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Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 42,904 bioRxiv papers from 193,370 authors.

Most tweeted bioRxiv papers, last 24 hours

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

1: A method for genome-wide genealogy estimation for thousands of samples
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Posted to bioRxiv 14 Feb 2019

A method for genome-wide genealogy estimation for thousands of samples
78 tweets genetics

Leo Speidel, Marie Forest, Sinan Shi, Simon Myers

Knowledge of genome-wide genealogies for thousands of individuals would simplify most evolutionary analyses for humans and other species, but has remained computationally infeasible. We developed a method, Relate, scaling to > 10,000 sequences while simultaneously estimating branch lengths, mutational ages, and variable historical population sizes, as well as allowing for data errors. Application to 1000 Genomes Project haplotypes produces joint genealogical histories for 26 human populations. Highly diverged lineages are present in all groups, but most frequent in Africa. Outside Africa, these mainly reflect ancient introgression from groups related to Neanderthals and Denisovans, while African signals instead reflect unknown events, unique to that continent. Our approach allows more powerful inferences of natural selection than previously possible. We identify multiple novel regions under strong positive selection, and multi-allelic traits including hair colour, BMI, and blood pressure, showing strong evidence of directional selection, varying among human groups.

2: Ohana: detecting selection in multiple populations by modelling ancestral admixture components
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Posted to bioRxiv 14 Feb 2019

Ohana: detecting selection in multiple populations by modelling ancestral admixture components
72 tweets bioinformatics

Jade Yu Cheng, Fernando Racimo, Rasmus Nielsen

One of the most powerful and commonly used methods for detecting local adaptation in the genome is the identification of extreme allele frequency differences between populations. In this paper, we present a new maximum likelihood method for finding regions under positive selection. The method is based on a Gaussian approximation to allele frequency changes and it incorporates admixture between populations. The method can analyze multiple populations simultaneously and retains power to detect selection signatures specific to ancestry components that are not representative of any extant populations. We evaluate the method using simulated data and compare it to related methods based on summary statistics. We also apply it to human genomic data and identify loci with extreme genetic differentiation between major geographic groups. Many of the genes identified are previously known selected loci relating to hair pigmentation and morphology, skin and eye pigmentation. We also identify new candidate regions, including various selected loci in the Native American component of admixed Mexican-Americans. These involve diverse biological functions, like immunity, fat distribution, food intake, vision and hair development.

3: Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior
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Posted to bioRxiv 13 Feb 2019

Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior
64 tweets neuroscience

Jingwei Li, Ru Kong, Raphael Liegeois, Csaba Orban, Yanrui Tan, Nanbo Sun, Avram Holmes, Mert R. Sabuncu, Tian Ge, B.T. Thomas Yeo

Global signal regression (GSR) is one of the most debated preprocessing strategies for resting-state functional MRI. GSR effectively removes global artifacts driven by motion and respiration, but also discards globally distributed neural information and introduces negative correlations between certain brain regions. The vast majority of previous studies have focused on the effectiveness of GSR in removing imaging artifacts, as well as its potential biases. Given the growing interest in functional connectivity fingerprinting, here we considered the utilitarian question of whether GSR strengthens or weakens associations between resting-state functional connectivity (RSFC) and multiple behavioral measures across cognition, personality and emotion. By applying the variance component model to the Brain Genomics Superstruct Project (GSP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 47% across 23 behavioral measures after GSR. In the Human Connectome Project (HCP), we found that behavioral variance explained by whole-brain RSFC increased by an average of 40% across 58 behavioral measures, when GSR was applied after ICA-FIX de-noising. To ensure generalizability, we repeated our analyses using kernel regression. GSR improved behavioral prediction accuracies by an average of 64% and 12% in the GSP and HCP datasets respectively. Importantly, the results were consistent across methods. A behavioral measure with greater RSFC-explained variance (using the variance component model) also exhibited greater prediction accuracy (using kernel regression). A behavioral measure with greater improvement in behavioral variance explained after GSR (using the variance component model) also enjoyed greater improvement in prediction accuracy after GSR (using kernel regression). Furthermore, GSR appeared to benefit task performance measures more than self-reported measures. Since GSR was more effective at removing motion-related and respiratory-related artifacts, GSR-related increases in variance explained and prediction accuracies were unlikely the result of motion-related or respiratory-related artifacts. However, it is worth emphasizing that the current study focused on whole-brain RSFC, so it remains unclear whether GSR improves RSFC-behavioral associations for specific connections or networks. Overall, our results suggest that at least in the case for young healthy adults, GSR strengthens the associations between RSFC and most (although not all) behavioral measures. Code for the variance component model and ridge regression can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/preprocessing/Li2019_GSR.

