Cross-ancestry analysis identifies genes associated with obesity risk and protection
Banerjee D, Girirajan S*.

Gene discoveries in obesity have largely been based on European cohorts, leading to an ancestral bias, that limits their generalizability across populations. We performed a gene-based rare variant association study of 721,941 individuals and identified 116 novel BMI-associated genes with consistent effects across ancestries, including 50 risk-conferring and 66 protective genes against obesity. Protective genes such as DCUN1D3 and NEUROD6 had effect sizes comparable to high-risk genes such as MC4R and BSN, and nearly twice that of known protective genes such as GPR75, which, along with five other genes, showed strong European bias. Notably, 82 of the 116 genes showed functional relevance to obesity including adiposity, energy homeostasis, and glucose metabolism. While polygenic risks or an obesogenic lifestyle amplified the effect of 15 genes on BMI, including the combination of low physical activity and MACROD1, 23 genes including VIRMA, AQP3, and PML retained protective effects even at high polygenic scores. Our findings provide further insights into the genetic basis of obesity that is conserved across ancestries and their interactions with obesogenic factors.

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.