Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 64,897 bioRxiv papers from 287,634 authors.

Most downloaded bioRxiv papers, since beginning of last month

60,343 results found. For more information, click each entry to expand.

1: Insights from a survey-based analysis of the academic job market
more details view paper

Posted to bioRxiv 09 Oct 2019

Insights from a survey-based analysis of the academic job market
10,175 downloads scientific communication and education

Jason D Fernandes, Sarvenaz Sarabipour, Christopher T Smith, Natalie M Niemi, Nafisa M Jadavji, Ariangela J Kozik, Alex S Holehouse, Vikas Pejaver, Orsolya Symmons, Alexandre Wilson Bisson Filho, Amanda Haage

Many postdoctoral fellows in the STEM fields enter the academic job market with little knowledge of the process and expectations, and without any means to assess their qualifications relative to the general applicant pool. Demystifying this process is critical, as there is little information publicly available. In this work, we provide insight into the process of academic job searches by gathering data to establish background metrics for typical faculty job applicants, and further correlate these metrics with job search outcomes. We analyzed 317 responses to an anonymous survey for faculty job applicants from the May 2018 - May 2019 market cycle. Responses were about evenly split by gender, largely North American-centric and life science focused, and highly successful with 58% of applicants receiving at least one offer. Traditional metrics (funding, publications, etc.) of a positive research track record above a certain threshold of qualifications were unable to completely differentiate applicants that did and did not receive a job offer. Our findings suggest that there is no single clear path to a faculty job offer and that perhaps criteria not captured by our survey may also influence landing a faculty position above a certain threshold of qualification. Furthermore, our survey did capture applicants perception of the faculty job application process as unnecessarily stressful, time-consuming, and largely lacking in feedback, irrespective of a successful outcome. We hope that this study will provide an avenue for better data-driven decision making by the applicants and search committees, better evidence-based mentorship practices by principal investigators, and improved hiring practices by institutions.

2: An integrated brain-machine interface platform with thousands of channels
more details view paper

Posted to bioRxiv 17 Jul 2019

An integrated brain-machine interface platform with thousands of channels
9,059 downloads neuroscience

Elon Musk, Neuralink

Brain-machine interfaces (BMIs) hold promise for the restoration of sensory and motor function and the treatment of neurological disorders, but clinical BMIs have not yet been widely adopted, in part because modest channel counts have limited their potential. In this white paper, we describe Neuralink’s first steps toward a scalable high-bandwidth BMI system. We have built arrays of small and flexible electrode “threads”, with as many as 3,072 electrodes per array distributed across 96 threads. We have also built a neurosurgical robot capable of inserting six threads (192 electrodes) per minute. Each thread can be individually inserted into the brain with micron precision for avoidance of surface vasculature and targeting specific brain regions. The electrode array is packaged into a small implantable device that contains custom chips for low-power on-board amplification and digitization: the package for 3,072 channels occupies less than (23 × 18.5 × 2) mm3. A single USB-C cable provides full-bandwidth data streaming from the device, recording from all channels simultaneously. This system has achieved a spiking yield of up to 70% in chronically implanted electrodes. Neuralink’s approach to BMI has unprecedented packaging density and scalability in a clinically relevant package.

3: Mammalian Y RNAs are modified at discrete guanosine residues with N-glycans
more details view paper

Posted to bioRxiv 30 Sep 2019

Mammalian Y RNAs are modified at discrete guanosine residues with N-glycans
7,629 downloads molecular biology

Ryan A. Flynn, Benjamin A. H. Smith, Alex G Johnson, Kayvon Pedram, Benson M. George, Stacy A. Malaker, Karim Majzoub, Jan E. Carette, Carolyn R. Bertozzi

Glycans modify lipids and proteins to mediate inter- and intramolecular interactions across all domains of life. RNA, another multifaceted biopolymer, is not thought to be a major target of glycosylation. Here, we challenge this view with evidence that mammalian cells use RNA as a third scaffold for glycosylation in the secretory pathway. Using a battery of chemical and biochemical approaches, we find that a select group of small noncoding RNAs including Y RNAs are modified with complex, sialylated N-glycans (glycoRNAs). These glycoRNA are present in multiple cell types and mammalian species, both in cultured cells and in vivo. Finally, we find that RNA glycosylation depends on the canonical N-glycan biosynthetic machinery within the ER/Golgi luminal spaces. Collectively, these findings suggest the existence of a ubiquitous interface of RNA biology and glycobiology suggesting an expanded role for glycosylation beyond canonical lipid and protein scaffolds.

