hepatic lineage in the endoderm, and how the gallbladder differentiates from the adjacent endoderm population, are not fully understood. Using a transgenic Foxa2eGFP reporter mouse line, we performed deep single-cell RNA sequencing on 1,966 individual cells, including nascent hepatic and gallbladder cells, isolated from the endoderm and hepatic regions from ten embryonic stages, ranging from day E7.5 to E15.5. We identified the embryonic liver developmental trajectory from primitive streak to hepatoblasts and characterized the transcriptome of the hepatic lineage. During pre-hepatogenesis (5-6 somite stage), we have identified two groups of foregut endoderm cells, one derived from visceral endoderm and the second derived from primitive streak via a mesenchymal-epithelial transition (MET). During the liver specification stages, liver primordium was identified to share both foregut and liver features. We also documented dynamic gene expression during the epithelial-hepatic transition (EHT). Six gene groups were found to switch on or off at different stages during liver specification. Importantly, we found that RXR complex signaling and newly identified transcription factors associated with liver specification. Moreover, we revealed the gallbladder primordium cells at E9.5 and found genes that transcriptionally distinguish them from the liver primordium. The present data provides a high-resolution resource and critical insights for understanding the emergence of the endoderm, liver and gallbladder development.

developmental biology↗

bioRxiv2019

Quantitative proximity proteomics resolves the epithelial apical-lateral border and uncovers a vertebrate marginal zone defined by the polarity protein Pals1

Epithelial apico-basal polarity is established through the asymmetric cortical distribution of the Par, Crumbs and Scribble polarity modules. Apical (Par and Crumbs) and basolateral (Scribble) polarity modules overlap at the apical-lateral border, which, in mammals, is defined by the apical junctional complex (AJC). The AJC is composed of tight junctions (TJ) and adherens junctions (AJ) and plays fundamental roles in epithelial morphogenesis and plasticity. However, the molecular composition and precise sub-junctional organization of the AJC and its associated polarity regulators are still not well defined. Here we used the peroxidase APEX2 for quantitative proximity proteomics (QPP) and electron microscopy (EM) imaging to generate a nanometer-scale spatio-molecular map of the apical-lateral border in fully polarized MDCK-II cells. Using Par3 and Pals1 as surrogates for QPP we present a spatially resolved network of [~]800 junction-associated proteins. The network dissects TJ and AJ components and provides strong evidence that TJ are composed of distinct apical and basal subdomains. Moreover, we find that Pals1 and its binding partners PatJ, Lin7c and Crumbs3 define a hitherto unidentified membrane compartment apical of TJ, which we coin the vertebrate marginal zone (VMZ). The VMZ is physically associated with HOMER scaffolding proteins, regulators of apical exocytosis, and membrane-proximal HIPPO pathway proteins. Taken together our work defines the spatial and molecular organization of the apical-lateral border in fully polarized mammalian epithelial cells, reveals an intriguing molecular and spatial conservation of invertebrate and vertebrate cell polarity protein domains, and provides a comprehensive resource of potentially novel regulators of cell polarity and the mammalian AJC.

cell biology↗

bioRxiv2019

MATE-Seq: Microfluidic Antigen-TCR Engagement Sequencing

Adaptive immunity is based on peptide antigen recognition. Our ability to harness the immune system for therapeutic gain relies on the discovery of the T cell receptor (TCR) genes that selectively target antigens from infections, mutated proteins, and foreign agents. Here we present a method that selectively labels peptide antigen-specific CD8+ T-cells in human blood using magnetic nanoparticles functionalized with peptide-MHC tetramers, isolates these specific cells within an integrated microfluidic device, and directly amplifies the TCR genes for sequencing. Critically, the identity of the peptide recognized by the TCR is preserved, providing the link between peptide and gene. The platform requires inputs on the order of just 100,000 CD8+ T cells, can be multiplexed for simultaneous analysis of multiple peptides, and performs sorting and isolation on chip. We demonstrate 1000-fold sensitivity enhancement of antigen-specific T-cell receptor detection and simultaneous capture of two virus antigen-specific T-cell receptors from samples of human blood.

