Biology subjects

S

Publications and source records attributed to S.

9 recordsLinked to original sources

bioRxiv2025

Improving American chestnut resistance to two invasive pathogens through genome-enabled breeding

Over a century after two introduced pathogens decimated American chestnut populations, breeding programs continue to incorporate resistance from Chinese chestnut to recover self-sustaining populations. Due to complex genetics of chestnut blight resistance, it is challenging to obtain trees with sufficient resistance and competitive growth. We developed high quality reference genomes for Chinese and American chestnut and leveraged large disease phenotype and genotype datasets to develop accurate genomic selection. Inoculation and simulation results indicate that resistance may be substantially increased in trees that inherited 70% to 100% of their genome from American chestnut. To facilitate gene editing, we integrated multiple lines of evidence to discover candidate alleles for blight resistance and susceptibility. These genomic resources provide a strong foundation to accelerate restoration of this iconic tree.

genomics↗

bioRxiv2024

Activation mapping in multi-center rat sensory-evoked functional MRI datasets using a unified pipeline.

Functional Magnetic Resonance Imaging (fMRI) in rodents is pivotal for understanding the mechanisms underlying Blood Oxygen Level-Dependent (BOLD) signals and phenotyping animal models of disorders, amongst other applications. Despite its growing use, comparing rodent fMRI results across different research sites remains challenging due to variations in experimental protocols. Here, we aggregated and analyzed 22 sensory-evoked rat fMRI datasets from 12 imaging centers, totaling scans from 220 rats, to assess the consistency of results across diverse protocols. We applied a standardized preprocessing pipeline and evaluated the impact of different hemodynamic response function models on group and individual level activity patterns. Our analysis revealed inter-dataset variability attributed to differences in experimental design, anesthesia protocols, and imaging parameters. We identified robust activation clusters in all (22/22) datasets. The comparison between stock human models implemented in software and rat-specific models showed significant variations in the resulting statistical maps. Our findings emphasize the necessity for standardized protocols and collaborative efforts to improve the reproducibility and reliability of rodent fMRI studies. We provide open access to all datasets and analysis code to foster transparency and further research in the field.

neuroscience↗

bioRxiv2024

Bird Name-a-thon: Categorizing English bird names using crowdsourcing

Common names of species are important for communicating with the general public. In principle, these names should provide an accessible way to engage with and identify species. The common names of species have historically been labile without standard guidelines, even within a language. Currently, there is no systematic assessment of how often common names communicate identifiable and biologically relevant characteristics about species. This is a salient issue in ornithology, where common names are used more often than scientific names for species of birds in written and spoken English, even by professional researchers. To gain a better understanding of the types of terminology used in the English-language common names of bird species, a group of 85 professional ornithologists and non-professional contributors classified unique descriptors in the common names of all recognized species of birds. In the AvianLexiconAtlas database produced by this work, each species common name is assigned to one of ten categories associated with aspects of avian biology, ecology, or human culture. Across 10,906 species of birds, 89% have names describing the biology of the species, while the remaining 11% of species have names derived from human cultural references, human names, or local non-English languages. Species with common names based on features of avian biology are more likely to be related to each other or be from the same geographic region. The crowdsourced data collection also revealed that many common names contain specialized or historic terminology unknown to many of the data collectors, and we include these terms in a glossary and gazetteer alongside the dataset. The AvianLexiconAtlas can be used as a quantitative resource to assess the state of terminology in English-language common names of birds. Future research using the database can shed light on historical approaches to nomenclature and how people engage with species through their names.