4: Muscle strength, size and composition following 12 months of gender-affirming treatment in transgender individuals: retained advantage for the transwomen
more details view paper

Posted to bioRxiv 26 Sep 2019

Muscle strength, size and composition following 12 months of gender-affirming treatment in transgender individuals: retained advantage for the transwomen
6,752 downloads physiology

Anna Wiik, Tommy R Lundberg, Eric Rullman, Daniel P Andersson, Mats Holmberg, Mirko Mandic, Torkel B Brismar, Olof Dahlqvist Leinhard, Setareh Chanpen, John Flanagan, Stefan Arver, Thomas Gustafsson

Objectives: This study explored the effects of gender-affirming treatment, which includes inhibition of endogenous sex hormones and replacement with cross-sex hormones, on muscle function, size and composition in 11 transwomen (TW) and 12 transmen (TM). Methods: Isokinetic knee extensor and flexor muscle strength was assessed at baseline (T00), 4 weeks after gonadal suppression of endogenous hormones but before hormone replacement (T0), and 3 (T3) and 11 (T12) months after hormone replacement. In addition, at T00 and T12, we assessed lower-limb muscle volume using MRI, and cross-sectional area (CSA) and radiological density using CT. Results: Thigh muscle volume increased (15%) in TM, which was paralleled by increased quadriceps CSA (15%) and radiological density (6%). In TW, the corresponding parameters decreased by -5% (muscle volume) and -4% (CSA), while density remained unaltered. The TM increased strength over the assessment period, while the TW generally maintained or slightly increased in strength. Baseline muscle volume correlated highly with strength (R>0.75), yet the relative change in muscle volume and strength correlated only moderately (R=0.65 in TW and R=0.32 in TM). The absolute levels of muscle volume and knee extension strength after the intervention still favored the TW. Conclusion: Cross-sex hormone treatment markedly affects muscle strength, size and composition in transgender individuals. Despite the robust increases in muscle mass and strength in TM, the TW were still stronger and had more muscle mass following 12 months of treatment. These findings add new knowledge that could be relevant when evaluating transwomen's eligibility to compete in the women's category of athletic competitions.

5: Natural image reconstruction from brain waves: a novel visual BCI system with native feedback
more details view paper

Posted to bioRxiv 01 Oct 2019

Natural image reconstruction from brain waves: a novel visual BCI system with native feedback
6,655 downloads neuroscience

Grigory V. Rashkov, Anatoly S. Bobe, Dmitry V. Fastovets, Maria V. Komarova

Here we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naive subjects because of the user-friendly and intuitive way the visual patterns are employed to modify the brain states.

6: Automated analysis of whole brain vasculature using machine learning
more details view paper

Posted to bioRxiv 18 Apr 2019

Automated analysis of whole brain vasculature using machine learning
5,968 downloads neuroscience

Mihail Ivilinov Todorov, Johannes C. Paetzold, Oliver Schoppe, Giles Tetteh, Velizar Efremov, Katalin Völgyi, Marco Düring, Martin Dichgans, Marie Piraud, Bjoern Menze, Ali Ertürk

Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge. Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a fully convolutional network with a transfer learning approach for segmentation. We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas. We reported the first evidence of secondary intracranial collateral vascularization in CD1-Elite mice and found reduced vascularization in the brainstem as compared to the cerebrum. VesSAP thus enables unbiased and scalable quantifications for the angioarchitecture of the cleared intact mouse brain and yields new biological insights related to the vascular brain function.

7: Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body
more details view paper

Posted to bioRxiv 05 Feb 2019

Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body
4,822 downloads cancer biology

Chenchen Pan, Oliver Schoppe, Arnaldo Parra-Damas, Ruiyao Cai, Mihail Ivilinov Todorov, Gabor Gondi, Bettina von Neubeck, Alireza Ghasemi, Madita Alice Reimer, Javier Coronel, Boyan K. Garvalov, Bjoern Menze, Reinhard Zeidler, Ali Erturk

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer.

