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Eggplant Domestication: Pervasive Gene Flow, Feralization, and Transcriptomic Divergence

Page A, Gibson J, Meyer RS, Chapman MA

Mol Biol Evol, 2019 07 01;36(7):1359-1372.
PMID: 31039581 DOI: 10.1093/molbev/msz062

In the context of food security, examining the genomics of domestication will help identify genes underlying adaptive and economically important phenotypes, for example, larger fruit, improved taste, and loss of agronomically inferior phenotypes. Examination of genome-scale single nucleotide polymorphisms demonstrates the relationships between wild ancestors of eggplant (Solanum melongena L.), confirming that Solanum insanum L. is the wild progenitor. This species is split roughly into an Eastern (Malaysian, Thai, and Vietnamese) and Western (Indian, Madagascan, and Sri Lankan) group, with domesticates derived from the former. Additional "wild" accessions from India appear to be feral escapes, derived multiple times from domesticated varieties through admixture. Accessions with small egg-shaped fruit are generally found intermixed with East Asian Solanum insanum confirming they are primitive relative to the large-fruited domesticates. Comparative transcriptomics was used to track the loci under selection. Sequence analysis revealed a genetic bottleneck reducing variation by almost 50% in the primitive accessions relative to the wild species and a further 10% in the landraces. We also show evidence for selection on genes with a role in response to wounding and apoptosis. Genes showing a significant difference in expression between wild and primitive or between primitive and landrace genepools were mostly (>75%) downregulated in the derived populations and enriched for gene ontologies related to defense, flowering, signaling, and response to biotic and abiotic stimuli. This work reveals genomic changes involved in crop domestication and improvement, and the population genetics work explains why defining the eggplant domestication trajectory has been so challenging.
Fulltext Association of Whole-Genome and NETRIN1 Signaling Pathway-Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank

Barbu MC, Zeng Y, Shen X, Cox SR, Clarke TK, Gibson J, et al.

Biol Psychiatry Cogn Neurosci Neuroimaging, 2019 01;4(1):91-100.
PMID: 30197049 DOI: 10.1016/j.bpsc.2018.07.006

BACKGROUND: Major depressive disorder is a clinically heterogeneous psychiatric disorder with a polygenic architecture. Genome-wide association studies have identified a number of risk-associated variants across the genome and have reported growing evidence of NETRIN1 pathway involvement. Stratifying disease risk by genetic variation within the NETRIN1 pathway may provide important routes for identification of disease mechanisms by focusing on a specific process, excluding heterogeneous risk-associated variation in other pathways. Here, we sought to investigate whether major depressive disorder polygenic risk scores derived from the NETRIN1 signaling pathway (NETRIN1-PRSs) and the whole genome, excluding NETRIN1 pathway genes (genomic-PRSs), were associated with white matter microstructure.
METHODS: We used two diffusion tensor imaging measures, fractional anisotropy (FA) and mean diffusivity (MD), in the most up-to-date UK Biobank neuroimaging data release (FA: n = 6401; MD: n = 6390).
RESULTS: We found significantly lower FA in the superior longitudinal fasciculus (β = -.035, pcorrected = .029) and significantly higher MD in a global measure of thalamic radiations (β = .029, pcorrected = .021), as well as higher MD in the superior (β = .034, pcorrected = .039) and inferior (β = .029, pcorrected = .043) longitudinal fasciculus and in the anterior (β = .025, pcorrected = .046) and superior (β = .027, pcorrected = .043) thalamic radiation associated with NETRIN1-PRS. Genomic-PRS was also associated with lower FA and higher MD in several tracts.
CONCLUSIONS: Our findings indicate that variation in the NETRIN1 signaling pathway may confer risk for major depressive disorder through effects on a number of white matter tracts.
Image collection and annotation platforms to establish a multi-source database of oral lesions

Rajendran S, Lim JH, Yogalingam K, Kallarakkal TG, Zain RB, Jayasinghe RD, et al.

Oral Dis, 2023 Jul;29(5):2230-2238.
PMID: 35398971 DOI: 10.1111/odi.14206

OBJECTIVE: To describe the development of a platform for image collection and annotation that resulted in a multi-sourced international image dataset of oral lesions to facilitate the development of automated lesion classification algorithms.
MATERIALS AND METHODS: We developed a web-interface, hosted on a web server to collect oral lesions images from international partners. Further, we developed a customised annotation tool, also a web-interface for systematic annotation of images to build a rich clinically labelled dataset. We evaluated the sensitivities comparing referral decisions through the annotation process with the clinical diagnosis of the lesions.
RESULTS: The image repository hosts 2474 images of oral lesions consisting of oral cancer, oral potentially malignant disorders and other oral lesions that were collected through MeMoSA® UPLOAD. Eight-hundred images were annotated by seven oral medicine specialists on MeMoSA® ANNOTATE, to mark the lesion and to collect clinical labels. The sensitivity in referral decision for all lesions that required a referral for cancer management/surveillance was moderate to high depending on the type of lesion (64.3%-100%).
CONCLUSION: This is the first description of a database with clinically labelled oral lesions. This database could accelerate the improvement of AI algorithms that can promote the early detection of high-risk oral lesions.

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