4: Novel Algorithms for the Taxonomic Classification of Metagenomic Linked Reads
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Posted to bioRxiv 14 Feb 2019

Novel Algorithms for the Taxonomic Classification of Metagenomic Linked Reads
33 tweets bioinformatics

David C. Danko, Dmitry Meleshko, Daniela Bezdan, Christopher C Mason, Iman Hajirasouliha

We present KrakenLinked, a metagenomic read classifier for Linked-Reads. We have formulated two algorithms for read classification of metagenomic samples using linked reads: tree pruning and taxa promotion. Tree pruning improves specificity while taxa promotion improves sensitivity. Used together the algorithms improve the taxonomic classification of linked-reads compared to short reads, particularly reducing false identification of taxa. We have implemented these algorithms as functions in KrakenUniq which we make available as KrakenLinked.

5: EpiMethylTag simultaneously detects ATAC-seq or ChIP-seq signals with DNA methylation
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Posted to bioRxiv 14 Feb 2019

EpiMethylTag simultaneously detects ATAC-seq or ChIP-seq signals with DNA methylation
30 tweets genomics

Priscillia Lhoumaud, Gunjan Sethia, Franco Izzo, Sana Badri, MacIntosh Cornwell, Kyu-Tae Kim, Dan Landau, Jane Skok

Activation of regulatory elements is thought to be inversely correlated with DNA methylation levels. However, it is difficult to determine whether DNA methylation is compatible with chromatin accessibility or transcription factor (TF) binding if assays are performed separately. We developed a low input, low sequencing depth method, EpiMethylTag that combines ATAC-seq or ChIP-seq (M-ATAC or M-ChIP) with bisulfite conversion, to simultaneously examine accessibility/TF binding and methylation on the same DNA.

6: The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function.
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Posted to bioRxiv 14 Feb 2019

The genomic basis of mood instability: identification of 46 loci in 363,705 UK Biobank participants, genetic correlation with psychiatric disorders, and association with gene expression and function.
22 tweets genetics

Joey Ward, Elizabeth M. Tunbridge, Cynthia Sandor, Laura Lyall, Amy Ferguson, Rona J Strawbridge, Donald M Lyall, Breda Cullen, Nicholas Graham, Keira JA Johnston, Caleb P Webber, Valentina Escott-Price, Michael O'Donovan, Jill P Pell, Mark ES Bailey, Paul J. Harrison, Daniel J Smith

Genome-wide association studies (GWAS) of psychiatric phenotypes have tended to focus on categorical diagnoses, but to understand the biology of mental illness it may be more useful to study traits which cut across traditional boundaries. Here we report the results of a GWAS of mood instability (MI) as a trait in a large population cohort (UK Biobank, n=363,705). We also assess the clinical and biological relevance of the findings, including whether genetic associations show enrichment for nervous system pathways. Forty six unique loci associated with MI were identified with a heritability estimate of 9%. Linkage Disequilibrium Score Regression (LDSR) analyses identified genetic correlations with Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizophrenia (SZ), anxiety and Post Traumatic Stress Disorder (PTSD). Gene-level and gene set analyses identified total 244 significant genes and 6 enriched gene sets. Tissue expression analysis from the SNP level data found enrichment in multiple brain regions, and eQTL analyses highlighted an inversion on chromosome 17 plus two brain-specific eQTLs. Additionally, we used a Phenotype Linkage Network (PLN) analysis and community analysis to assess for enrichment of nervous system gene sets using mouse orthologue databases. The PLN analysis found enrichment in nervous system PLNs for a community containing serotonin and melatonin receptors. In summary, this work has identified novel loci, tissues, and gene sets contributing to MI as a normal trait and will inform future work on the biology of mood and psychotic disorders, and to point the way towards potential for new stratified medicine approaches and the identification of novel trans-diagnostic drug targets.

