Transgenerational inheritance of acquired epigenetic signatures at CpG islands in mice.

Transgenerational epigenetic inheritance in mammals remains a debated subject. Here, we demonstrate that DNA methylation of promoter-associated CpG islands (CGIs) can be transmitted from parents to their offspring in mice. We generated DNA methylation-edited mouse embryonic stem cells (ESCs), in which CGIs of two metabolism-related genes, the Ankyrin repeat domain 26 and the low-density lipoprotein receptor, were specifically methylated and silenced. DNA methylation-edited mice generated by microinjection of the methylated ESCs exhibited abnormal metabolic phenotypes. Acquired methylation of the targeted CGI and the phenotypic traits were maintained and transmitted across multiple generations. The heritable CGI methylation was subjected to reprogramming in parental PGCs and subsequently reestablished in the next generation at post-implantation stages. These observations provide a concrete step toward demonstrating transgenerational epigenetic inheritance in mammals, which may have implications in our understanding of evolutionary biology as well as the etiology, diagnosis, and prevention of non-genetically inherited human diseases.

Massive haplotypes underlie ecotypic differentiation in sunflowers.

Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2-4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1-100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other-possibly now-extinct-congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.

PCBS: an R package for fast and accurate analysis of bisulfite sequencing data.

Motivation: Whole-genome bisulfite sequencing is a powerful tool for analyzing chromatin methylation genome-wide, but analysis of whole-genome bisulfite data is hampered by slow, inaccurate, and inflexible pipelines. Results: We developed PCBS, a computationally efficient R package for Whole Genome Bisulfite Sequencing analysis that demonstrates remarkable accuracy and flexibility compared to current tools. PCBS identifies differentially methylated loci and differentially methylated regions and offers novel functionality that allows for more targeted methylation analyses. PCBS uses minimal computational resources; a complete pipeline in mouse can run on a local RStudio instance in a matter of minutes. Availability and Implementation: PCBS is an R package available under a GNU GPLv3 license at: https://github.com/katlande/PCBS and from CRAN: https://CRAN.R-project.org/package=PCBS. Instructions for use are available at: https://katlande.github.io/PCBS/.

Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation.

Mathematical models of biochemical reaction networks are an important and emerging tool for the study of cell signaling networks involved in disease processes. One promising potential application of such mathematical models is the study of how disease-causing mutations promote the signaling phenotype that contributes to the disease. It is commonly assumed that one must have a thorough characterization of the network readily available for mathematical modeling to be useful, but we hypothesized that mathematical modeling could be useful when there is incomplete knowledge and that it could be a tool for discovery that opens new areas for further exploration. In the present study, we first develop a mechanistic mathematical model of a G-protein coupled receptor signaling network that is mutated in almost all cases of uveal melanoma and use model-driven explorations to uncover and explore multiple new areas for investigating this disease. Modeling the two major, mutually-exclusive, oncogenic mutations (Gαq/11 and CysLT2R) revealed the potential for previously unknown qualitative differences between seemingly interchangeable disease-promoting mutations, and our experiments confirmed oncogenic CysLT2R was impaired at activating the FAK/YAP/TAZ pathway relative to Gαq/11. This led us to hypothesize that CYSLTR2 mutations in UM must co-occur with other mutations to activate FAK/YAP/TAZ signaling, and our bioinformatic analysis uncovers a role for co-occurring mutations involving the plexin/semaphorin pathway, which has been shown capable of activating this pathway. Overall, this work highlights the power of mechanism-based computational systems biology as a discovery tool that can leverage available information to open new research areas.

The effect of extracellular matrix on the precision medicine utility of pancreatic cancer patient-derived organoids.

The use of patient-derived organoids (PDOs) to characterize therapeutic sensitivity and resistance is a promising precision medicine approach, and its potential to inform clinical decisions is now being tested in several large multiinstitutional clinical trials. PDOs are cultivated in the extracellular matrix from basement membrane extracts (BMEs) that are most commonly acquired commercially. Each clinical site utilizes distinct BME lots and may be restricted due to the availability of commercial BME sources. However, the effect of different sources of BMEs on organoid drug response is unknown. Here, we tested the effect of BME source on proliferation, drug response, and gene expression in mouse and human pancreatic ductal adenocarcinoma (PDA) organoids. Both human and mouse organoids displayed increased proliferation in Matrigel compared with Cultrex and UltiMatrix. However, we observed no substantial effect on drug response when organoids were cultured in Matrigel, Cultrex, or UltiMatrix. We also did not observe major shifts in gene expression across the different BME sources, and PDOs maintained their classical or basal-like designation. Overall, we found that the BME source (Matrigel, Cultrex, UltiMatrix) does not shift PDO dose-response curves or drug testing results, indicating that PDO pharmacotyping is a robust approach for precision medicine.

The impact of extracellular matrix on the precision medicine utility of pancreatic cancer patient-derived organoids.

The use of patient-derived organoids (PDOs) to characterize therapeutic sensitivity and resistance (pharmacotyping) is a promising precision medicine approach. The potential of this approach to inform clinical decisions is now being tested in several large multi-institutional clinical trials. PDOs are cultivated in extracellular matrix from basement membrane extracts (BMEs) that are most commonly acquired commercially. Each clinical site utilizes distinct BME lots and may be restricted due to the availability of commercial BME sources. However, the impact of different sources and lots of BMEs on organoid drug response is unknown. Here, we tested the impact of BME source and lot on proliferation, chemotherapy and targeted therapy drug response, and gene expression in mouse and human pancreatic ductal adenocarcinoma (PDA) organoids. Both human and mouse organoids displayed increased proliferation in Matrigel (Corning) compared to Cultrex (RnD) and UltiMatrix (RnD). However, we observed no substantial impact on drug response when oragnoids were cultured in Matrigel, Cultrex, or UltiMatrix. We also did not observe major shifts in gene expression across the different BME sources, and PDOs maintained their Classical or Basal-like designation. Overall, we find that BME source (Matrigel, Cultrex, UltiMatrix) does not shift PDO dose-response curves and drug testing results, indicating that PDO pharmacotyping is a robust approach for precision medicine.