Improved methods for detecting selection by mutation analysis of Ig V region sequences.

Statistical methods based on the relative frequency of replacement mutations in B lymphocyte Ig V region sequences have been widely used to detect the forces of selection that shape the B cell repertoire. However, current methods produce an unexpectedly high frequency of false positives and are sensitive to intrinsic biases of somatic hypermutation that can give the appearance of selection. The new statistical test proposed here provides a better trade-off between sensitivity and specificity compared with previous approaches. The low specificity of existing methods was shown in silico to result from an interaction between the effects of positive and negative selection. False detection of positive selection was confirmed in vivo through a re-analysis of published sequence data from diffuse large B cell lymphomas, highlighting the need for re-analysis of some existing studies. The sensitivity of the proposed method to detect selection was validated using new Ig transgenic mouse models in which positive selection was expected to be a significant force, as well as with a simulation-based approach. Previous concerns that intrinsic biases of somatic hypermutation could give the appearance of selection were addressed by extending the current mutation models to more fully account for the impact of microsequence on relative mutability and to include transition bias. High specificity was confirmed using a large set of non-productively rearranged Ig sequences. These results show that selection can be detected in vivo with high specificity using the new method proposed here, allowing greater insight into the existence and direction of antigen-driven selection.