Computational biology and bioinformatics articles within Nature Communications

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  • Article
    | Open Access

    Traditional methods to identify genomic regions identical-by-descent (IBD) do not scale well to biobank-level datasets. Here, the authors describe a new IBD algorithm, iLASH, which uses LocAlity-Sensitive Hashing to provide rapid IBD estimation when applied to the PAGE and UK Biobank datasets.

    • Ruhollah Shemirani
    • , Gillian M. Belbin
    •  & José Luis Ambite

  • Article
    | Open Access

    Inaccurate cell segmentation has been the major problem for cell-type identification and tissue characterization of the in situ spatially resolved transcriptomics data. Here we show a robust cell segmentation-free computational framework (SSAM), for identifying cell types and tissue domains in 2D and 3D.

    • Jeongbin Park
    • , Wonyl Choi
    •  & Naveed Ishaque

  • Article
    | Open Access

    Technical advancements have significantly improved early diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various practical factors. Here, the authors develop an artificial intelligence assistive diagnostic solution to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria in a large multicenter study.

    • Xiaohui Zhu
    • , Xiaoming Li
    •  & Yanqing Ding

  • Article
    | Open Access

    Non-coding RNA function is poorly understood, partly due to the challenge of determining RNA secondary (2D) structure. Here, the authors present a framework for the reproducible prediction and visualization of the 2D structure of a wide array of RNAs, which enables linking RNA sequence to function.

    • Blake A. Sweeney
    • , David Hoksza
    •  & Anton I. Petrov

  • Article
    | Open Access

    Regular exercise promotes overall health and prevents non-communicable diseases, but the adaptation mechanisms are unclear. Here, the authors perform a meta-analysis to reveal time-specific patterns of the acute and long-term exercise response in human skeletal muscle, and identify sex- and age-specific changes.

    • David Amar
    • , Malene E. Lindholm
    •  & Euan A. Ashley

  • Article
    | Open Access

    Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. Here, authors present a deep learning-based approach to characterise how chromatin structure relates to transcriptional state of individual cells and determine which structural features of chromatin regulation are important for gene expression state.

    • Aparna R. Rajpurkar
    • , Leslie J. Mateo
    •  & Alistair N. Boettiger

  • Article
    | Open Access

    Several existing algorithms predict the methylation of DNA using Nanopore sequencing signals, but it is unclear how they compare in performance. Here, the authors benchmark the performance of several such tools, and propose METEORE, a consensus tool that improves prediction accuracy.

    • Zaka Wing-Sze Yuen
    • , Akanksha Srivastava
    •  & Eduardo Eyras

  • Article
    | Open Access

    Our understanding of human disease can be improved by integrating the abundance of high throughput biomedical data. Here, the authors use deep learning methods successfully used on images to integrate various types of omics data to improve patient classification and identify disease biomarkers.

    • Tongxin Wang
    • , Wei Shao
    •  & Kun Huang

  • Article
    | Open Access

    Many job sectors classified as ‘essential’ have continued operating with limited restrictions during the COVID-19 pandemic, potentially placing workers at higher risk of infection. Here, the authors show that seropositivity rates in workers vary widely across and between job sectors in Geneva, Switzerland.

    • Silvia Stringhini
    • , María-Eugenia Zaballa
    •  & Idris Guessous

  • Article
    | Open Access

    The genome-wide investigation of chromatin organization enables insights into global gene expression control. Here, the authors present a computationally efficient method for the analysis of chromatin organization data and use it to recover principles of 3D organization across conditions.

    • Merve Sahin
    • , Wilfred Wong
    •  & Christina S. Leslie

  • Article
    | Open Access

    Allele-specific expression in diploid organisms can be quantified by RNA-seq and it is common practice to rely on a single library. Here, the authors show that the standard approach has variable error rate and present Qllelic as a tool to improve reproducibility of allele-specific RNA-seq analysis.

    • Asia Mendelevich
    • , Svetlana Vinogradova
    •  & Alexander A. Gimelbrant

  • Article
    | Open Access

    The identification of HLA peptides by mass spectrometry is non-trivial. Here, the authors extended and used the wealth of data from the ProteomeTools project to improve the prediction of non-tryptic peptides using deep learning, and show their approach enables a variety of immunological discoveries.

    • Mathias Wilhelm
    • , Daniel P. Zolg
    •  & Bernhard Kuster

  • Article
    | Open Access

    Single-cell proteomics can provide insights into the molecular basis for cellular heterogeneity. Here, the authors develop a multiplexed single-cell proteomics and computational workflow, and show that their strategy captures the cellular hierarchies in an Acute Myeloid Leukemia culture model.

    • Erwin M. Schoof
    • , Benjamin Furtwängler
    •  & Bo T. Porse

  • Article
    | Open Access

    Cyclic peptides are of particular interest due to their pharmacological properties, but their design for binding to a target protein is challenging. Here, the authors present a computational “anchor extension” methodology for de novo design of cyclic peptides that bind to the target protein with high affinity, and validate the approach by developing cyclic peptides that inhibit histone deacetylases 2 and 6.

