Biology subjects

Ramachandran, S.

Publications and source records attributed to Ramachandran, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Integrating sex-bias into studies of archaic admixture on chromosome X

Evidence of interbreeding between archaic hominins and humans comes from methods that infer the locations of segments of archaic haplotypes, or archaic coverage using the genomes of people living today. As more estimates of archaic coverage have emerged, it has become clear that most of this coverage is found on the autosomes-- very little is retained on chromosome X. Here, we summarize published estimates of archaic coverage on autosomes and chromosome X from extant human samples. We find on average 7.9 times more archaic coverage on autosomes than chromosome X, and identify broad continental patterns in this ratio: greatest in American samples, and least in South Asian samples. We also perform extensive simulation studies to investigate how the amount of archaic coverage, lengths of coverage, and rates of purging of archaic coverage are affected by sex-bias caused by an unequal sex ratio within the archaic introgressors. Our results generally confirm that, with increasing male sex-bias, less archaic coverage is retained on chromosome X. Ours is the first study to explicitly model such sex-bias and its potential role in creating the dearth of archaic coverage on chromosome X. Author summaryTens of thousands of years ago, humans interbred with our close hominin relatives (e.g. Neanderthals), which we know from finding segments of archaic hominin DNA in our genomes. Up to 4% of a human genome may be archaic DNA, but most of that archaic part is on the autosomes (the non-sex chromosomes). Chromosome X usually contains 3 to 10 times less archaic DNA than the autosomes. Also unlike the autosomes, it is always passed down by mothers, but only sometimes by fathers. There are several hypotheses for why chromosome X has less archaic DNA than the autosomes; one that has not been fully explored is whether the archaic hominins that interbred with our ancestors were mostly male or mostly female, known as sex-bias. In this paper, we use simulations to investigate whether sex-bias could produce less archaic DNA on chromosome X. Using simulation studies, we find that when the archaics are mostly male, modern humans end up with less archaic DNA on chromosome X than their autosomes, compared to when there is a female-bias or no sex-bias. Therefore, male sex-bias could be contributing to the difference in the amount of archaic DNA on chromosome X versus the autosomes. Of course, there are still plenty of other factors to be explored about how demography and selection have shaped our DNA. Studying patterns like this helps us learn more about early hominin natural history, and contextualizes archaic interbreeding events among other sex-biased events in human history.

evolutionary biology↗

bioRxiv2022

Nucleation and spreading rejuvenate polycomb domains every cell cycle

Gene repression by the polycomb pathway is essential for proper development in metazoans. Polycomb domains, characterized by trimethylation of histone H3 (H3K27me3), carry the memory of repression through successive cell divisions, and hence, need to be maintained to counter dilution during replication of parental H3K27me3 with unmodified nascent H3. Yet, how locus-specific H3K27me3 is maintained through replication is unknown. To understand H3K27me3 recovery post-replication, we first defined nucleation sites within each polycomb domain in mouse embryonic stem cells. Then, to track H3K27me3 dynamics in unperturbed cells during replication, we developed CUT&Flow, which maps H3K27me3 domains as a function of the cell cycle stage. Using CUT&Flow, we show that post-replication rejuvenation of polycomb domains occurs by nucleation and spreading, using the same nucleation sites used during de novo domain formation. By using subunit-specific inhibitors of the PRC2 complex, we find that PRC2 need not rely on pre-existing H3K27me3 to target nucleation sites post-replication. The timing of nucleation relative to the cell cycle reflects the combination of replication timing and H3K27me3 deposition kinetics derived from de novo domain formation. Thus, competition between H3K27me3 deposition and nucleosome turnover drives both de novo domain formation and maintenance during every cell cycle.

molecular biology↗

bioRxiv2022

Partitioning Marginal Epistasis Distinguishes Nonlinear Effects from Polygenicity and Other Biases in GWA Summary Statistics

LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e., interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.

genomics↗

bioRxiv2022

HSV-1 exploits host heterochromatin for egress

Herpes simplex virus (HSV-1) progeny form in the nucleus and must exit to successfully infect other cells. These newly formed viral capsids navigate the complex chromatin architecture of the nucleus to reach the inner nuclear membrane and egress. Here, we demonstrate by transmission electron microscopy (TEM) that HSV-1 capsids traverse dense heterochromatin in the nuclear periphery to reach the inner nuclear membrane. We found that this heterochromatin is dependent on the specific chromatin marks of trimethylation on histone H3 lysine 27 (H3K27me3) and the histone variant macroH2A1. Through chromatin profiling over the course of infection, we revealed massive host genomic regions bound by macroH2A1 and H3K27me3 that correlate with decreased host transcription in active compartments. This indicates the formation of new heterochromatin during infection. We found that loss of these markers resulted in significantly lower viral titers but did not impact viral genome or protein accumulation. Strikingly, we discovered by TEM that loss of macroH2A1 or H3K27me3 resulted in nuclear trapping of viral capsids. Thus, our work demonstrates that HSV-1 takes advantage of the dynamic nature of host heterochromatin formation during infection for efficient viral egress.

