Biology subjects

Dalal, J.

Publications and source records attributed to Dalal, J..

3 recordsLinked to original sources

bioRxiv2025

Morphogen-guided neocortical organoids recapitulate regional areal identity and model neurodevelopmental disorder pathology

The human neocortex exhibits characteristic regional patterning (arealization) critical for higher-order cognitive function. Disrupted arealization is strongly implicated in neurodevelopmental disorders (NDDs), but current neocortical organoid models largely fail to recapitulate this patterning, limiting mechanistic understanding. Here, we establish a straightforward method for generating arealized organoids through short-term early exposure to anterior (FGF8) or posterior (BMP4/CHIR-99021) morphogens. These treatments created distinct anterior and posterior signaling centers, supporting long-lasting polarization, which we validated with single-cell RNA sequencing that revealed area-specific molecular signatures matching prenatal human cortex. To demonstrate the utility of this platform, we modeled Fragile X Syndrome (FXS) in organoids with distinct anterior and posterior regional identities. FXS organoids showed highly disrupted SOX4/SOX11 expression gradients along the anterior-posterior axis, consistent with alterations found in autism spectrum disorder (ASD) and demonstrate how regional patterning defects may contribute to NDD pathology. Together, our study provides a robust platform for generating neocortical organoids with anterior-posterior molecular signatures and highlights the importance of modeling NDDs using experimental platforms with neuroanatomic specificity.

developmental biology↗

bioRxiv2021

Loss of Tsc1 in cerebellar Purkinje cells induces transcriptional and translation changes in FMRP target transcripts

Tuberous sclerosis complex (TSC) is a genetic disorder that is associated with multiple neurological manifestations. Previously, we demonstrated that Tsc1 loss in cerebellar Purkinje cells (PCs) can cause altered social behavior in mice. Here, we performed detailed transcriptional and translational analyses of Tsc1-deficient PCs to understand the molecular alterations in these cells. We found that target transcripts of the Fragile X Mental Retardation Protein (FMRP) are reduced in mutant PCs with evidence of increased degradation. Surprisingly, we observed unchanged ribosomal binding for many of these genes using Translating Ribosome Affinity Purification (TRAP). Finally, we found that the FMRP target, SHANK2, was reduced in PC synapses, suggesting that compensatory increases in ribosomal binding efficiency may be unable to overcome reduced transcript levels. These data further implicate dysfunction of FMRP and its targets in TSC and suggest that treatments aimed at restoring the function of these pathways may be beneficial.

neuroscience↗

bioRxiv2019

A likelihood method for estimating present-day human contamination in ancient DNA samples using low-depth haploid chromosome data

1MotivationThe presence of present-day human contaminating DNA fragments is one of the challenges defining ancient DNA (aDNA) research. This is especially relevant to the ancient human DNA field where it is difficult to distinguish endogenous molecules from human contaminants due to their genetic similarity. Recently, with the advent of high-throughput sequencing and new aDNA protocols, hundreds of ancient human genomes have become available. Contamination in those genomes has been measured with computational methods often developed specifically for these empirical studies. Consequently, some of these methods have not been implemented and tested while few are aimed at low-depth data, a common feature in aDNA datasets.\n\nResultsWe develop a new X-chromosome-based maximum likelihood method for estimating present-day human contamination in low-depth sequencing data. We implement our method for general use, assess its performance under conditions typical of ancient human DNA research, and compare it to previous nuclear data-based methods through extensive simulations. For low-depth data, we show that existing methods can produce unusable estimates or substantially underestimate contamination. In contrast, our method provides accurate estimates for a depth of coverage as low as 0.5x on the X-chromosome when contamination is below 25%. Moreover, our method still yields meaningful estimates in very challenging situations, i.e., when the contaminant and the target come from closely related populations or with increased error rates. With a running time below five minutes, our method is applicable to large scale aDNA genomic studies.\n\nAvailability and implementationThe method is implemented in C++ and R and is freely available in https://github.com/sapfo/contaminationX.\n\nContactmorenomayar@gmail.com, annasapfo.malaspinas@unil.ch.

genomics↗