8: A proximity biotinylation map of a human cell
more details view paper

Posted to bioRxiv 07 Oct 2019

A proximity biotinylation map of a human cell
4,787 downloads molecular biology

Christopher D Go, James D R Knight, Archita Rajasekharan, Bhavisha Rathod, Geoffrey G Hesketh, Kento T Abe, Ji-Young Youn, Payman Samavarchi-Tehrani, Hui Zhang, Lucie Y Zhu, Evelyn Popiel, Jean-Philippe Lambert, Étienne Coyaud, Sally W T Cheung, Dushyandi Rajendran, Cassandra J Wong, Hana Antonicka, Laurence Pelletier, Brian Raught, Alexander F Palazzo, Eric A Shoubridge, Anne-Claude Gingras

Compartmentalization is an essential characteristic of eukaryotic cells, ensuring that cellular processes are partitioned to defined subcellular locations. High throughput microscopy and biochemical fractionation coupled with mass spectrometry have helped to define the proteomes of multiple organelles and macromolecular structures. However, many compartments have remained refractory to such methods, partly due to lysis and purification artefacts and poor subcompartment resolution. Recently developed proximity-dependent biotinylation approaches such as BioID and APEX provide an alternative avenue for defining the composition of cellular compartments in living cells. Here we report an extensive BioID-based proximity map of a human cell, comprising 192 markers from 32 different compartments that identifies 35,902 unique high confidence proximity interactions and localizes 4,145 proteins expressed in HEK293 cells. The recall of our localization predictions is on par with or better than previous large-scale mass spectrometry and microscopy approaches, but with higher localization specificity. In addition to assigning compartment and subcompartment localization for many previously unlocalized proteins, our data contain fine- grained localization information that, for example, allowed us to identify proteins with novel roles in mitochondrial dynamics. As a community resource, we have created humancellmap.org, a website that allows exploration of our data in detail, and aids with the analysis of BioID experiments.

9: A simple method for spray-on gene editing in planta
more details view paper

Posted to bioRxiv 25 Oct 2019

A simple method for spray-on gene editing in planta
3,093 downloads plant biology

Cara Doyle, Katie Higginbottom, Thomas A Swift, Mark Winfield, Christopher Bellas, David Benito-Alifonso, Taryn Fletcher, Carmen M Galan, Keith Edwards, Heather M Whitney

Potential innovation in Plant research using gene-edited and genetically modified plants is currently being hindered by inefficient and costly plant transformation. We show that carbon dots formed from natural materials (quasi-spherical, <10nm nanoparticles) can act as a fast vehicle for carrying plasmids into mature plant cells, resulting in transient plant transformation in a number of important crop species with no negative impacts on photosynthesis or growth. We further show that GFP, Cas9, and gRNA introduced into wheat via foliar application (spraying on) of plasmid coated carbon dots are expressed and, in the case of Cas9, make genome edits in SPO11 genes. Therefore, we present a protocol for spray-on gene editing that is simple, inexpensive, fast, transforms in planta , and is applicable to multiple crop species. We believe this technique creates many opportunities for the future of plant transformation in research and shows great promise for plant protein production systems.

10: Plants with self-sustained luminescence
more details view paper

Posted to bioRxiv 18 Oct 2019

Plants with self-sustained luminescence
3,035 downloads plant biology

Tatiana Mitiouchkina, Alexander S. Mishin, Louisa Gonzalez Somermeyer, Nadezhda M Markina, Tatiana V Chepurnyh, Elena B Guglya, Tatiana A Karataeva, Kseniia A Palkina, Ekaterina S Shakhova, Liliia I Fakhranurova, Sofia V Chekova, Aleksandra S Tsarkova, Yaroslav V Golubev, Vadim V Negrebetsky, Sergey A Dolgushin, Pavel V Shalaev, Olesya A Melnik, Victoria O Shipunova, Sergey M Deyev, Andrey I Bubyrev, Alexander S Pushin, Vladimir V Choob, Sergey V Dolgov, Fyodor A Kondrashov, Ilia V Yampolsky, Karen S. Sarkisyan

In contrast to fluorescent proteins, light emission from luciferase reporters requires exogenous addition of a luciferin substrate. Bacterial bioluminescence has been the single exception, where an operon of five genes is sufficient to produce light autonomously. Although commonly used in prokaryotic hosts, toxicity of the aldehyde substrate has limited its use in eukaryotes. Here we demonstrate autonomous luminescence in a multicellular eukaryotic organism by incorporating a recently discovered fungal bioluminescent system into tobacco plants. We monitored these light-emitting plants from germination to flowering, observing temporal and spatial patterns of luminescence across time scales from seconds to months. The dynamic patterns of luminescence reflected progression through developmental stages, circadian oscillations, transport, and response to injuries. As with other fluorescent and luminescent reporters, we anticipate that this system will be further engineered for varied purposes, especially where exogenous addition of substrate is undesirable.

