Biology subjects

Joshi, A.

Publications and source records attributed to Joshi, A..

8 recordsLinked to original sources

bioRxiv2018

Causal gene regulatory network inference using enhancer activity as a causal anchor

MotivationTranscription control plays a crucial role in establishing a unique gene expression signature for each of the hundreds of mammalian cell types. Though gene expression data has been widely used to infer the cellular regulatory networks, the methods mainly infer correlations rather than causality. We propose that a causal inference framework successfully used for eQTL data can be extended to infer causal regulatory networks using enhancers as causal anchors and enhancer RNA expression as a readout of enhancer activity.\n\nResultsWe developed statistical models and likelihood-ratio tests to infer causal gene regulatory networks using enhancer RNA (eRNA) expression information as a causal anchor and applied the framework to eRNA and transcript expression data from the FANTOM consortium. Predicted causal targets of transcription factors (TFs) in mouse embryonic stem cells, macrophages and erythroblastic leukemia overlapped significantly with experimentally validated targets from ChIP-seq and perturbation data. We further improved the model by taking into account that some TFs might act in a quantitative, dosage-dependent manner, whereas others might act predominantly in a binary on/off fashion. We predicted TF targets from concerted variation of eRNA and TF and target promoter expression levels within a single cell type as well as across multiple cell types. Importantly, TFs with high-confidence predictions were largely different between these two analyses, demonstrating that variability within a cell type is highly relevant for target prediction of cell type specific factors. Finally, we generated a compendium of high-confidence TF targets across diverse human cell and tissue types.\n\nAvailabilityMethods have been implemented in the Findr software, available at https://github.com/lingfeiwang/findr\n\nContactTom.Michoel@roslin.ed.ac.uk, Anagha.Joshi@roslin.ed.ac.uk

bioinformatics↗

bioRxiv2018

ERBB2 and KRAS Alterations Mediate Response to EGFR Inhibitors in early stage Gallbladder Cancer

The uncommonness of gallbladder cancer has contributed to the generally poor understanding of the disease, with scant reports restricted to advance-stage tumors. Here, using an integrated analysis of whole exome and phospho-proteome, we show recurrent activating ERBB2 and KRAS somatic mutations are present in 6 and 3 of 44 early-stage rare gallbladder tumors, respectively. In vitro and in vivo cell-based and biochemical assays reveal an essential role of ErbB pathway activation for the survival of gallbladder cells. Interestingly, the genetic and pharmacological dependencies of gallbladder cells are dependent on the KRAS mutant allele status, reminiscent of the clinical algorithm commonly practiced to opt for anti-EGFR treatment in colorectal cancer. In overall, we present the first evidence that the presence of KRAS (G12V), but not KRAS (G13D) mutation, may preclude gallbladder cancer patients to respond to anti-EGFR treatment, leading to an early adoption of an approved treatment regimen for gallbladder cancer patients.

cancer biology↗

bioRxiv2017

Understanding The Dynamics Of Laboratory Populations Of Drosophila melanogaster: Long-Term Experiments Meet Individual-Based Modelling

The dynamics of stage-structured populations facing variability in resource availability and/or demographic factors like unequal sex-ratios, remains poorly understood. We addressed these issues using a stage-structured individual-based model that incorporates life-history parameters common to many holometabolous insects. The model was calibrated using time series data from a 49-generation experiment on laboratory populations of Drosophila melanogaster, subjected to four different combinations of larval and adult nutritional levels. The model was able to capture multiple qualitative and quantitative aspects of the empirical time series across three independent studies. We then simulated the model to explore the interaction of various life-history parameters and nutritional levels in determining population stability. In all nutritional regimes, stability of the populations was reduced upon increasing egg-hatchability, critical mass and proportion of body resource allocated to female fecundity. However, the stability-effects of increasing sensitivity of female-fecundity to adult density varied across nutrition regimes. The effects of unequal sex-ratio and sex-specific culling were greatly influenced by fecundity but not by levels of juvenile nutrition. Finally, we investigated the implications of some of these insights on the efficiency of the widely-used pest control method, Sterile Insect Technique (SIT). We show that increasing the amount of juvenile food had no effects on SIT efficiency when the density-independent fecundity is low, but reduces SIT efficiency when the density-independent fecundity is high.

ecology↗

bioRxiv2017

Meta-Analysis Of Liver Transcriptomic Data To Identify Mammalian Functional Orthologs

Functional annotation transfer across multi-gene family orthologs can lead to functional misannotations. We hypothesised that co-expression network will help predict functional orthologs amongst complex homologous gene families. To explore the use of transcriptomic data available in public domain to identify functionally equivalent ones from all predicted orthologs, we collected genome wide expression data in mouse and rat liver from over 1500 experiments with varied treatments. We used a hyper-graph clustering method to identify clusters of orthologous genes co-expressed in both mouse and rat. We validated these clusters by analysing expression profiles in each species separately, and demonstrating a high overlap. We then focused on genes in 18 homology groups with one-to-many or many-to-many relationships between two species, to discriminate between functionally equivalent and non-equivalent orthologs. Finally, we further applied our method by collecting heart transcriptomic data (over 1400 experiments) in rat and mouse to validate the method in an independent tissue.

bioinformatics↗

bioRxiv2017

Effects of Social Organization, Trap Arrangement and Density, Sampling Scale, and Population Density on Bias in Population Size Estimation Using Some Common Mark-Recapture Estimators

Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.

ecology↗

bioRxiv2017

Niche construction in evolutionary theory: the construction of an academic niche?

