The placenta plays an important role as a regulator of fetal nutrition and growth throughout development and placental factors contribute to gestational abnormalities such as preeclampsia. This study describes the genome-wide gene expression profiles of a large (n=60) set of human placentas in order to uncover gene expression patterns associated with preeclampsia. In addition to confirming changes in expression of soluble factors associated with preeclampsia such as sFLT1 (soluble fms-like tyrosine kinase-1), sENG (soluble endoglin), and INHA (inhibin alpha), we also find changes in immune-associated signaling pathways, offering a potential upstream explanation for the shallow trophoblast invasion and inadequate uterine remodeling typically observed in pathogenesis of preeclampsia. Notably, we also find evidence of preeclampsiaassociated placental upregulation of sialic acid acetylesterase (SIAE), a gene functionally associated with autoimmune diseases.

To increase our understanding of imprinted genes in swine, we carried out a comprehensive analysis of this gene family using two complementary approaches: expression and phenotypic profiling of parthenogenetic fetuses, and analysis of imprinting by pyrosequencing. The parthenote placenta and fetus were smaller than those of controls but had no obvious morphological differences at Day 28 of gestation. By Day 30, however, the parthenote placentas had decreased chorioallantoic folding, decreased chorionic ruggae, and reduction of fetal-maternal interface surface in comparison with stage-matched control fetuses. Using Affymetrix Porcine GeneChip microarrays and/or semiquantitative PCR, brain, fibroblast, liver, and placenta of Day 30 fetuses were profiled, and 25 imprinted genes were identified as differentially expressed in at least one of the four tissue types: AMPD3, CDKN1C, COPG2, DHCR7, DIRAS3, IGF2 (isoform specific), IGF2AS, IGF2R, MEG3, MEST, NAP1L5, NDN, NNAT, OSBPL1A, PEG3, APEG3, PEG10, PLAGL1, PON2, PPP1R9A, SGCE, SLC38A4, SNORD107, SNRPN, and TFPI2. For DIRAS3, PLAGL1, SGCE, and SLC38A4, tissue-specific differences were detected. In addition, we examined the imprinting status of candidate genes by quantitative allelic pyrosequencing. Samples were collected from Day 30 pregnancies generated from reciprocal crosses of Meishan and White Composite breeds, and single-nucleotide polymorphisms were identified in candidate genes. Imprinting was confirmed for DIRAS3, DLK1, H19, IGF2AS, NNAT, MEST, PEG10, PHLDA2, PLAGL1, SGCE, and SNORD107. We also found no evidence of imprinting in ASB4, ASCL2, CD81, COMMD1, DCN, DLX5, and H13. Combined, these results represent the most comprehensive survey of imprinted genes in swine to date.

Aims Individualization of cancer chemotherapy based on the patient’s genetic makeup holds promise for reducing side effects and improving efficacy. However, the relative contribution of genetics to drug response is unknown. Materials & methods In this study, we investigated the cytotoxic effect of 29 commonly prescribed chemotherapeutic agents from diverse drug classes on 125 lymphoblastoid cell lines derived from 14 extended families. Results The results of this systematic study highlight the variable role that genetics plays in response to cytotoxic drugs, ranging from a heritability of <0.15 for gemcitabine to >0.60 for epirubicin. Conclusion Putative quantitative trait loci for cytotoxic response were identified, as well as drug class-specific signatures, which could indicate possible shared genetic mechanisms. In addition to the identification of putative quantitative trait locis, the results of this study inform the prioritization of chemotherapeutic drugs with a sizable genetic response component for future investigation.

Introduction This study focuses on the implementation of modulated modularity clustering (MMC) a new cluster algorithm for the identification of molecular signatures of preeclampsia and intrauterine growth restriction (IUGR), and the identification of affected microRNAs Methods Eighty-six human placentas from normal (40), growth-restricted (27), and preeclamptic (19) term pregnancies were profiled using Illumina Human-6 Beadarrays. MMC was utilized to generate modules based on similarities in placental transcriptome. Gene Set Enrichment Analysis (GSEA) was used to predict affected microRNAs. Expression levels of these candidate microRNAs were investigated in seventy-one human term placentas as follows: control (29); IUGR (26); and preeclampsia (16). Results MMC identified two modules, one representing IUGR placentas and one representing preeclamptic placentas. 326 differentially expressed genes in the module representing IUGR and 889 differentially expressed genes in a module representing preeclampsia were identified. Functional analysis of molecular signatures associated with IUGR identified P13K/AKT, mTOR, p70S6K, apoptosis and IGF-1 signaling as being affected. Analysis of variance of GSEA-predicted microRNAs indicated that miR-194 was significantly down-regulated both in preeclampsia (p=0.0001) and IUGR (p=0.0304), and miR-149 was significantly down-regulated in preeclampsia (p=0.0168). Discussion Implementation of MMC, allowed identification of genes disregulated in IUGR and preeclampsia. The reliability of MMC was validated by comparing to previous linear modeling analysis of preeclamptic placentas. Conclusion MMC allowed the elucidation of a molecular signature associated with preeclampsia and a subset of IUGR samples. This allowed the identification of genes, pathways, and microRNAs affected in these diseases.

To date, the Centre d'Etude Polymorphism Humain (CEPH) cell line model has only been used as a pharmacogenomic tool to evaluate which genes are responsible for the disparity in response to a single drug. The purpose of this study was demonstrate the model's ability to establish a specific pattern of quantitative trait loci (QTL) related to a shared mechanism for multiple structurally related drugs, the camptothecins, which are Topoisomerase 1 inhibitors. A simultaneous screen of six camptothecin analogues for in vitro sensitivity in the CEPH cell lines resulted in cytotoxicity profiles and orders of potency which were in agreement with the literature. For all camptothecins studied, heritability estimates for cytotoxic response averaged 23.1±2.6%. Nonparametric linkage analysis was used to identify a relationship between genetic markers and response to the camptothecins. Ten QTLs on chromosomes 1, 3, 5, 6, 11, 12, 16 and 20 were identified as shared by all six camptothecin analogues. In a separate validation experiment, nine of the ten QTLs were replicated at the significant and suggestive levels using three additional camptothecin analogues. To further refine this list of QTLs, another validation study was undertaken and seven of the nine QTLs were independently replicated for all nine camptothecin analogues. This is the first study using the CEPH cell lines that demonstrates that a specific pattern of QTLs could be established for a class of drugs which share a mechanism of action. Moreover, it is the first study to report replication of linkage results for drug-induced cytotoxicity using this model. The QTLs, which have been identified as shared by all camptothecins and replicated across multiple datasets, are of considerable interest; they harbor genes related to the shared mechanism of action for the camptothecins, which are responsible for variation in response.