Literature DB >> 28532380

The Determination of Rod and Cone Photoreceptor Fate.

Constance L Cepko1.   

Abstract

Photoreceptors have been the most intensively studied retinal cell type. Early lineage studies showed that photoreceptors are produced by retinal progenitor cells (RPCs) that produce only photoreceptor cells and by RPCs that produce both photoreceptor cells and other retinal cell types. More recent lineage studies have shown that there are intrinsic, molecular differences among these RPCs and that these molecular differences operate in gene regulatory networks (GRNs) that lead to the choice of the rod versus the cone fate. In addition, there are GRNs that lead to the choice of a photoreceptor fate and that of another retinal cell type. An example of such a GRN is one that drives the binary fate choice between a rod photoreceptor and bipolar cell. This GRN has many elements, including both feedforward and feedback regulatory loops, highlighting the complexity of such networks. This and other examples of retinal cell fate determination are reviewed here, focusing on the events that direct the choice of rod and cone photoreceptor fate.

Entities:  

Keywords:  enhancer; gene regulatory network; lineage; progenitor cell; retinal development; transcription factor

Year:  2015        PMID: 28532380     DOI: 10.1146/annurev-vision-090814-121657

Source DB:  PubMed          Journal:  Annu Rev Vis Sci        ISSN: 2374-4642            Impact factor:   6.422


  11 in total

1.  Foxn4 is a temporal identity factor conferring mid/late-early retinal competence and involved in retinal synaptogenesis.

Authors:  Shuting Liu; Xiaoning Liu; Shengguo Li; Xiuting Huang; Haohua Qian; Kangxin Jin; Mengqing Xiang
Journal:  Proc Natl Acad Sci U S A       Date:  2020-02-18       Impact factor: 11.205

2.  Top2b is involved in the formation of outer segment and synapse during late-stage photoreceptor differentiation by controlling key genes of photoreceptor transcriptional regulatory network.

Authors:  Ying Li; Hailing Hao; Mavis R Swerdel; Hyeon-Yeol Cho; Ki-Bum Lee; Ronald P Hart; Yi Lisa Lyu; Li Cai
Journal:  J Neurosci Res       Date:  2017-03-30       Impact factor: 4.164

Review 3.  Retinal Vasculature in Development and Diseases.

Authors:  Ye Sun; Lois E H Smith
Journal:  Annu Rev Vis Sci       Date:  2018-09-15       Impact factor: 6.422

4.  Fgf8 Expression and Degradation of Retinoic Acid Are Required for Patterning a High-Acuity Area in the Retina.

Authors:  Susana da Silva; Constance L Cepko
Journal:  Dev Cell       Date:  2017-06-22       Impact factor: 12.270

5.  Enhancer transcription identifies cis-regulatory elements for photoreceptor cell types.

Authors:  Carlos Perez-Cervantes; Linsin A Smith; Rangarajan D Nadadur; Andrew E O Hughes; Sui Wang; Joseph C Corbo; Constance Cepko; Nicolas Lonfat; Ivan P Moskowitz
Journal:  Development       Date:  2020-02-05       Impact factor: 6.862

Review 6.  Eyeing up the Future of the Pupillary Light Reflex in Neurodiagnostics.

Authors:  Charlotte A Hall; Robert P Chilcott
Journal:  Diagnostics (Basel)       Date:  2018-03-13

7.  Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling.

Authors:  Qingnan Liang; Rachayata Dharmat; Leah Owen; Akbar Shakoor; Yumei Li; Sangbae Kim; Albert Vitale; Ivana Kim; Denise Morgan; Shaoheng Liang; Nathaniel Wu; Ken Chen; Margaret M DeAngelis; Rui Chen
Journal:  Nat Commun       Date:  2019-12-17       Impact factor: 14.919

8.  Global chromatin relabeling accompanies spatial inversion of chromatin in rod photoreceptors.

Authors:  Cheryl L Smith; Yemin Lan; Rajan Jain; Jonathan A Epstein; Andrey Poleshko
Journal:  Sci Adv       Date:  2021-09-24       Impact factor: 14.136

9.  Whole-Body Single-Cell Sequencing Reveals Transcriptional Domains in the Annelid Larval Body.

Authors:  Kaia Achim; Nils Eling; Hernando Martinez Vergara; Paola Yanina Bertucci; Jacob Musser; Pavel Vopalensky; Thibaut Brunet; Paul Collier; Vladimir Benes; John C Marioni; Detlev Arendt
Journal:  Mol Biol Evol       Date:  2018-05-01       Impact factor: 16.240

10.  Analysis of the bystander effect in cone photoreceptors via a guided neural network platform.

Authors:  Yuan Ma; Xin Han; Ricardo Bessa de Castro; Pengchao Zhang; Kai Zhang; Zhongbo Hu; Lidong Qin
Journal:  Sci Adv       Date:  2018-05-09       Impact factor: 14.136

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