7: ENDOSOMAL MEMBRANE TENSION CONTROLS ESCRT-III-DEPENDENT INTRA-LUMENAL VESICLE FORMATION
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Posted to bioRxiv 14 Feb 2019

ENDOSOMAL MEMBRANE TENSION CONTROLS ESCRT-III-DEPENDENT INTRA-LUMENAL VESICLE FORMATION
19 tweets cell biology

Aurelien Roux, Jean Gruenberg, Vincent Mercier, Jorge Larios, Antoine Goujon, Stefan Matile, Guillaume Molinard

Plasma membrane tension strongly affects cell surface processes, such as migration, endocytosis and signalling. However, it is not known whether membrane tension of organelles regulates their functions, notably intracellular traffic. The ESCRT-III complex is the major membrane remodelling complex that drives Intra-Lumenal Vesicle (ILV) formation on endosomal membranes. Here, we made use of a new fluorescent membrane tension probe to show that ESCRT-III subunits are recruited onto endosomal membranes when membrane tension is reduced. We find that tension-dependent recruitment is associated with ESCRT-III polymerization and membrane deformation in vitro, and correlates with increased ILVs formation in ESCRT-III decorated endosomes in vivo. Finally, we find that endosomal membrane tension decreases when ILV formation is triggered by EGF under physiological conditions. These results indicate that membrane tension is a major regulator of ILV formation and of endosome trafficking, leading us to conclude that membrane tension can control organelle functions.

8: Unmatched level of molecular convergence among deeply divergent complex multicellular fungi
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Posted to bioRxiv 14 Feb 2019

Unmatched level of molecular convergence among deeply divergent complex multicellular fungi
18 tweets evolutionary biology

Zsolt Merenyi, Arun N Prasanna, Wang Zheng, Karoly Kovacs, Botond Hegedus, Balazs Balint, Balazs Papp, Jeffrey P. Townsend, Laszlo G Nagy

Convergent evolution is pervasive in nature, but it is poorly understood how various constraints and natural selection limit the diversity of evolvable phenotypes. Here, we report that, despite >650 million years of divergence, the same genes have repeatedly been co-opted for the development of complex multicellularity in the two largest clades of fungi-the Ascomycota and Basidiomycota. Co-opted genes have undergone duplications in both clades, resulting in >81% convergence across shared multicellularity-related families. This convergence is coupled with a rich repertoire of multicellularity-related genes in ancestors that predate complex multicellular fungi, suggesting that the coding capacity of early fungal genomes was well suited for the repeated evolution of complex multicellularity. Our work suggests that evolution may be predictable not only when organisms are closely related or are under similar selection pressures, but also if the genome biases the potential evolutionary trajectories organisms can take, even across large phylogenetic distances.

9: Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters
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Posted to bioRxiv 11 Oct 2018

Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters
17 tweets evolutionary biology

Sandra Alvarez-Carretero, Anjali Goswami, Ziheng Yang, Mario dos Reis

Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modelled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population "noise") and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analysed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.

