Brief Population Bottlenecks Are Beyond The Genetic Streetlight

Inferring human demographic history from extant genomes is an important goal of population genetics. To date, the sensitivity of coalescence-based methods in detecting population bottlenecks has not been well characterized. In this study, we find that brief bottlenecks, of just a few generations, are undetectable by current methods. A new approach to population inference, Lineage Time Inference (LiTI), uses data-derived windows to demarcate the limits of the genetic data. We find that a sharp population bottleneck at the time of the Youngest Toba Eruption, and also at more ancient timepoints in the human lineage, would be outside the genetic streetlight.

CheSPI: Chemical shift Secondary structure Population Inference

NMR chemical shifts (CSs) are delicate reporters of local protein structure, and recent advances in random coil CS (RCCS) prediction and interpretation now offer the compelling prospect of inferring small populations of structure from small deviations from RCCSs. Here, we present CheSPI, a simple and efficient method that provides unbiased and sensitive aggregate measures of local structure and disorder. It is demonstrated that CheSPI can predict even very small amounts of residual structure and robustly delineate subtle differences into four structural classes for intrinsically disordered proteins. For structured regions and proteins, CheSPI can assign up to eight structural classes, which coincide with the well-known DSSP classification. The program is freely available, and can either be invoked from URL www.protein-nmr.org as a web implementation, or run locally from command line as a python program. CheSPI generates comprehensive numeric and graphical output for intuitive annotation and visualization of protein structures. A number of examples are provided.