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Written | November https:// column | General: Cerebral cortex motor neuron map landscape and database alliance BICCN; "BICCN column" Nature | Mouse brain single cell DNA methylation map; "BICCN column" Nature | Human neocortex expansion and glutamatergic neuron diversification; "BICCN column" Nature | | Mouse cortex-basal ganglia-thalamic network Working model; "BICCN column" Nature | Peng Hanchuan/Zeng Hongkui and other reporters define the morphological diversity of individual neurons in cell types; "BICCN column" Nature | Establishment of genetic tools-motor neuron cortical glutamatergic neuron specificity Sex Strains On October 6, 2021, the Cerebral Cortex Motor Neuron Atlas Landscape and the database consortium BICCN jointly published a collection of articles in Nature (see: Sixteen Nature's Heavy Release of Cerebral Motor Cortex Cell Atlas)
.
The Lior Pachter research group of California Institute of Technology in the BICCN consortium published a paper entitled Isoform cell-type specificity in the mouse primary motor cortex, which revealed the resolution of genotype subtypes through SMART-seq [1] and the combination with spatial transcriptome technology.
The level classifies the brain motor cortex neurons and non-neuronal cells, thereby obtaining a full map of the transcription level of the mouse primary motor cortex, and also provides a multi-platform analysis condition for the research of motor neurons
.
The original intention of the BICCN Alliance is to enrich the global understanding of precise behaviors such as sports by classifying and defining cells in the motor neuron cortex of the brain
.
The transcription and transcriptional regulation of individual gene subtypes in the process of neural differentiation are very important [2,3]
.
In the brains of mice and humans, some genes and their subtypes have cell type specificity.
Therefore, abnormal gene splicing can cause neurodevelopment and neuropsychiatric diseases [4]
.
The more popular high-throughput sequencing methods include Drop-seq, 10xGenomics Chromium, and inDrops technologies [5, 6].
These technologies produce information reading at the 3'end of the initial stage of mRNA preprocessing
.
SMART-seq is a single-cell RNA-seq method that generates full-length sequences, which can use algorithms to quantify different subtypes of genes, so as to obtain information that cannot be obtained by 3'end sequencing [7]
.
Full-length SMART-seq [1] Single-cell RNA sequencing technology can be used to measure the expression of different gene subtypes at a resolution level, so as to identify specific markers of gene expression subtypes of different cell types, and combine with spatial transcriptomes It can be used to infer the expression patterns of different cell types in different spatial structures
.
However, the improvement of resolution in SMART-seq requires an increase in the number of cells, and more sequencing of each cell is required
.
Therefore, the authors hope to combine different methods to maximize the advantages of each technology
.
In order to identify subtype cell markers in different cell types, the authors first used the data in the BICCN consortium for SMART-seq visualization
.
Using genetic marker technology SMART-seq, 10xGenomics Chromium for RNA measurement, and using MERFISH technology for spatial pattern positioning, it is possible to spatially capture RNA information and genotype information to establish cell type-specific markers (Figure 1)
.
Figure 1 Multi-platform and multi-mode RNA measurement of mouse brain motor neuron cortex.
From this, the authors identified 398 subtype markers of 310 genes, and through clustering the authors divided the specific cell types into three Levels: Classes, Subclasses and Clusters
.
SMART-seq data identified two major categories, namely glutamatergic neurons and γ-aminobutyric neurons, as well as 18 subcategories and 62 cell groups
.
The identification results of 10xGenomics Chromium are similar to SMART-seq, indicating that the gene expressions identified by the two methods are highly similar
.
Through the analysis of male and female mice, the authors identified gender differences in specific cell types in the motor neuron cortex and found that several autosomal subtypes are differentially expressed between male and female mice
.
The authors’ data shows that different genotypes can help refine the classification of cell types in mouse motor neuron cortex, which is more refined and accurate than using only gene expression levels
.
By using the MERFISH probe in combination, the authors further increased the spatial structure information of single-cell sequencing, which can reveal the spatial expression patterns of different genes and different subtypes of genes in the motor neuron cortex
.
The quantification of different genotypes obtained by RNA-seq can be used to distinguish specific expression changes between transcripts that share a transcription initiation site and transcripts that use different transcription initiation sites
.
