Comparative Genomic Characterization of the Multimammate Mouse Mastomys coucha.

Mastomys are the most widespread African rodent and carriers of various diseases such as the plague or Lassa virus. In addition, mastomys have rapidly gained a large number of mammary glands. Here, we generated a genome, variome, and transcriptomes for Mastomys coucha. As mastomys diverged at similar times from mouse and rat, we demonstrate their utility as a comparative genomic tool for these commonly used animal models. Furthermore, we identified over 500 mastomys accelerated regions, often residing near important mammary developmental genes or within their exons leading to protein sequence changes. Functional characterization of a noncoding mastomys accelerated region, located in the HoxD locus, showed enhancer activity in mouse developing mammary glands. Combined, our results provide genomic resources for mastomys and highlight their potential both as a comparative genomic tool and for the identification of mammary gland number determining factors

Liver-Specific Polygenic Risk Score Is Associated with Alzheimer's Disease Diagnosis

BACKGROUND: Our understanding of the pathophysiology underlying Alzheimer's disease (AD) has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. The use of functional annotation has been able to improve the power of genomic models. OBJECTIVE: We sought to leverage genomic functional annotations to build tissue-specific AD PRS models and study their relationship with AD and its biomarkers. METHODS: We built 13 tissue-specific AD PRS and studied the scores' relationships with AD diagnosis, cerebrospinal fluid (CSF) amyloid, CSF tau, and other CSF biomarkers in two longitudinal cohort studies of AD. RESULTS: The AD PRS model that was most predictive of AD diagnosis (even without APOE) was the liver AD PRS: n = 1,115; odds ratio = 2.15 (1.67-2.78), p = 3.62×10-9. The liver AD PRS was also statistically significantly associated with cerebrospinal fluid biomarker evidence of amyloid-β (Aβ 42:Aβ 40 ratio, p = 3.53×10-6) and the phosphorylated tau:amyloid-β ratio (p = 1.45×10-5). CONCLUSION: These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research

A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis

Background: The course of disease for patients with idiopathic pulmonary fibrosis (IPF) is highly heterogeneous. Prognostic models rely on demographic and clinical characteristics and are not reproducible. Integrating data from genomic analyses may identify novel prognostic models and provide mechanistic insights into IPF. Methods: Total RNA of peripheral blood mononuclear cells was subjected to microarray profiling in a training (45 IPF individuals) and two independent validation cohorts (21 IPF/10 controls, and 75 IPF individuals, respectively). To identify a gene set predictive of IPF prognosis, we incorporated genomic, clinical, and outcome data from the training cohort. Predictor genes were selected if all the following criteria were met: 1) Present in a gene co-expression module from Weighted Gene Co-expression Network Analysis (WGCNA) that correlated with pulmonary function (p 1.5 and false discovery rate (FDR) < 2 %; and 3) Predictive of mortality (p < 0.05) in univariate Cox regression analysis. "Survival risk group prediction" was adopted to construct a functional genomic model that used the IPF prognostic predictor gene set to derive a prognostic index (PI) for each patient into either high or low risk for survival outcomes. Prediction accuracy was assessed with a repeated 10-fold cross-validation algorithm and independently assessed in two validation cohorts through multivariate Cox regression survival analysis. Results: A set of 118 IPF prognostic predictor genes was used to derive the functional genomic model and PI. In the training cohort, high-risk IPF patients predicted by PI had significantly shorter survival compared to those labeled as low-risk patients (log rank p < 0.001). The prediction accuracy was further validated in two independent cohorts (log rank p < 0.001 and 0.002). Functional pathway analysis revealed that the canonical pathways enriched with the IPF prognostic predictor gene set were involved in T-cell biology, including iCOS, T-cell receptor, and CD28 signaling. Conclusions: Using supervised and unsupervised analyses, we identified a set of IPF prognostic predictor genes and derived a functional genomic model that predicted high and low-risk IPF patients with high accuracy. This genomic model may complement current prognostic tools to deliver more personalized care for IPF patients

Ancient Pbx-Hox signatures define hundreds of vertebrate developmental enhancers

Background: Gene regulation through cis-regulatory elements plays a crucial role in development and disease. A major aim of the post-genomic era is to be able to read the function of cis-regulatory elements through scrutiny of their DNA sequence. Whilst comparative genomics approaches have identified thousands of putative regulatory elements, our knowledge of their mechanism of action is poor and very little progress has been made in systematically de-coding them. Results: Here, we identify ancient functional signatures within vertebrate conserved non-coding elements (CNEs) through a combination of phylogenetic footprinting and functional assay, using genomic sequence from the sea lamprey as a reference. We uncover a striking enrichment within vertebrate CNEs for conserved binding-site motifs of the Pbx-Hox hetero-dimer. We further show that these predict reporter gene expression in a segment specific manner in the hindbrain and pharyngeal arches during zebrafish development. Conclusions: These findings evoke an evolutionary scenario in which many CNEs evolved early in the vertebrate lineage to co-ordinate Hox-dependent gene-regulatory interactions that pattern the vertebrate head. In a broader context, our evolutionary analyses reveal that CNEs are composed of tightly linked transcription-factor binding-sites (TFBSs), which can be systematically identified through phylogenetic footprinting approaches. By placing a large number of ancient vertebrate CNEs into a developmental context, our findings promise to have a significant impact on efforts toward de-coding gene-regulatory elements that underlie vertebrate development, and will facilitate building general models of regulatory element evolution

Phase resetting reveals network dynamics underlying a bacterial cell cycle

Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS)

Methods for Scarless, Selection-Free Generation of Human Cells and Allele-Specific Functional Analysis of Disease-Associated SNPs and Variants of Uncertain Significance.

With the continued emergence of risk loci from Genome-Wide Association studies and variants of uncertain significance identified from patient sequencing, better methods are required to translate these human genetic findings into improvements in public health. Here we combine CRISPR/Cas9 gene editing with an innovative high-throughput genotyping pipeline utilizing KASP (Kompetitive Allele-Specific PCR) genotyping technology to create scarless isogenic cell models of cancer variants in ~1 month. We successfully modeled two novel variants previously identified by our lab in the PALB2 gene in HEK239 cells, resulting in isogenic cells representing all three genotypes for both variants. We also modeled a known functional risk SNP of colorectal cancer, rs6983267, in HCT-116 cells. Cells with extremely low levels of gene editing could still be identified and isolated using this approach. We also introduce a novel molecular assay, ChIPnQASO (Chromatin Immunoprecipitation and Quantitative Allele-Specific Occupation), which uses the same technology to reveal allele-specific function of these variants at the DNA-protein interaction level. We demonstrated preferential binding of the transcription factor TCF7L2 to the rs6983267 risk allele over the non-risk. Our pipeline provides a platform for functional variant discovery and validation that is accessible and broadly applicable for the progression of efforts towards precision medicine