immunology↗

bioRxiv2019

Shotgun Metagenomics of 361 elderly women reveals gut microbiome change in bone mass loss

Bone mass loss contributes to the risk of bone fracture in the elderly. Many factors including age, obesity, estrogen and diet, are associated with bone mass loss. Mice studies suggest that the intestinal microbiome might influence the bone mass by regulating the immune system, however there has been little evidence from human studies. We have recruited 361 Chinese elderly women to collect data for a metagenomic-wide association study (MWAS) to investigate the influence of the gut microbiome on bone health. Gut microbiome data were produced using BGISEQ500 sequencing, BMD was calculated using Hologic dual energy X-ray machine, BMI (Body Mass Index) and age were also provided. This therefore data allows exploration of gut microbiome diversity and links to bone mass loss, as well as microbial species and modules as markers for bone mineral density. Making these data potentially useful in studying the role the gut microbiota might play in bone mass loss and offering exploration into the bone mass loss process.

microbiology↗

bioRxiv2019

Allelic polymorphism shapes collective phenotypes in evolving Pseudomonas aeruginosa populations

Pseudomonas aeruginosa is an opportunistic pathogen that chronically infects the lungs of individuals with cystic fibrosis (CF) by forming antibiotic resistant biofilms. Emergence of phenotypically diverse isolates within CF P. aeruginosa populations has previously been reported, however, the impact of heterogeneity on social behaviors and community function is poorly understood. Here we describe how this heterogeneity impacts on behavioral traits by evolving the strain PAO1 in biofilms grown in a synthetic sputum medium for 50 days. We measured social trait production and antibiotic tolerance and used a metagenomic approach to analyze and assess genomic changes over the duration of the evolution experiment. We found that (i) evolutionary trajectories were reproducible in independently evolving populations; (ii) over 60% of genomic diversity occurred within the first 10 days of selection. We then focused on quorum sensing (QS), a well-studied P. aeruginosa trait that is commonly mutated in strains isolated from CF lungs. We found that at the population level (i) evolution in sputum medium selected for decreased production of QS and QS-dependent traits; (ii) there was a significant correlation between lasR mutant frequency, the loss of protease and the 3O-C12-HSL signal, and an increase in resistance to clinically relevant {beta}-lactam antibiotics, despite no previous antibiotic exposure. Overall, our findings provide insights into the effect of allelic polymorphism on community functions in diverse P. aeruginosa populations. Further, we demonstrate that P. aeruginosa population and evolutionary dynamics can impact on traits important for virulence and can lead to increased tolerance to {beta}-lactam antibiotics.

microbiology↗

bioRxiv2019

Intra-familial phenotypic heterogeneity and telomere abnormality in von Hippel-Lindau disease

Von Hippel-Lindau (VHL) disease is a hereditary cancer syndrome with poor survival. The current recommendations have proposed uniform surveillance strategies for all patients, neglecting the obvious phenotypic varieties. In this study, we aim to confirm the phenotypic heterogeneity in VHL disease and the underlying mechanism. A total of 151 parent-child pairs were enrolled for genetic anticipation analysis, and 77 sibling pairs for birth order effect analysis. Four statistical methods were used to compare the onset age of patients among different generations and different birth orders. The results showed that the average onset age was 18.9 years earlier in children than in their parents, which was statistically significant in all of the four statistical methods. Furthermore, the first-born siblings were affected 8.3 years later than the other ones among the maternal patients. Telomere shortening was confirmed to be associated with genetic anticipation in VHL families, while it failed to explain the birth order effect. Moreover, no significant difference was observed for overall survival between parents and children (p=0.834) and between first-born patients and the other siblings (p=0.390). This study provides definitive evidence and possible mechanisms of intra-familial phenotypic heterogeneity in VHL families, which is helpful to the update of surveillance guidelines.