The authors identified 1971 different gene expression subtypes from 128 sets of transcription initiation sites, which will show different preferences in glutamatergic neurons, γ-aminobutyric acid neurons, and non-neuronal cells The preferential expression of, this may be the result of the regulation of different transcription programs
.
In general, this work integrates the unique advantages of different technologies, such as the subtype resolution of SMART-seq, the cell reading depth of 10x Genomics, and the spatial resolution of MERFISH to achieve spatial analysis of gene subtypes in different cell types.
Type mark
.
The labeling of spatial subtype cell markers makes the detection of tissue specificity more precise and helps to identify the function of specific cell type subtypes.
This will be a key step in understanding the importance of a large number of gene variants in the brain
.
Original link: https://doi.
org/10.
1038/s41586-021-03969-3 Platemaker: Eleven References 1 Picelli, S.
et al.
Full-length RNA-seq from single cells using Smart-seq2.
Nature protocols 9, 171-181, doi:10.
1038/nprot.
2014.
006 (2014).
2 Weyn-Vanhentenryck, SM et al.
Precise temporal regulation of alternative splicing during neural development.
Nature communications 9, 2189, doi:10.
1038/s41467-018 -04559-0 (2018).
3 Porter, RS, Jaamour, F.
& Iwase, S.
Neuron-specific alternative splicing of transcriptional machineries: Implications for neurodevelopmental disorders.
Molecular and cellular neurosciences 87, 35-45, doi:10.
1016/ j.
mcn.
2017.
10.
006 (2018).
4 Gandal, MJ et al.
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder.
Science (New York, NY) 362, doi:10.
1126/science.
aat8127 (2018).
5 Klein, AM et al.
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.
Cell 161, 1187-1201, doi:10.
1016/j.
cell.
2015.
04.
044 (2015).
6 Macosko, EZ et al.
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Cell 161, 1202-1214, doi:10.
1016/j.
cell.
2015.
05.
002 (2015).
7 Ramsköld, D.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and Individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Reprint instructions [Original articles] BioArt original articles, personal forwarding and sharing are welcome, reprinting without permission is prohibited, all published works The copyrights of are owned by BioArtD.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Instructions for reprinting 【Original Article】BioArt Original articles are welcome to be shared by individuals.
Reprinting is prohibited without permission.
The copyrights of all published works are owned by BioArtD.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Instructions for reprinting 【Original Article】BioArt Original articles are welcome to be shared by individuals.
Reprinting is prohibited without permission.
The copyrights of all published works are owned by BioArt
.
BioArt reserves all statutory rights and offenders must be investigated
.
.
The Lior Pachter research group of California Institute of Technology in the BICCN consortium published a paper entitled Isoform cell-type specificity in the mouse primary motor cortex, which revealed the resolution of genotype subtypes through SMART-seq [1] and the combination with spatial transcriptome technology.
The level classifies the brain motor cortex neurons and non-neuronal cells, thereby obtaining a full map of the transcription level of the mouse primary motor cortex, and also provides a multi-platform analysis condition for the research of motor neurons
.
The original intention of the BICCN Alliance is to enrich the global understanding of precise behaviors such as sports by classifying and defining cells in the motor neuron cortex of the brain
.
The transcription and transcriptional regulation of individual gene subtypes in the process of neural differentiation are very important [2,3]
.
In the brains of mice and humans, some genes and their subtypes have cell type specificity.
Therefore, abnormal gene splicing can cause neurodevelopment and neuropsychiatric diseases [4]
.
The more popular high-throughput sequencing methods include Drop-seq, 10xGenomics Chromium, and inDrops technologies [5, 6].
These technologies produce information reading at the 3'end of the initial stage of mRNA preprocessing
.
SMART-seq is a single-cell RNA-seq method that generates full-length sequences, which can use algorithms to quantify different subtypes of genes, so as to obtain information that cannot be obtained by 3'end sequencing [7]
.
Full-length SMART-seq [1] Single-cell RNA sequencing technology can be used to measure the expression of different gene subtypes at a resolution level, so as to identify specific markers of gene expression subtypes of different cell types, and combine with spatial transcriptomes It can be used to infer the expression patterns of different cell types in different spatial structures
.
However, the improvement of resolution in SMART-seq requires an increase in the number of cells, and more sequencing of each cell is required
.
Therefore, the authors hope to combine different methods to maximize the advantages of each technology
.
