In vivo functional phenotypes from a computational epistatic model of evolution.

Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with in vivo functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. We demonstrate the power of epistasis inferred from natural protein families to evolve sequence variants in an algorithm we developed called sequence evolution with epistatic contributions (SEEC).

Metabolic and other morbid complications in congenital generalized lipodystrophy type 4.

Morbidity and mortality rates in patients with autosomal recessive, congenital generalized lipodystrophy type 4 (CGL4), an ultra-rare disorder, remain unclear. We report on 30 females and 16 males from 10 countries with biallelic null variants in CAVIN1 gene (mean age, 12 years; range, 2 months to 41 years). Hypertriglyceridemia was seen in 79% (34/43), hepatic steatosis in 82% (27/33) but diabetes mellitus in only 21% (8/44).

functional phenotypes from a computational epistatic model of evolution.

Computational models of evolution are valuable for understanding the dynamics of sequence variation, to infer phylogenetic relationships or potential evolutionary pathways and for biomedical and industrial applications. Despite these benefits, few have validated their propensities to generate outputs with functionality, which would enhance their value as accurate and interpretable evolutionary algorithms. We demonstrate the power of epistasis inferred from natural protein families to evolve sequence variants in an algorithm we developed called Sequence Evolution with Epistatic Contributions.