11: The GTEx Consortium atlas of genetic regulatory effects across human tissues
more details view paper

Posted to bioRxiv 03 Oct 2019

The GTEx Consortium atlas of genetic regulatory effects across human tissues
2,967 downloads genetics

Francois Aguet, Alvaro N Barbeira, Rodrigo Bonazzola, Andrew Brown, Stephane E Castel, Brian Jo, Silva Kasela, Sarah Kim-Hellmuth, Yanyu Liang, Meritxell Oliva, Princy E Parsana, Elise Flynn, Laure Fresard, Eric R Gaamzon, Andrew R Hamel, Yuan He, Farhad Hormozdiari, Pejman Mohammadi, Manuel Muñoz-Aguirre, YoSon Park, Ashis Saha, Ayellet V Segrć, Benjamin J. Strober, Xiaoquan Wen, Valentin Wucher, Sayantan Das, Diego Garrido-Martín, Nicole R Gay, Robert E Handsaker, Paul J. Hoffman, Seva Kashin, Alan Kwong, Xiao Li, Daniel MacArthur, John M Rouhana, Matthew Stephens, Ellen Todres, Ana Viñuela, Gao Wang, Yuxin Zou, The GTEx Consortium, Christopher D Brown, Nancy Cox, Emmanouil Dermitzakis, Barbara E Engelhardt, Gad Getz, Roderic Guigo, Stephen B. Montgomery, Barbara E. Stranger, Hae Kyung Im, Alexis Battle, Kristin Ardlie, Tuuli Lappalainen

The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues, and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue-specificity of genetic effects, and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

12: Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3
more details view paper

Posted to bioRxiv 25 Oct 2019

Single-cell RNA counting at allele- and isoform-resolution using Smart-seq3
2,938 downloads genomics

Michael Hagemann-Jensen, Christoph Ziegenhain, Ping Chen, Daniel Ramsköld, Gerardus Hendriks, Anton JM Larsson, Omid R Faridani, R. Sandberg

Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5' unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

13: Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis
more details view paper

Posted to bioRxiv 25 Oct 2019

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis
2,865 downloads bioinformatics

Yu Fu, Alexander W Jung, Ramon Vinas Torne, Santiago Gonzalez Rosado, Harald Vohringer, Mercedes Jimenez-Linan, Luiza Moore, Moritz Gerstung

Here we use deep transfer learning to quantify histopathological patterns across 17,396 H&E stained histopathology image slides from 28 cancer types and correlate these with underlying genomic and transcriptomic data. Pan-cancer computational histopathology (PC-CHiP) classifies the tissue origin across organ sites and provides highly accurate, spatially resolved tumor and normal distinction within a given slide. The learned computational histopathological features correlate with a large range of recurrent genetic aberrations, including whole genome duplications (WGDs), arm-level copy number gains and losses, focal amplifications and deletions as well as driver gene mutations within a range of cancer types. WGDs can be predicted in 25/27 cancer types (mean AUC=0.79) including those that were not part of model training. Similarly, we observe associations with 25% of mRNA transcript levels, which enables to learn and localise histopathological patterns of molecularly defined cell types on each slide. Lastly, we find that computational histopathology provides prognostic information augmenting histopathological subtyping and grading in the majority of cancers assessed, which pinpoints prognostically relevant areas such as necrosis or infiltrating lymphocytes on each tumour section. Taken together, these findings highlight the large potential of PC-CHiP to discover new molecular and prognostic associations, which can augment diagnostic workflows and lay out a rationale for integrating molecular and histopathological data.

14: Report of Partial findings from the National Toxicology Program Carcinogenesis Studies of Cell Phone Radiofrequency Radiation in Hsd: Sprague Dawley® SD rats (Whole Body Exposure)
more details view paper

Posted to bioRxiv 26 May 2016

Report of Partial findings from the National Toxicology Program Carcinogenesis Studies of Cell Phone Radiofrequency Radiation in Hsd: Sprague Dawley® SD rats (Whole Body Exposure)
2,745 downloads cancer biology

Michael Wyde, Mark Cesta, Chad Blystone, Susan Elmore, Paul Foster, Michelle Hooth, Grace Kissling, David Malarkey, Robert Sills, Matthew Stout, Nigel Walker, Kristine Witt, Mary Wolfe, John Bucher

