Jessica's Journey

This personal story chapter describes the journey undertaken by a transgender youth as she discovers her true gender identity. Told by a mother and daughter team, each individual shares her feelings and experiences from the time J is a toddler until the present, including preschool experiences, travel abroad anecdotes, school and social encounters, and family reactions and adjustments to J's transition and ongoing transformation. The chapter addresses the social, emotional, physical, academic, and economic factors that many transgender youth and adults face on a daily basis and suggests ways that schools and society can ease this complex process for individuals who are LGBTQ+.

Identification of a PROM1 mutation in a Spanish family with inherited retinal dystrophies

Background: We report a Spanish family, comprising an affected mother and daughter, respectively diagnosed with retinitis pigmentosa and Stargardt-like macular dystrophy, in whom we identified a PROM1 mutation. Methods: A custom gene panel consisting of 119 inherited retinal dystrophies (IRD)-genes was applied in the two affected individuals of this family and sequenced using the Illumina´s NextSeq500 platform. Results: The analysis of the resulting data allowed us to identify the pathogenic PROM1 mutation c.1117C>T (p.Arg373Cys) as the primary cause of the disease in both patients. No additional variants contributing to the extent of retinal dysfunction were detected. Conclusion: The variable expressivity of the detected PROM1 mutation is the most likely responsible for the intrafamilial phenotypic variability observed in this family. Screening of this mutation should be considered in patients with compatible clinical manifestations, especially when accompanied by an autosomal dominant family history.

LRRTM4 Terminal Exon Duplicated in Family with Tourette Syndrome, Autism and ADHD

Tourette syndrome (TS) is a neurodevelopmental disorder characterised by motor and vocal tics and strong association with autistic deficits, obsessive–compulsive disorder (OCD) and attention-deficit/hyperactivity disorder (ADHD). The genetic overlap between TS and autism spectrum disorder (ASD) includes those genes that encode the neurexin trans-synaptic connexus (NTSC) inclusive of the presynaptic neurexins (NRXNs) and postsynaptic neuroligins (NLGNs), cerebellin precursors (CBLNs in complex with the glutamate ionotropic receptor deltas (GRIDs)) and the leucine-rich repeat transmembrane proteins (LRRTMs). In this study, we report the first evidence of a TS and ASD association with yet another NTSC gene family member, namely LRRTM4. Duplication of the terminal exon of LRRTM4 was found in two females with TS from the same family (mother and daughter) in association with autistic traits and ASD.

The MAP She1 coordinates directional spindle positioning by spatially restricting dynein activity

Dynein motors move the mitotic spindle to the cell division plane in many cell types, including in budding yeast, in which dynein is assisted by numerous factors including the microtubule-associated protein (MAP) She1. Evidence suggests that She1 plays a role in polarizing dynein-mediated spindle movements toward the daughter cell; however, how She1 performs this function is unknown. We find that She1 assists dynein in maintaining the spindle in close proximity to the bud neck, such that at anaphase onset the chromosomes are segregated to mother and daughter cells. She1 does so by attenuating the initiation of dynein-mediated spindle movements within the mother cell, thus ensuring such movements are polarized toward the daughter cell. Our data indicate that this activity relies on She1 binding to the microtubule-bound conformation of the dynein microtubule-binding domain, and to astral microtubules within mother cells. Our findings reveal how an asymmetrically localized MAP directionally tunes dynein activity by attenuating motor activity in a spatially confined manner.

YeastMate: Neural network-assisted segmentation of mating and budding events in S. cerevisiae

Here, we introduce YeastMate, a user-friendly deep learning- based application for automated detection and segmentation of Saccharomyces cerevisiae cells and their mating and budding events in microscopy images. We build upon Mask R-CNN with a custom segmentation head for the subclassification of mother and daughter cells during lifecycle transitions. YeastMate can be used directly as a Python library or through a stand-alone GUI application and a Fiji plugin as easy to use frontends. The source code for YeastMate is freely available at https://github.com/hoerlteam/YeastMate under the MIT license. We offer packaged installers for our whole software stack for Windows, macOS and Linux. A detailed user guide is available at https://yeastmate.readthedocs.io.