In recent years, fairly far-reaching claims have been repeatedly made about how niche construction, the modification by organisms of their environment, and that of other organisms, represents a vastly neglected phenomenon in ecological and evolutionary thought. The proponents of this view claim that the niche construction perspective greatly expands the scope of standard evolutionary theory and that niche construction deserves to be treated as a significant evolutionary process in its own right, almost at par with natural selection. Claims have also been advanced about how niche construction theory represents a substantial extension to, and re-orientation of, standard evolutionary theory, which is criticized as being narrowly gene-centric and ignoring the rich complexity and reciprocity of organism-environment interactions. We examine these claims in some detail and show that they do not stand up to scrutiny. We suggest that the manner in which niche construction theory is sought to be pushed in the literature is better viewed as an exercise in academic niche construction whereby, through incessant repetition of largely untenable claims, and the deployment of rhetorically appealing but logically dubious analogies, a receptive climate for a certain sub-discipline is sought to be manufactured within the scientific community. We see this as an unfortunate, but perhaps inevitable, nascent post-truth tendency within science.

evolutionary biology↗

bioRxiv2016

Contribution of mobile elements to the uniqueness of human genome with more than 15,000 human-specific insertions

Mobile elements (MEs) collectively constituted to at least 51% of the human genome. Due to their past incremental accumulation and ongoing DNA transposition of members from certain subfamilies, MEs serve as a significant source for both inter- and intra-species genetic diversity during primate and human evolution. Since MEs can exert direct impact on gene function via a plethora of mechanism, it is believed that the ME-derived genetic diversity has contributed to the phenotypic differences between human and non-human primates, as well as among human populations and individuals. To define the specific contribution of MEs in making Human sapiens as a biologically unique species, we aim to compile a complete list of MEs that are only uniquely present in the human genome, i.e., human-specific MEs (HS-MEs).\n\nBy making use of the most recent reference genome sequences for human and many other primates and a unbiased more robust and integrative multi-way comparative genomic approach, we identified a total of 15,463 HS-MEs. This list of HS-MEs represents a 120% increase from prior studies with over 8,000 being newly identified as HS-MEs. Collectively, these ~15,000 HS-MEs have contributed to a total of 15 million base pair (Mbp) sequence increase through insertion, generation of target site duplications, and transductions, as well as a 0.5 Mbp sequence loss via insertion- mediated deletions, leading to a net total of 14.5 Mbp genome size increase. Other new observations made with these HS-MEs include: 1) identification of several additional ME subfamilies with significant transposition activities not visible with prior smaller datasets (e.g. L1HS, L1PA2, and HERV-K); 2) A clear similarity of the retrotransposition mechanism among L1, Alus, and SVAs that is distinct from HERVs based on the pre- integration site sequence motifs; 3) Y-chromosome as a strikingly hot target for HS-MEs, particularly for LTRs, which showed an insertion rate 15 times higher than the genome average; 4) among the ME types, SVAs seem to show a very strong bias in inserting into existing SVAs. Among the HS-MEs, more than 8,000 elements were integrated into the vicinity of ~4900 unique genes, in regions including CDS, untranslated exon regions, promoters, and introns of protein coding genes, as well as promoters and exons of non- coding RNAs. In seven cases, MEs participate in protein coding. Furthermore, 1,213 HS-MEs contributed to a total of 3,124 experimentally identified binding sites for 146 of the 161 transcriptional factors in association with 622 genes. All these data suggest that these HS-MEs, despite being very young, already showed sufficient sign for their participation in gene function via regulation of transcription, splicing, and protein coding, with more potential for future participation.\n\nIn conclusion, our results demonstrate that the amount of MEs uniquely occurred in the human genome is much higher than previously known, and we predict that the same is true regarding their impact on human genome evolution and function. The comprehensive list of HS-MEs provides an important reference resource for studying the impact of DNA transposition in human genome evolution and gene function.

evolutionary biology↗

bioRxiv2016

Protected corridors preserve tiger genetic diversity and minimize extinction into the next century

Habitat loss is the greatest threat to large carnivores around the world. Maintenance of functional connectivity in fragmented landscapes will be important for long-term species persistence. Here, we merge landscape genetics analyses and spatially-explicit simulations to understand future persistence and extinction of tigers (Panthera tigris) in Central India. Tigers in this landscape are restricted to Protected Areas (PAs) and forest fragments embedded within a mosaic of agricultural fields and human settlements. We examined current population connectivity of tigers across nine reserves (using 116 non-invasively sampled individuals and 12 microsatellites). Genetic data was used to infer resistance-to-movement. Our results suggest that dense human settlements and roads with high traffic are detrimental to tiger movement. We used landscape genetic simulations to model 86 different scenarios that incorporated impacts of future land-use change on inferred population connectivity and extinction. Our results confirm that genetic variability (heterozygosity) will decrease in the future and small and/or isolated PAs will have a high risk of local extinction. The average extinction risk of small PAs reduced by 23-70% on adding a 5 km buffer around exiting boundaries. Unplanned development results in 35% lower heterozygosity and 56% higher average extinction probability for tigers even within protected areas. Increasing tiger numbers in such a scenario decreases extinction probability just by 12 % (from 56% to 44%). Scenarios where habitat connectivity was enhanced and maintained, stepping-stone populations were introduced/maintained, and tiger numbers were increased, led to low overall extinction probability (between 3-21%). Our simulations provide a means to quantitatively evaluate the effects of different land-use change scenarios on connectivity and extinction, linking basic science to land-use change policy and planned infrastructure development.

genetics↗