The U.S. National Toxicology Program (NTP) has carried out extensive rodent toxicology and carcinogenesis studies of radiofrequency radiation (RFR) at frequencies and modulations used in the U.S. telecommunications industry. This report presents partial findings from these studies. The occurrences of two tumor types in male Harlan Sprague Dawley rats exposed to RFR, malignant gliomas in the brain and schwannomas of the heart, were considered of particular interest and are the subject of this report. The findings in this report were reviewed by expert peer reviewers selected by the NTP and National Institutes of Health (NIH). These reviews and responses to comments are included as appendices to this report, and revisions to the current document have incorporated and addressed these comments. When the studies are completed, they will undergo additional peer review before publication in full as part of the NTP's Toxicology and Carcinogenesis Technical Reports Series. No portion of this work has been submitted for publication in a scientific journal. Supplemental information in the form of four additional manuscripts has or will soon be submitted for publication. These manuscripts describe in detail the designs and performance of the RFR exposure system, the dosimetry of RFR exposures in rats and mice, the results to a series of pilot studies establishing the ability of the animals to thermoregulate during RFR exposures, and studies of DNA damage. (1) Capstick M, Kuster N, Kuhn S, Berdinas-Torres V, Wilson P, Ladbury J, Koepke G, McCormick D, Gauger J, and Melnick R. A radio frequency radiation reverberation chamber exposure system for rodents; (2) Yijian G, Capstick M, McCormick D, Gauger J, Horn T, Wilson P, Melnick RL, and Kuster N. Life time dosimetric assessment for mice and rats exposed to cell phone radiation; (3) Wyde ME, Horn TL, Capstick M, Ladbury J, Koepke G, Wilson P, Stout MD, Kuster N, Melnick R, Bucher JR, and McCormick D. Pilot studies of the National Toxicology Program's cell phone radiofrequency radiation reverberation chamber exposure system; (4) Smith-Roe SL, Wyde ME, Stout MD, Winters J, Hobbs CA, Shepard KG, Green A, Kissling GE, Tice RR, Bucher JR, and Witt KL. Evaluation of the genotoxicity of cell phone radiofrequency radiation in male and female rats and mice following subchronic exposure.

15: The Future of OA: A large-scale analysis projecting Open Access publication and readership
more details view paper

Posted to bioRxiv 09 Oct 2019

The Future of OA: A large-scale analysis projecting Open Access publication and readership
2,707 downloads scientific communication and education

Heather Piwowar, Jason Priem, Richard Orr

Understanding the growth of open access (OA) is important for deciding funder policy, subscription allocation, and infrastructure planning. This study analyses the number of papers available as OA over time. The models includes both OA embargo data and the relative growth rates of different OA types over time, based on the OA status of 70 million journal articles published between 1950 and 2019. The study also looks at article usage data, analyzing the proportion of views to OA articles vs views to articles which are closed access. Signal processing techniques are used to model how these viewership patterns change over time. Viewership data is based on 2.8 million uses of the Unpaywall browser extension in July 2019. We found that Green, Gold, and Hybrid papers receive more views than their Closed or Bronze counterparts, particularly Green papers made available within a year of publication. We also found that the proportion of Green, Gold, and Hybrid articles is growing most quickly. In 2019:- 31% of all journal articles are available as OA. - 52% of article views are to OA articles. Given existing trends, we estimate that by 2025: - 44% of all journal articles will be available as OA. - 70% of article views will be to OA articles. The declining relevance of closed access articles is likely to change the landscape of scholarly communication in the years to come.

16: Simultaneous measurement of biochemical phenotypes and gene expression in single cells
more details view paper

Posted to bioRxiv 29 Oct 2019

Simultaneous measurement of biochemical phenotypes and gene expression in single cells
2,025 downloads biochemistry

Amanda L Richer, Kent Riemondy, Lakotah Hardie, Jay R. Hesselberth

Methods to measure heterogeneity among cells are rapidly transforming our understanding of biology but are currently limited to molecular abundance measurements. We developed an approach to simultaneously measure biochemical activities and mRNA abundance in single cells to understand the heterogeneity of DNA repair activities across thousands of human lymphocytes, identifying known and novel cell-type-specific DNA repair phenotypes. Our approach provides a general framework for understanding functional heterogeneity among single cells.

