Page 32 - OR-1-3

organoids enriched in oligodendrocytes, astrocytes, human neural organoid cell atlas, which combines multiple
and neurons to study myelin formation and cellular scRNA-seq datasets to map the primary human brain cell
interactions. 84,85 Microglia plays a crucial role in regulating types. This facilitates comparative analysis across various
brain health through inflammatory responses, microbial models and disease conditions. For example, organoids at
phagocytosis, and synaptic pruning. Incorporating 6 months of age demonstrate increasingly complex gene
microglial cells into brain organoids provides a valuable expression signatures, reflecting cellular maturation and
model for studying microglia migration and response differentiation. 94,95 Advanced trajectory inference methods
to neural damage in a 3D environment. 86,87 Compared to have provided insights into differentiation processes, such
unguided differentiation, guided differentiation enhances as the transformation of radial glia into mature excitatory
reproducibility and facilitates the study of specific brain and inhibitory neurons. In addition, scRNA-seq has
96
structures, advancing research in neurodevelopment, expanded beyond mRNA expression to include long
disease modeling, and regenerative medicine. non-coding RNAs (lncRNAs), providing deeper insights
into brain development, NDDs, and neuropsychiatric
4. Deciphering cellular complexity: conditions. These evolving transcriptomic tools offer a
97
Integrative insights from transcriptomic, more comprehensive understanding of cellular dynamics
metabolic, and functional analyses in brain in both healthy and diseased states.
organoids Despite their remarkable potential, organoid-based

Brain organoids provide a versatile model for investigating transcriptomics faces several challenges (Table 2). Variability
human neurodevelopment and disease, integrating in organoid culture conditions, underrepresentation of
transcriptomic, metabolic, and functional processes. 42,88 certain cell types such as inhibitory neurons, limitations
scRNA-seq and chromatin accessibility profiling have of single-cell transcriptomic platforms, and difficulties
enabled precise mapping of lineage-specific gene expression in data interpretation present ongoing obstacles. 18,98
and regulatory mechanisms underlying differentiation. Variability in growth conditions and ECM components
89
Metabolic profiling highlights the critical balance between across laboratories can introduce inconsistencies in results.
glycolysis and oxidative phosphorylation in neurogenesis, Platforms such as droplet-seq and split-seq, though effective
with metabolomic and isotope tracing approaches offering for large-scale profiling, suffer from low sequencing depth
insights into cellular energy flux. Functional studies per cell, complicating the detection of rare populations
90
99
leveraging electrophysiology and high-resolution imaging or low-expression genes. Furthermore, tools like Cell
have advanced our understanding of neural network Ranger, commonly used for processing scRNA-seq data,
activity, synaptic plasticity, and circuit maturation, with often struggle with data interpretation, especially when
techniques such as multielectrode arrays (MEAs) and comparing datasets across studies. 100
genetically encoded voltage indicators (GEVIs) providing To overcome these challenges, integrative approaches
scalable assessment platforms. and machine learning frameworks such as BOMA (Brain

4.1. Transcriptomic insights in human brain and Organoid Manifold Alignment) have been developed
organoids to integrate datasets and identify common developmental
trajectories across human organoids and primary brain
Cellular physiology is governed by the transcriptome, tissues. Moreover, scRNA-seq alone is insufficient
109
which orchestrates a range of biological processes essential for fully defining cell types and lineage relationships.
for cellular function and development. With the advent Combining transcriptomics with chromatin accessibility
91
of next-generation sequencing technologies, such as bulk profiling, such as single-cell ATAC-seq, has proven
RNA sequencing (RNA-seq) and scRNA-seq, researchers invaluable for providing a more holistic understanding of
have gained unprecedented insights into the transcriptomic gene regulatory networks. 110,111 This integrated approach
profiles of various cell types, developmental stages, has revealed critical regulatory mechanisms, including
and disease states. However, the limited availability of interactions between transcription factors and distal
92
human brain tissue remains a significant challenge for enhancers. However, challenges such as high noise levels,
neuroscientific research. To address this, human brain batch effects, and complexities in data integration persist.
organoids have emerged as powerful models that enable the
study of transcriptomic dynamics at single-cell resolution. 4.2. Metabolic regulation and analytical advances in
brain organoids
Human brain organoids, including cortical, thalamic,
and medial ganglionic eminence models, exhibit distinct yet The brain’s high metabolic demands necessitate a continuous
reproducible transcriptomic profiles that serve as reliable supply of ATP to sustain cellular and neuronal activities.
representations of human neurodevelopment. 12,93 A notable Disruptions in these metabolic processes are closely
advancement in this field is the development of an integrated linked to various neurological disorders, 112,113 highlighting

Volume 1 Issue 3 (2025) 6 doi: 10.36922/OR025100010