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Understanding the impact of splicing and nonsense variants on RNA is crucial for the resolution of variant classification as well as their suitability for precision medicine interventions. This is primarily enabled through RNA studies involving transcriptomics followed by targeted assays using RNA isolated from clinically accessible tissues (CATs) such as blood or skin of affected individuals. Insufficient disease gene expression in CATs does however pose a major barrier to RNA based investigations, which we show is relevant to 1,436 Mendelian disease genes. We term these "silent" Mendelian genes (SMGs), the largest portion (36%) of which are associated with neurological disorders. We developed two approaches to induce SMG expression in human dermal fibroblasts (HDFs) to overcome this limitation, including CRISPR-activation-based gene transactivation and fibroblast-to-neuron transdifferentiation. Initial transactivation screens involving 40 SMGs stimulated our development of a highly multiplexed transactivation system culminating in the 6- to 90,000-fold induction of expression of 20/20 (100%) SMGs tested in HDFs. Transdifferentiation of HDFs directly to neurons led to expression of 193/516 (37.4%) of SMGs implicated in neurological disease. The magnitude and isoform diversity of SMG expression following either transactivation or transdifferentiation was comparable to clinically relevant tissues. We apply transdifferentiation and/or gene transactivation combined with short- and long-read RNA sequencing to investigate the impact that variants in USH2A, SCN1A, DMD, and PAK3 have on RNA using HDFs derived from affected individuals. Transactivation and transdifferentiation represent rapid, scalable functional genomic solutions to investigate variants impacting SMGs in the patient cell and genomic context.

The impact of aging on intestinal stem cells (ISCs) has not been fully elucidated. In this study, we identified widespread epigenetic and transcriptional alterations in old ISCs. Using a reprogramming algorithm, we identified a set of key transcription factors (Egr1, Irf1, FosB) that drives molecular and functional differences between old and young states. Overall, by dissecting the molecular signature of aged ISCs, our study identified transcription factors that enhance the regenerative capacity of ISCs.

BACKGROUND: Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of the effect of induced DNA methylation on endogenous promoters; however, the downstream effects have not yet been comprehensively assessed. RESULTS: Here, we simultaneously induce methylation at thousands of promoters in human cells using an engineered zinc finger-DNMT3A fusion protein, enabling us to test the effect of forced DNA methylation upon transcription, chromatin accessibility, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that transcriptional responses to DNA methylation are highly context-specific, including lack of repression, as well as cases of increased gene expression, which appears to be driven by the eviction of methyl-sensitive transcriptional repressors. Furthermore, we find that some regulatory networks can override DNA methylation and that promoter methylation can cause alternative promoter usage. DNA methylation deposited at promoter and distal regulatory regions is rapidly erased after removal of the zinc finger-DNMT3A fusion protein, in a process combining passive and TET-mediated demethylation. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II. CONCLUSIONS: These findings have important implications for epigenome engineering and demonstrate that the response of promoters to DNA methylation is more complex than previously appreciated.

Brain somatic mutations are an increasingly recognized cause of epilepsy, brain malformations and autism spectrum disorders and may be a hidden cause of other neurodevelopmental and neurodegenerative disorders. At present, brain mosaicism can be detected only in the rare situations of autopsy or brain biopsy. Liquid biopsy using cell-free DNA derived from cerebrospinal fluid has detected somatic mutations in malignant brain tumours. Here, we asked if cerebrospinal fluid liquid biopsy can be used to detect somatic mosaicism in non-malignant brain diseases. First, we reliably quantified cerebrospinal fluid cell-free DNA in 28 patients with focal epilepsy and 28 controls using droplet digital PCR. Then, in three patients we identified somatic mutations in cerebrospinal fluid: in one patient with subcortical band heterotopia the LIS1 p. Lys64* variant at 9.4% frequency; in a second patient with focal cortical dysplasia the TSC1 p. Phe581His*6 variant at 7.8% frequency; and in a third patient with ganglioglioma the BRAF p. Val600Glu variant at 3.2% frequency. To determine if cerebrospinal fluid cell-free DNA was brain-derived, whole-genome bisulphite sequencing was performed and brain-specific DNA methylation patterns were found to be significantly enriched (P = 0.03). Our proof of principle study shows that cerebrospinal fluid liquid biopsy is valuable in investigating mosaic neurological disorders where brain tissue is unavailable.