zoology↗

bioRxiv2022

Manipulating the 3D organization of the largest synthetic yeast chromosome

Whether synthetic genomes can power life has attracted broad interest in the synthetic biology field, especially when the synthetic genomes are extensively modified with thousands of designer features. Here we report de novo synthesis of the largest eukaryotic chromosome thus far, synIV, a 1,454,621-bp Saccharomyces cerevisiae chromosome resulting from extensive genome streamlining and modification. During the construction of synIV, we developed megachunk assembly combined with a hierarchical integration strategy, which significantly increased the accuracy and flexibility of synthetic chromosome construction and facilitated chromosome debugging. In addition to the drastic sequence changes made to synIV by rewriting it, we further manipulated the three-dimensional structure of synIV in the yeast nucleus to explore spatial gene regulation within the nuclear space. Surprisingly, we found few gene expression changes, suggesting that positioning inside the yeast nucleoplasm plays a minor role in gene regulation. Lastly, we tethered synIV to the inner nuclear membrane via its hundreds of loxPsym sites and observed transcriptional repression of the entire chromosome, demonstrating chromosome-wide transcription manipulation without changing the DNA sequences. Our manipulation of the spatial structure of the largest synthetic yeast chromosome shed light on higher-order architectural design of the synthetic genomes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/487066v2_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@18bf586org.highwire.dtl.DTLVardef@1a471d5org.highwire.dtl.DTLVardef@12d7690org.highwire.dtl.DTLVardef@1c32510_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDe novo synthesis of the largest eukaryotic chromosome, synIV C_LIO_LISynIV shows similar 3D structure to wild-type IV, despite thousands of changes made to it C_LIO_LI"Inside-out" repositioning of synIV in nucleus shows minor transcriptional changes C_LIO_LIMultipoint tethering synIV to inner nuclear membrane represses transcription of whole chromosome C_LI

synthetic biology↗

bioRxiv2022

Neuroimaging within the Dominantly Inherited Alzheimer's Network (DIAN): PET and MRI

The Dominantly Inherited Alzheimer Network (DIAN) Observational Study is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). This rare form of Alzheimer disease (AD) is caused by mutations in the presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) genes. As individuals from these families have a 50% chance of inheriting the familial mutation, this provides researchers with a well-matched cohort of carriers vs non-carriers for case-control studies. An important trait of ADAD is that the age at symptom onset is highly predictable and consistent for each specific mutation, allowing researchers to estimate an individuals point in their disease time course prior to symptom onset. Although ADAD represents only a small proportion (approximately 0.1%) of all AD cases, studying this form of AD allows researchers to investigate preclinical AD and the progression of changes that occur within the brain prior to AD symptom onset. Furthermore, the young age at symptom onset (typically 30-60 years) means age-related comorbidities are much less prevalent than in sporadic AD, thereby allowing AD pathophysiology to be studied independent of these confounds. A major goal of the DIAN Observational Study is to create a global resource for AD researchers. To that end, the current manuscript provides an overview of the DIAN magnetic resonance imaging (MRI) and positron emission tomography (PET) protocols and highlights the key imaging results of this study to date.

neuroscience↗

bioRxiv2021

Petascale neural circuit reconstruction: automated methods

3D electron microscopy (EM) has been successful at mapping invertebrate nervous systems, but the approach has been limited to small chunks of mammalian brains. To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels as axon, dendrite, soma, and other semantic categories, and detect synapses and assign them to presynaptic and postsynaptic segments. The output of neuronal boundary detection is segmented by mean affinity agglomeration with semantic and size constraints. Pipeline operations are implemented by leveraging distributed and cloud computing. Intermediate results of the pipeline are held in cloud storage, and can be effortlessly viewed as images, which aids debugging. We applied the pipeline to create an automated reconstruction of an EM image volume spanning four visual cortical areas of a mouse brain. Code for the pipeline is publicly available, as is the reconstructed volume.

neuroscience↗

bioRxiv2021

A new pipeline for the normalization and pooling of metabolomics data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through PC-PR2 analysis; (iii) application of linear mixed models to remove unwanted variability, including samples originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

bioinformatics↗

bioRxiv2020

Highly potent anti-SARS-CoV-2 multi-DARPin therapeutic candidates

Globally accessible therapeutics against SARS-CoV-2 are urgently needed. Here, we report the generation of the first anti-SARS-CoV-2 DARPin molecules with therapeutic potential as well as rapid large-scale production capabilities. Highly potent multivalent DARPin molecules with low picomolar virus neutralization efficacies were generated by molecular linkage of three different monovalent DARPin molecules. These multivalent DARPin molecules target various domains of the SARS-CoV-2 spike protein, thereby limiting possible viral escape. Cryo-EM analysis of individual monovalent DARPin molecules provided structural explanations for the mode of action. Analysis of the protective efficacy of one multivalent DARPin molecule in a hamster SARS-CoV-2 infection model demonstrated a significant reduction of pathogenesis. Taken together, the multivalent DARPin molecules reported here, one of which has entered clinical studies, constitute promising therapeutics against the COVID-19 pandemic.

immunology↗

bioRxiv2018

Trans-ethnic genome-wide association study provides insight into effector genes and molecular mechanisms for kidney function and highlights a causal effect on kidney-specific disease aetiologies

Chronic kidney disease (CKD) affects [~]10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

genetics↗