17: In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with Autism risk genes
more details view paper

Posted to bioRxiv 07 Oct 2019

In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with Autism risk genes
2,023 downloads genomics

Xin Jin, Sean K Simmons, Amy X Guo, Ashwin S Shetty, Michelle Ko, Lan Nguyen, Elise B Robinson, Paul Oyler, Nathan Curry, Giulio Deangeli, Simona Lodato, Joshua Z Levin, Aviv Regev, Feng Zhang, Paola Arlotta

The thousands of disease risk genes and loci identified through human genetic studies far outstrip our current capacity to systematically study their functions. New experimental approaches are needed for functional investigations of large panels of genes in a biologically relevant context. Here, we developed a scalable genetic screen approach, in vivo Perturb-Seq, and applied this method to the functional evaluation of 35 autism spectrum disorder (ASD) de novo loss-of-function risk genes. Using CRISPR-Cas9, we introduced frameshift mutations in these risk genes in pools, within the developing brain in utero, and then performed single-cell RNA-Seq in the postnatal brain. We identified cell type-specific gene signatures from both neuronal and glial cell classes that are affected by genetic perturbations and pointed at elements of both convergent and divergent cellular effects across this cohort of ASD risk genes. In vivo Perturb-Seq pioneers a systems genetics approach to investigate at scale how diverse mutations affect cell types and states in the biologically relevant context of the developing organism.

18: Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing
more details view paper

Posted to bioRxiv 03 Sep 2018

Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing
2,002 downloads cancer biology

Sanju Sinha, Karina Barbosa Guerra, Kuoyuan Cheng, Mark DM Leiserson, David M Wilson, Bríd M Ryan, Ze’ev A. Ronai, Joo Sang Lee, Aniruddha J Deshpande, Eytan Ruppin

Recent studies have reported that CRISPR-Cas9 gene editing induces a p53 -dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations[11][1],[12][2]. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL , at a level comparable to that reported for p53 . These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients’ tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing. [1]: #ref-11 [2]: #ref-12

19: A guide to performing Polygenic Risk Score analyses
more details view paper

Posted to bioRxiv 14 Sep 2018

A guide to performing Polygenic Risk Score analyses
1,996 downloads genomics

Shing Wan Choi, Timothy Mak, Paul F O'Reilly

The application of polygenic risk scores (PRS) has become routine in genetic epidemiological studies. Among a range of applications, PRS are commonly used to assess shared aetiology among different phenotypes and to evaluate the predictive power of genetic data, while they are also now being exploited as part of study design, in which experiments are performed on individuals, or their biological samples (eg. tissues, cells), at the tails of the PRS distribution and contrasted. As GWAS sample sizes increase and PRS become more powerful, they are also set to play a key role in personalised medicine. Despite their growing application and importance, there are limited guidelines for performing PRS analyses, which can lead to inconsistency between studies and misinterpretation of results. Here we provide detailed guidelines for performing polygenic risk score analyses relevant to different methods for their calculation, outlining standard quality control steps and offering recommendations for best-practice. We also discuss different methods for the calculation of PRS, common misconceptions regarding the interpretation of results and future challenges.

20: An association between sexes of successive siblings in the data from Demographic and Health Survey program
more details view paper

Posted to bioRxiv 12 Nov 2015

An association between sexes of successive siblings in the data from Demographic and Health Survey program
1,952 downloads physiology

Mikhail Monakhov

The prediction of future child's sex is a question of keen public interest. The probability of having a child of either sex is close to 50%, although multiple factors may slightly change this value. Some demographic studies suggested that sex determination can be influenced by previous pregnancies, although this hypothesis was not commonly accepted. This paper explores the correlations between siblings' sexes using data from the Demographic and Health Survey program. In the sample of about 2,214,601 women (7,985,855 children), the frequencies of sibships with multiple siblings of the same sex were significantly higher than can be expected by chance. A formal modelling demonstrated that sexes of the children were dependent on three kinds of sex ratio variation: a variation between families (Lexian), a variation within a family (Poisson) and a variation contingent upon the sex of preceding sibling (Markovian). There was a positive correlation between the sexes of successive siblings (coefficient = 0.067, p < 0.001), i.e. a child was more likely to be of the same sex as its preceding sibling. This correlation could be caused by secondary sex ratio adjustment in utero since the effect was decreasing with the length of birth-to-birth interval, and the birth-to-birth interval was longer for siblings with unlike sex.

Previous page 1 2 3 4 5 . . . 3018 Next page

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News