Although of high priority for the development of genetic tools to control malaria-transmitting mosquitoes, only a few germline-specific regulatory regions have been characterised to date and the presence of global regulatory mechanisms, such as dosage compensation and meiotic sex chromosome inactivation (MSCI), are mostly assumed from transcriptomic analyses of reproductive tissues or whole gonads. In such studies, samples include a significant portion of somatic tissues inevitably complicating the reconstruction of a defined transcriptional map of gametogenesis. By exploiting recent advances in transgenic technologies and gene editing tools, combined with fluorescence-activated cell sorting and RNA sequencing, we have separated four distinct cell lineages from the Anopheles gambiae male gonads: premeiotic, meiotic (primary and secondary spermatocytes) and postmeiotic. By comparing the overall expression levels of X-linked and autosomal genes across the four populations, we revealed a striking transcriptional repression of the X chromosome coincident with the meiotic phase, classifiable as MSCI, and highlighted genes that may evade silencing. In addition, chromosome-wide median expression ratios of the premeiotic population confirmed the absence of dosage compensation in the male germline. Applying differential expression analysis, we highlighted genes and transcript isoforms enriched at specific timepoints and reconstructed the expression dynamics of the main biological processes regulating the key stages of sperm development and maturation. We generated the first transcriptomic atlas of A. gambiae spermatogenesis that will expand the available toolbox for the genetic engineering of vector control technologies. We also describe an innovative and multidimensional approach to isolate specific cell lineages that can be used for the targeted analysis of other A. gambiae organs or transferred to other medically relevant species and model organisms.

High-resolution transcriptional profiling of Anopheles gambiae spermatogenesis reveals mechanisms of sex chromosome regulation

Crisanti A;
2019

Abstract

Although of high priority for the development of genetic tools to control malaria-transmitting mosquitoes, only a few germline-specific regulatory regions have been characterised to date and the presence of global regulatory mechanisms, such as dosage compensation and meiotic sex chromosome inactivation (MSCI), are mostly assumed from transcriptomic analyses of reproductive tissues or whole gonads. In such studies, samples include a significant portion of somatic tissues inevitably complicating the reconstruction of a defined transcriptional map of gametogenesis. By exploiting recent advances in transgenic technologies and gene editing tools, combined with fluorescence-activated cell sorting and RNA sequencing, we have separated four distinct cell lineages from the Anopheles gambiae male gonads: premeiotic, meiotic (primary and secondary spermatocytes) and postmeiotic. By comparing the overall expression levels of X-linked and autosomal genes across the four populations, we revealed a striking transcriptional repression of the X chromosome coincident with the meiotic phase, classifiable as MSCI, and highlighted genes that may evade silencing. In addition, chromosome-wide median expression ratios of the premeiotic population confirmed the absence of dosage compensation in the male germline. Applying differential expression analysis, we highlighted genes and transcript isoforms enriched at specific timepoints and reconstructed the expression dynamics of the main biological processes regulating the key stages of sperm development and maturation. We generated the first transcriptomic atlas of A. gambiae spermatogenesis that will expand the available toolbox for the genetic engineering of vector control technologies. We also describe an innovative and multidimensional approach to isolate specific cell lineages that can be used for the targeted analysis of other A. gambiae organs or transferred to other medically relevant species and model organisms.
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3368704
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