Chenlu Di

This paper uses causal inference to show that background selection and mutation rate variation jointly shape human genetic diversity, with mutation rate variation having comparable impact in some chromosomes.

The paper constructs a high-resolution human pangenome structural variant resource, identifies disease-associated SVs, and demonstrates its utility in filtering variants from probands and associating SVs with traits in a large cohort.

This study detects pervasive cryptic negative selection in human noncoding regions using a statistical test, finding that at least 7% of the genome is under negative selection, surpassing previous estimates from conservation-based methods.

The paper infers the fitness effects of noncoding mutations in humans using genomic annotations and polymorphism data, finding distinct selection patterns across different noncoding regions.

The paper compares the distribution of fitness effects of new amino acid changing mutations between dogs and wolves to assess the impact of domestication on selective pressures.