microbiology↗

bioRxiv2022

SOPHIE: viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, while common source outbreaks violate this assumption. We propose a maximum likelihood framework SOPHIE (SOcial and PHilogenetic Investigation of Epidemics) based on integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modelled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity and accurately infers transmissions without case-specific epidemiological data. SOPHIE code is freely available at https://github.com/compbel/SOPHIE/

bioinformatics↗

bioRxiv2022

Deceptive learning in histopathology

Deep learning holds immense potential for histopathology, automating tasks that are simple for expert pathologists, and revealing novel biology for tasks that were previously considered difficult or impossible to solve by eye alone. However, the extent to which the visual strategies learned by deep learning models in histopathological analysis are trustworthy or not has yet to be systematically analyzed. In this work, we address this problem and discover new limits on the histopathological tasks for which deep learning models learn trustworthy versus deceptive solutions. While tasks that have been extensively studied in the field like tumor detection are reliable and trustworthy, recent advances demonstrating the ability to learn molecular profiling from hematoxylin and eosin (H&E) stained slides do not hold up to closer scrutiny. Our analysis framework represents a new approach in understanding the capabilities of deep learning models, which should be incorporated into the computational pathologists toolkit.

pathology↗

bioRxiv2022

Ultrasound Neuromodulation and Correlation Change in the Rat Somatosensory Cortex

Transcranial focused ultrasound (tFUS) is a neuromodulation technique which has been the focus of increasing interest for noninvasive brain stimulation with high spatial specificity. Its ability to excite and inhibit neural circuits as well as to modulate perception and behavior has been demonstrated, however, we currently lack understanding of how tFUS modulates the ways neurons interact with each other. This understanding would help explain tFUSs mechanism of high-level neuromodulation and allow future development of therapies for neurological disorders. In this study we investigate how tFUS modulates neural interaction and response to peripheral electrical limb stimulation through intracranial multi-electrode recordings in the rat somatosensory cortex. We deliver ultrasound in a pulsed pattern to attempt to induce frequency dependent plasticity in a manner similar to that found following electrical stimulation. We show that neural firing in response to peripheral electrical stimulation is increased after ultrasound stimulation at all frequencies, showing tFUS induced excitation in individual neurons in vivo. We demonstrate tFUS frequency dependent pairwise correlation changes between neurons, with both potentiation and depression observed at different frequencies. These results extend previous research showing tFUS to be capable of inducing synaptic depression and demonstrate its ability to modulate network dynamics as a whole.

neuroscience↗

bioRxiv2022

Uncertainty Quantification in Variable Selection for Genetic Fine-Mapping using Bayesian Neural Networks

In this paper, we propose a new approach for variable selection using a collection of Bayesian neural networks with a focus on quantifying uncertainty over which variables are selected. Motivated by fine-mapping applications in statistical genetics, we refer to our framework as an "ensemble of single-effect neural networks" (ESNN) which generalizes the "sum of single-effects" regression framework by both accounting for nonlinear structure in genotypic data (e.g., dominance effects) and having the capability to model discrete phenotypes (e.g., case-control studies). Through extensive simulations, we demonstrate our methods ability to produce calibrated posterior summaries such as credible sets and posterior inclusion probabilities, particularly for traits with genetic architectures that have significant proportions of non-additive variation driven by correlated variants. Lastly, we use real data to demonstrate that the ESNN framework improves upon the state-of-the-art for identifying true effect variables underlying various complex traits.

bioinformatics↗

bioRxiv2022

Enabling interpretable machine learning for biological data with reliability scores

Machine learning has become an important tool across biological disciplines, allowing researchers to draw conclusions from large datasets, and opening up new opportunities for interpreting complex and heterogeneous biological data. Alongside the rapid growth of machine learning, there have also been growing pains: some models that appear to perform well have later been revealed to rely on features of the data that are artifactual or biased; this feeds into the general criticism that machine learning models are designed to optimize model performance over the creation of new biological insights. A natural question thus arises: how do we develop machine learning models that are inherently interpretable or explainable? In this manuscript, we describe reliability scores, a new concept for scientific machine learning studies that assesses the ability of a classifier to produce a reliable classification for a given instance. We develop a specific implementation of a reliability score, based on our work in Sugden et al. 2018 in which we introduced SWIF(r), a generative classifier for detecting selection in genomic data. We call our implementation the SWIF(r) Reliability Score (SRS), and demonstrate the utility of the SRS when faced with common challenges in machine learning including: 1) an unknown class present in testing data that was not present in training data, 2) systemic mismatch between training and testing data, and 3) instances of testing data that are missing values for some attributes. We explore these applications of the SRS using a range of biological datasets, from agricultural data on seed morphology, to 22 quantitative traits in the UK Biobank, and population genetic simulations and 1000 Genomes Project data. With each of these examples, we demonstrate how interpretability tools for machine learning like the SRS can allow researchers to interrogate their data thoroughly, and to pair their domain-specific knowledge with powerful machine-learning frameworks. We hope that this tool, and the surrounding discussion, will aid researchers in the biological machine learning space as they seek to harness the power of machine learning without sacrificing rigor and biological understanding.