10: Principles of Meiotic Chromosome Assembly
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Posted to bioRxiv 13 Oct 2018

Principles of Meiotic Chromosome Assembly
15 tweets molecular biology

Stephanie A Schalbetter, Geoffrey Fudenberg, Jonathan Baxter, Katherine S Pollard, Matthew J Neale

During meiotic prophase, chromosomes organise into a series of chromatin loops emanating from a proteinaceous axis, but the mechanisms of assembly remain unclear. Here we elucidate how this elaborate three-dimensional chromosome organisation is underpinned by genomic sequence in Saccharomyces cerevisiae. Entering meiosis, strong cohesin-dependent grid-like Hi-C interaction patterns emerge, reminiscent of mammalian interphase organisation, but with distinct regulation. Meiotic patterns agree with simulations of loop extrusion limited by barriers, yet are patterned by convergent transcription rather than binding of the mammalian interphase factor, CTCF, which is absent in S. cerevisiae - thereby both challenging and extending current paradigms of local chromosome organisation. While grid-like interactions emerge independently of meiotic chromosome synapsis, synapsis itself generates additional compaction that matures differentially according to telomere proximity and chromosome size. Collectively, our results elucidate fundamental principles of chromosome assembly and demonstrate the essential role of cohesin within this evolutionarily conserved process.

11: Cannabis use, depression and self-harm: phenotypic and genetic relationships
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Posted to bioRxiv 14 Feb 2019

Cannabis use, depression and self-harm: phenotypic and genetic relationships
14 tweets genetics

Karen Hodgson, Jonathan Coleman, Saskia P Hagenaars, Kirstin L Purves, Shing Wan Choi, Paul F O'Reilly, Gerome F Breen, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Cathryn M Lewis

Background and Aims: The use of cannabis has previously been linked to both depression and self-harm, however the role of genetics in this relationship are unclear. We aimed to examine the phenotypic and genetic relationships between these traits. Design: Genetic and cross-sectional phenotypic data collected through UK Biobank, together with consortia genome-wide association study summary statistics. These data were used to assess the phenotypic and genetic relationship between cannabis use, depression and self harm. Setting: UK, with additional international consortia data Participants N=126,291 British adults aged between 40 and 70 years, recruited into UK Biobank. Measurements: Genome-wide genetic data, phenotypic data on lifetime history of cannabis use, depression and self-harm. Findings: In UK Biobank, cannabis use is associated with increased likelihood of depression (OR=1.64, 95% CI=1.59-1.70, p=1.19x10-213) and self-harm (OR=2.85, 95% CI=2.69-3.01, p=3.46x10-304). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Additionally, significant genetic correlations are seen between cannabis use and depression using consortia summary statistics (rg=0.289, SE=0.036, p=1.45x10-15). Polygenic risk scores for cannabis use and depression both explain a small but significant proportion of variance in cannabis use, depression and self harm within a UK Biobank target sample. However, two-sample Mendelian randomisation analyses were not significant. Conclusions: Cannabis use is both phenotypically and genetically associated with depression and self harm. Future work dissecting the causal mechanism linking these traits may have implications for cannabis users.

12: Exercise twice-a-day potentiates skeletal muscle signalling responses associated with mitochondrial biogenesis in humans, which are independent of lowered muscle glycogen content
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Posted to bioRxiv 12 Feb 2019

Exercise twice-a-day potentiates skeletal muscle signalling responses associated with mitochondrial biogenesis in humans, which are independent of lowered muscle glycogen content
11 tweets molecular biology

Victor Amorim Andrade-Souza, Thaysa Ghiarone, Andre Sansonio, Kleiton Augusto Santos Silva, Fabiano Tomazini, Lucyana Arcoverde, Jackson J Fyfe, Enrico Perri, Nicholas Saner, Jujiao Kuang, Romulo Bertuzzi, Carol Gois Leandro, David J Bishop, Adriano Eduardo Lima-Silva