    • Parisa Hosseinzadeh
    • , Paris R. Watson
    •  & David Baker

  • Article
    | Open Access

    Existing studies of the chromatin accessibility, the primary mark of regulatory DNA, in Arabidopsis are based mainly on bulk samples. Here, the authors report the regulatory landscape of Arabidopsis thaliana roots at single-cell resolution.

    • Michael W. Dorrity
    • , Cristina M. Alexandre
    •  & Josh T. Cuperus

  • Article
    | Open Access

    Sequencing methods such as icSHAPE were developed to probe RNA structures transcriptome-wide in cells. To probe intact RNA structures, the authors develop icSHAPE-MaP and apply to Dicer-bound substrates showing that distance measuring is important for Dicer cleavage of pre-miRNAs.

    • Qing-Jun Luo
    • , Jinsong Zhang
    •  & Qiangfeng Cliff Zhang

  • Article
    | Open Access

    RNA localization plays an important role in transcriptome regulation. The majority of TERT transcripts are detected in the nucleus and TUG1 lncRNAs in both the nucleus and cytoplasm. Here, the authors combine single-cell RNA imaging, antisense oligonucleotides and splicing analyses to show that retention of specific introns drives stable compartmentalization of TERT and TUG1 transcripts in the nucleus, and that splicing of TERT retained introns is mitotically regulated.

    • Gabrijela Dumbović
    • , Ulrich Braunschweig
    •  & John L. Rinn

  • Article
    | Open Access

    The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts.

    • Anna Cichońska
    • , Balaguru Ravikumar
    •  & Tero Aittokallio

  • Article
    | Open Access

    Mammalian genomes are scattered with repetitive sequences, but their biology remains largely elusive. Here, the authors show that transcription can initiate from short tandem repetitive sequences, and that genetic variants linked to human diseases are preferentially found at repeats with high transcription initiation level.

    • Mathys Grapotte
    • , Manu Saraswat
    •  & Charles-Henri Lecellier

  • Article
    | Open Access

    Although autophagy has been linked to tumourigenesis, it is unclear how genomic alterations affect autophagy selectivity in tumours. Here, the authors establish a pipeline that integrates computational and experimental approaches to show that altered autophagy selectivity is frequent in cancer cells and link glycogen autophagy with tumourigenesis.

    • Zhu Han
    • , Weizhi Zhang
    •  & Da Jia

  • Article
    | Open Access

    Single-cell RNA-Seq allows us to observe snapshots of how biological systems change over time at cellular resolution. Here, the authors develop a generative framework that uses time-resolved single-cell data to model how cells change in physical time, including in response to perturbations.

    • Grace Hui Ting Yeo
    • , Sachit D. Saksena
    •  & David K. Gifford

  • Article
    | Open Access

    Current genome mining methods predict many putative non-ribosomal peptides (NRPs) from their corresponding biosynthetic gene clusters, but it remains unclear which of those exist in nature and how to identify their post-assembly modifications. Here, the authors develop NRPminer, a modification-tolerant tool for the discovery of NRPs from large genomic and mass spectrometry datasets, and use it to find 180 NRPs from different environments.

    • Bahar Behsaz
    • , Edna Bode
    •  & Hosein Mohimani

  • Article
    | Open Access

    MALDI-mass spectrometry imaging (MSI) can reveal the distribution of proteins in tissues but tools for protein identification and annotation are sparse. Here, the authors develop an open-source bioinformatic workflow for false discovery rate-controlled protein annotation and spatial mapping from MALDI-MSI data.

    • G. Guo
    • , M. Papanicolaou
    •  & A. C. Grey

  • Article
    | Open Access

    Liquid biopsies enable minimally invasive applications for diagnosis and treatment monitoring. Here the authors analyse fragmentation patterns of circulating tumour DNA on multiple levels and develop a bioinformatic tool, LIQUORICE, to accurately detect and classify paediatric cancers with low mutational burden.

    • Peter Peneder
    • , Adrian M. Stütz
    •  & Eleni M. Tomazou

  • Article
    | Open Access

    Predicting chromatographic retention times (RTs) has proven beneficial in proteomics but has not yet been achieved for crosslinked peptides. Here, the authors develop an RT prediction tool for crosslinked peptides and leverage predicted RTs to increase identifications in crosslinking mass spectrometry studies.

    • Sven H. Giese
    • , Ludwig R. Sinn
    •  & Juri Rappsilber

  • Article
    | Open Access

    Multi-layered epigenetic regulation in higher eukaryotes makes it challenging to disentangle the individual effects of modifications on chromatin structure and function. Here, the authors expressed mammalian DNA methyltransferases in yeast, which have no DNA methylation, to show that methylation has intrinsic effects on chromatin structure.