[This corrects the article DOI: 10.1093/braincomms/fcaa235.][This corrects the article DOI: 10.1093/braincomms/fcaa235.].

The reprogramming of human somatic cells to primed or naive induced pluripotent stem cells recapitulates the stages of early embryonic development1,2,3,4,5,6. The molecular mechanism that underpins these reprogramming processes remains largely unexplored, which impedes our understanding and limits rational improvements to reprogramming protocols. Here, to address these issues, we reconstruct molecular reprogramming trajectories of human dermal fibroblasts using single-cell transcriptomics. This revealed that reprogramming into primed and naive pluripotency follows diverging and distinct trajectories. Moreover, genome-wide analyses of accessible chromatin showed key changes in the regulatory elements of core pluripotency genes, and orchestrated global changes in chromatin accessibility over time. Integrated analysis of these datasets revealed a role for transcription factors associated with the trophectoderm lineage, and the existence of a subpopulation of cells that enter a trophectoderm-like state during reprogramming. Furthermore, this trophectoderm-like state could be captured, which enabled the derivation of induced trophoblast stem cells. Induced trophoblast stem cells are molecularly and functionally similar to trophoblast stem cells derived from human blastocysts or first-trimester placentas7. Our results provide a high-resolution roadmap for the transcription-factor-mediated reprogramming of human somatic cells, indicate a role for the trophectoderm-lineage-specific regulatory program during this process, and facilitate the direct reprogramming of somatic cells into induced trophoblast stem cells.

Cellular identity is ultimately dictated by the interaction of transcription factors with regulatory elements (REs) to control gene expression. Advances in epigenome profiling techniques have significantly increased our understanding of cell-specific utilization of REs. However, it remains difficult to dissect the majority of factors that interact with these REs due to the lack of appropriate techniques. Therefore, we developed TINC: TALE-mediated isolation of nuclear chromatin. Using this new method, we interrogated the protein complex formed at the Nanog promoter in embryonic stem cells (ESCs) and identified many known and previously unknown interactors, including RCOR2. Further interrogation of the role of RCOR2 in ESCs revealed its involvement in the repression of lineage genes and the fine-tuning of pluripotency genes. Consequently, using the Nanog promoter as a paradigm, we demonstrated the power of TINC to provide insight into the molecular makeup of specific transcriptional complexes at individual REs as well as into cellular identity control in general.

© 2020 Association for Computing Machinery. ACM ISBN 978-1-4503-7686-0/20/02...$15.00 Several previous research studies have found a relationship between the ability of novices to trace and explain code, and the ability to write code. Harrington and Cheng refer to that relationship as the Learning Hierarchy. However, almost all of those studies examined students at the end of their first semester of learning to program (i.e. CS1). This paper is only the third paper to describe a study of explain in plain English questions on students at the end of an introductory data structures course. The preceding two papers reached contradictory conclusions. Corney et al. presented results consistent with the Learning Hierarchy identified in the CS1 studies. However, Harrington and Cheng presented results for data structures students suggesting that the hierarchy reversed by the time students had progressed to the level of learning about data structures; that is, tracing and explaining were skills that followed writing. In our study of data structures students, we present results that are consistent with the Learning Hierarchy derived from the CS1 students. We believe that the reversal identified by Harrington and Cheng can occur, but only as a consequence of a mismatch in the relative difficulty of tracing, explaining and writing questions.

© 2020 A large dataset that contains the eye movements of N=216 programmers of different experience levels captured during two code comprehension tasks is presented. Data are grouped in terms of programming expertise (from none to high) and other demographic descriptors. Data were collected through an international collaborative effort that involved eleven research teams across eight countries on four continents. The same eye tracking apparatus and software was used for the data collection. The Eye Movements in Programming (EMIP) dataset is freely available for download. The varied metadata in the EMIP dataset provides fertile ground for the analysis of gaze behavior and may be used to make novel insights about code comprehension.