Endurance exercise begun with reduced muscle glycogen stores seems to potentiate skeletal muscle protein abundance and gene expression. However, it is unknown whether this greater signalling responses is due to low muscle glycogen per se or to performing two exercise sessions in close proximity - as a first exercise session is necessary to reduce the muscle glycogen stores. In the present study, we manipulated the recovery duration between a first muscle glycogen-depleting exercise and a second exercise session, such that the second exercise session started with reduced muscle glycogen in both approaches but was performed either two or 15 h after the first exercise session (so-called twice-a-day and once-daily approaches, respectively). We found that exercise twice-a-day increased the nuclear abundance of transcription factor EB (TFEB) and nuclear factor of activated T cells (NFAT) and potentiated the transcription of peroxisome proliferator-activated receptor-ɣ coactivator 1 alpha (PGC-1a), peroxisome proliferator-activated receptor alpha (PPARa;) and peroxisome proliferator-activated receptor beta/delta (PPARb/d) genes, in comparison with the once-daily exercise. These results suggest that the elevated molecular signalling reported with previous train-low approaches can be attributed to performing two exercise sessions in close proximity rather than the reduced muscle glycogen content per se. The twice-a-day approach might be an effective strategy to induce adaptations related to mitochondrial biogenesis and fat oxidation.

13: SCANVIS: a tool for SCoring, ANnotating and VISualing splice junctions
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Posted to bioRxiv 14 Feb 2019

SCANVIS: a tool for SCoring, ANnotating and VISualing splice junctions
11 tweets bioinformatics

Phaedra Agius, Heather Geiger, Nicolas Robine

The association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy, frequently requiring detailed analysis of splicing events across multiple samples. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions by gene name, junction type and any frame shifts incurred. SCANVIS has a novel and fast visualization technique that distinguishes annotated splice junctions from unannotated ones in the context of nearby variants and read coverage. It also allows users to merge samples across cohorts, thereby allowing for quick comparisons of splice junctions across diseases and tissue types. We show that SCANVIS generates reasonable PSI scores by demonstrating that tis-sue/cancer types in GTEX and TCGA are well separated and easily predicted from a few thou-sand SJs. We also show how SCANVIS can be used to map out junctions overlaid with variants and read coverage for one or more samples, with line types and colors delineating frame shifts and junction types.

14: Speed, accuracy, sensitivity and quality control choices for detecting clinically relevant microbes in whole blood from patients.
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Posted to bioRxiv 14 Feb 2019

Speed, accuracy, sensitivity and quality control choices for detecting clinically relevant microbes in whole blood from patients.
11 tweets bioinformatics

James Eric Thornton, George S. Watts, Kenneth Youens-Clark, Lee D. Cranmer, Bonnie L Hurwitz

Infections are a serious health concern worldwide, particularly in vulnerable populations such as the immunocompromised, elderly, and young. Advances in metagenomic sequencing availability, speed, and decreased cost offer the opportunity to supplement or replace culture-based identification of pathogens with DNA sequence-based diagnostics. Adopting metagenomic analysis for clinical use requires that all aspects of the pipeline are optimized and tested, including data analysis. We tested the accuracy, sensitivity, and resource requirements of Centrifuge within the context of clinically relevant bacteria. Binary mixtures of bacteria showed Centrifuge reliably identified organisms down to 0.1% relative abundance. A staggered mock bacterial community showed Centrifuge outperformed CLARK while requiring less computing resources. Shotgun metagenomes obtained from whole blood in three febrile neutropenia patients showed Centrifuge could identify both bacteria and viruses as part of a culture-free workflow. Finally, Centrifuge results changed minimally by eliminating time-consuming read quality control and host screening steps.

15: Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues
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Posted to bioRxiv 13 Feb 2019

Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues
11 tweets bioengineering

Adam K Glaser, Nicholas P. Reder, Ye Chen, Chengbo Yin, Linpeng Wei, Soyoung Kang, Lindsey A. Barner, Weisi Xie, Erin F. McCarty, Chenyi Mao, Aaron R. Halpern, Caleb R. Stoltzfus, Jonathan S. Daniels, Michael Y. Gerner, Philip R Nicovich, Joshua C Vaughan, Lawrence D. True, Jonathan T.C. Liu

Recent advances in optical clearing and light-sheet microscopy have provided unprecedented access to structural and molecular information from intact tissues. However, current light-sheet microscopes have imposed constraints on the size, shape, number of specimens, and compatibility with various clearing protocols. Here we present a multi-immersion open-top light-sheet microscope that enables simple mounting of multiple specimens processed with a variety of protocols, which will facilitate wider adoption by preclinical researchers and clinical laboratories.