genetics↗

bioRxiv2019

Comparative analysis of mitochondrial genome between UG93A and UG93B reveal common feature of 5’-end heterogeneity in mitochondrial genes of kenaf

Plant cytoplasmic male sterility (CMS) being maternal phenomenon trait that result from pollen abortion and closely linked with mitochondrial DNA rearrangement in many crops including kenaf. However, the molecular mechanism in kenaf is poorly known. In present work, we described the mitochondrial genome in isonuclear CMS line UG93A and its maintainer line UG93B. Findings of the current study revealed that a total of 398 SNPs and 230 InDels were identified in UG93A mtDNA. Total of 26 SNPs variations and three InDels were identified in the coding region of atp6, indicating its active role in mitochondrial genome re-arrangement. Northern blot analysis showed that the transcripts of atp1, atp4, atp6, cox3 and sdh4 in F1 were consistent with UG93A but different for UG93B. The transcript of atp9 was found similar between UG93B and F1 while different for UG93A, which depict that atp9 may be regulated by nuclear genes in F1 hybrid. The expression of atp9 in UG93A was substantially lower compared with UG93B, suggesting its key role for energy supplying in microspore development of kenaf. Circularized RNA (CR)-RT-PCR revealed that mitochondrial RNAs with heterogeneous 5-ends but uniform 3 - ends are common feature in kenaf mitochondrial genes, and the promoter architecture analysis showed that the promoter sequences in kenaf mitochondrial genome are highly diverged in comparison to those in other plants. Our data highlight that the translation of mitochondrial genes in kenaf is closely associated with heterogeneity of the 5-end of plant mRNA. The present result provides the basic information in understanding the transcription of kenaf mitochondrial genome and can be used as reference in other plants.

molecular biology↗

bioRxiv2018

Genetic effect of type 2 Diabetes to the progression of Neurological Diseases

Neurological Diseases (NDs) are progressive disorder often advances with age and comorbidities of Type 2 diabetes (T2D). Epidemiological, clinical and neuropathological evidence advocate that patients with T2D are at an increased risk of getting NDs. However, it is very little known how T2D affects the risk and severity of NDs.\n\nTo tackle these problems, we employed a transcriptional analysis of affected tissues using agnostic approaches to identify overlapping cellular functions. In this study, we examined gene expression microarray human datasets along with control and disease-affected individuals. Differentially expressed genes (DEG) were identified for both T2D and NDs that includes Alzheimer Disease (AD), Parkinson Disease (PD), Amyotrophic Lateral Sclerosis (ALS), Epilepsy Disease (ED), Huntington Disease (HD), Cerebral Palsy (CP) and Multiple Sclerosis Disease (MSD).\n\nWe have developed genetic association and diseasome network of T2D and NDs based on the neighborhood-based benchmarking and multilayer network topology approaches. Overlapping DEG sets go through protein-protein interaction for hub protein identification and gene enrichment using pathway analysis and gene ontology methods that enhance our understanding of the fundamental molecular procedure of NDs progression.\n\nGene expression analysis platforms have been extensively used to investigate altered pathways and to identify potential biomarkers and drug targets. Finally, we validated our identified biomarkers using the gold benchmark datasets which identified the corresponding relationship of T2D and NDs. Therapeutic targets aimed at attenuating identified altered pathway could ameliorate neurological dysfunction in a T2D patient.

bioinformatics↗

bioRxiv2018

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individuals own genotype on BW and subsequent disease risk from indirect effects of their mothers correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offsprings later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

genetics↗

bioRxiv2018

Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 are associated with gestational duration

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. We conducted a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 was associated with gestational duration; the association was replicated in 9,291 additional infants (combined P = 3.96 x 10-14). Analysis of 15,536 mother-child pairs showed that the association was driven by fetal rather than maternal genotype. Functional experiments showed that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.

genetics↗