Negative selection

About: Negative selection is a research topic. Over the lifetime, 2461 publications have been published within this topic receiving 121259 citations.

Clonal selection and learning in the antibody system

Abstract: Each antibody-producing B cell makes antibodies of unique specificity, reflecting a series of ordered gene rearrangements which must be successfully performed if the cell is to survive. A second selection process occurs during immune responses in which a new antibody repertoire is generated through somatic hypermutation. Here only mutants binding antigen with high affinity survive to become memory cells. Cells expressing autoreactive receptors are counter-selected at both stages. This stringent positive and negative selection allows the generation and diversification of cells while rigorously controlling their specificity.

Evaluation of an Improved Branch-Site Likelihood Method for Detecting Positive Selection at the Molecular Level

Abstract: Detecting positive Darwinian selection at the DNA sequence level has been a subject of considerable interest. However, positive selection is difficult to detect because it often operates episodically on a few amino acid sites, and the signal may be masked by negative selection. Several methods have been developed to test positive selection that acts on given branches (branch methods) or on a subset of sites (site methods). Recently, Yang, Z., and R. Nielsen (2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19:908-917) developed likelihood ratio tests (LRTs) based on branch-site models to detect positive selection that affects a small number of sites along prespecified lineages. However, computer simulations suggested that the tests were sensitive to the model assumptions and were unable to distinguish between relaxation of selective constraint and positive selection (Zhang, J. 2004. Frequent false detection of positive selection by the likelihood method with branch-site models. Mol. Biol. Evol. 21:1332-1339). Here, we describe a modified branch-site model and use it to construct two LRTs, called branch-site tests 1 and 2. We applied the new tests to reanalyze several real data sets and used computer simulation to examine the performance of the two tests by examining their false-positive rate, power, and robustness. We found that test 1 was unable to distinguish relaxed constraint from positive selection affecting the lineages of interest, while test 2 had acceptable false-positive rates and appeared robust against violations of model assumptions. As test 2 is a direct test of positive selection on the lineages of interest, it is referred to as the branch-site test of positive selection and is recommended for use in real data analysis. The test appeared conservative overall, but exhibited better power in detecting positive selection than the branch-based lest. Bayes empirical Bayes identification of amino acid sites under positive selection along the foreground branches was found to be reliable, but lacked power.

Positive and Negative Selection of T Cells

Abstract: A functional immune system requires the selection of T lymphocytes expressing receptors that are major histocompatibility complex restricted but tolerant to self-antigens. This selection occurs predominantly in the thymus, where lymphocyte precursors first assemble a surface receptor. In this review we summarize the current state of the field regarding the natural ligands and molecular factors required for positive and negative selection and discuss a model for how these disparate outcomes can be signaled via the same receptor. We also discuss emerging data on the selection of regulatory T cells. Such cells require a high-affinity interaction with self-antigens, yet differentiate into regulatory cells instead of being eliminated.

Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages.

Abstract: The nonsynonymous (amino acid-altering) to synonymous (silent) substitution rate ratio (omega = d(N)/d(S)) provides a measure of natural selection at the protein level, with omega = 1, >1, and <1, indicating neutral evolution, purifying selection, and positive selection, respectively. Previous studies that used this measure to detect positive selection have often taken an approach of pairwise comparison, estimating substitution rates by averaging over all sites in the protein. As most amino acids in a functional protein are under structural and functional constraints and adaptive evolution probably affects only a few sites at a few time points, this approach of averaging rates over sites and over time has little power. Previously, we developed codon-based substitution models that allow the omega ratio to vary either among lineages or among sites. In this paper we extend previous models to allow the omega ratio to vary both among sites and among lineages and implement the new models in the likelihood framework. These models may be useful for identifying positive selection along prespecified lineages that affects only a few sites in the protein. We apply those branch-site models as well as previous branch- and site-specific models to three data sets: the lysozyme genes from primates, the tumor suppressor BRCA1 genes from primates, and the phytochrome (PHY) gene family in angiosperms. Positive selection is detected in the lysozyme and BRCA genes by both the new and the old models. However, only the new models detected positive selection acting on lineages after gene duplication in the PHY gene family. Additional tests on several data sets suggest that the new models may be useful in detecting positive selection after gene duplication in gene family evolution.