Discovery of novel obesity genes through cross-ancestry analysis
Banerjee D, Girirajan S*.

Gene discoveries in obesity have largely relied on homogeneous populations, limiting their generalizability across ancestries. We performed a gene-based rare variant association study of BMI on 839,110 individuals from six ancestries across two population-scale biobanks. A cross-ancestry meta-analysis identified 13 genes, including five novel ones: YLPM1, RIF1, GIGYF1, SLC5A3, and GRM7, that conferred about three-fold risk for severe obesity, were expressed in the brain and adipose tissue, and were linked to obesity traits such as body-fat percentage. While YLPM1, MC4R, and SLTM showed consistent effects, GRM7 and APBA1 showed significant ancestral heterogeneity. Polygenic risk additively increased obesity penetrance, and phenome-wide studies identified additional associations, including YLPM1 with altered mental status. These genes also influenced cardiometabolic comorbidities, including GIGYF1 and SLTM towards type 2 diabetes with or without BMI as a mediator, and altered levels of plasma proteins, such as LECT2 and NCAN, which in turn affected BMI. Our findings provide insights into the genetic basis of obesity and its related comorbidities across ancestries and ascertainments.

Genetic modifiers and ascertainment drive variable expressivity of complex disorders
Jensen M, Smolen C, Tyryshkina A, Pizzo L, Banerjee D, Oetjens M, Shimelis H, Taylor CM, Pounraja VK, Song H, Rohan L, Huber E, El Khattabi L, van de Laar I, Tadros R, Bezzina C, van Slegtenhorst M, Kammeraad J, Prontera P, Caberg JH, Fraser H, Banka S, Van Dijck A, Schwartz C, Voorhoeve E, Callier P, Mosca-Boidron AL, Marle N, Lefebvre M, Pope K, Snell P, Boys A, Lockhart PJ, Ashfaq M, McCready E, Nowacyzk M, Castiglia L, Galesi O, Avola E, Mattina T, Fichera M, Bruccheri MG, Luana Mandarà GM, Mari F, Privitera F, Longo I, Curró A, Renieri A, Keren B, Charles P, Cuinat S, Nizon M, Pichon O, Bénéteau C, Stoeva R, Martin-Coignard D, Blesson S, Le Caignec C, Mercier S, Vincent M, Martin C, Mannik K, Reymond A, Faivre L, Sistermans E, Kooy RF, Amor DJ, Romano C, Andrieux J, Girirajan S*.

Variable expressivity of disease-associated variants implies a role for secondary variants that modify clinical features. We assessed the effects of modifier variants towards clinical outcomes of 2,252 individuals with primary variants. Among 132 families with the 16p12.1 deletion, distinct rare and common variant classes conferred risk for specific developmental features, including short tandem repeats for neurological defects and SNVs for microcephaly, while additional disease-associated variants conferred multiple genetic diagnoses. Within disease and population cohorts of 773 individuals with the 16p12.1 deletion, we found opposing effects of secondary variants towards clinical features across ascertainments. Additional analysis of 1,479 probands with other primary variants, such as 16p11.2 deletion and CHD8 variants, and 1,084 without primary variants, showed that phenotypic associations differed by primary variant context and were influenced by synergistic interactions between primary and secondary variants. Our study provides a paradigm to dissect the genomic architecture of complex disorders towards personalized treatment.

Flynotyper 2.0: an updated tool for rapid quantitative assessment of Drosophila eye phenotypes
Ray J, Banerjee D, Wang Q, Girirajan S*.

About two-thirds of the genes in the Drosophila melanogaster genome are also involved in its eye development, making the Drosophila eye an ideal system for genetic studies. We previously developed Flynotyper, a software that uses image processing operations to identify and quantify the degree of roughness by measuring disorderliness of ommatidial arrangement in the fly eye. This software has enabled researchers to quantify morphological defects of thousands of eye images caused by genetic perturbations. Here, we present Flynotyper 2.0, a software that has an updated computer vision library, improved performance, and a streamlined pipeline for high-throughput analysis of multiple eye images. We also tested several batches of Drosophila eye images to ensure robustness and reproducibility of the updated Flynotyper 2.0 software.