bioinformatics↗

bioRxiv2021

Boosting of SARS-CoV-2 immunity in nonhuman primates using an oral rhabdoviral vaccine

An orally active vaccine capable of boosting SARS-CoV-2 immune responses in previously infected or vaccinated individuals would help efforts to achieve and sustain herd immunity. Unlike mRNA-loaded lipid nanoparticles and recombinant replication-defective adenoviruses, replicating vesicular stomatitis viruses with SARS-CoV-2 spike glycoproteins (VSV-SARS2) were poorly immunogenic after intramuscular administration in clinical trials. Here, by G protein trans-complementation, we generated VSV-SARS2(+G) virions with expanded target cell tropism. Compared to parental VSV-SARS2, G-supplemented viruses were orally active in virus-naive and vaccine-primed cynomolgus macaques, powerfully boosting SARS-CoV-2 neutralizing antibody titers. Clinical testing of this oral VSV-SARS2(+G) vaccine is planned.

immunology↗

bioRxiv2021

Multiphoton microscopy for label-free multicolor imaging of peripheral nerve

Conventional histomorphometry of peripheral nerve entails lengthy chemical processing, ultrathin sectioning in resin, and imaging by light or electron microscopy. Multiphoton microscopy techniques exist enabling label-free and in vivo imaging of histological samples. Third-harmonic-generation microscopy has recently been demonstrated effective for imaging the myelin sheath of peripheral nerve axons in animal models. Herein, we characterize use of second and third harmonic generation microscopy for label-free imaging of murine and human peripheral nerve via a novel multicolor multiphoton microscope based on a single excitation wavelength at 1300 nm. Second harmonic generation signal from collagen centered about 650 nm delineates neural connective tissue, while third harmonic general signal centered about 433 nm delineates myelin and other lipids. In transgenic mice expressing yellow fluorescent protein linked to the thy1 promoter, three-photon-excitation with emission peak at 527 nm delineates axoplasm. We compare label-free multiphoton imaging of murine and human peripheral nerve against conventional chemical stains and discuss clinical implications of this approach in guiding intraoperative decision making in nerve transfer procedures.

cell biology↗

bioRxiv2021

Zebrafish Information Network, the knowledgebase for Danio rerio research

The Zebrafish Information Network (ZFIN, zfin.org) is the central repository for zebrafish genetic and genomic data. ZFIN expertly curates, integrates, and displays zebrafish data including genes, alleles, human disease models, gene expression, phenotype, gene function, orthology, morpholino, CRISPR, TALEN, and antibodies. ZFIN makes zebrafish research data Findable, Accessible, Interoperable, and Reusable (FAIR) through nomenclature, curatorial and annotation activities, web interfaces, and data downloads. ZFIN is a founding member of the Alliance of Genome Resources, providing zebrafish data for integration into the cross species platform as well as contributing to model organism data harmonization efforts.

genetics↗

bioRxiv2021

New Insights into the Mechanisms Used by Inhibitors Targeting Glutamine Metabolism in Cancer Cells

Many cancer cells become dependent on glutamine metabolism to compensate for glycolysis being uncoupled from the TCA cycle. The mitochondrial enzyme Glutaminase C (GAC) satisfies this glutamine addiction by catalyzing the first step in glutamine metabolism, making it an attractive drug target. Despite one of the allosteric inhibitors (CB-839) being in clinical trials, none of the drugs targeting GAC are approved for cancer treatment and their mechanism of action is not well understood. A major challenge has been the rational design of better drug candidates: standard cryo-cooled X-ray crystal structures of GAC bound to CB-839 and its analogs fail to explain their potency differences. Here, we address this problem by using an emerging technique, serial room temperature crystallography, which enabled us to observe clear differences between the binding conformations of inhibitors with significantly different potencies. A computational model was developed to further elucidate the molecular basis of inhibitor potency. We then corroborated the results from our modeling efforts by using recently established fluorescence assays that directly read-out inhibitor binding to GAC. Together, these findings provide new insights into the mechanisms used by a major class of allosteric GAC inhibitors and for the future rational design of more potent drug candidates.

