2020
DOI: 10.1101/gad.332577.119
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Positive autofeedback regulation of Ptf1a transcription generates the levels of PTF1A required to generate itch circuit neurons

Abstract: Peripheral somatosensory input is modulated in the dorsal spinal cord by a network of excitatory and inhibitory interneurons. PTF1A is a transcription factor essential in dorsal neural tube progenitors for specification of these inhibitory neurons. Thus, mechanisms regulating Ptf1a expression are key for generating neuronal circuits underlying somatosensory behaviors. Mutations targeted to distinct cis-regulatory elements for Ptf1a in mice, tested the in vivo contribution of each element individually and in co… Show more

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Cited by 10 publications
(11 citation statements)
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“…First, highly reliable clusters were identified based on four independent integration methodologies -Seurat V3, Harmony, Conos, and LIGERsuggesting that these clusters represent the underlying biological reality of cell types. Second, these clusters correspond well with prior gene expression analysis of the postnatal spinal cord including many classic and wellestablished marker gene studies as well as three independent single nucleus sequencing datasets that were not included in the harmonized clustering: an independent dataset that we clustered separately and used to test the SeqSeek Classify algorithm, and two recent studies that used different analysis strategies but found similar markers to the harmonized set 8,9 . Third, and most importantly, this atlas does not rest only on select studies or on computational approaches that would be subject to the biases of particular tools and parameter choices.…”
Section: Discussionsupporting
confidence: 62%
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“…First, highly reliable clusters were identified based on four independent integration methodologies -Seurat V3, Harmony, Conos, and LIGERsuggesting that these clusters represent the underlying biological reality of cell types. Second, these clusters correspond well with prior gene expression analysis of the postnatal spinal cord including many classic and wellestablished marker gene studies as well as three independent single nucleus sequencing datasets that were not included in the harmonized clustering: an independent dataset that we clustered separately and used to test the SeqSeek Classify algorithm, and two recent studies that used different analysis strategies but found similar markers to the harmonized set 8,9 . Third, and most importantly, this atlas does not rest only on select studies or on computational approaches that would be subject to the biases of particular tools and parameter choices.…”
Section: Discussionsupporting
confidence: 62%
“…Sixteen major types were identified that represent all known classes of spinal cord cell types. These cell types are: (1) oligodendrocyte precursor cells; (2-3) two maturational stages of oligodendrocyte progenitors; (4-5) two types of oligodendrocytes that likely correspond to myelinating and mature cell types and that blend into each other; (6) Schwann cells; (7) peripheral glia; (8)(9) two types of meninges that likely correspond to vascular leptomeningeal cells and arachnoid barrier cells; (10) ependymal cells that surround the central canal; (11)(12) two types of astrocytes that likely correspond to a major population of regular astrocytes and a minor population of Gfap-expressing proliferating/activated/white matter astrocytes; (13)(14) two types of vascular cells that likely correspond to endothelial cells and pericytes; (15) microglia; and (16) neurons, which are discussed in detail below.…”
Section: Resultsmentioning
confidence: 99%
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“…First, these clusters are robust to different clustering approaches, suggesting that they reflect underlying biological signatures rather than a technical artifact. Second, these clusters correspond well with prior gene expression studies of the postnatal spinal cord, including three single nucleus sequencing datasets that were not included in the harmonized clustering: an independent dataset that we clustered separately and used to test the SeqSeek Classify algorithm, and two very recent studies that found similar markers to the harmonized set 8,9 . Third, and most importantly, nearly all of the predicted marker neuronal coexpression patterns could be validated in tissue and several represent well-established molecular markers of accepted "cell types".…”
Section: Using Machine Learning To Classify Spinal Cord Cell Typessupporting
confidence: 64%
“…In a rat pancreatic acinar cell line (AR4-2J cells), the ablation of just one of the two PTF1 binding sites has a dramatic impact on enhancer activity [57]. In contrast, while adult mice with homozygous deletions spanning the two PTF1 binding sites have adverse somatosensory phenotypes, mice that retain at least one of the sites develop normally [81]. To date, there are no studies documenting the phenotypic outcome in the pancreas of ablating only one PTF1 binding site.…”
Section: The Cre Network Controlling Ptf1a Expressionmentioning
confidence: 99%