16: Potato genotypes differentially alter the expression of Phytophthora infestans effectors during PAMP-mediated resistance induction
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Posted to bioRxiv 14 Feb 2019

Potato genotypes differentially alter the expression of Phytophthora infestans effectors during PAMP-mediated resistance induction
10 tweets plant biology

Cecile Monique THOMAS, Pauline LE BOULCH, Didier ANDRIVON, Florence VAL

Pathogen recognition by plants via pathogen-associated molecular patterns leads to PAMP-triggered immunity. However, pathogens can modulate it via the secretion of effectors. We hypothesize that in potato, induced defense triggered by a Phytophthora infestans concentrated culture filtrate (CCF) could alter both effector expression and disease severity. CCF was sprayed onto three potato genotypes with different resistance levels, before inoculation with P. infestans. Symptoms were scored visually at 1-4 dpi, while the expression of defense and effector genes was assessed by qRT-PCR. CCF induced most defense genes in Desiree (PRs, EIN3) and Bintje (PRs, PAL and POX), but repressed most defense genes in Rosafolia. On the contrary, CCF induced most effector genes in Rosafolia (Pi03192, Avrblb2, Avr3a, EPIC2B and SNE1). INF1 was over-expressed in Bintje, despite its earlier expression in both Desiree and Rosafolia compared to unsprayed controls. Pi03192 was repressed in Desiree, and was expressed earlier in Rosafolia than in controls. However, induced defense responses by CCF significantly reduced lesion areas at 3 dpi only in Desiree. The effectiveness of induced defense thus depends on host genotypes. It results from differential interactions and kinetics of defense and effector genes expressions.

17: mRNA structure regulates protein expression through changes in functional half-life
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Posted to bioRxiv 13 Feb 2019

mRNA structure regulates protein expression through changes in functional half-life
10 tweets molecular biology

David M. Mauger, B. Joseph Cabral, Vladimir Presnyak, Stephen V. Su, David W Reid, Brooke Goodman, Kristian Link, Nikhil Khatwani, John Reynders, Melissa J Moore, Iain J. McFadyen

Messenger RNAs (mRNAs) encode information in both their primary sequence and their higher order structure. The independent contributions of factors like codon usage and secondary structure to regulating protein expression are difficult to establish as they are often highly correlated in endogenous sequences. Here, we used two approaches, global inclusion of modified nucleotides and rational sequence design of exogenously delivered constructs to understand the role of mRNA secondary structure independent from codon usage. Unexpectedly, highly-expressed mRNAs contained a highly-structured coding sequence (CDS). Modified nucleotides that stabilize mRNA secondary structure enabled high expression across a wide-variety of primary sequences. Using a set of eGFP mRNAs that independently altered codon usage and CDS structure, we find that the structure of the CDS regulates protein expression through changes in functional mRNA half-life (i.e. mRNA being actively translated). This work highlights an underappreciated role of mRNA secondary structure in the regulation of mRNA stability.

18: Ecological Representations
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Posted to bioRxiv 15 Jun 2016