biochemistry↗

bioRxiv2021

Adaptive convergent evolution of genome proofreading in SARS-CoV2: insights into the Eigen's paradox

Evolutionary history of coronaviruses holds the key to understand mutational behavior and prepare for possible future outbreaks. By performing comparative genome analysis of nidovirales that contain the family of coronaviruses, we traced the origin of proofreading, surprisingly to the eukaryotic antiviral component ZNFX1. This common recent ancestor contributes two zinc finger (ZnF) motifs that are unique to viral exonuclease, segregating them from DNA proof-readers. Phylogenetic analyses indicate that following acquisition, genomes of coronaviruses retained and further fine-tuned proofreading exonuclease, whereas related families harbor substitution of key residues in ZnF1 motif concomitant to a reduction in their genome sizes. Structural modelling followed by simulation suggests the role of ZnF in RNA binding. Key ZnF residues strongly coevolve with replicase, and the helicase involved in duplex RNA unwinding. Hence, fidelity of replication in coronaviruses is a result of convergent evolution, that enables maintenance of genome stability akin to cellular proofreading systems.

evolutionary biology↗

bioRxiv2021

Expression and function of SLC38A5, an amino acid-coupled Na+/H+ exchanger, in triple-negative breast cancer and its relevance to macropinocytosis.

Metabolic reprogramming in cancer cells necessitates increased amino acid uptake, which is accomplished by upregulation of specific amino acid transporters. Since amino acid transporters differ in substrate selectivity, mode of transport, and driving forces, not all tumors rely on any single amino acid transporter for this purpose. Here we report on the differential upregulation of the amino acid transporter SLC38A5 in triple-negative breast cancer (TNBC). The upregulation is evident in primary TNBC tumors, conventional TNBC cell lines, patient-derived xenograft TNBC cell lines, and a mouse model of spontaneous mammary tumor representing TNBC. The upregulation is confirmed by functional assays. SLC38A5 is an amino acid-dependent Na+/H+ exchanger which transports Na+ and amino acids into cells coupled with H+ efflux. Since the traditional Na+/H+ exchanger is an established inducer of macropinocytosis, an endocytic process for cellular uptake of bulk fluid and its components, we examined the impact of SLC38A5 on macropinocytosis in TNBC cells. We found that the transport function of SLC38A5 is coupled to induction of macropinocytosis. Surprisingly, the transport function of SLC38A5 is inhibited by amilorides, the well-known inhibitors of Na+/H+ exchanger, possibly related to the amino acid-dependent Na+/H+ exchange function of SLC38A5. The Cancer Genome Atlas database corroborates SLC38A5 upregulation in TNBC. This represents the first report on the selective expression of SLC38A5 in TNBC and its role as an inducer of macropinocytosis, thus revealing a novel, hitherto unsuspected, function for an amino acid transporter that goes beyond amino acid delivery but is still relevant to cancer cell nutrition. Summary StatementSLC38A5 is an amino acid-coupled Na+/H+ exchanger that is upregulated in triple-negative breast cancer, and its function in cancer cells goes beyond amino acid delivery; it promotes macropinocytosis, a distinct form of endocytic process for cellular uptake of proteins and other nutrients present in extracellular fluid.

cancer biology↗

bioRxiv2021

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multigenerational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within the African continent, as well as how within-Africa variation can be informative for broader variant interpretation; many variants appearing rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity within Africa.

genomics↗

bioRxiv2021

Kinesin-3 mediated delivery of presynaptic neurexin stabilizes growing dendritic spines and postsynaptic components in vivo

The functional properties of neural circuits are defined by the patterns of synaptic connections between their partnering neurons, but the mechanisms that stabilize circuit connectivity are poorly understood. We systemically examined this question at synapses onto newly characterized dendritic spines of C. elegans GABAergic motor neurons. We show that the presynaptic adhesion protein, neurexin/NRX-1, is required for stabilization of postsynaptic structure. We find that early postsynaptic developmental events proceed without a strict requirement for synaptic activity and are not disrupted by deletion of neurexin/nrx-1. However, in the absence of presynaptic NRX-1, dendritic spines and receptor clusters become destabilized and collapse prior to adulthood. We demonstrate that kinesin-3/UNC-104 delivers NRX-1 to presynaptic terminals and show that ongoing delivery is required for postsynaptic maintenance in mature animals. By defining the dynamics and temporal order of synapse formation events in vivo, we describe a mechanism for stabilizing mature circuit connectivity through neurexin-based adhesion.

neuroscience↗

bioRxiv2021

Redefining replication in multi-ancestry genome-wide association studies

Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals due to various confounding challenges. Here, we demonstrate that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales--from genes to genomic regions and pathways--have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits, as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts.

genomics↗