    • Diana Buitrago
    • , Mireia Labrador
    •  & Modesto Orozco

  • Article
    | Open Access

    Intratumour heterogeneity (ITH) is associated with worse prognosis in cancer, and efficient frameworks to measure it are needed. Here the authors develop a method to estimate copy number heterogeneity, and propose that it is driven by chromosomal instability and can predict pan-cancer survival.

    • Erik van Dijk
    • , Tom van den Bosch
    •  & Daniël M. Miedema

  • Article
    | Open Access

    The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.

    • Vladimir Gligorijević
    • , P. Douglas Renfrew
    •  & Richard Bonneau

  • Article
    | Open Access

    Association analyses that capture rare and noncoding variants in whole genome sequencing data are limited by factors like statistical power. Here, the authors present KnockoffScreen, a statistical method using the knockoff framework to detect, localise and prioritise rare and common risk variants at genome-wide scale.

    • Zihuai He
    • , Linxi Liu
    •  & Iuliana Ionita-Laza

  • Article
    | Open Access

    A major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.

    • Mohammadali Sharifshazileh
    • , Karla Burelo
    •  & Giacomo Indiveri

  • Article
    | Open Access

    Cellular genetic heterogeneity is common across biological conditions, yet application of long-read sequencing to this subject is limited by error rates. Here, the authors present iGDA, a tool for detection and phasing of minor variants from long-read sequencing data, allowing accurate reconstruction of haplotypes.

    • Zhixing Feng
    • , Jose C. Clemente
    •  & Eric E. Schadt

  • Article
    | Open Access

    High-grade serous ovarian cancer (HGSOC) is prone to developing resistance to treatment. Here, the authors use single-cell RNA-seq and an analysis of archetypes, and find that shifts in metabolism and proliferation are associated with the response to treatment and clonal heterogeneity in HGSOC.

    • Aritro Nath
    • , Patrick A. Cosgrove
    •  & Andrea H. Bild

  • Article
    | Open Access

    Combining scRNA-seq with spatial information to enable the reconstruction of spatially-resolved cell atlases is challenging for rare cell types. Here the authors present ClumpSeq, an approach for sequencing small clumps of tissue attached cells, and apply it to establish spatial atlases for all secretory cell types in the small intestine.

    • Rita Manco
    • , Inna Averbukh
    •  & Shalev Itzkovitz

  • Article
    | Open Access

    The vast majority of somatic mutations observed in tumors are rare. Here, the authors show that these large numbers of rare mutations are more predictive of the tissue of origin of a tumor than the information from a few common driver mutations.

    • Saptarshi Chakraborty
    • , Axel Martin
    •  & Ronglai Shen

  • Article
    | Open Access

    Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Here, the authors propose a computationally efficient Permutation-based Feature Importance Test to assist interpretation and selection of individual features in complex machine learning models for complex disease analysis.

    • Xinlei Mi
    • , Baiming Zou
    •  & Jianhua Hu

  • Article
    | Open Access

    Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures, with enormous societal and economic costs. Here, the authors demonstrate the feasibility of a test-trace-quarantine strategy using an agent-based model and detailed data on the Seattle region.

    • Cliff C. Kerr
    • , Dina Mistry
    •  & Daniel J. Klein

  • Article
    | Open Access

    One challenge of single cell RNA sequencing analysis is how to consistently identify cell subtypes and states across different datasets. Here the authors propose the use of a reference single-cell atlas as a stable system of coordinates to characterize T cell states across studies, diseases and species.

    • Massimo Andreatta
    • , Jesus Corria-Osorio
    •  & Santiago J. Carmona

  • Article
    | Open Access

    Here, combing the massive gene-universe of the gut microbiome to identify strain-specific, cross-disease, associations across seven human diseases, the authors introduce the concept of microbiome architecture, defined as the complete set of positive and negative associations between microbial genes and human host disease, highlighting microbiome architectures as potential diagnostic indicators.

    • Braden T. Tierney
    • , Yingxuan Tan
    •  & Chirag J. Patel

  • Article
    | Open Access

    Whole genome sequencing data are increasingly becoming routinely available but generating actionable insights is challenging. Here, the authors describe Pathogenwatch, a web tool for genomic surveillance of S. Typhi, and demonstrate its use for antimicrobial resistance assignment and strain risk assessment.

    • Silvia Argimón
    • , Corin A. Yeats
    •  & David M. Aanensen

  • Article
    | Open Access

    Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for classification and prediction in big datasets.

    • Joshua T. Vogelstein
    • , Eric W. Bridgeford
    •  & Mauro Maggioni

  • Article
    | Open Access

    Differentiating neutrophil functional states is difficult. Here the authors show, using single cell RNA-sequencing and trajectory analyses, that mouse neutrophils can be presented as a transcriptome continuum rather than discrete subsets, but are affected by inflammation to express distinct transcriptional states.

    • Ricardo Grieshaber-Bouyer
    • , Felix A. Radtke
    •  & Hideyuki Yoshida

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