In order to identify subtype cell markers in different cell types, the authors first used the data in the BICCN consortium for SMART-seq visualization
.
Using genetic marker technology SMART-seq, 10xGenomics Chromium for RNA measurement, and using MERFISH technology for spatial pattern positioning, it is possible to spatially capture RNA information and genotype information to establish cell type-specific markers (Figure 1)
.
Figure 1 Multi-platform and multi-mode RNA measurement of mouse brain motor neuron cortex.
From this, the authors identified 398 subtype markers of 310 genes, and through clustering the authors divided the specific cell types into three Levels: Classes, Subclasses and Clusters
.
SMART-seq data identified two major categories, namely glutamatergic neurons and γ-aminobutyric neurons, as well as 18 subcategories and 62 cell groups
.
The identification results of 10xGenomics Chromium are similar to SMART-seq, indicating that the gene expressions identified by the two methods are highly similar
.
Through the analysis of male and female mice, the authors identified gender differences in specific cell types in the motor neuron cortex and found that several autosomal subtypes are differentially expressed between male and female mice
.
The authors’ data shows that different genotypes can help refine the classification of cell types in mouse motor neuron cortex, which is more refined and accurate than using only gene expression levels
.
By using the MERFISH probe in combination, the authors further increased the spatial structure information of single-cell sequencing, which can reveal the spatial expression patterns of different genes and different subtypes of genes in the motor neuron cortex
.
The quantification of different genotypes obtained by RNA-seq can be used to distinguish specific expression changes between transcripts that share a transcription initiation site and transcripts that use different transcription initiation sites
.
The authors identified 1971 different gene expression subtypes from 128 sets of transcription initiation sites, which will show different preferences in glutamatergic neurons, γ-aminobutyric acid neurons, and non-neuronal cells The preferential expression of, this may be the result of the regulation of different transcription programs
.
In general, this work integrates the unique advantages of different technologies, such as the subtype resolution of SMART-seq, the cell reading depth of 10x Genomics, and the spatial resolution of MERFISH to achieve spatial analysis of gene subtypes in different cell types.
Type mark
.
The labeling of spatial subtype cell markers makes the detection of tissue specificity more precise and helps to identify the function of specific cell type subtypes.
This will be a key step in understanding the importance of a large number of gene variants in the brain
.
Original link: https://doi.
org/10.
1038/s41586-021-03969-3 Platemaker: Eleven References 1 Picelli, S.
et al.
Full-length RNA-seq from single cells using Smart-seq2.
Nature protocols 9, 171-181, doi:10.
1038/nprot.
2014.
006 (2014).
2 Weyn-Vanhentenryck, SM et al.
Precise temporal regulation of alternative splicing during neural development.
Nature communications 9, 2189, doi:10.
1038/s41467-018 -04559-0 (2018).
3 Porter, RS, Jaamour, F.
& Iwase, S.
Neuron-specific alternative splicing of transcriptional machineries: Implications for neurodevelopmental disorders.
Molecular and cellular neurosciences 87, 35-45, doi:10.
1016/ j.
mcn.
2017.
10.
006 (2018).
4 Gandal, MJ et al.
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder.
Science (New York, NY) 362, doi:10.
1126/science.
aat8127 (2018).
5 Klein, AM et al.
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.
Cell 161, 1187-1201, doi:10.
1016/j.
cell.
2015.
04.
044 (2015).
6 Macosko, EZ et al.
Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Cell 161, 1202-1214, doi:10.
1016/j.
cell.
2015.
05.
002 (2015).
7 Ramsköld, D.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and Individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Reprint instructions [Original articles] BioArt original articles, personal forwarding and sharing are welcome, reprinting without permission is prohibited, all published works The copyrights of are owned by BioArtD.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Instructions for reprinting 【Original Article】BioArt Original articles are welcome to be shared by individuals.
Reprinting is prohibited without permission.
The copyrights of all published works are owned by BioArtD.
et al.
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.
Nature biotechnology 30, 777-782, doi:10.
1038/nbt.
2282 (2012).
Instructions for reprinting 【Original Article】BioArt Original articles are welcome to be shared by individuals.
Reprinting is prohibited without permission.
The copyrights of all published works are owned by BioArt
.
BioArt reserves all statutory rights and offenders must be investigated
.