Ecological Representations
10 tweets animal behavior and cognition

Sabrina Golonka, Andrew D Wilson

Mainstream cognitive science and neuroscience both rely heavily on the notion of representation in order to explain the full range of our behavioral repertoire. The relevant feature of representation is its ability to designate (stand in for) spatially or temporally distant properties, When we organize our behavior with respect to mental or neural representations, we are (in principle) organizing our behavior with respect to the property it designates. While representational theories are a potentially a powerful foundation for a good cognitive theory, problems such as grounding and system-detectable error remain unsolved. For these and other reasons, ecological explanations reject the need for representations and do not treat the nervous system as doing any mediating work. However, this has left us without a straight-forward vocabulary to engage with so-called 'representation-hungry' problems or the role of the nervous system in cognition. In an effort to develop such a vocabulary, here we show that James J Gibson's ecological information functions to designate the ecologically-scaled dynamical world to an organism. We then show that this designation analysis of information leads to an ecological conceptualization of the neural activity caused by information, which in turn we argue can together support intentional behavior with respect to spatially and temporally distal properties. Problems such as grounding and error detection are solved via law-based specification. This analysis extends the ecological framework into the realm of 'representation-hungry' problems, making it as powerful a potential basis for theories of behavior as traditional cognitive approaches. The resulting analysis does, according to some definitions, allow information and the neural activity to be conceptualized as representations; however, the key work is done by information and the analysis remains true to Gibson's ecological ontology.

19: Unpacking conditional neutrality: genomic signatures of selection on conditionally beneficial and conditionally deleterious mutations
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Posted to bioRxiv 13 Feb 2019

Unpacking conditional neutrality: genomic signatures of selection on conditionally beneficial and conditionally deleterious mutations
9 tweets evolutionary biology

Jonathan A Mee, Sam Yeaman

It is common to look for signatures of local adaptation in genomes by identifying loci with extreme levels of allele frequency divergence among populations. This approach to finding genes associated with local adaptation often assumes antagonistic pleiotropy, wherein alternative alleles are strongly favoured in alternative environments. Conditional neutrality has been proposed as an alternative to antagonistic pleiotropy, but conditionally neutral polymorphisms are transient and it is unclear how much outlier signal would be maintained under different forms of conditional neutrality. Here, we use individual-based simulations and a simple analytical heuristic to show that a pattern that mimics local adaptation at the phenotypic level, where each genotype has the highest fitness in its home environment, can be produced by the accumulation of mutations that are neutral in their home environment and deleterious in non-local environments. Because conditionally deleterious mutations likely arise at a rate many times higher than conditionally beneficial mutations, they can have a significant cumulative effect on fitness even when individual effect sizes are small. We show that conditionally deleterious mutations driving non-local maladaptation may be undetectable by even the most powerful genome scans, as differences in allele frequency between populations are typically small. We also explore the evolutionary effects of conditionally-beneficial mutations and find that they can maintain significant signals of local adaptation, and they would be more readily detectable than conditionally deleterious mutations using conventional genome scan approaches. We discuss implications for interpreting outcomes of transplant experiments and genome scans that are used to study the genetic basis of local adaptation.

20: Detection of Base Analogs Incorporated During DNA Replication by Nanopore Sequencing
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Posted to bioRxiv 14 Feb 2019

Detection of Base Analogs Incorporated During DNA Replication by Nanopore Sequencing
9 tweets genomics

Daniela Georgieva, Qian Liu, Kai Wang, Dieter Egli

DNA synthesis is a fundamental requirement for cell proliferation and DNA repair, but no tools exist to identify the location, direction and speed of replication forks with base pair resolution. Mammalian cells have the ability to incorporate thymidine analogs along with the natural A, T, G and C bases during DNA synthesis, which allows for labelling of replicating or repaired DNA. Most sequencing platforms rely on base-pairing to identify the four canonical nucleotides, and are thus unable to distinguish them from these analogs. In contrast, the Oxford Nanopore Technologies (ONT) MinION infers nucleotide identity from changes in the ionic current as DNA strands are pulled through nanopores and can in principle differentiate noncanonical nucleotides from natural ones. Here, we demonstrate the use of the ONT MinION to detect 11 different thymidine analogs including CldU, BrdU, IdU, as well as, EdU alone or coupled to Biotin and other bulky adducts in synthetic DNA templates. We also show detection of IdU in the genome of mouse pluripotent stem cells. We find that different modifications generate variable shifts in ionic signals, providing a method of using analog combinations to identify the location and direction of DNA synthesis and repair at high resolution. We conclude that this novel method has the potential for single-base, genome-wide examination of DNA replication in stem cell differentiation or cell transformation.

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